Login Register Cart 0
Generic placeholder image

Current HIV Research

Editor-in-Chief

ISSN (Print): 1570-162X
ISSN (Online): 1873-4251

Back
Journal Home About Journal Editorial Board Journal Insight Current Issue Volumes/Issues
Subscribe
Research Article

Improved 3D-QSAR Prediction by Multiple Conformational Alignments and Molecular Docking Studies to Design and Discover HIV-I Protease Inhibitors

Author(s): Paresh K. Patel and Hardik G. Bhatt*

Volume 19, Issue 2, 2021

Published on: 19 November, 2020

Page: [154 - 171] Pages: 18

DOI: 10.2174/1570162X18666201119143457

Price: $65

Abstract

Background: Inhibition of HIV-I protease enzyme is a strategic step for providing better treatment in retrovirus infections, which avoids resistance and possesses less toxicity.

Objectives: In the course of our research to discover new and potent protease inhibitors, 3D-QSAR (CoMFA and CoMSIA) models were generated using 3 different alignment techniques, including multifit alignment, docking based and Distill based alignment for 63 compounds. Novel molecules were designed from the output of this study.

Methods: A total of 3 alignment methods were used to generate CoMFA and CoMSIA models. A Distill based alignment method was considered a better method according to different validation parameters. A 3D-QSAR model was generated and contour maps were discussed. The biological activity of designed molecules was predicted using the generated QSAR model to validate QSAR. The newly designed molecules were docked to predict binding affinity.

Results: In CoMFA, leave one out cross-validated coefficient (q2), conventional coefficient (r2) and predicted correlation coefficient (r2Predicted) values were found to be 0.721, 0.991 and 0.780, respectively. The best obtained CoMSIA model also showed significant cross-validated coefficient (q2), conventional coefficient (r2) and predicted correlation coefficient (r2Predicted) values of 0.714, 0.987 and 0.721, respectively. Steric and electrostatic contour maps generated from CoMFA and hydrophobic and hydrogen bond donor and hydrogen bond acceptor contour maps from CoMSIA models were used to design new and bioactive protease inhibitors by incorporating bioisosterism and knowledge-based structure-activity relationship.

Conclusion: The results from both these approaches, ligand-based drug design and structure-based drug design, are adequate and promising to discover protease inhibitors.

Keywords: HIV protease, 3D-QSAR, CoMFA, CoMSIA, molecular docking, design.

