Prebiotic synthesis of nucleic acids and their building blocks at the

PCCP
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
PERSPECTIVE
Cite this: Phys. Chem. Chem. Phys.,
2016, 18, 20047
View Journal | View Issue
Prebiotic synthesis of nucleic acids and their
building blocks at the atomic level – merging
models and mechanisms from advanced
computations and experiments
Judit E. Šponer,ab Rafał Szabla,a Robert W. Góra,c A. Marco Saitta,d Fabio Pietrucci,d
Franz Saija,e Ernesto Di Mauro,f Raffaele Saladino,g Martin Ferus,h Svatopluk Civišh
and Jiřı́ Šponer*ab
The origin of life on Earth is one of the most fascinating questions of contemporary science. Extensive
research in the past decades furnished diverse experimental proposals for the emergence of first
informational polymers that could form the basis of the early terrestrial life. Side by side with the
experiments, the fast development of modern computational chemistry methods during the last 20 years
facilitated the use of in silico modelling tools to complement the experiments. Modern computations can
provide unique atomic-level insights into the structural and electronic aspects as well as the energetics of
Received 29th January 2016,
Accepted 8th April 2016
key prebiotic chemical reactions. Many of these insights are not directly obtainable from the experimental
DOI: 10.1039/c6cp00670a
experiments and for qualified predictions. This review illustrates the synergy between experiment and
techniques and the computations are thus becoming indispensable for proper interpretation of many
theory in the origin of life research focusing on the prebiotic synthesis of various nucleic acid building
www.rsc.org/pccp
blocks and on the self-assembly of nucleotides leading to the first functional oligonucleotides.
Introduction
The RNA-world hypothesis is one of the most popular concepts
of the origin of terrestrial life.1,2 It assumes the existence of an
ancient life-form in which RNA served as both the carrier of
genetic information and a catalyst capable of catalyzing its own
replication. One of the key questions of the origin of life
research is therefore related to the synthesis of nucleic acids’
a
Institute of Biophysics, Academy of Sciences of the Czech Republic, Královopolská 135,
CZ-612 65 Brno, Czech Republic. E-mail: [email protected]
b
CEITEC – Central European Institute of Technology, Masaryk University,
Campus Bohunice, Kamenice 5, CZ-62500 Brno, Czech Republic
c
Theoretical Chemistry Group, Institute of Physical and Theoretical Chemistry,
Wrocław University of Technology, Wybrzeże Wyspiańskiego 27,
50-370 Wrocław, Poland
d
Sorbonne Universités, Université Pierre et Marie Curie Paris 6, CNRS,
Institut de Minéralogie, de Physique des Matériaux et de Cosmochimie,
Muséum National d’Histoire Naturelle, Institut de Recherche pour le
Développement, UMR 7590, F-75005 Paris, France
e
CNR-IPCF, Viale Ferdinando Stagno d’Alcontres 37, 98158 Messina, Italy
f
Dipartimento di Biologia e Biotecnologie ‘‘Charles Darwin’’,
‘‘Sapienza’’ Università di Roma, Piazzale Aldo Moro 5, Rome 00185, Italy
g
Dipartimento di Scienze Ecologiche e Biologiche Università della Tuscia,
Via San Camillo De Lellis, 01100 Viterbo, Italy
h
J. Heyrovský Institute of Physical Chemistry, Academy of Sciences of the
Czech Republic, Dolejškova 3, CZ-182 23 Prague 8, Czech Republic
This journal is © the Owner Societies 2016
building blocks and the subsequent self-assembly thereof to
form functional oligonucleotides.
Parallel to the astonishing information growth on prebiotic
strategies reconstructing life’s origin the last decade witnessed
an unprecedented step forward in the computational modelling
of these processes. This enabled the elaboration of an ‘‘in silico’’
approach to the origin of informational polymers. The great
advantage of computations when complementing experiments in
the origin of life studies is that they provide information on selected single molecules and chemical reactions, whereas prebiotic
experiments always work with complex mixtures, which often make
the interpretation of these studies very challenging. This is the area
where computational chemistry might be instrumental for experimentalists, since theory may supplement the experimentally available information with an atomic level insight into the structural
aspects, electronic structure changes, energetics, spectroscopic
properties and dynamic behavior of the studied systems.
Since computational chemistry is still not fully recognized as
a frontline method to study life’s origin, the main aim of the
current review article is to illustrate with a couple of examples
the synergism between theory and experiment in this field and
to foster further combined experimental–theoretical studies in
this incredibly exciting topic.
Traditionally, HCN has been considered to be the ‘‘stone of
wisdom’’ of prebiotic chemistry.3 During the last 50 years an
Phys. Chem. Chem. Phys., 2016, 18, 20047--20066 | 20047
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
Perspective
PCCP
enormous amount of experimental information has been accumulated on the chemistry of this molecule, and currently the passage
from HCN to the building blocks of nucleic acids, i.e. nucleotides
is well characterized.4 In the beginning of the new millennium a
new concurrent hypothesis appeared, which derives nucleic acid
building blocks from formamide and enables a non-aqueous way
to nucleotides.5 Although the formamide-based scenario is still
quite recent and less elaborated, it represents the only prebiotic
scenario, which outlines a continuous path from a simple
prebiotic precursor up to the first catalytic oligonucleotides.6
In the current review we will follow both the HCN and formamide concepts and provide a comprehensive overview of the
topic both from the side of experiment and theory.
Judit E. Šponer received her MSc
degree from the Eötvös University,
Budapest in 1993 and her PhD
from the Hungarian Academy
of Sciences and the Technical
University, Budapest in 1996,
working with Prof. Magdolna
Hargittai. Then she spent four
years at the J. Heyrovský Institute
of Physical Chemistry in Prague.
Since 2001 she has been working
as a senior researcher at the
Institute of Biophysics of the
Judit E. Šponer
Academy of Sciences of the Czech
Republic. Her current research focuses on the computational modelling
of problems related to the origin of life.
Rafał Szabla is a PhD Student at
the Institute of Biophysics of the
Academy of Sciences of the Czech
Republic under the supervision of
Prof. Jiri Sponer. He obtained his
MSc degree in 2012 from the
Wroclaw University of Technology.
During his Master’s studies he
spent one year at the Technical
University in Munich collaborating
with the group of Prof. Wolfgang
Domcke. He is primarily interested
in theoretical investigations of the
photochemistry of nucleic acids
and their prebiotically plausible
precursors.
A. Marco Saitta obtained a PhD
in Condensed Matter Theory from
the International School for
Advanced Studies (SISSA/ISAS)
in Trieste in 1997, and then
moved to Philadelphia, USA, for
a postdoctoral position at the
University of Pennsylvania. In
2000 he was appointed Maı̂tre
de Conférences at Université
Pierre et Marie Curie, where he
is currently a full professor. A
specialist of electronic structure
A. Marco Saitta
theory and ab initio calculations,
his research activity has spanned from bulk semiconductors to
graphene and nanotubes, to water and ices. His main interests are
the exotic properties of molecular crystals, liquids and amorphous
under extreme conditions of pressure and temperature, for which he
has received in 2006 the Young Scientist Award from the European
High Pressure Research Group. In recent years his research has
opened up into more interdisciplinary fields, such as Earth sciences
and geochemistry. He has authored more than 80 articles, including
1 Nature, 2 Nature Materials, 5 PNAS, and 18 Phys. Rev. Lett. He has
been serving since February 2013 as Deputy Dean of the Physics
Faculty of UPMC.
20048 | Phys. Chem. Chem. Phys., 2016, 18, 20047--20066
Tools for reconstructing the
beginnings of life ‘‘in silico’’
Prior to discussing the key recent achievements in the modelling
of processes relevant to the origin of life, let us briefly overview
Rafał Szabla
Ernesto Di Mauro was born in
Valmontone, Italy, in 1945. In
1967 he obtained his Degree
in Biological Sciences from
‘‘Sapienza’’ University of Rome,
Italy. In 1969 he joined the
Department of Genetics (Seattle),
as a postdoctoral fellow. Appointed
in 1978 as an associate professor
of Enzymology at the University of Rome, he has been a
professor of Molecular Biology
since 1987. His research interests
Ernesto Di Mauro
were centered on gene regulation,
DNA and chromatin structure and topology and, at present, on the
various aspects of the origin of life.
This journal is © the Owner Societies 2016
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
PCCP
Perspective
the most frequently used computational techniques. The spectrum of available methods is very broad and the methods widely
differ in the employed approximations and areas of applicability.
Good quality computations are not easy and require extensive
prior experience, understanding of all the physical approximations of the methods and an intimate knowledge of the studied
processes. Using computational methods in a black-box manner
is responsible for numerous studies which either use inappropriate methods or are incorrectly interpreted.
Quantum chemical (QC) calculations can be primarily considered as methods which aim to achieve as complete as possible
a physical description of the studied molecules, but are quite
expensive in terms of computer resources. QC methods that do
not utilize any parameters are known as ‘‘ab initio’’ or ‘‘first
principles’’ methods. QC methods are typically used for small
model systems. Nevertheless, since in prebiotic chemistry we
often investigate properties and chemical reactions of small
molecules, we can very often afford computations on essentially
complete systems. This is of great advantage compared to
applications of QC methods to, e.g., enzymatic reactions. QC
calculations are sometimes likened to hypothetical energymeasuring experiments carried out at a temperature of 0 K,
since we aim to construct point-by-point the potential energy
surfaces of the studied molecules or chemical reactions.7 In
other words, we calculate a set of relative electronic energies for
a series of single configurations of the atomic positions of the
studied systems. Other typical properties that can be derived
from QC calculations are spectroscopic properties, like IR,
Raman or UV-Vis band positions and intensities. Major limitations of QC calculations are difficulties to derive free energies
due to entire lack of sampling of the Boltzmann distribution
and uncertainties in the inclusion of solvation effects. Rather
crude free energy corrections are estimated from the harmonic
approximation (vibrational frequencies) and solvent is often
represented using continuum models.8 Fortunately, reaction
mechanisms (including the thermodynamic corrections) for
typical non-enzymatic prebiotic reactions can be calculated quite
reliably. Contemporary QC calculations achieve an impressive accuracy in the description of ground state properties of closed-shell
electronic structure systems. On the other hand, calculations on
open shell systems, excited states etc. often remain challenging. For
a review summarizing the meaning of QC computations and written
for non-specialists, see ref. 9.
Wave-function-based approaches represent the traditional
family of QC methods. This group comprises some of the most
widely used ‘‘all-purpose’’ theoretical chemistry methods, like the
HF (Hartree–Fock, another abbreviation is SCF, self-consistent
field) and MP2 (second-order perturbation theory)10 techniques,
as well as the more specialized and highly accurate CI (configuration interaction) type methods, like CC11 (coupled clusters),
MCSCF12 (multi-configurational SCF) and CASSCF13 (complete
active space SCF). To obtain reliable results, an appropriate
level of theory (inclusion of electron correlation effects) needs
to be selected and combined with a sufficiently large basis set of
atomic orbitals. The quality requirements vary with the nature of
the chemical problem studied.9
The wave-function-based techniques are all common in that
they solve the Schrödinger-equation14 to obtain information
about the geometry, energy and electronic properties of the
studied system. The primary physical quantity provided by these
computations is thus the electronic energy that is a function of
the intrinsic molecular structural parameters: this enables
studying reaction mechanisms by mapping the potential energy
surface of the studied system as a function of the structural
changes implied by the reorganization of the reaction complex.
Another product of QC calculations is the electronic wavefunction (i.e., the molecular orbitals) which can be used to
derive accurate information about the electronic structure of
the studied systems. Other properties of the molecules are
derived from the wave-functions using appropriate algorithms
available in the main QC codes, using the basic principles of
quantum mechanics.
It is highly popular to discuss the properties of different
molecules using the so-called partial atomic charge distributions derived from some QC computations. Here we wish to
point out that derivation of atomic charges is always an arbitrary
(definition-dependent) procedure. Atomic charges, despite being
very intuitive, are not real physical quantities (i.e., observables)
Raffaele Saladino is a full
professor of Organic Chemistry,
Bioorganic Chemistry and Chemistry of Natural Substances at
the University of Tuscia, Viterbo
(Italy). He is involved in prebiotic
chemistry, with particular attention to the development of plausible
synthetic models for the emergence
of nucleic acids, amino acids, lipids
and sugars.
Jiřı́ Šponer is the head of the
Laboratory of Structure and
Dynamics of Nucleic Acids at the
Institute of Biophysics, Academy
of Sciences of the Czech Republic,
and a Professor at Palacky University, Olomouc and Masaryk University, Brno. He has published
around 260 papers with more
than 12 000 citations. His research
interests are computational and
theoretical studies of structure,
dynamics, function and evolution
of nucleic acids.
