Designing potential HIV-1 integrase inhibitors: An In silico approach

Year 2021, Volume: 3 Issue: 2, 45 - 53, 30.12.2021

Arif Mermer

https://doi.org/10.51435/turkjac.950248

Cited By: 1

Abstract

Human immunodeficiency virus is a spectrum of conditions caused by infection with the human immunodeficiency virus. In 2019, about 38 million people worldwide were living with HIV and 690,000 deaths had occurred in that year. To date, for the treatment of HIV-1 disease, many compounds have been synthesized and some of them was approved by FDA. However, the use of these drugs has been limited due to reasons such as resistance caused by the misuse of drugs and bad side effects. We describe herein designing 48 novel compounds as a potential inhibitor of HIV-1 integrase through in silico studies such as molecular docking, target analysis, toxicity prediction and ADME prediction. The online web-based platform, SwissADME, also predicts these molecules solubility, pharmacodynamics property and target accuracy.

Keywords

Swissadme, HIV-1 Integrase, Molecular Docking, In Silico Study, Toxicity

References

• 1. O. Delelis, K. Carayon, A. Saib, E. Deprez, J.F. Mouscadet, Integrase and integration: biochemical activities of HIV-1 integrase, Retrovirology 5, 2008, 114-127.
• 2. N. Neamati, Z. Lin, R.G. Karki, A. Orr, K. Cowansage, D. Strumberg, Metal-dependent inhibition of HIV-1 integrase, J Med Chem, 45, 2002, 5661-5670.
• 3. T. Kawasuji, T. Yoshinaga, A. Sato, M. Yodo, T. Fujiwara, R. Kiyama, A platform for designing HIV integrase inhibitors. Part 1: 2-hydroxy-3-heteroaryl acrylic acid derivatives as novel HIV integrase inhibitor and modeling of hydrophilic and hydrophobic pharmacophores, Bioorg Med Chem, 14, 2006, 8430-8445.
• 4. B.A. Johns, A.C. Svolto, Advances in two-metal chelation inhibitors of HIV integrase, Expert Opin Ther Pat, 18, 2008, 1225-1237.
• 5. M. Rowley, The discovery of raltegravir, an integrase inhibitor for the treatment of HIV infection, Prog Med Chem, 46, 2008, 1-28.
• 6. M. Sato, H. Kawakami, T. Motomura, H. Aramaki, T. Matsuda, M. Yamashita, Quinolone carboxylic acids as a novel monoketo acid class of human immunodeficiency virus type 1 integrase inhibitors, J Med Chem, 52, 2009, 4869-4882.
• 7. C. Katlama, R. Murphy, Dolutegravir for the treatment of HIV, Expert Opin Investig Drugs, 21, 2008, 523-530.
• 8. R. Di Santo, Inhibiting the HIV integration process: past, present, and the future, J Med Chem, 57, 2014, 539-566.
• 9. C. Liao, C. Marchand, T.R. Burke, Y. Pommier, M.C. Nicklaus, Authentic HIV-1 integrase inhibitors, Future Med Chem, 2, 2010, 1107-1122.
• 10. H. Sirous, G. Chemi, S. Gemma, S. Butini, Z. Debyser, F. Christ, L. Saghaie, S. Brogi, A. Fassihi, G. Campiani, M. Brindisi, Identification of Novel 3-Hydroxy-pyran-4-One Derivatives as Potent HIV-1 Integrase Inhibitors Using in silico Structure-Based Combinatorial Library Design Approach, Frontiers in Chemistry, 7, 2019, 1-20.
• 11. M. Hay, D.W. Tomas, J.L. Craighead, C. Economides, J. Rosenthal, Clinical development success rates for investigational drugs, Nature Biotechnol, 32, 2014, 40-51.
• 12. J.L. Dahlin, J. Inglese, M.A. Walters, Mitigating risk in academic preclinical drug discovery, Nature Rev Drug Discov, 14, 2015, 279-294.
• 13. D.E.V. Pires, T.L. Blundell, D.B. Ascher, pkCSM: Predicting Small-Molecule Pharmacokinetic and Toxicity Properties Usin Graph-Based Signatures, J Med Chem, 58, 2015, 4066-4072.
