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Medicinal Chemistry

Author(s): Arthur Sarron and Kevin A. Lobb*

DOI: 10.2174/1871520622666220202161543

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Drug Resistance in the HIV-1 Subtype C Protease Enzyme: A High Throughput Virtual Screening Approach in Search of New Ligands with Activity

Page: [970 - 979] Pages: 10

  • * (Excluding Mailing and Handling)

Abstract

Background: HIV-1 subtype C protease is a strategic target for antiretroviral treatment. However, resistance to protease inhibitors appears after months of treatment. Chromones and 2- biscoumarin derivatives show potential for inhibition of the HIV- subtype C protease.

Objective: Different heterocyclic structures from the ZINC database were docked against Human Immunodeficiency Virus-1 (HIV) subtype C protease crystal structure 2R5Q and 2R5P. The 5 best molecules were selected to be docked against 62 homology models based on HIV-protease sequences from infants failing antiretroviral protease treatment. This experimentation was performed with two molecular docking programs: Autodock and Autodock Vina. These molecules were modified by substituting protons with different moieties, and the derivatives were docked against the same targets. Ligand-protein interactions, physical/chemical proprieties of the molecules, and dynamics simulations were analyzed.

Methods: Docking of all of the molecules was performed to find out the binding sites of HIV-1 subtype C proteases. An in-house script was made to substitute protons of molecules with different moieties. According to the Lipinski rule of five, physical and chemical properties were determined. Complexes of certain ligands-protease were compared to the protein alone in molecular dynamics simulations.

Results: From the first docking results, the 5 best (lowest energy) ligands (dibenz[a,h]acridine, dibenz[a, i]acridine, NSC114903, dibenz[c,h]acridine, benzo[a]acridine) were selected. The binding energy of the modified ligands increased, including the poorest-performing molecules. A correlation between nature, the position, and the resulting binding energy was observed. According to the Lipinski rules, the physico-chemical characteristics of the five best-modified ligands are ideal for oral bioavailability. Molecular dynamics simulations show that some lead-protease complexes were stable.

Conclusion: Dibenz[a,h]acridine, dibenz[a, i]acridine, NSC114903, dibenz[c,h]acridine, benzo[ a]acridine and their derivatives might be considered as promising HIV-1 subtype C protease inhibitors. This could be confirmed through synthesis and subsequent in vitro assays.

Keywords: HIV-1 subtype C protease, drug resistance, docking, dynamics simulation, library creation, high throughput screening.