Raffaele Saladino
This journal is © the Owner Societies 2016
Jiřı́ Šponer
Phys. Chem. Chem. Phys., 2016, 18, 20047--20066 | 20049
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
Perspective
according to a thorough quantum-mechanical definition. There
exist a plenty of arbitrary methods for deriving partial atomic
charges from the computed electronic densities that are extensively used in organic chemistry. The meaning of the fractional
charges, however, should not be overvalued.
The second class of basic QM methods is represented by
DFT (density functional theory) methods. The DFT-based studies
became, in fact, dominant in the last decade. The massive
expansion of DFT-based computational techniques revolutionized almost all areas of computational modelling. These techniques are based on the Hohenberg–Kohn theorem,15 which
states that the ground state electronic energy of a system is
determined by the electronic density. Since the electronic density
is also dependent on the structural parameters, DFT-techniques
basically provide a powerful and fast method to get information
about the structure and energy of the studied systems, at least in
the electronic ground state. While selection of an appropriate
wave-function method is straightforward though not always easy,
an appropriate choice of the DFT method requires quite a lot of
insights into the latest literature. There are several different
levels of DFT approximation and literally hundreds of available
variants of DFT functionals.16–22 Thus, we strongly advice that
inexperienced users consult a specialized laboratory before
executing such computations. An alternative option is to search
through benchmark databases and method-testing papers
for related chemical problems/reactions that are commonly
published in this research field and are reliable.23–25
A properly chosen DFT method can provide results that are
comparable and sometimes (due to appropriate compensation
of errors) even better than those obtained by the wave-function
approach, with a fraction of computational resources. The QC
community and literature are usually very open about accuracy
limitations of the methods.
Classical atomistic molecular dynamics (MD) simulations are
primarily aimed at describing thermal dynamics (Boltzmann
distribution) of the studied systems.26 Assumption of the ergodic
hypothesis means that infinitely long simulation would provide
converged sampling of the phase space and thus correct thermodynamics. The extensive sampling comes at the expense of
unphysical description of the molecules which are approximated
by simple parameterized atomistic potentials (force fields) using
van der Waals Lennard-Jones spheres, atom-centered fixed point
charges and simple analytic functions to describe the covalent
structure. Such potentials cannot include any explicit polarization or electronic structure effects; these need to be taken into
account implicitly in the course of the parameterization. With
prolongation of the simulations and advance of methods that
allow enhancing sampling along the most relevant degrees of
freedom,27,28 the highly approximate nature of the force fields is
becoming the most crucial limitation. Despite the efforts to
improve the biomolecular force fields it seems that their quality
has reached a plateau and it is not clear if any fundamental
improvement of their accuracy will be possible in the foreseeable
future.26 MD simulations are based on describing the studied
system by solving Newtonian equations of motion typically at room
temperature with an integration time step of 2–4 femtoseconds.
20050 | Phys. Chem. Chem. Phys., 2016, 18, 20047--20066
PCCP
The classical force fields do not allow studying chemical reactions, as they do not describe bond breaking and bond formation. In contrast to the usually rigorous QC literature, it is not
uncommon in the MD literature to extensively hide simulation
artifacts and over-interpret the results, although there are studies
proving frank assessments of the limits.29–32 We strongly advise
anyone attempting MD simulations to perform tests of the
technique and of the selected force field using the available
atomistic structures as the reference, to verify that the simulated
molecules do not structurally degrade. Mere literature search of
what other groups use may be insufficient in this particular case.
There are intense efforts to develop more physical polarizable force fields.33–36 However, while specialized force fields for
narrow sets of compounds can be quite well parameterized, it is
not yet clear whether it will be, in the near future, possible to
parameterize sufficiently balanced multipurpose biomolecular
polarizable force field. The larger complexity of the polarizable
force fields compared to the simple pair-additive force fields is
a major challenge when diverse energy contributions need to be
appropriately balanced.
Recently, ‘‘first-principles’’ or ‘‘ab initio’’ QC molecular
dynamics (AIMD) methodology has also been applied to problems of prebiotic chemistry. AIMD is a method combining a
quantum treatment of the electronic degrees of freedom, with the
numerical solution and time-integration of Newton classical
dynamic equations on atoms, by making use of the quantumcalculated forces acting on the atoms included in the simulation.
As in classical MD, the system then evolves in time, within the
chosen statistical ensemble, most of the times the canonical
number of particles–volume–temperature (NVT) or the number of
particles–pressure–temperature (NPT) ensembles. The goal is to
let the system evolve for as-long-as-possible trajectories which,
within the ergodic hypothesis, allow determining the ensemble
statistical averages of the relevant physical observables of the
systems, such as the thermodynamic (enthalpy, free-energies),
structural (pair-correlation functions, structural factors), and
dynamic (self-diffusion) properties. AIMD trajectories are generally
of the order of tens of picoseconds, with typical timesteps of the
order of 104 ps, thus implying that the quantum-derived forces
and energies of the system must be calculated 105–106 times to
obtain such trajectories (for comparison, classical MD simulations
of solvated biomolecules are nowadays routinely done on a ms time
scale26). These performances are achieved by using a densityfunctional theory (DFT) treatment of the electronic degrees of
freedom, as wave-function-based QC methods are computationally too costly for these system sizes.
In the general chemistry context, AIMD allows following
the complete chemical evolution of the system, i.e. the rupture
and formation of chemical bonds, according to the chosen
thermodynamic simulation conditions. In the prebiotic case, for
example, one can target specific reactions in different situations,
such as in bulk solution or in the presence of a specific mineral
surface, under given pressure–temperature hydrothermal conditions, and so forth. However, the predictive power of AIMD
in these cases is often hindered by large barriers. These are
typically too high to be spontaneously overcome by the system,
This journal is © the Owner Societies 2016
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
PCCP
(i.e., only thanks to the thermal energy), within the short simulation times. To speed up the trajectory evolution, new methods are
being developed to accelerate dynamics and, more generally, to
address the free-energy calculations, among which the so-called
umbrella sampling37 and metadynamics method38 are widely
employed. Note that these enhanced-sampling methods are highly
popular also in the field of classical MD simulations (see above).
For the sake of completeness, let us mention that the
combination of quantum chemical and molecular dynamics/
mechanics (QM/MM and QM/MD, i.e., hybrid) methods is so far
less popular in the origin of life field, in contrast to studies of
enzyme reaction mechanisms.39 In these methods, a small part of
the molecule of chemical interest is treated via QC and the rest by
MM. The unphysical border between the QC and MM regions is a
common source of inaccuracies.
Prebiotic synthesis of nucleic acid
building blocks
Nucleobases
Out of all nucleic acid building blocks perhaps prebiotic synthesis of nucleobases has attracted the greatest attention among
both experimentalists and theoreticians. The pioneering
experimental studies by Oro40 and Ferris et al.41 soon after the
Miller–Urey experiment42,43 have shown that nucleobases can be
synthesized from simple precursor molecules, like HCN, urea or
cyanoacetylene. Indeed these reactions were exploited in the
experimentally reported synthetic procedures, among which
pentamerization of HCN leading to adenine has also been
studied in detail by QC. Since experiments have clearly shown
that pentamerization of HCN proceeds via 4-aminoimidazole5-carbonitrile (AICN) the theoretical study of Roy et al. has
concentrated on the description of the conversion of AICN to
adenine via addition of HCN, which is the crucial, rate determining step of the mechanism.44 (Scheme 1) They show that the
otherwise kinetically unfavorable reaction steps may proceed
with significantly lower activation energies if catalytic water or
ammonia molecules are involved in the chemical transformations. Another study by Glaser et al. has shown that monocyclic
HCN pentamers readily undergo cyclization leading to adenine
with surprisingly low activation barriers, which make this pathway
relevant also in an extraterrestrial environment.45 Photochemical
steps in the formation of nucleobases are overviewed in a separate
section devoted to prebiotic photochemistry.
Perspective
Formamide, formally the hydrolysis product of HCN, is
considered a thermodynamically more stable and thus lessreactive variant thereof.48 It has been suggested that formamide
could accumulate on the slowly cooling surface of the hot early
Earth as the thermal dissociation product of ammonium-formate,
formed in the reaction of NH3 and formic acid.6 Recently, a DFTbased AIMD study reported on the first simulation of a Miller-like
experiment.49 In this work, a liquid phase, constituted by simple
molecules such as water, ammonia, methane, carbon monoxide
and molecular nitrogen, was simulated under ambient thermodynamic conditions but under strong uniform electric fields,
which triggered the formation of small organic molecules, such
as formic acid and formamide. The latter one, in particular,
seemingly plays a ‘‘hub’’ role, being either broken into water
and HCN or CO and NH3 and, when reformed, being an
intermediate to the field-induced formation of larger molecules. In particular, it is able to form a C–C bond with formic
acid resulting in hydroxyglycine, which later evolves to glycine.
A follow-up of this study focused on the development of a novel,
general computational method, based on metadynamics,38
which allows an unbiased exploration of the chemical reaction
network of a given system, and/or the unbiased determination
of the most-convenient free-energy pathway of a given chemical
reaction.50 Furthermore, this approach allows treatment on the
same footing both gas-phase and condensed-phase reactions.
The study used the formamide dissociation/recombination to
HCN + H2O as a test-case, showing that in the solution under
ambient conditions reactants and products have comparable stability, with formamide being sizably more stable at
higher temperatures (400 K), and thus suggesting that the
formamide and the hydrogen cyanide prebiotic scenarios might
be compatible.
Experimental studies by Saladino and coworkers demonstrated
that in the presence of meteoritic materials all four nucleobases
can be synthesized from formamide.51,52 While the synthesis
reported in ref. 51 utilized thermal energy as an energy source,
the chemistry described in ref. 52 was triggered by protonirradiation, relevant to cosmic rays. The thermal mechanism of
the reaction was extensively studied using QC calculations.53–56
The main steps of the theoretically proposed reaction pathways
are summarized in Scheme 2A and B.
During the last 12 years, Civiš et al. published a series of
studies devoted to studying high-density-energy events as a
possible source of energy in prebiotic synthesis as well as extraterrestrial chemical processes.57–60 Recently, using ultra-high
Scheme 1 Pentamerization of HCN leads to adenine.46,47 Computations by Roy et al. have shown that the addition of HCN to AICN might be catalyzed
by water or ammonia molecules.44
This journal is © the Owner Societies 2016
Phys. Chem. Chem. Phys., 2016, 18, 20047--20066 | 20051
View Article Online
PCCP
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
Perspective
Scheme 2 Nucleobases from formamide. (A) The thermal route via pyrimidine nucleobases as suggested in ref. 5, 56 and 68. (B) A concurrent idea of the
thermal pathway assuming the formation of 2-iminoacetonitrile as the introductory step of the pathway.53–55,69 (C) The reaction route by Ferus et al.
utilizes high-energy activators ( NH2 and CN radicals) to trigger the formation of nucleobases in a clearly exergonic fashion.61 (D) A radical-route via
2-iminoacetonitrile by Jeilani et al.70
energy laser experiments, Ferus et al. convincingly demonstrated that all four nucleobases present in RNA can be formed
from formamide in a high-energy density event, like the impact
20052 | Phys. Chem. Chem. Phys., 2016, 18, 20047--20066
of an extraterrestrial body.61–63 This work outlined a chemistry,
which could be highly relevant to the early Earth, because during
the Late Heavy Bombardment period ca. four billion years ago,
This journal is © the Owner Societies 2016
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
PCCP
i.e. at the time when terrestrial life emerged, our planet likely
witnessed extreme impact activity, which endured for hundreds
of millions of years. The experiments presented in this work
support the view that high-energy precursors ( CN and NH2
radicals) formed in an extraterrestrial impact could induce a
cascade of chemical transformations that ended up with the
formation of nucleobases. In other words, the high-energydensity event first leads to a violent radical chemistry64,65 and a
destructive decomposition of the molecules, as expected. However, then in the cooling plasma a very rich creative chemistry can
occur. In other words, the extraterrestrial impacts may be not
only destructive, but also lead to easy spontaneous synthesis of a
rich spectrum of prebiotic molecules. Specifically for the synthesis of nucleobases from formamide, these transformations
could take place both in small reservoirs concentrating liquid
formamide on our planet and in the crust of a falling extraterrestrial body when reaching the Earth’s atmosphere. The latter
scenario might provide a plausible explanation for the formation
of nucleobases detected in meteorites.66,67 It suggests that
nucleobases may form during the impact from small molecular
precursors of extraterrestrial origin and do not need to be
imported from the space. In addition, it also explains the
presence of nucleobases and other complex molecules deep
inside the impacting species such as the Murchison meteorite.