• 14. F. Cheng, W. Li, Y. Zhou, J. Shen, Z. Wu, G. Liu, P.W. Lee, Y. Tang, admetSAR: a comprehensive source and free tool for assessment of chemical ADMET properties, J Chem Inf Model, 52, 2012, 3099-3105.
• 15. A. Daina, O. Michielin, V. Zoete, iLOGP: A Simple, Robust, and Efcient Description of n-Octanol/Water Partition Coefcient for Drug Design Using the GB/SA Approach, J Chem Inf Model, 54, 2014, 3284-3301.
• 16. L. Di, P. Artursson, A. Avdeef, G.F. Ecker, B. Faller, H. Fischer, J.B. Houston, M. Kansy, E.H. Kerns, S.D. Krämer, H. Lennernäs, K. Sugano, Evidence-based approach to assess passive diffusion and carrier-mediated drug transport, Drug Discovery Today, 17, 2012, 905-912.
• 17. V. Zoete, A. Daina, C. Bovigny, O. Michielin, SwissSimilarity: A Web Tool for Low to Ultra High Troughput Ligand-Based Virtual Screening, J Chem Inf Model, 56, 2016, 1399-1404.
• 18. D. Gfeller, SwissTargetPrediction: a web server for target prediction of bioactive small molecules, Nucleic Acids Res, 42, 2014, W32–W38.
• 19. A. Grosdidier, V. Zoete, O. Michielin, SwissDock, a protein-small molecule docking web service based on EADock DSS, Nucleic Acids Res, 39, 2011, W270–W277.
• 20. M. Wirth, V. Zoete, O. Michielin, W.H.B. Sauer, SwissBioisostere: a database of molecular replacements for ligand design, Nucleic Acids Res, 41, 2013, D1137-D1143.
• 21. V. Zoete, M.A. Cuendet, A. Grosdidier, O. Michielin, SwissParam: a fast force feld generation tool for small organic molecules, J Comput Chem, 32, 2011, 2359-2368.
• 22. A. Daina, O. Michielin, V. Zoete, SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules, Scientific Reports, 7, 2017, 42717.
• 23. M.J. Keiser, B.L. Roth, B.N. Armbruster, P. Ernsberger, J.J. Irwin, B.K. Shoichet, Relating protein pharmacology by ligand chemistry, Nature Biotechnology, 25, 2007, 197-206.
• 24. D.E. Pires, T.L. Blundell, D.B. Ascher, PkCSM: Predicting small-molecule pharmacokinetic and toxicity properties using graphbased signatures, J Med Chem, 58, 2015, 4066-4072.
• 25. A. Daina, V. Zoete, A BOILED-Egg To Predict Gastrointestinal Absorption and Brain Penetration of Small Molecules, ChemMedChem, 11, 2016, 1117–1121.
• 26. P. Selvam, M. Chandramohan, E. De Clercq, C. Pannecouque, M. Witrouw, Synthesis and anti-HIV activity of 4-[(1,2-dihydro-2-oxo-3H-indol-3-ylidene)amino]-N-(4,6-dimethyl-2-pyrimidinyl)-benzene sulphonamide and its derivatives, Eur J Pharm Sci, 14, 2001, 313-316.
• 27. G.M. Sastry, M. Adzhigirey, T. Day, R. Annabhimoju, W. Sherman, Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments, J Comput Aided Mol Des, 27, 2013, 221-234.
• 28. R.A. Friesner, J.L. Banks, R.B. Murphy, T.A. Halgren, J.J. Klicic, D.T. Mainz, M.P. Repasky, E.H. Knoll, M. Shelley, J.K. Perry, Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy, J Med Chem, 47, 2004, 1739-1749.
• 29. R.A. Friesner, R.B. Murphy, M.P. Repasky, L.L. Frye, J.R. Greenwood, T. Halgren, P.C. Sanschagrin, D.T. Mainz, Extra precision glide: Docking and scoring incorporating a model of hydrophobic enclosure for protein− ligand complexes, J Med Chem, 49, 2006, 6177-6196.
• 30. T.A. Halgren, R.B. Murphy, R.A. Friesner, H.S. Beard, L.L. Frye, W.T. Pollard, J.L. Banks, Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening, J Med Chem, 47, 2004, 1750-1759.
• 31. B. Debnath, S. Ganguly, Synthesis, biological evaluation, in silico docking, and virtual ADME studies of 2-[2-Oxo-3-(arylimino) indolin-1-yl]-N-arylacetamides as potent anti-breast cancer agents, Monatshefte für Chemie-Chemical Monthly, 147, 2016, 565-574.