Graphical Abstract

[1]
UNAIDS. In: Global AIDS Update; 2016; pp. 1-16. Available from: https://www.unaids.org/en/resources/documents/2016/Global-AIDS-update-2016
[2]
Menéndez-Arias, L. Molecular basis of human immunodeficiency virus drug resistance: An update. Antiviral Res., 2010, 85(1), 210-231.
[http://dx.doi.org/10.1016/j.antiviral.2009.07.006] [PMID: 19616029]
[3]
Wensing, A.M.J.; van Maarseveen, N.M.; Nijhuis, M. Fifteen years of HIV protease inhibitors: Raising the barrier to resistance. Antiviral Res., 2010, 85(1), 59-74.
[http://dx.doi.org/10.1016/j.antiviral.2009.10.003] [PMID: 19853627]
[4]
Martinez-Cajas, J.L.; Wainberg, M.A. Protease inhibitor resistance in HIV-infected patients: Molecular and clinical perspectives. Antiviral Res., 2007, 76(3), 203-221.
[http://dx.doi.org/10.1016/j.antiviral.2007.06.010] [PMID: 17673305]
[5]
Coman, R.M.; Robbins, A.H.; Fernandez, M.A.; Gilliland, C.T.; Sochet, A.A.; Goodenow, M.M.; McKenna, R.; Dunn, B.M. The contribu-tion of naturally occurring polymorphisms in altering the biochemical and structural characteristics of HIV-1 subtype C protease. Biochemistry, 2008, 47(2), 731-743.
[http://dx.doi.org/10.1021/bi7018332] [PMID: 18092815]
[6]
Onywera, D.H. Influence of non-synonymous sequence mutations on the architecture of HIV-1 Clade C protease receptor site: Docking and molecular dynamics studies, Master Dissertation, Rhodes University: Grahamstown. 2013.
[7]
Standford University. Major HIV-1 Drug Resistance Mutations updated March 9, 2015. Available from: http://hivdb.stanford.edu/pages/download/resistanceMutations_handout.pdf (accessed 18/05/2015).
[8]
Krohn, A.; Redshaw, S.; Ritchie, J.C.; Graves, B.J.; Hatada, M.H. Novel binding mode of highly potent HIV-proteinase inhibitors incorpo-rating the (R)-hydroxyethylamine isostere. J. Med. Chem., 1991, 34(11), 3340-3342.
[http://dx.doi.org/10.1021/jm00115a028] [PMID: 1956054]
[9]
Olomola, T.O.; Klein, R.; Mautsa, N.; Sayed, Y.; Kaye, P.T. Synthesis and evaluation of coumarin derivatives as potential dual-action HIV-1 protease and reverse transcriptase inhibitors. Bioorg. Med. Chem., 2013, 21(7), 1964-1971.
[http://dx.doi.org/10.1016/j.bmc.2013.01.025] [PMID: 23415084]
[10]
Kipp, D.R.; Hirschi, J.S.; Wakata, A.; Goldstein, H.; Schramm, V.L. Transition states of native and drug-resistant HIV-1 protease are the same. Proc. Natl. Acad. Sci. USA, 2012, 109(17), 6543-6548.
[http://dx.doi.org/10.1073/pnas.1202808109] [PMID: 22493227]
[11]
Piana, S.; Butcher, S.; Carloni, P.; Rothlisberger, U. reaction mechanism of hiv-1 protease by hybrid car-parrinello/classical MD simula-tions. J. Phys. Chem. B, 2004, 108(30), 11139-11149.
[http://dx.doi.org/10.1021/jp037651c]
[12]
Irwin, J.J.; Shoichet, B.K. ZINC-a free database of commercially available compounds for virtual screening. J. Chem. Inf. Model., 2005, 45(1), 177-182.
[http://dx.doi.org/10.1021/ci049714+] [PMID: 15667143]
[13]
Berman, H.M.; Westbrook, J.; Feng, Z.; Gilliland, G.; Bhat, T.N.; Weissig, H.; Shindyalov, I.N.; Bourne, P.E. The protein data bank. Nucleic Acids Res., 2000, 28(1), 235-242.
[http://dx.doi.org/10.1093/nar/28.1.235] [PMID: 10592235]
[14]
BIOVIA. Dassault Systèmes; In: Discovery Studio Modeling Environment; Release 2017.Dassault Systèmes: San Diego, 2016. Available from: https://www.bibsonomy.org/bibtex/23b2245c892c43eb0c25b9e7096a7737a/salotz
[15]
Morris, G.M.; Huey, R.; Lindstrom, W.; Sanner, M.F.; Belew, R.K.; Goodsell, D.S.; Olson, A.J. AutoDock4 and AutoDockTools4: Auto-mated docking with selective receptor flexibility. J. Comput. Chem., 2009, 30(16), 2785-2791.
[http://dx.doi.org/10.1002/jcc.21256] [PMID: 19399780]
[16]
Trott, O.; Olson, A.J. AutoDock Vina: Improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J. Comput. Chem., 2010, 31(2), 455-461.
[PMID: 19499576]
[17]
Abraham, M.J.; Murtola, T.; Schulz, R.; Páll, S.; Smith, J.C.; Hess, B.; Lindahl, E. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX, 2015, 1-2, 19-25.
[http://dx.doi.org/10.1016/j.softx.2015.06.001]
[18]
Duan, Y.; Wu, C.; Chowdhury, S.; Lee, M.C.; Xiong, G.; Zhang, W.; Yang, R.; Cieplak, P.; Luo, R.; Lee, T.; Caldwell, J.; Wang, J.; Koll-man, P. A point-charge force field for molecular mechanics simulations of proteins based on condensed-phase quantum mechanical calcu-lations. J. Comput. Chem., 2003, 24(16), 1999-2012.
[http://dx.doi.org/10.1002/jcc.10349] [PMID: 14531054]
[19]
Guha, R. CDK descriptor calculator GUI (V1.4.6). Available from: http://www.rguha.net/code/java/cdkdesc.html (accessed 03/07/2015).