The formation of large meteorites and asteroids through accretion
is necessarily associated with countless high-energy-density events
and under appropriate composition of the asteroid materials
will be necessarily associated with synthetic processes. The
work by Civis et al. is thus related not only to possible prebiotic
scenarios on the early Earth, but also to high-energy-density
impacts anywhere in the space. Essential for understanding
this chemistry is to take into consideration the fact that it
occurs under highly non-equilibrium conditions, where the
high-energy-density impact first decomposes the material and
the accumulated energy is then used for synthesis in the highly
variable process of cooling of the environment. The synthetic
processes so far detected experimentally in the high-energydensity events thus may be just the tip of the iceberg of real
chemistries that can be achieved, since an asteroid impact is
an incomparably more complex and powerful process than a
terawatt laser pulse. The temporal and spatial dimensions of the
radical-containing plasma cooling processes will be orders of
magnitude larger than in laser pulses, with enormous potential
for material mixing.
The high-energy synthesis of nucleobases described in
ref. 61–63 is a textbook example of the complementary role of
experiment and theory. The computations were instrumental to
propose a plausible pathway of the reaction (see Scheme 2C)
and were also essential in interpretation of the spectra. The
viability of the theoretical model was justified by the fact that
two of the proposed reaction intermediates of this multistep
pathway have been identified in the reaction mixture based
on their signatures in the experimentally measured highresolution infrared spectra. Note that the computations readily
identify other important intermediates that are not directly
detectable by the experiments due to their short life times.
This journal is © the Owner Societies 2016
Perspective
Thus, in fact, the resolution of the QC method is higher than
that of the experimental spectroscopy. The computations have
shown that the great advantage of the impact synthesis over the
thermal route is that due to the involvement of high-energy
activators the chemical transformations are exothermic and the
activation energies are much lower than those of the analogous
thermal pathways.
Further mechanistic proposals for the synthesis of nucleobases from formamide utilizing radical chemistry have been
presented by Jeilani et al. in ref. 70–72 (see Scheme 2D).
Sugars
According to the generally accepted view sugars can be synthesized from formaldehyde via the so-called formose reaction
(see Scheme 3).73,74 The formose reaction is a classical aldoladdition, which implies that one of the reactants enolizes prior
to the attack on the carbonyl group of the other reactant. This
excludes the possibility that two formaldehyde molecules can
dimerize on their own according to the aldol-mechanism. Thus,
the prerequisite for the success of this synthetic scenario is
that glycolaldehyde, at least in trace amounts, is present in the
reaction mixture.75
To form glycolaldehyde under plausible prebiotic conditions
has been for a long time a challenging task for the origin of life
studies and only a couple of proposals have been put forward
in the literature. Perhaps the most popular one assumes that
glycolaldehyde, an ubiquitous molecule in the space, was delivered
to the Earth from the space.75 Others suggest that it could be
formed in low concentrations via UV irradiation of formaldehyde76 or in the reaction of CH4 and CO2.77 Recently an HCNbased photochemical synthetic route has been suggested for the
synthesis of glycolaldehyde, which will be discussed in detail in
the photochemical part of this review.78 The latest study demonstrated that glycolaldehyde could have been synthesized in the
course of impacts of extraterrestrial bodies on the Earth.79
There exist numerous experimental reports on efficient catalytic
syntheses producing sugars from formaldehyde, nonetheless,
Scheme 3
The formose reaction.
Phys. Chem. Chem. Phys., 2016, 18, 20047--20066 | 20053
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
Perspective
PCCP
Scheme 4 Stereoelectronic reasons make the N-glycosylation of ribose
endothermic.86
Fig. 1 Optimized geometry of the ribose–borate 2 : 1 complex from QC
calculations (DFT B3LYP/6-311++G** calculations). The strongly stabilizing
H-bond between the 3 0 -hydroxyl of ribose and one of the anionic oxygens
of the borate is highlighted with a blue dotted line.82
the exact experimental mechanism has been deciphered only in
the case of the borate-assisted reaction route.80 The tremendous
potential of prebiotic borate chemistry lies not only in the fact
that borate minerals could sequester aldopentoses from the
prebiotic mix.75,81 Complexation by borate minerals provides a
clue to understand why among the four aldopentoses ribose has
been selected to be the component of the first genetic materials.
The studies of Benner et al. suggest that ribose forms the most
stable borate complexes,75 thus it could accumulate on the early
Earth in the highest concentration. QC calculations have suggested that a highly polarized intramolecular H-bond formed
between the anionic oxygen of borate and that of the 3 0 -hydroxyl
of ribose is responsible for the distinct stability of the complex
formed between ribose and borate-minerals (see Fig. 1).82 Logically,
analogous silicate complexes of aldopentoses have also been
studied both experimentally83 and using computations.84 Nevertheless, in these studies the preference for stabilization of ribose
was not as clear as in the case of borate-complexes.
Nucleosides
In the beginning of the new millennium Zubay and Mui wrote in
their critical assessment85 of the RNA-world theory: ‘‘The one
area where little progress has been made is on joining ribose to
the nitrogenous bases.’’ Physico-chemical reasons for this failure
are rather obvious: the syntheses of ribose and nucleobases from
small molecular precursors are markedly exothermic processes,
i.e., both molecules are highly stable and not apt for further
stabilization in the form of N-glycosides.86 A natural bond orbital
(NBO)-analysis87 of the electronic wave-function unraveled the
underlying reason for this. It has been shown that, due to
electron delocalization over the aromatic ring of the nucleobase,
nucleosides lack the stabilizing n - s* hyperconjugation from
the glycosidic N atom to the C10 –O4 0 antibonding orbital, which
leads to their partial destabilization with respect to free ribose
(see Scheme 4).86 Nonetheless, as experimental studies also
suggest, the N-glycosylation might be exothermic if it is preceded
by a phosphorylation step, because phosphorylation prevents the
stabilizing n - s* hyperconjugation in ribose-1 0 -phosphate.
Another novel possibility of forming nucleosides is the
formose-like condensation of formaldehyde and nucleobases
20054 | Phys. Chem. Chem. Phys., 2016, 18, 20047--20066
in a formamide-environment in the presence of UV-light and a
TiO2-catalyst.88 The experimentally suggested mechanism88
involves TiO2-catalyzed conversion of formamide to formaldehyde triggered by UV-light which is followed by N-formylation of
the base and subsequent formose-like chain extension steps.88
Albeit the N-glycosylation reaction has not yet been studied by
computational methods, a recent work89 offers a plausible
theoretical model for the conversion of formamide to formaldehyde over TiO2. More recently, it has been shown that
formamide irradiated with slow protons in the presence of
meteoritic materials also leads to the formation of nucleosides.52
The reaction most likely involves a radical chemistry, and might
serve as an exciting topic for future computations.
From nucleosides to nucleotides in formamide
Phosphorylation of nucleosides is essentially a condensation
reaction, and, as such, is obviously thermodynamically highly
disfavored in the presence of excess water molecules. In addition,
most of the phosphate minerals exhibit low solubility in water,
or if they are solvable, they are kinetically inactive.
Introducing formamide medium in the synthesis of prebiotic
building blocks solved also the problems related to the phosphorylation of nucleosides in an aqueous environment. It has
been suggested that phosphate minerals are solvable in formamide in the form of metaphosphates (see Scheme 5) which then
readily react with nucleosides leading to variously phosphorylated variants.90–92 Although metaphosphates could have never
been detected experimentally, ref. 90 puts forward the idea that
formamide, in contrast to water, may stabilize metaphosphates
via complex formation. Despite its high relevance, this ‘‘classical’’
problem of prebiotic chemistry has never been addressed by
computations. AIMD-simulations could provide an answer to
this question.
Aminooxazolines: a shortcut to nucleotides
The notion that both the glycosidation and phosphorylation
steps are highly disfavored in water motivated the efforts to find
Scheme 5
The metaphosphate anion.
This journal is © the Owner Societies 2016
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
PCCP
Scheme 6
Perspective
Main steps of the synthesis of cytidine-2 0 ,3 0 cyclic phosphate suggested by Powner et al.93
synthetic pathways diametrically different from the genealogical
approach used for decades in prebiotic chemistry, which tried to
build up nucleotides from their constitutional units, i.e. nucleobases, ribose and phosphates. The synthetic pathway proposed
by the Sutherland-group93,94 derives nucleotides from simple
organic precursors, like glycolaldehyde, glyceraldehyde, cyanamide and cyanoacetylene, and from inorganic phosphates (see
Scheme 6). A computational QC analysis86 of the free-energy
profile of this synthetic pathway shows similarities with that
of modern biochemical reactions, i.e., in contrast to the genealogical approach, this synthetic pathway includes smaller
energetic steps and proceeds in an exergonic fashion. In addition, the initial and concluding steps of the pathway are clearly
exergonic, i.e., the reaction is ‘‘pulled’’ toward the products,
cyclic nucleotides, which can accumulate in the prebiotic pool.
As Benner emphasized this is a common feature of modern
biochemical pathways.95
The mechanism of the reaction was analyzed computationally in ref. 96 and 97. It has been shown that phosphates –
in addition to being an obvious precursor needed to synthesize
nucleotides – play a unique catalytic role in the nucleotide
synthesis. Computations have shown that the amphoteric
character of phosphates enables them to participate as acid–
base catalysts in the key-step associated with the formation
of 2-aminooxazole (see Fig. 2). Let us note that phosphates
are the only ubiquitous anions existing in nature with oxidation
states varying from 0 to 3, which could also play a role in
their involvement in those chemical transformations that led
to the emergence of life on our planet. Since carbonates are
even more ubiquitous in the Earth’s crust than phosphates and
also exhibit an amphoteric character it would be interesting
This journal is © the Owner Societies 2016
Fig. 2 Phosphate catalysis in the rate-determining step of 2-aminooxazole
formation, i.e., the cyclization reaction.
to see by future experiments whether they exhibit the same
catalytic effect.
Quantum chemical calculations have shown that the regioselectivity of the phosphorylation reaction of the anhydroarabinonucleoside intermediate is governed by a stabilizing n - p*
hyperconjugation between the O5 0 of ribose and the C2QN3
linkage of cytosine.98
The astonishingly rich photochemistry triggered by UV irradiation undoubtedly available on the early Earth is also an important
part in Sutherland’s nucleotide synthesis model and is discussed
in detail in a separate section of this review.
Photochemical processes in the
synthesis of prebiotic building blocks
The total amount of UV-B and and UV-C radiation that reached
the surface of early Earth in the Archean age was much higher
than nowadays due to lack of the ozone layer99,100 and higher
activity of the young Sun in the ultraviolet range.101 Exposure of
Phys. Chem. Chem. Phys., 2016, 18, 20047--20066 | 20055
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
Perspective
the early Earth’s chemistry to sunlight resulted in the significant
enrichment of molecules that are exceptionally resistant to the
deleterious effects of UV irradiation.102 Therefore, the remarkable photostability of nucleic acids103,104 and peptides105,106 has
for long been considered as an important molecular fossil
indicating the invaluable role of UV radiation in the early stages
of abiogenesis.107–109 Ultraviolet light is also an important source
of energy that often promotes selective reactions which would
otherwise require significant amounts of heat or the presence of
a specific catalyst.
A thorough understanding of the underlying photochemical
reaction mechanisms can be essential for finding better variants
of the known prebiotically plausible reactions and might enable
their validation. Both theoretical and experimental approaches
can serve this purpose, providing different sorts of information.
Usually the most challenging problems can be tackled by a
synergistic approach, which allows assessing the results from
theoretical and experimental perspectives simultaneously.