« Previous Next »
Graphical Abstract

[1]
UNAIDs: AIDSinfo. https://aidsinfo.unaids.org/
[2]
Pironti A, Pfeifer N, Kaiser R, Walter H, Lengauer T. Improved therapy-success prediction with GSS estimated from clinical HIV-1 sequences. J Int AIDS Soc 2014; 17(4)(Suppl. 3): 19743.
[http://dx.doi.org/10.7448/IAS.17.4.19743] [PMID: 25397488]
[3]
Hamarsheh O. HIV/AIDS in Palestine: A growing concern. Int J Infect Dis 2020; 90: 18-20.
[http://dx.doi.org/10.1016/j.ijid.2019.10.019] [PMID: 31648004]
[4]
Dou Y, Zhu M, Dong B, et al. Design, synthesis and biological evaluation of HIV-1 protease inhibitors with morpholine derivatives as P2 ligands in combination with cyclopropyl as P1′ ligand. Bioorg Med Chem Lett 2020; 30(7): 127019.
[http://dx.doi.org/10.1016/j.bmcl.2020.127019] [PMID: 32057582]
[5]
Ghosh AK, Williams JN, Kovela S, et al. Potent HIV-1 protease inhibitors incorporating squaramide-derived P2 ligands: Design, synthesis, and biological evaluation. Bioorg Med Chem Lett 2019; 29(18): 2565-70.
[http://dx.doi.org/10.1016/j.bmcl.2019.08.006] [PMID: 31416666]
[6]
Tong J, Bai M, Zhao X. 3D-QSAR and docking studies of HIV-1 protease inhibitors using R-group search and Surflex-dock. Med Chem Res 2016; 25: 2619-30.
[http://dx.doi.org/10.1007/s00044-016-1701-0]
[7]
Calugi C, Guarna A, Trabocchi A. Heterocyclic HIV-protease inhibitors. Curr Med Chem 2013; 20(30): 3693-710.
[http://dx.doi.org/10.2174/09298673113209990135] [PMID: 23746271]
[8]
Pang X, Liu Z, Zhai G. Advances in non-peptidomimetic HIV protease inhibitors. Curr Med Chem 2014; 21(17): 1997-2011.
[http://dx.doi.org/10.2174/0929867321666140217115951] [PMID: 24533811]
[9]
Voshavar C. Protease inhibitors for the treatment of hiv/aids: recent advances and future challenges. Curr Top Med Chem 2019; 19(18): 1571-98.
[http://dx.doi.org/10.2174/1568026619666190619115243] [PMID: 31237209]
[10]
Lindsten K, Uhlíková T, Konvalinka J, Masucci MG, Dantuma NP. Cell-based fluorescence assay for human immunodeficiency virus type 1 protease activity. Antimicrob Agents Chemother 2001; 45(9): 2616-22.
[http://dx.doi.org/10.1128/AAC.45.9.2616-2622.2001] [PMID: 11502538]
[11]
Benko Z, Elder RT, Liang D, Zhao RY. Fission yeast as a HTS platform for molecular probes of HIV-1 Vpr-induced cell death. Int J High Throughput Screen 2010; 2010(1): 151-62.
[12]
Telvekar VN, Chaudhari HK. 3D-QSAR and docking-based combined in silico study on C-5 methyl substituted 4-arylthio and 4-aryloxy-3-iodopyridin-2-(1H)-one as HIV-1 RT inhibitors. Med Chem Res 2012; 21: 2032-43.
[http://dx.doi.org/10.1007/s00044-011-9720-3]
[13]
Das K, Arnold E. HIV-1 reverse transcriptase and antiviral drug resistance. Part 1. Curr Opin Virol 2013; 3(2): 111-8.
[http://dx.doi.org/10.1016/j.coviro.2013.03.012] [PMID: 23602471]
[14]
Götte M. Mechanisms of resistance associated with excision of incorporated nucleotide analogue inhibitors of HIV-1 reverse transcriptase. Curr Opin HIV AIDS 2007; 2(2): 103-7.
[http://dx.doi.org/10.1097/COH.0b013e3280287a60] [PMID: 19372874]
[15]
Das K, Arnold E. HIV-1 reverse transcriptase and antiviral drug resistance. Part 2. Curr Opin Virol 2013; 3(2): 119-28.
[http://dx.doi.org/10.1016/j.coviro.2013.03.014] [PMID: 23602470]
[16]
Rhee S-Y, Gonzales MJ, Kantor R, Betts BJ, Ravela J, Shafer RW. Human immunodeficiency virus reverse transcriptase and protease sequence database. Nucleic Acids Res 2003; 31(1): 298-303.
[http://dx.doi.org/10.1093/nar/gkg100] [PMID: 12520007]
[17]
Karmochkine M, Si Mohamed A, Piketty C, et al. The cumulative occurrence of resistance mutations in the HIV-1 protease gene is associated with failure of salvage therapy with ritonavir and saquinavir in protease inhibitor-experienced patients. Antiviral Res 2000; 47(3): 179-88.
[http://dx.doi.org/10.1016/S0166-3542(00)00110-8] [PMID: 10974370]
[18]
Yili D, Kenneth LS, Chamakura VNS, Vara P, Bingyun W. Synthesis of novel heterocyclic sulfonamides as protease inhibitors of HIV-1. Lett Org Chem 2018; 15: 87-91.
[19]
Wensing AM, van Maarseveen NM, 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]
