Optimization of Carbocyclic Analogues to a Specific Pharmaceutical Enzyme Target via Discovery StudioTM
Douglas Harris
Department of Chemistry and Biochemistry, Utah State University, 0300 Old Main Hill, Logan, UT 83422-0300, USA
[email protected]
Abstract:
The following teaching biochemistry laboratory experiment introduces students to principles of structure-based drug design and the important role that molecular modeling plays in optimizing drug
leads. The discovery and development of the potent influenza neuraminidase antivirals oseltamivir (Tamiflu) and Tamiphosphor are highlighted. The user-friendly graphical interface of the Discovery
Studio molecular modeling software provides an excellent environment to introduce students to the techniques of molecular minimization and calculation of relative enzyme/inhibitor interaction
energies. A strong correlation between the experimentally determined inhibition constant values of various carbocyclic analogues and calculated relative interaction energies is obtained.
Experimental Confirmation of Previous Computer Calculations [5]
Presented Topics:
Structure-Based Drug Design Cycle
Phosphono group orientation
3rd added phosphono oxygen atom
Ei = -3.08 kcal/mol (O up vs O down)
Minimized phosphono group orientation relative to OC
Molecular mechanics
Force field
E = EB + EA + ET + EI + EVDW + EQ + EHB (Dreiding) [1]
Energy Minimizations
Local potential energy minimum and global minimum
Figure 1 Left to right - Minimized water system depicting optimized hydrogen bonds, local cyclohexane
minimized structure – 34 kcal/mole, global cyclohexane minimized structure – 11 kcal/mole, and
intermediate “boat” cyclohexane structure – 19.2 kcal/mole.
Figure 2 Oseltamivir carboxylate/neuraminidase active site system that includes the
inhibitor (pink) and all atoms (light blue) of the neuraminidase structure within 8
angstroms of the inhibitor. The remaining atoms (element colors) are within 16
angstroms of the inhibitor.
Figure 3 Left – Compound 17 [4] minimized within the active site of influenza neuraminidase type 1.
Right – Compound 13b [6] minimized within the active site of influenza neuraminidase type 1.
Compound
Ki (nM) [6]
Ei
(kcal/mole)
Determination of Relative Interaction Energies of Inhibitors to a Receptor Enzyme
Interaction Energy
Ei = E[Enz:I] - E[I] - E[Enz]
Relative Interaction Energy
Ei = Ei,analogue – Ei,reference
Oseltamivir carboxylate
(OC)
2.90
0
13a (Guanidine-OC)
2.02
-2.23
Determination of Relative Interaction Energies of Various Carbocyclic Inhibitor
Analogues to Neuraminidase of Influenza Virus and Drug Lead Optimization
Neuraminidase type 1/oseltamivir carboxylate complex crystal structure
2HU4.pdb [2]
3TI6.pdb [3]
Gilead Sciences
Structure activity relationship [4]
ITC and X-ray crystallography [5]
Academia Sinica
Tamiphosphor development [6 and 7]
Importance of Correlation Between Experimental and Theoretical Results
Similar established method [8]
Tamiphosphor
0.15
13b
0.06
References
[1] Mayo S, Olafson B, Goddard W, J. of Phys. Chem. 94, 8897 – 8909 (1990)
[2] Russell et al., Nature 443, 45-49 (2006)
[3] Vavricka et al., PLoS Pathog. 7, e1002249 (2011)
[4] Lew et al., Curr. Med.. Chem. 7, 663 – 672 (2000)
Excellent agreement with x-ray crystral structure
Minimized structure (pink) overlay with x-ray crystal
structure (light blue)
X-ray crystal structure coordinates provided by
corresponding authors of reference [5]
Flu strain-dependent inhibition and interaction energy values
ITC indicates that Tamiphosphor has a slightly more negative
H value compared to OC[5]
Flu strain
Ki (nM)
-3.39
A/WSN/1933 (H1N1)[6]
-2.75
-5.16
A/California/07/2009[5]
+2
(±4 precision)
Combined 13b and 17
-7.78
Drug lead optimization
-8.40
Ei
(kcal/mole)
2HU4 (H5N1 with 7 genes
from WSN and NA gene
from
A/Vietnam/1203/04)[2]
-3.39
3TI6 (2009 N1)[3]
-1.14
[5] Albiania et. al., Eur. J. Med. Chem. 121, 100 – 109 (2016)
[6] Shie J J et al., JACS 129, 11892-11893 (2007)
[7] Cheng TJ et al., J. Med. Chem. 55, 8657-8670 (2012)
[8] Nair et al., J. Mol. Graph. Modelling 21, 171-179 (2002)