Experiments ranging from NMR spectroscopic studies of
reaction products to time-resolved ultrafast measurements of
excited state dynamics may provide a lot of useful information
about the underlying elementary photophysical and photochemical processes. NMR spectroscopy proved to be particularly
useful in conjunction with isotopic labeling or when the substrates were irradiated in D2O.110 In the latter case incorporation
of deuterium from the environment could indicate a direct
involvement of water in the photorelaxation mechanism or a
possible photoinduced hydrogen atom transfer or abstraction
processes.110 In contrast, ultrafast time-resolved spectroscopic
approaches provide data about the evolution of photochemical
reactions on a femtosecond timescale.108,111 These methods
proved particularly useful in investigations of gas phase photochemistry of isolated molecules and clusters,108,111,112 but
recently more and more ultrafast spectroscopic experiments
are conducted on fully solvated compounds as well.113,114
High-level ab initio simulations facilitate the interpretation
of the experimental data and often provide answers to questions that cannot be approached using spectroscopic methods
alone. The central properties studied by computational photochemistry are conical intersections between two or more
electronic states of same multiplicity.115 These crucial points
on the potential energy surfaces are of comparable importance
as transition states for ground-state chemistry and enable the
identification of the existing photoreaction channels.115 For this
purpose, multiconfigurational self-consistent field (MCSCF)12
approaches with second order perturbation theory correction
(e.g. CASPT2)116,117 and multireference configuration interaction
(MRCI)12 yield a particularly reliable description of excited-state
potential energy surfaces, and state crossings. However, the
multireference and multiconfigurational approaches often
require significant computational resources and depend on
the arbitrary selection of active spaces.118,119 Coupled-cluster
based approaches like CC2120 and ADC(2)121 are usually very
robust and efficient alternatives,122,123 especially in conjunction
with resolution-of-the-identity approximation (RI).124 ADC(2)
was successfully used for simulations of biomolecular building
20056 | Phys. Chem. Chem. Phys., 2016, 18, 20047--20066
PCCP
blocks and showed relatively good performance when compared
to other computational methods and experiments.125 It should be
noted though that ADC(2) and CC2 are slightly less accurate than
CASPT2 in predicting excitation energies and are not applicable
for systems with clearly multiconfigurational character of the
ground state.126 Special caution needs to be taken with respect to
the popular time-dependent density functional theory (TDDFT)
computations, which are highly dependent on the choice of the
functional and generally should be benchmarked for specific
applications against higher level ab initio methods.118
For many decades, UV-light has been considered as an
important element of synthetic experiments simulating conditions that conduced abiogenesis. One of the first and most
prominent examples is the series of studies by Ferris and
co-workers related to pentamerization of HCN leading to
adenine, which appeared between 1966 and 1974.46,47,127–129 The
multistep photoisomerization of diaminomaleonitrile (DAMN) to
AICN is one of the key steps of this reaction sequence.128 Even
though the scenario proposed by Ferris was a milestone in
studies of the origins of RNA, some drawbacks can be pointed
out including the necessity of considering HCN ices as the
reaction environment130 and the lack of efficient pathway
leading from nucleobases to nucleosides (owing to both kinetic
and thermodynamic reasons).4 A notable modification of this
pathway was published in 2010 by Barks et al.,131 who showed
that the same reaction can be conducted in neat formamide
and formamide solutions yielding guanine and hypoxanthine
as additional products apart from adenine. Mechanistic details
of the above reactions were investigated theoretically. Barbatti
et al.130 proposed a full reaction mechanism of the multi-step
DAMN to AICN photoisomerisation based on non-adiabatic
molecular dynamics simulations. This reaction pathway is
also consistent with some of the mechanistic suggestions of
Ferris et al.128 The initial DAMN to diaminofumaronitrile
(DAFN) photoisomerisation mechanism was also described in
detail by Szabla et al.,132 and was shown to occur on the singlet
hypersurface and not with the participation of triplet states as
formerly postulated by Ferris et al.128 An interesting alternative
to the photoinduced HCN oligomerization involved photocatalytic formation of all five nucleobases from formamide on
the reactive TiO2(001) surface.133
In 1970, Sanchez and Orgel published a prebiotically plausible and indirect photochemical route leading to pyrimidine
nucleosides which did not involve the endergonic nucleobase
glycosylation.134 The synthesis assumed the formation of aminooxazoline from D-ribose and cyanamide, and the further formation of a-ribocytidine after the reaction of aminooxazoline with
cyanoacetylene. Irradiation of alpha-ribocytidine resulted in
partial photoanomerisation to the biologically relevant b-cytidine,
with a relatively low yield of just 4%.134 Even though the
reaction was criticized because of problems in obtaining a
prebiotically plausible pathway to ribose135 and low reaction
yield, it became an important inspiration for a series of studies
published by Sutherland and co-workers which eventually
resulted in a very elegant synthesis of pyrimidine nucleotides
from small feedstock molecules.93,136–140 While the former
This journal is © the Owner Societies 2016
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
PCCP
studies considered the ways of enhancing Orgel’s134 photoanomerisation reaction,139,140 the latter and most successful
contribution proposed a different role for UV light.93 Namely,
UV irradiation purified the product mixture by destructing the
biologically irrelevant stereoisomers of pyrimidine nucleotides.
In addition, it enabled the partial conversion of cytidine to
uridine.93
Szabla et al.110 investigated the photoanomerisation mechanism of 2 0 -deoxycytidine which evinced somewhat similar photochemistry to its ribo-counterpart (see Fig. 3).139 Joint theoretical
and experimental efforts led to the conclusion that the photoanomerisation of 2 0 -deoxycytidine is triggered by the excited-state
C1 0 –H atom abstraction by the carbonyl group of cytosine.110 It is
tempting to assume that a similar mechanism could explain the
photoanomerisation of ribocytidines, however, the presence of
the 2 0 -OH group may significantly alter the photochemistry of a
nucleoside. This is reflected by the formation of oxazolidinone in
the products of Sutherland’s synthesis,93 and the ultrafast intramolecular electron-driven proton transfer mechanisms proposed
for adenosine and 8-oxoguanosine.141,142 Therefore, the apparently more complex photochemistry of a-ribocytidine is currently
under exploration. Furthermore, efficient prebiotic routes to
pyrimidine nucleosides (and not only nucleotides) and their
purine counterparts are among the most prominent challenges
that can be addressed in this topic.
Initially, one of the major uncertainties of Sutherland’s
synthesis of pyrimidine nucleotides was the origin of an important substrate and the simplest sugar, i.e. glycolaldehyde. For
many years, it was anticipated that sugars on the early Earth
could have been formed from formaldehyde via the basecatalysed formose reaction.74 As mentioned before, C–C bond
formation between two formaldehyde molecules is prevented by
the inherent polarity of the carbonyl group and thus the formose
reaction does not operate without at least trace amounts of
glycolaldehyde early on. A plausible synthesis of glycolaldehyde
from one-carbon substrates was proposed in 2012, and involved
photoredox cycling of copper cyanide complexes in the presence
of HCN.78 The mechanistic rationale for this reaction is based on
the generation of cyanogen and hydrated electrons among the
Perspective
initial photoproducts. An alternative mechanism was derived
from DFT and MP2 simulations and considered the possible
role of dipole bound anions.143 However, this photochemical
reaction pathway requires further validation with MCSCF-based
approaches, and a direct comparison to the mechanism proposed
by experiments.
The above-mentioned reaction pathways often contain intermediates that are supposed to accumulate in the environment
over longer periods of time. Therefore, these compounds should
evince resistance to different environmental conditions of early
Earth including UV radiation. Probably the most distinctive
intermediates that appeared in the prebiotically plausible reaction pathways described above are AICN128 and 2-aminooxazole
(a precursor of pyrimidine nucleotides in Sutherland’s suggested
synthesis).93 The photostability of AICN was observed by Ferris,128
however, there is no experimental evidence for the photostability
of 2-aminooxazole. Gas phase ab initio calculations identified the
major photodeactivation mechanisms of 2-aminooxazole and
AICN as N–H bond fission and ring-puckering processes, driven
by ps* and pp* electronic states respectively.144,145 Furthermore,
non-adiabatic molecular dynamics simulations of 2-aminooxazole
revealed a relatively large contribution of the potentially photodestructive ring-opening channel, which implies that further
studies are necessary to elucidate the photochemistry of this
molecule.146
When investigating the photochemistry and photostability
of biomolecules it is crucial to look at the environmental effects
exerted on the chromophores that could potentially modify the
photorelaxation mechanisms. Even though it is tempting to
apply one of the widely used continuum solvation models, such
an approach does not take into account the possible direct
involvement of strongly interacting solvents (e.g. water). For
instance, in the case of chromophores with low-lying ps*
electronic states, water significantly alters the N–H bond fission
mechanism. Photoexcitation of indole, phenol, AICN and
2-aminooxazole clustered with several water molecules results
in the ejection of one electron in the direction of the solvent
molecules (also referred to as charge transfer to solvent).145–148
The electron may be then followed by a proton from an
Fig. 3 The mechanism of the photoanomerisation and nucleobase loss reactions of 2 0 -deoxycytidine triggered by excited-state hydrogen atom
abstraction by the carbonyl group of cytidine.
This journal is © the Owner Societies 2016
Phys. Chem. Chem. Phys., 2016, 18, 20047--20066 | 20057
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
Perspective
amino (or hydroxyl) group of the chromophore leading to the
formation of a complex containing a radical of the deprotonated
molecule, the hydronium cation and a hydrated electron.148
Subsequent proton transfers along H2O wires leading to the
recombination of the migrating proton with the hydrated electron
may enable photodeactivation via a conical intersection with the
electronic ground-state.145,146 This was shown for both prebiotically relevant intermediates, AICN and 2-aminooxazole.145,146
Another photorelaxation mechanism involving the direct participation of solvent molecules is the water-to-chromophore electron transfer reported by Barbatti for microsolvated adenine.149
It is worth noting that these mechanisms would not be
observed in conventional QM/MM simulations treating all the
water molecules surrounding the chromophore at the molecular mechanics level.
Formamide, water, or both?
The role of water in prebiotic chemistry is a controversial topic.
Even though water is supposedly the environment in which life
originated, chemical precursors such as formamide and hydrogen cyanide (and their derivatives) might be degraded in water,
decreasing the effectiveness of their role in the synthesis of
biomolecules.150 A plausible way for the formation of formamide on the early Earth could be the hydrolysis of HCN. HCN
is a gas at ambient pressure and temperature. Once absorbed in
water it undergoes two possible processes depending on pH and
concentration: (a) direct condensation to biomolecules, like
adenine, or polymerization to poly(hydrogen cyanide) derivatives
that may be transformed further into biomolecules or (b) the
hydrolysis by addition of H2O on the CN triple bond to give
formamide. These two competitive processes show a similar
kinetics at relatively high HCN concentrations, in the range
between 0.01 and 0.1 M, and at alkaline pH (the optimal value
being between pH 8 and 9). The hydrolysis of formamide prevails
in more dilute solutions.47 A theoretical study on the possible
concentration of HCN on early Earth suggested that the steady
state concentration of HCN in the primitive ocean was
4 1012 M at pH 7 and 100 1C, with a slight increase of concentration at lower temperature (2 105 M at pH 7 and 0 1C).151
Similar results were obtained for formamide. These concentration values appear to be too low for the formation of the
appropriate amounts of biomolecules suitable to support the
emergence of life. On the other hand, alternative mechanisms
exist for the solution of this problem, as for instance, the
processes based on the colligative properties of the two compounds. HCN and formamide might have accumulated through
the formation of an eutectic phase with water at low temperatures, as reported for HCN, or by evaporation processes, a
phenomenon that affects mainly formamide, which is characterized by a high boiling point (4200 1C) without azeotropic effects
with water.152 Furthermore, concentration processes might have
been favored by the presence of minerals, considering as an
example the high efficiency of absorption of formamide in clays
of the montmorillonite family.153 Thermoconvention processes
20058 | Phys. Chem. Chem. Phys., 2016, 18, 20047--20066
PCCP
can also concentrate formamide. Thermal condensation of
mixed formamide/water in the presence of iron sulfur and
iron–copper sulfur minerals yields a significant panel of compounds, including two nucleobases (adenine and cytosine)
and one carboxylic acid (oxalic acid). The amount of products
decreased by increasing the water content, only few compounds
being detected in the presence of 30 wt% water154,155 The
synthesis is more efficient in the presence of meteoritic materials,
yielding a larger panel (in larger amount) of biomolecules (data on
submission for publication). Another plausible way for the accumulation of formamide on the hot surface of early Earth is the
thermal dissociation of ammonium-formate at B180 1C. This
temperature is significantly higher than the boiling point of water
and therefore the latter synthetic way could lead to the accumulation of an essentially water-free formamide medium.6
Recent progress of the AIMD simulation techniques enables
an explicit quantum chemical treatment of solvent molecules,
which might revolutionize the understanding of the formamidechemistry. Such calculations could thus be instrumental to
provide with the long-sought answer to the question: how does
chemical reactivity change with the formamide/water ratio?
Creating the first templates
Modern biochemical machineries utilize templates to form oligonucleotides, but how did nature create the very first templates
without enzymes from nucleotide building blocks? This has been
one of the most intriguing questions of the origin of life research
for decades.
Historically, the first proposals for template-free non-enzymatic
oligomerization of nucleotides came from the 70’s and 80’s
of the last century. The recognition that cyclic nucleotides (see
Scheme 7A) are readily formed upon phosphorylation of nucleosides in the presence of urea156 fostered the first efforts to use
them as precursors to synthesize oligonucleotides.157 The clearly
exothermic character of the hydrolysis of cyclic nucleotides158
demonstrated that cyclic ring formation accumulates energy
which can serve as the driving force for transphosphorylation
reactions leading to oligonucleotides. Early synthetic approaches
by Verlander and Orgel157 as well as by Usher and Yee159 utilized
Scheme 7 The phosphate group of nucleotides may be activated (A) in
the form of cyclic ring formation or activation via cyclization or (B) by the
formation of phosphoimidazolides.
This journal is © the Owner Societies 2016
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
PCCP
these chemistries to create short oligonucleotide sequences.
Later studies suggested that higher oligomerization yields can be
achieved when incorporating a phosphate-activation step in the
synthetic scheme prior to the polymerization (see Scheme 7).160
This motivated a series of studies utilizing imidazole to activate the
phosphate group of nucleotides for the polymerization reaction.160
More recently, the success of demonstrating plausible prebiotic routes to cyclic nucleotides5,92–94 shifted the attention of
experimentalists again to cyclic nucleotides. Oligomerization of
3 0 ,5 0 -cyclic guanosine monophosphate (GMP)161–164 represents so
far the only known nonenzymatic template-free polymerization
method, which yields selectively 3 0 ,5 0 -linked oligonucleotides. Let
us note here that in the literature experiments of the Braun
group163 have been intensively used to refute the experimental
results in ref. 161 and 162. However, the detection limits of the
fluorescence labelling method used by Braun et al. in ref. 163
were clearly not sufficient to detect the oligomers reported in
ref. 161 and 162 (see ref. 6 for more details).
The first mechanistic studies on the stereochemistry of the
transphosphorylation reactions leading to oligonucleotides were
based on a thorough analysis of crystal geometries of cyclic
nucleotides. Usher and Yee in their seminal study demonstrated
that oligomerization of 2 0 ,3 0 -cyclic nucleotides involves an in-line
attack of the 5 0 -hydroxyl of the ribose at the phosphate of the
other reactant. Since the nucleophilic attack at phosphorus is
sterically not hindered, both 2 0 ,5 0 - and 3 0 ,5 0 -linkages may form in
the reaction.159
A major step forward in uncovering the general principles
of the chemistry that drives the template-free non-enzymatic
oligomerization came from recent QC calculations. These
studies suggested a unique anionic ring-opening polymerization mechanism leading to 3 0 ,5 0 -linkage selectivity in the oligomerization of 3 0 ,5 0 GMPs (see Fig. 4).164 Analogous ring-opening
cyclic polymerization reactions of cyclic phosphate and phosphonate esters were documented in ref. 165 and 166. The QC
model shows that the reaction is optimal under anionic conditions while no efficient reaction pathway was found under
Perspective
neutral conditions. The model164 thus reflects the experimental
observation that the efficiency of the reaction decreases with
increasing concentration of highly mobile cations, like Na+,
while it is totally unaffected in the presence of slowly moving
bulky alkylammonium cations.
Although the QC technique is robust enough to capture
the basic intrinsic electronic structure properties of different
potential reaction pathways assuming certain reactants and their
configurations, QC modelling of fine environmental effects of
biologically relevant reactions is not easy with the presently
available techniques (see above). With the available methods
and hardware, we are not able to simultaneously achieve a bruteforce description of (i) an efficient treatment of hydrated cations
distributed in the vicinity of reaction complexes and (ii) an
accurate description of the reaction pathways in reaction complexes consisting of ca. 200 atoms. In the near future, emerging
large-scale QC modelling methods presented, for example, in
ref. 168–170 may provide a solution for the above problem. Most
likely, these problems will require the development of case-bycase multiscale approaches where the cation distributions will
be first probed by classical atomistic simulations. Extended
classical MD can reveal the distribution of the ions depending
on their concentration and identify the main ion-binding sites
coupled with the solute structural dynamics.171–173 Then a series
of potential reactive conformations suggested by atomistic simulations can be investigated by large-scale QC or hybrid quantumclassical methods, in a way reminiscent of studies of catalytic
mechanisms of ribozymes.174–177
Note that modern calculations are capable of unambiguously
identifying the reaction pathways for some efficient enzymatic
reactions that are precisely geometrically tuned to every single
atomistic detail. However, the calculations are not always sufficient to obtain an exact single atomistic reaction pathway for
systems where more atomistic pathways with similar reaction
profiles co-exist and even in reality contribute to the reaction. This
is likely to be the case of ribozymes as well as of many prebiotic
chemical reactions that are more loosely structurally controlled.
Fig. 4 Stacking interactions are responsible for the 3 0 ,5 0 -linkage selectivity of the anionic ring-opening polymerization of 3 0 ,5 0 cyclic GMPs. Dispersioncorrected DFT calculations using the DFT-D2 formalism167 developed by Grimme helped to unravel the reaction mechanism. Computations in ref. 164
have shown that in the chain-propagation step the 3 0 -deprotonated oxygen of a 5 0 -GMP is optimally positioned to initiate an in-line attack at the next
cyclic phosphate of the stacked supramolecular architecture. Thus, the genuine self-assembly of 3 0 ,5 0 cyclic GMP is sufficient to arrange the molecules in
such a way that they can reach highly reactive configuration essentially from the ground state configuration without any substantial rearrangements.
This journal is © the Owner Societies 2016
Phys. Chem. Chem. Phys., 2016, 18, 20047--20066 | 20059
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
Perspective
However, the calculations can decidedly prove if a reaction is
electronically feasible, i.e., if the system is ready to react under
appropriate reactant arrangements.
Another comparative theoretical study addressed the mechanism of all known non-enzymatic template-free oligomerization
scenarios, which utilize non- or mildly activated precursors
(i.e. nucleotides or cyclic nucleotides).178 It has illuminated that
the role of simple amines in the synthesis is to activate the
phosphate via proton-transfer processes. The study has shown
that basically the same principle of activation is relevant to the
recent experimental work by Deamer and Maurel, who report
that adenosine- and uridine 5 0 -monophosphates efficiently
co-oligomerize in a highly acidic hydrothermal environment
(see Fig. 5).179
Non-enzymatic, template free oligomerization of imidazoleactivated oligonucleotides over montmorillonites was demonstrated by the Ferris group.180 The reaction has been extensively
studied using computational methods as well. Mignon et al.
provided a detailed QC characterization of the adsorption of
nucleobases onto the external surface of montmorillonite using
periodic plane-wave calculations.181–183 This, otherwise very
promising approach, due to size limitations could not be
so far applied to describe the transphosphorylation reaction
leading to the phosphodiester linkage. Ferris et al. reported that
the montmorillonite-catalyzed oligomerization of nucleosidephosphoimidazolides exhibits a remarkable homochiral
selectivity.184,185 Classical MD simulations by Matthew and LutheySchulten have shown that activated nucleotides preferentially
PCCP
form homochiral supramolecular assemblies over the montmorillonite surface prior to the oligomerization.186 The same
homochiral selectivity was also observed in the formation of
cyclic dinucleotides. QC calculations have suggested that this
might be caused by the lower stability of heterochiral forms as
compared to the homochiral ones.187
Template directed oligomerization
As Leu et al. formulated ‘‘Nonenzymatic, template-directed synthesis of nucleic acids is a paradigm for self-replicating systems’’.188
Starting from 1980s several highly efficient template-directed
oligomerization (see Fig. 6) methods have been elaborated utilizing
nucleotide-activation in the form of phosphoimidazolides.189–192
This relatively simple chemistry involves transphosphorylation
steps between the activated 5 0 -phosphate group and the 2 0 or
3 0 -hydroxyls of the ribose. Proper positioning of the nucleotides
is ensured by H-bonding and stacking interactions with the
template. Since the transphosphorylation steps can be initiated
by both the 2 0 and 3 0 hydroxyls of the ribose the reaction
produces a mixture of 2 0 ,5 0 - and 3 0 ,5 0 -phosphodiester linkages.
This motivated the combined experimental–theoretical study
of Sheng et al., aimed at analyzing how incorporation of the
‘‘unnatural’’ 2 0 ,5 0 -linkages might influence the function of RNA
molecules.193 Their classical molecular dynamics simulations
suggest that RNA duplexes are flexible enough to accommodate
a low amount of such linkage heterogeneities without substantially influencing the global folding, although the force-field
choice could be a concern in this particular case.29
The route towards functional RNAs
The evolution of species as we see it today was made possible
by a perfectly designed RNA-machinery, which is based on a
complex network of tertiary interactions involving thousands
of atoms. Since the evolutionary function of RNA is strongly
associated with its catalytic function, one can reasonably raise a
question, is RNA-catalysis possible with simple oligonucleotides?
Can RNA catalysis arise spontaneously and what are the simplest
RNA systems that can exhibit at least some catalytic activities?
Fig. 5 Amines157,159 and protons179 catalyze the oligomerization of nucleotides. The role of amines in the non-enzymatic oligomerization of cyclic
nucleotides has for long been an enigma of the origin of life research. After
40 years a plausible explanation has come from recent QC calculations.178
They have suggested that protonation of the phosphate oxygen either via
H-bonding with protonated amines or direct proton-binding improves the
kinetics of various template-free non-enzymatic oligomerization scenarios
because it makes the phosphorus of the substrates more positive. This study
exemplifies that ‘‘in silico’’ studies can provide a unique insight into such
physico-chemical details of prebiotic processes, which are otherwise completely inaccessible for experiments.
20060 | Phys. Chem. Chem. Phys., 2016, 18, 20047--20066
Fig. 6
Oligomerization of nucleotides along a template.
This journal is © the Owner Societies 2016
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
PCCP
Recent experiments of the Di Mauro group have shown that
Watson–Crick (WC) complementary oligonucleotide strands as
short as ca. 9–12 nucleotides may be associated with a catalytic
activity194–196 and MD simulations have helped to disclose the
underlying chemical mechanisms.196 They have shown that
transient catalytic centers (see Fig. 7) might be stabilized even
by short oligonucleotides for sufficiently long times (for several
tens to hundreds of nanoseconds) to support a very primitive
form of RNA-catalysis.6 Basically, the model presented in ref. 6,
195 and 196 suggests that catalytic activity of RNA could have
emerged as a result of (i) the hydrolytic instability of RNA and
(ii) the transient stabilization of imperfectly paired forms of
WC-complementary donor and acceptor oligonucleotide strands.
The MD simulations can be considered as a textbook example of
application of the method to catalyzed reactions. Although the
MD method cannot directly capture the chemical reaction, it can
suggest the formation of catalytically relevant geometries. In this
particular case, the formation of tetraloop-like overhang geometries appeared to be critical to access the catalytically competent
micro-arrangements. Note that the catalysis does not need to be
promoted by the dominantly populated arrangements, but may
proceed from rarely sampled but highly-reactive configurations
(minor species), which are difficult to capture by experimental
methods. The above-noted simulations also greatly profited from
the recently reached ms-scale of the simulations and substantial
improvement of the AMBER RNA force field.197 Shorter simulations would not be sufficient to obtain the structural insights
while older versions of the RNA force field would provide
Perspective
unstable trajectories. A possible extension of this research
could be to evaluate whether 3- and 5-loops may also provide
a similar catalytic function. Nonetheless, due to the complexity
of the studied system, any efforts in this direction must be
based on a very firm experimental background. As we cautioned
above, the currently available RNA simulation force fields are
far from being perfect. The single-stranded RNA regions and
over-hangs, albeit looking simple at first sight, are exceptionally
difficult for MD simulations due to their broad unrestricted
conformational space.
Currently, perhaps the most challenging goal of the origin of
life field is to understand the connections between the RNAand protein worlds. Indeed, it has been demonstrated that very
simple oligonucleotides could make the first steps on this
road.198 Experiments by Yarus and coworkers have shown that
catalytic centers formed by as few as 3 nucleotides are able to
mediate aminoacylation of oligonucleotides.199 MD simulations
by the same group led to the proposal of a plausible structural
model of the reaction center. Based on the structural-dynamics
data the authors suggested that the aminoacylation is made
possible by a proton transfer from the 2 0 -hydroxyl of the
3 0 -terminal uridine to the carbonyl oxygen of the phenylalanineadenylate substrate.199 Essentially, the proton transfer increases
the positive charge on the carbonyl C of the substrate, which
makes this activation mechanism highly reminiscent of those
used to activate cyclic nucleotides for transphosphorylation
leading to the formation of oligonucleotides in a nonenzymatic
template-free manner.157,178
Outlook and summary
Fig. 7 MD simulations have suggested that tetraloop-like overhangs may
mediate the cleavage of the 5 0 -terminal nucleotide of the donor strand.
A prerequisite for the reaction is the stabilization of the imperfectly paired
form of the WC complementary donor and acceptor strands. This requires
about 5–6 WC base pairs, which set the lower limit of oligonucleotide
length to ca. 10 nucleotides necessary for the onset of RNA-catalysis.
This journal is © the Owner Societies 2016
We provide an account of theoretical studies which are aimed
to complement experiments to unravel chemical routes leading
to the emergence of life on our planet. The examples shown
illustrate that modern computational chemistry provides an
impressive arsenal of powerful tools to study the origin of life at
various levels. It should be noted that modern computational
chemistry is still under-represented in the prebiotic field compared to many other areas of chemistry and biochemistry, which
in addition are often dealing with considerably more complex
chemical reactions than prebiotic chemistry.
Perhaps one of the most ubiquitous areas of application so
far has been the energetic characterization of reaction pathways
of simple prebiotic reactions at the electronic-structure level
of resolution, where QC theory has made enormous progress
recently. Contemporary standard QC is capable of providing
a close-to-converged description of the intrinsic electronic
structural changes (assuming the idealized configuration of
the reactants) of the ground-state chemical reactions. However,
future studies should provide more insights into the effects
of chemical environment on modulation of the chemical reactions, as noted above.
Further development of computational models related to
the prebiotic chemistry of nucleic acids is possible in two
directions.
Phys. Chem. Chem. Phys., 2016, 18, 20047--20066 | 20061
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
Perspective
The ‘‘vertical direction’’ follows basically the trend dictated
by experimental research and progresses towards higher and
higher levels of molecular evolution. Undoubtedly, the synthesis
of nucleic acid building blocks has so far been the most popular
area of origin of life research addressed by computations. Albeit
there are still many questions to solve in this topic, in the
experimental literature a gradual shift can be recognized
towards larger systems, such as the formation of the simplest
oligonucleotide architectures or the origin of translation. In our
opinion, these are the areas where modern computations have
the potential to visibly improve our understanding in the near
future. The increase of complexity of the systems will likely lead
to applications of methods similar to those used in studies of
enzyme reactions.174–177
The ‘‘horizontal direction’’ means that at each level of molecular complexity new methodological approaches bring about a
more comprehensive description of the studied systems. One
promising development is the use of quantum molecular
dynamics instead of mere potential energy scans in the studies
of chemical reactions.49 While the latter approach is equivalent to
the 0 K electronic energy scans from a given configuration of the
reactants, the former approach allows including the Boltzmann
sampling, i.e., the real thermodynamics (free energy surfaces
instead of potential energy surfaces). Ideally, such methods
should be capable of spontaneously reaching the reactive configurations from an equilibrated ensemble of the ground state.
Note that the reactive configurations do not always correspond
to the dominantly sampled conformation, i.e., the actual chemical
transition may be initiated from a rarely accessed but highly
reactive configuration. In addition, thermal sampling of the
orthogonal (with respect to the reaction path) degrees of freedom
may significantly contribute to the reaction kinetics. It is well
established from enzyme reactions that thermal motions can be
essential.200–202
The cardinal problem of computational biochemistry has
always been the balance between the accuracy of the primary
description of the chemical problems and the sampling of the
configurational space. Both issues are critically important for
chemical reactions. On one hand, computational chemistry
possesses exceptionally accurate QC methods to study (in the
ground state) reaction pathways provided the reactive configuration of the reactants is known. Thus, we have powerful
methods to study the energetics of the reactions along pathways with pre-determined reactant and product configurations
while disregarding the thermal motions. We also have approximate force fields that allow large-scale MD simulations. What is
currently missing are intermediary methods that would be
sufficiently intrinsically accurate and would at the same time
allow appropriate sampling. As noted above, there are intense
ongoing efforts to develop such methods starting from both
‘‘classical’’ and ‘‘electronic structure’’ corners of the description. One direction includes the development of refined pairadditive and polarizable force fields. The other direction is the
development of fast QC methods. Unfortunately, as mentioned
several times above, achieving a balance between accuracy and
speed appears to be a real challenge. While the pair-additive
20062 | Phys. Chem. Chem. Phys., 2016, 18, 20047--20066
PCCP
force fields may be at the edge of their principally achievable
accuracy,26 polarizable force fields face unexpectedly large
problems when balancing all the energy contributions. All our
tests of fast QC methods for real chemical problems similar to
those in prebiotic chemistry (such as RNA self-cleavage reactions
or description of RNA chain conformations) so far revealed a
rather detrimental loss of accuracy.23,203 None of the available
methods of the so-called semi-empirical nature (QC methods
that include adjustable parameters, such as various variants of
PM6 or AM1 approaches) that we tested provided satisfactory
results. For conformational energies, their accuracy dropped
below the AMBER force field performance23 while for chemistry
we, for example, documented a loss of non-bridging phosphate
oxygen when calculating free energy surface of the hairpin
ribozyme self-cleavage reaction.203 It looks like that we are losing
accuracy far more quickly than gaining the speed. Although this
is an area of intense ongoing research in many leading methoddeveloping laboratories, it is uncertain if and when fast and
accurate QC methods will be available for biomolecular structure
and chemistry computations. Nevertheless, even without marked
method breakthroughs, the mere increase of the capacity of
available hardware and optimized efficiency of the computer
codes are opening windows for new applications.
A representative example of the growing capacity of computational methods are the recent AIMD simulations. Until
very recently, almost all computational studies in prebiotic
chemistry neglected the molecular and dynamic nature of the
chemical environment (explicit inclusion of solvent molecules,
finite temperature and pressure, mineral surfaces, etc.). Two
main reasons hampered more realistic investigations: the very
large computational cost of AIMD simulations including several
hundreds of atoms and the lack of robust enhanced sampling
methodologies flexible enough to afford free energy landscapes
for a range of (possibly unknown) different reaction mechanisms.
Both of these issues are becoming resolvable, thanks to the fast
improvement of high-performance computers on one hand and
of innovative algorithms on the other hand. The sampling
problem may be partially eliminated by using important
sampling methods, such as the metadynamics. The important
sampling methods identify the fundamental degrees of freedom (so-called collective variables, typically the reaction paths)
which allow minimizing the time spent by sampling thermal
fluctuations of the less relevant degrees of freedom. This, in
principle, enables a more accurate description of the effect of
the environment on the mechanism of a chemical reaction. In
the next decade we expect progressive accumulation of a large
body of knowledge about prebiotic reaction mechanisms and
free energy profiles in a series of different condensed-phase
environments. Albeit the method is highly challenging, there is
space for further development. In particular, the development
of simulation techniques deciphering out-of-equilibrium processes will play a central role.
We also expect substantial progress in state-of-the-art ab initio
approaches to study mechanisms of photochemical reactions,
which remain very costly. Since UV-light was suggested as an
important source of energy in multiple prebiotically plausible
This journal is © the Owner Societies 2016
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
PCCP
reaction pathways, a thorough understanding of the underlying
mechanisms may eventually guide us towards the prebiotic
synthesis of the remaining biomolecular building blocks.
We hope that the current review provides a compelling
evidence about the predictive power of computational methods.
Albeit we understand that theory cannot solve the problem of
the origin of terrestrial life on its own, we believe that it is able
to transmit ideas, interpret experiments, provide predictions
and universalize the results and concepts. A close collaboration
between experimental and theoretical groups will be essential to
fully exploit the arsenal of computational methods in prebiotic
chemistry. We hope that this potential of modern computational
methods will also be fruitfully utilized by experimental chemists
working on the origin of life (as it is becoming common in many
other areas of chemistry), because as the great Carl Sagan taught
us: ‘‘Imagination will often carry us to worlds that never were.
But without it we go nowhere.’’204
Acknowledgements
Financial support from the grant GAČR 14-12010S is gratefully
acknowledged. JS acknowledges support by Praemium Academiae.
This research has been financially supported by the Ministry of
Education, Youth and Sports of the Czech Republic under the
project CEITEC 2020 (LQ1601).
References
1 W. Gilbert, Nature, 1986, 319, 618.
2 L. E. Orgel, J. Mol. Biol., 1968, 38, 381–393.
3 A. I. Oparin, The Origin of Life, Moscow Worker, Moscow,
1924.
4 J. D. Sutherland, Angew. Chem., Int. Ed., 2016, 55, 104–121.
5 R. Saladino, G. Botta, S. Pino, G. Costanzo and E. Di Mauro,
Chem. Soc. Rev., 2012, 41, 5526–5565.
6 J. E. Šponer, J. Šponer, O. Nováková, V. Brabec, O. Šedo,
Z. Zdráhal, G. Costanzo, S. Pino, R. Saladino and E. Di Mauro,
Chem. – Eur. J., 2016, 22, 3572–3586.
7 J. Šponer, J. E. Šponer, A. Mládek, P. Jurečka, P. Banáš and
M. Otyepka, Biopolymers, 2013, 99, 978–988.
8 J. Tomasi, B. Mennucci and R. Cammi, Chem. Rev., 2005,
105, 2999–3094.
9 J. Šponer, J. E. Šponer, A. Mládek, P. Banáš, P. Jurečka and
M. Otyepka, Methods, 2013, 64, 3–11.
10 C. Møller and M. S. Plesset, Phys. Rev., 1934, 46, 618–622.
11 J. Čı́žek, J. Chem. Phys., 1966, 45, 4256–4266.
12 P. G. Szalay, T. Muller, G. Gidofalvi, H. Lischka and
R. Shepard, Chem. Rev., 2012, 112, 108–181.
13 B. O. Roos, P. R. Taylor and P. E. M. Siegbahn, Chem. Phys.,
1980, 48, 157–173.
14 E. Schrödinger, Phys. Rev., 1926, 28, 1049–1070.
15 P. Hohenberg and W. Kohn, Phys. Rev., 1964, 136,
B864–B871.
16 S. Ehrlich, J. Moellmann and S. Grimme, Acc. Chem. Res.,
2013, 46, 916–926.
This journal is © the Owner Societies 2016
Perspective
17 S. Grimme, Chem. – Eur. J., 2012, 18, 9955–9964.
18 Y. Zhao and D. G. Truhlar, Acc. Chem. Res., 2008, 41,
157–167.
19 S. Grimme, Wiley Interdiscip. Rev.: Comput. Mol. Sci., 2011,
1, 211–228.
20 Y. Zhao and D. G. Truhlar, J. Chem. Theory Comput., 2011,
7, 669–676.
21 A. J. Cohen, P. Mori-Sánchez and W. Yang, Chem. Rev.,
2012, 112, 289–320.
22 W. Koch and M. C. Holthausen, A Chemist’s Guide to
Density Functional Theory, Wiley, Weinheim, New York,
2nd edn, 2001.
23 H. Kruse, A. Mladek, K. Gkionis, A. Hansen, S. Grimme and
J. Sponer, J. Chem. Theory Comput., 2015, 11, 4972–4991.
24 R. Sure and S. Grimme, J. Chem. Theory Comput., 2015, 11,
3785–3801.
25 L. Goerigk and S. Grimme, Phys. Chem. Chem. Phys., 2011,
13, 6670–6688.
26 J. Šponer, P. Banáš, P. Jurečka, M. Zgarbová, P. Kührová,
M. Havrila, M. Krepl, P. Stadlbauer and M. Otyepka, J. Phys.
Chem. Lett., 2014, 5, 1771–1782.
27 C. Abrams and G. Bussi, Entropy, 2014, 16, 163.
28 O. Valsson, P. Tiwary and M. Parrinello, Annu. Rev. Phys. Chem.,
2016, 67, DOI: 10.1146/annurev-physchem-040215-112229.
29 P. Banáš, P. Sklenovský, J. E. Wedekind, J. Šponer and
M. Otyepka, J. Phys. Chem. B, 2012, 116, 12721–12734.
30 D. R. Roe, C. Bergonzo and T. E. Cheatham, J. Phys.
Chem. B, 2014, 118, 3543–3552.
31 D. E. Condon, S. D. Kennedy, B. C. Mort, R. Kierzek,
I. Yildirim and D. H. Turner, J. Chem. Theory Comput.,
2015, 11, 2729–2742.
32 R. F. Brown, C. T. Andrews and A. H. Elcock, J. Chem.
Theory Comput., 2015, 11, 2315–2328.
33 A. Savelyev and A. D. MacKerell Jr., J. Comput. Chem., 2014,
35, 1219–1239.
34 P. E. M. Lopes, J. Huang, J. Shim, Y. Luo, H. Li, B. Roux and
A. D. MacKerell, J. Chem. Theory Comput., 2013, 9, 5430–5449.
35 N. Gresh, J. E. Šponer, N. Špačková, J. Leszczynski and
J. Šponer, J. Phys. Chem. B, 2003, 107, 8669–8681.
36 T. A. Halgren and W. Damm, Curr. Opin. Struct. Biol., 2001,
11, 236–242.
37 G. M. Torrie and J. P. Valleau, J. Comput. Phys., 1977, 23,
187–199.
38 A. Laio and M. Parrinello, Proc. Natl. Acad. Sci. U. S. A.,
2002, 99, 12562–12566.
39 P. Banáš, P. Jurečka, N. G. Walter, J. Šponer and M. Otyepka,
Methods, 2009, 49, 202–216.
40 J. Oró, Biochem. Biophys. Res. Commun., 1960, 2, 407–412.
41 J. P. Ferris, R. A. Sanchez and L. E. Orgel, J. Mol. Biol., 1968,
33, 693–704.
42 S. L. Miller, Science, 1953, 117, 528–529.
43 S. L. Miller and H. C. Urey, Science, 1959, 130, 245–251.
44 D. Roy, K. Najafian and P. von Ragué Schleyer, Proc. Natl.
Acad. Sci. U. S. A., 2007, 104, 17272–17277.
45 R. Glaser, B. Hodgen, D. Farrelly and E. McKee, Astrobiology,
2007, 7, 455–470.
Phys. Chem. Chem. Phys., 2016, 18, 20047--20066 | 20063
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
Perspective
46 J. P. Ferris and L. E. Orgel, J. Am. Chem. Soc., 1966,
88, 1074.
47 R. A. Sanchez, J. P. Ferris and L. E. Orgel, J. Mol. Biol., 1967,
30, 223–253.
48 R. Saladino, C. Crestini, F. Ciciriello, S. Pino, G. Costanzo
and E. Di Mauro, Res. Microbiol., 2009, 160, 441–448.
49 A. M. Saitta and F. Saija, Proc. Natl. Acad. Sci. U. S. A., 2014,
111, 13768–13773.
50 F. Pietrucci and A. M. Saitta, Proc. Natl. Acad. Sci. U. S. A.,
2015, 112, 15030–15035.
51 R. Saladino, G. Botta, M. Delfino and E. Di Mauro,
Chem. – Eur. J., 2013, 19, 16916–16922.
52 R. Saladino, E. Carota, G. Botta, M. Kapralov, G. N.
Timoshenko, A. Y. Rozanov, E. Krasavin and E. Di Mauro,
Proc. Natl. Acad. Sci. U. S. A., 2015, 112, E2746–E2755.
53 J. Wang, J. D. Gu, M. T. Nguyen, G. Springsteen and
J. Leszczynski, J. Phys. Chem. B, 2013, 117, 2314–2320.
54 J. Wang, J. D. Gu, M. T. Nguyen, G. Springsteen and
J. Leszczynski, J. Phys. Chem. B, 2013, 117, 9333–9342.
55 J. Wang, J. D. Gu, M. T. Nguyen, G. Springsteen and
J. Leszczynski, J. Phys. Chem. B, 2013, 117, 14039–14045.
56 J. E. Sponer, A. Mladek, J. Sponer and M. Fuentes-Cabrera,
J. Phys. Chem. A, 2012, 116, 720–726.
57 S. Civis, L. Juha, D. Babankova, J. Cvacka, O. Frank, J. Jehlicka,
B. Kralikova, J. Krasa, P. Kubat, A. Muck, M. Pfeifer, J. Skala
and J. Ullschmied, Chem. Phys. Lett., 2004, 386, 169–173.
58 D. Babankova, S. Civis and L. Juha, Prog. Quantum Electron.,
2006, 30, 75–88.
59 D. Babankova, S. Civis, L. Juha, M. Bittner, J. Cihelka,
M. Pfeifer, J. Skala, A. Bartnik, H. Fiedorowicz, J. Mikolajczyk,
L. Ryc and T. Sedivcova, J. Phys. Chem. A, 2006, 110,
12113–12120.
60 S. Civis, D. Babankova, J. Cihelka, P. Sazama and L. Juha,
J. Phys. Chem. A, 2008, 112, 7162–7169.
61 M. Ferus, D. Nesvorný, J. Šponer, P. Kubelı́k, R. Michalčı́ková,
V. Shestivská, J. E. Šponer and S. Civiš, Proc. Natl. Acad. Sci.
U. S. A., 2015, 112, 657–662.
62 M. Ferus, R. Michalčı́ková, V. Shestivská, J. Šponer, J. E.
Šponer and S. Civiš, J. Phys. Chem. A, 2014, 118, 719–736.
63 M. Ferus, S. Civis, A. Mladek, J. Sponer, L. Juha and
J. E. Sponer, J. Am. Chem. Soc., 2012, 134, 20788–20796.
64 M. Ferus, I. Matulkova, L. Juha and S. Civis, Chem. Phys.
Lett., 2009, 472, 14–18.
65 M. Ferus, P. Kubelik and S. Civis, J. Phys. Chem. A, 2011,
115, 12132–12141.
66 M. P. Callahan, K. E. Smith, H. J. Cleaves, J. Ruzicka,
J. C. Stern, D. P. Glavin, C. H. House and J. P. Dworkin,
Proc. Natl. Acad. Sci. U. S. A., 2011, 108, 13995–13998.
67 Z. Martins, O. Botta, M. L. Fogel, M. A. Sephton, D. P. Glavin,
J. S. Watson, J. P. Dworkin, A. W. Schwartz and P. Ehrenfreund,
Earth Planet. Sci. Lett., 2008, 270, 130–136.
68 R. Saladino, C. Crestini, F. Ciciriello, G. Costanzo and
E. Di Mauro, Chem. Biodiversity, 2007, 4, 694–720.
69 J. S. Hudson, J. F. Eberle, R. H. Vachhani, L. C. Rogers,
J. H. Wade, R. Krishnamurthy and G. Springsteen, Angew.
Chem., Int. Ed., 2012, 51, 5134–5137.
20064 | Phys. Chem. Chem. Phys., 2016, 18, 20047--20066
PCCP
70 Y. A. Jeilani, H. T. Nguyen, D. Newallo, J. M. D. Dimandja
and M. T. Nguyen, Phys. Chem. Chem. Phys., 2013, 15,
21084–21093.
71 Y. A. Jeilani, H. T. Nguyen, B. H. Cardelino and M. T.
Nguyen, Chem. Phys. Lett., 2014, 598, 58–64.
72 H. T. Nguyen, Y. A. Jeilani, H. M. Hung and M. T. Nguyen,
J. Phys. Chem. A, 2015, 119, 8871–8883.
73 R. Breslow, Tetrahedron Lett., 1959, 1, 22–26.
74 A. Butlerow, Justus Liebigs Ann. Chem., 1861, 120, 295–298.
75 A. Ricardo, M. A. Carrigan, A. N. Olcott and S. A. Benner,
Science, 2004, 303, 196.
76 O. Pestunova, A. Simonov, V. Snytnikov, V. Stoyanovsky and
V. Parmon, in Space Life Sciences: Astrobiology: Steps toward
Origin of Life and Titan before Cassini, ed. M. Bernstein,
R. Navarro-Gonzalez and R. Raulin, Elsevier Science Ltd,
Oxford, 2005, vol. 36, pp. 214–219.
77 C. E. Harman, J. F. Kasting and E. T. Wolf, Origins Life Evol.
Biospheres, 2013, 43, 77–98.
78 D. Ritson and J. D. Sutherland, Nat. Chem., 2012, 4,
895–899.
79 S. Civiš, R. Szabla, B. M. Szyja, D. Smykowski, O. Ivanek,
A. Knı́žek, P. Kubelı́k, J. Šponer, M. Ferus and J. E. Šponer,
Sci. Rep., 2016, 6, 23199.
80 H.-J. Kim, A. Ricardo, H. I. Illangkoon, M. J. Kim, M. A.
Carrigan, F. Frye and S. A. Benner, J. Am. Chem. Soc., 2011,
133, 9457–9468.
81 B. E. Prieur, C. R. Acad. Sci., Ser. IIc: Chim., 2001, 4,
667–670.
82 J. E. Sponer, B. G. Sumpter, J. Leszczynski, J. Sponer and
M. Fuentes-Cabrera, Chem. – Eur. J., 2008, 14, 9990–9998.
83 J. B. Lambert, G. Lu, S. R. Singer and V. M. Kolb, J. Am.
Chem. Soc., 2004, 126, 9611–9625.
84 Á. Vázquez-Mayagoitia, S. R. Horton, B. G. Sumpter,
J. Šponer, J. E. Šponer and M. Fuentes-Cabrera, Astrobiology,
2011, 11, 115–121.
85 G. Zubay and T. Mui, Origins Life Evol. Biospheres, 2001, 31,
87–102.
86 J. E. Sponer, J. Sponer and M. Fuentes-Cabrera,
Chem. – Eur. J., 2011, 17, 847–854.
87 E. D. Glendening, C. R. Landis and F. Weinhold, Wiley
Interdiscip. Rev.: Comput. Mol. Sci., 2012, 2, 1–42.
88 R. Saladino, U. Ciambecchini, C. Crestini, G. Costanzo,
R. Negri and E. Di Mauro, ChemBioChem, 2003, 4, 514–521.
89 H. T. Nguyen and M. T. Nguyen, Phys. Chem. Chem. Phys.,
2015, 17, 16927–16936.
90 A. Schoffstall and E. Laing, Origins Life Evol. Biospheres,
1985, 15, 141–150.
91 F. H. Westheimer, Chem. Rev., 1981, 81, 313–326.
92 G. Costanzo, R. Saladino, C. Crestini, F. Ciciriello and
E. Di Mauro, J. Biol. Chem., 2007, 282, 16729–16735.
93 M. W. Powner, B. Gerland and J. D. Sutherland, Nature,
2009, 459, 239–242.
94 M. W. Powner, J. D. Sutherland and J. W. Szostak, J. Am.
Chem. Soc., 2010, 132, 16677–16688.
95 S. A. Benner, A. Ricardo and M. A. Carrigan, Curr. Opin.
Chem. Biol., 2004, 8, 672–689.
This journal is © the Owner Societies 2016
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
PCCP
96 J. E. Sponer, J. Sponer and M. Fuentes-Cabrera, Chem. –
Eur. J., 2011, 17, 847–854.
97 R. Szabla, J. E. Sponer, J. Sponer and R. W. Gora, Phys.
Chem. Chem. Phys., 2013, 15, 7812–7818.
98 A. Choudhary, K. J. Kamer, M. W. Powner, J. D. Sutherland
and R. T. Raines, ACS Chem. Biol., 2010, 5, 655–657.
99 C. S. Cockell, Origins Life Evol. Biospheres, 2000, 30, 467–500.
100 C. S. Cockell and G. Horneck, Photochem. Photobiol., 2001,
73, 447–451.
101 K. J. Zahnle and J. C. G. Walker, Rev. Geophys., 1982, 20,
280–292.
102 C. E. Crespo-Hernandez, B. Cohen, P. M. Hare and
B. Kohler, Chem. Rev., 2004, 104, 1977–2019.
103 A. L. Sobolewski and W. Domcke, Phys. Chem. Chem. Phys.,
2004, 6, 2763–2771.
104 C. T. Middleton, K. de La Harpe, C. Su, Y. K. Law,
C. E. Crespo-Hernandez and B. Kohler, Annu. Rev. Phys.
Chem., 2009, 60, 217–239.
105 D. Shemesh, A. L. Sobolewski and W. Domcke, J. Am.
Chem. Soc., 2009, 131, 1374–1375.
106 A. L. Sobolewski and W. Domcke, ChemPhysChem, 2006, 7,
561–564.
107 C. Sagan, J. Theor. Biol., 1973, 39, 195–200.
108 K. Kleinermanns, D. Nachtigallová and M. S. de Vries,
Int. Rev. Phys. Chem., 2013, 32, 308–342.
109 A. L. Sobolewski and W. Domcke, Europhys. News, 2006, 37,
20–23.
110 R. Szabla, J. Campos, J. E. Sponer, J. Sponer, R. W. Gora
and J. D. Sutherland, Chem. Sci., 2015, 6, 2035–2043.
111 G. M. Roberts and V. G. Stavros, Chem. Sci., 2014, 5,
1698–1722.
112 T. E. Dermota, Q. Zhong and A. W. Castleman, Chem. Rev.,
2004, 104, 1861–1886.
113 G. M. Roberts, H. J. Marroux, M. P. Grubb, M. N. Ashfold and
A. J. Orr-Ewing, J. Phys. Chem. A, 2014, 118, 11211–11225.
114 K. Rottger, H. J. Marroux, M. P. Grubb, P. M. Coulter,
H. Bohnke, A. S. Henderson, M. C. Galan, F. Temps,
A. J. Orr-Ewing and G. M. Roberts, Angew. Chem., Int. Ed.,
2015, 54, 14719–14722.
115 F. Bernardi, M. Olivucci and M. A. Robb, Chem. Soc. Rev.,
1996, 25, 321–328.
116 J. Finley, P.-Å. Malmqvist, B. O. Roos and L. SerranoAndrés, Chem. Phys. Lett., 1998, 288, 299–306.
117 A. A. Granovsky, J. Chem. Phys., 2011, 134, 214113.
118 F. Plasser, M. Barbatti, A. J. A. Aquino and H. Lischka,
Theor. Chem. Acc., 2012, 131, 1–14.
119 J. J. Szymczak, M. Barbatti and H. Lischka, Int. J. Quantum
Chem., 2011, 111, 3307–3315.
120 O. Christiansen, H. Koch and P. Jørgensen, Chem. Phys.
Lett., 1995, 243, 409–418.
121 A. B. Trofimov and J. Schirmer, J. Phys. B: At., Mol. Opt.
Phys., 1995, 28, 2299.
122 A. Dreuw and M. Wormit, Wiley Interdiscip. Rev.: Comput.
Mol. Sci., 2015, 5, 82–95.
123 C. Hättig, in Adv. Quantum Chem., ed. H. J. Å. Jensen,
Academic Press, 2005, vol. 50, pp. 37–60.
This journal is © the Owner Societies 2016
Perspective
124 C. Hättig and F. Weigend, J. Chem. Phys., 2000, 113,
5154–5161.
125 F. Plasser, R. Crespo-Otero, M. Pederzoli, J. Pittner,
H. Lischka and M. Barbatti, J. Chem. Theory Comput.,
2014, 10, 1395–1405.
126 L. González, D. Escudero and L. Serrano-Andrés,
ChemPhysChem, 2012, 13, 28–51.
127 J. P. Ferris, J. E. Kuder and A. W. Catalano, Science, 1969,
166, 765–766.
128 J. P. Ferris and J. E. Kuder, J. Am. Chem. Soc., 1970, 92,
2527–2533.
129 J. P. Ferris, D. B. Donner and W. Lotz, J. Am. Chem. Soc.,
1972, 94, 6968–6974.
130 E. Boulanger, A. Anoop, D. Nachtigallova, W. Thiel and
M. Barbatti, Angew. Chem., Int. Ed., 2013, 125, 8158–8161.
131 H. L. Barks, R. Buckley, G. A. Grieves, E. Di Mauro, N. V.
Hud and T. M. Orlando, ChemBioChem, 2010, 11, 1240–1243.
132 R. Szabla, R. W. Gora, J. Sponer and J. E. Sponer,
Chem. – Eur. J., 2014, 20, 2515–2521.
133 S. D. Senanayake and H. Idriss, Proc. Natl. Acad. Sci.
U. S. A., 2006, 103, 1194–1198.
134 R. A. Sanchez and L. E. Orgel, J. Mol. Biol., 1970, 47,
531–543.
135 R. Shapiro, Origins Life Evol. Biospheres, 1988, 18, 71–85.
136 A. A. Ingar, R. W. Luke, B. R. Hayter and J. D. Sutherland,
ChemBioChem, 2003, 4, 504–507.
137 C. Anastasi, M. A. Crowe, M. W. Powner and J. D.
Sutherland, Angew. Chem., Int. Ed., 2006, 45, 6176–6179.
138 C. Anastasi, M. A. Crowe and J. D. Sutherland, J. Am. Chem.
Soc., 2007, 129, 24–25.
139 M. W. Powner, C. Anastasi, M. A. Crowe, A. L. Parkes,
J. Raftery and J. D. Sutherland, ChemBioChem, 2007, 8,
1170–1179.
140 M. W. Powner and J. D. Sutherland, ChemBioChem, 2008, 9,
2386–2387.
141 D. Tuna, A. L. Sobolewski and W. Domcke, J. Phys. Chem. A,
2014, 118, 122–127.
142 D. Tuna and W. Domcke, Phys. Chem. Chem. Phys., 2016,
18, 947–955.
143 A. Banerjee, G. Ganguly, R. Tripathi, N. N. Nair and A. Paul,
Chem. – Eur. J., 2014, 20, 6348–6357.
144 R. Szabla, D. Tuna, R. W. Góra, J. Šponer, A. L. Sobolewski
and W. Domcke, J. Phys. Chem. Lett., 2013, 4, 2785–2788.
145 R. Szabla, J. E. Sponer, J. Sponer, A. L. Sobolewski and
R. W. Gora, Phys. Chem. Chem. Phys., 2014, 16, 17617–17626.
146 R. Szabla, J. Šponer and R. W. Góra, J. Phys. Chem. Lett.,
2015, 6, 1467–1471.
147 A. L. Sobolewski and W. Domcke, Chem. Phys. Lett., 2000,
329, 130–137.
148 A. L. Sobolewski and W. Domcke, J. Phys. Chem. A, 2001,
105, 9275–9283.
149 M. Barbatti, J. Am. Chem. Soc., 2014, 136, 10246–10249.
150 G. Costanzo, R. Saladino, C. Crestini, F. Ciciriello and
E. Mauro, BMC Evol. Biol., 2007, 7, 1–8.
151 S. Miyakawa, H. J. Cleaves and S. L. Miller, Origins Life Evol.
Biospheres, 2002, 32, 195–208.
Phys. Chem. Chem. Phys., 2016, 18, 20047--20066 | 20065
View Article Online
Published on 13 April 2016. Downloaded by Universite Pierre et Marie Curie on 02/11/2016 09:21:31.
Perspective
152 R. E. Kirk and D. F. Othmer, ECT Encyclopedia of Chemical
Technology, Wiley Interscience, 1980, vol. 11, pp. 251–262.
153 P. M. Amarasinghe, K. S. Katti and D. R. Katti, J. Colloid
Interface Sci., 2009, 337, 97–105.
154 H. Slebocka-Tilk, F. Sauriol, M. Monette and R. S. Brown,
Can. J. Chem., 2002, 80, 1343–1350.
155 R. Saladino, V. Neri, C. Crestini, G. Costanzo, M. Graciotti
and E. Di Mauro, J. Am. Chem. Soc., 2008, 130, 15512–15518.
156 R. Lohrmann and L. E. Orgel, Science, 1971, 171, 490–494.
157 M. S. Verlander, R. Lohrmann and L. E. Orgel, J. Mol. Evol.,
1973, 2, 303–316.
158 S. A. Rudolph, E. M. Johnson and P. Greengard, J. Biol.
Chem., 1971, 246, 1271–1273.
159 D. A. Usher and D. Yee, J. Mol. Evol., 1979, 13, 287–293.
160 L. E. Orgel and R. Lohrmann, Acc. Chem. Res., 1974, 7,
368–377.
161 G. Costanzo, S. Pino, F. Ciciriello and E. Di Mauro, J. Biol.
Chem., 2009, 284, 33206–33216.
162 G. Costanzo, R. Saladino, G. Botta, A. Giorgi, A. Scipioni,
S. Pino and E. Di Mauro, ChemBioChem, 2012, 13, 999–1008.
163 M. Morasch, C. B. Mast, J. K. Langer, P. Schilcher and
D. Braun, ChemBioChem, 2014, 15, 879–883.
164 J. E. Sponer, J. Sponer, A. Giorgi, E. Di Mauro, S. Pino and
G. Costanzo, J. Phys. Chem. B, 2015, 119, 2979–2989.
165 B. Clément, B. Grignard, L. Koole, C. Jérôme and
P. Lecomte, Macromolecules, 2012, 45, 4476–4486.
166 T. Steinbach, S. Ritz and F. R. Wurm, ACS Macro Lett.,
2014, 3, 244–248.
167 S. Grimme, J. Comput. Chem., 2006, 27, 1787–1799.
168 H. Kruse and J. Sponer, Phys. Chem. Chem. Phys., 2015, 17,
1399–1410.
169 H. Kruse, M. Havrila and J. Sponer, J. Chem. Theory
Comput., 2014, 10, 2615–2629.
170 K. Gkionis, H. Kruse and J. Šponer, J. Chem. Theory
Comput., 2016, 12, 2000–2016.
171 M. A. Ditzler, M. Otyepka, J. Šponer and N. G. Walter,
Acc. Chem. Res., 2010, 43, 40–47.
172 M. V. Krasovska, J. Sefcikova, K. Réblová, B. Schneider,
N. G. Walter and J. Šponer, Biophys. J., 2006, 91, 626–638.
173 P. Auffinger, L. D’Ascenzo and E. Ennifar, Met. Ions Life
Sci., 2016, 16, 167–201.
174 T.-S. Lee, B. K. Radak, M. E. Harris and D. M. York,
ACS Catal., 2016, 6, 1853–1869.
175 V. Mlynsky, N. G. Walter, J. Sponer, M. Otyepka and
P. Banas, Phys. Chem. Chem. Phys., 2015, 17, 670–679.
176 P. Thaplyal, A. Ganguly, S. Hammes-Schiffer and P. C.
Bevilacqua, Biochemistry, 2015, 54, 2160–2175.
177 S. Zhang, A. Ganguly, P. Goyal, J. L. Bingaman, P. C.
Bevilacqua and S. Hammes-Schiffer, J. Am. Chem. Soc.,
2015, 137, 784–798.
178 J. E. Šponer, J. Šponer and E. Mauro, J. Mol. Evol., 2015, 82,
5–10.
20066 | Phys. Chem. Chem. Phys., 2016, 18, 20047--20066
PCCP
179 L. Da Silva, M. C. Maurel and D. Deamer, J. Mol. Evol.,
2015, 80, 86–97.
180 J. P. Ferris and G. Ertem, Science, 1992, 257, 1387–1389.
181 P. Mignon, P. Ugliengo and M. Sodupe, J. Phys. Chem. C,
2009, 113, 13741–13749.
182 P. Mignon, P. Ugliengo, M. Sodupe and E. R. Hernandez,
Phys. Chem. Chem. Phys., 2010, 12, 688–697.
183 P. Mignon and M. Sodupe, Phys. Chem. Chem. Phys., 2012,
14, 945–954.
184 P. C. Joshi, M. F. Aldersley and J. P. Ferris, Origins Life Evol.
Biospheres, 2011, 41, 213–236.
185 P. C. Joshi, M. F. Aldersley, J. D. Price, D. V. Zagorevski and
J. P. Ferris, Origins Life Evol. Biospheres, 2011, 41, 575–579.
186 D. C. Mathew and Z. Luthey-Schulten, Origins Life Evol.
Biospheres, 2010, 40, 303–317.
187 J. E. Sponer, A. Mladek and J. Sponer, Phys. Chem. Chem.
Phys., 2013, 15, 6235–6242.
188 K. Leu, E. Kervio, B. Obermayer, R. M. Turk-MacLeod,
C. Yuan, J. M. Luevano Jr., E. Chen, U. Gerland, C. Richert
and I. A. Chen, J. Am. Chem. Soc., 2013, 135, 354–366.
189 T. Wu and L. E. Orgel, J. Am. Chem. Soc., 1992, 114, 7963–7969.
190 S. S. Mansy, J. P. Schrum, M. Krishnamurthy, S. Tobe,
D. A. Treco and J. W. Szostak, Nature, 2008, 454, 122–125.
191 J. P. Schrum, A. Ricardo, M. Krishnamurthy, J. C. Blain and
J. W. Szostak, J. Am. Chem. Soc., 2009, 131, 14560–14570.
192 C. Deck, M. Jauker and C. Richert, Nat. Chem., 2011, 3,
603–608.
193 J. Sheng, L. Li, A. E. Engelhart, J. Gan, J. Wang and J. W.
Szostak, Proc. Natl. Acad. Sci. U. S. A., 2014, 111, 3050–3055.
194 S. Pino, G. Costanzo, A. Giorgi and E. Di Mauro, Biochemistry,
2011, 50, 2994–3003.
195 S. Pino, G. Costanzo, A. Giorgi, J. Šponer, J. Šponer and
E. Mauro, Entropy, 2013, 15, 5362.
196 P. Stadlbauer, J. Šponer, G. Costanzo, E. Di Mauro, S. Pino
and J. E. Šponer, Chem. – Eur. J., 2015, 21, 3596–3604.
197 M. Zgarbová, M. Otyepka, J. Šponer, A. Mládek, P. Banáš,
T. E. Cheatham and P. Jurečka, J. Chem. Theory Comput.,
2011, 7, 2886–2902.
198 M. Illangasekare, G. Sanchez, T. Nickles and M. Yarus,
Science, 1995, 267, 643–647.
199 N. V. Chumachenko, Y. Novikov and M. Yarus, J. Am. Chem.
Soc., 2009, 131, 5257–5263.
200 S. Hammes-Schiffer and J. Klinman, Acc. Chem. Res., 2015,
48, 899.
201 L. Masgrau and D. G. Truhlar, Acc. Chem. Res., 2015, 48,
431–438.
202 S. C. Kamerlin, P. K. Sharma, R. B. Prasad and A. Warshel,
Q. Rev. Biophys., 2013, 46, 1–132.
203 V. Mlýnský, P. Banáš, J. Šponer, M. W. van der Kamp,
A. J. Mulholland and M. Otyepka, J. Chem. Theory Comput.,
2014, 10, 1608–1622.
204 C. Sagan, Cosmos, Random House, New York, 1980.
This journal is © the Owner Societies 2016