[20]
Silverstein PS, Shah A, Weemhoff J, Kumar S, Singh DP, Kumar A. HIV-1 gp120 and drugs of abuse: interactions in the central nervous system. Curr HIV Res 2012; 10(5): 369-83.
[http://dx.doi.org/10.2174/157016212802138724] [PMID: 22591361]
[21]
Vivithanaporn P, Asahchop EL, Acharjee S, Baker GB, Power C. HIV protease inhibitors disrupt astrocytic glutamate transporter function and neurobehavioral performance. AIDS 2016; 30(4): 543-52.
[http://dx.doi.org/10.1097/QAD.0000000000000955] [PMID: 26558720]
[22]
Qiu X, Liu Z-P. Recent developments of peptidomimetic HIV-1 protease inhibitors. Curr Med Chem 2011; 18(29): 4513-37.
[http://dx.doi.org/10.2174/092986711797287566] [PMID: 21864279]
[23]
Ferreira LG, Andricopulo AD. Fragment-based qsar and structural analysis of a series of hydroxyethylamine derivatives as hiv-1 protease inhibitors. Comb Chem High Throughput Screen 2015; 18(5): 464-75.
[http://dx.doi.org/10.2174/1386207318666150508095331] [PMID: 25961662]
[24]
Calza L, Manfredi R. Protease inhibitor monotherapy as maintenance regimen in patients with HIV infection. Curr HIV Res 2012; 10(8): 661-72.
[http://dx.doi.org/10.2174/157016212803901419] [PMID: 23016538]
[25]
Huang L, Chen C. Understanding HIV-1 protease autoprocessing for novel therapeutic development. Future Med Chem 2013; 5(11): 1215-29.
[http://dx.doi.org/10.4155/fmc.13.89] [PMID: 23859204]
[26]
Agbowuro AA, Huston WM, Gamble AB, Tyndall JDA. Proteases and protease inhibitors in infectious diseases. Med Res Rev 2018; 38(4): 1295-331.
[http://dx.doi.org/10.1002/med.21475] [PMID: 29149530]
[27]
Lv Z, Chu Y, Wang Y. HIV protease inhibitors: a review of molecular selectivity and toxicity. HIV AIDS (Auckl) 2015; 7: 95-104.
[PMID: 25897264]
[28]
Subbaiah MAM, Meanwell NA, Kadow JF. Design strategies in the prodrugs of HIV-1 protease inhibitors to improve the pharmaceutical properties. Eur J Med Chem 2017; 139: 865-83.
[http://dx.doi.org/10.1016/j.ejmech.2017.07.044] [PMID: 28865281]
[29]
Vierling P, Greiner J. Prodrugs of HIV protease inhibitors. Curr Pharm Des 2003; 9(22): 1755-70.
[http://dx.doi.org/10.2174/1381612033454441] [PMID: 12871195]
[30]
Croxtall JD, Perry CM. Lopinavir/Ritonavir: a review of its use in the management of HIV-1 infection. Drugs 2010; 70(14): 1885-915.
[http://dx.doi.org/10.2165/11204950-000000000-00000] [PMID: 20836579]
[31]
Cleves AE, Jain AN. Effects of inductive bias on computational evaluations of ligand-based modeling and on drug discovery. J Comput Aided Mol Des 2008; 22(3-4): 147-59.
[http://dx.doi.org/10.1007/s10822-007-9150-y] [PMID: 18074107]
[32]
Bacilieri M, Moro S. Ligand-based drug design methodologies in drug discovery process: an overview. Curr Drug Discov Technol 2006; 3(3): 155-65.
[http://dx.doi.org/10.2174/157016306780136781] [PMID: 17311561]
[33]
Loganathan L, Muthusamy K. Current scenario in structure and ligand-based drug design on anti-colon cancer drugs. Curr Pharm Des 2018; 24(32): 3829-41.
[http://dx.doi.org/10.2174/1381612824666181114114513] [PMID: 30426891]
[34]
Ui M, Tsumoto K. An approach to rational ligand-design based on a thermodynamic analysis. Recent Pat Biotechnol 2010; 4(3): 183-8.
[http://dx.doi.org/10.2174/187220810793611482] [PMID: 21171955]
[35]
Gao Q, Yang L, Zhu Y. Pharmacophore based drug design approach as a practical process in drug discovery. Curr Comput Aided Drug Des 2010; 6(1): 37-49.
[http://dx.doi.org/10.2174/157340910790980151] [PMID: 20370694]
[36]
Baig MH, Ahmad K, Roy S, et al. Computer Aided Drug Design: Success and Limitations. Curr Pharm Des 2016; 22(5): 572-81.
[http://dx.doi.org/10.2174/1381612822666151125000550] [PMID: 26601966]
[37]
Matthias D, Kurt V, Danail B. Statistical modelling of molecular descriptors in QSAR/QSPR. J Cheminform 2012; 4: 36.
[38]
Akamatsu M. Current state and perspectives of 3D-QSAR. Curr Top Med Chem 2002; 2(12): 1381-94.
[http://dx.doi.org/10.2174/1568026023392887] [PMID: 12470286]
[39]
Arakawa M, Hasegawa K, Funatsu K. The recent trend in qsar modeling - variable selection and 3D-QSAR methods. Curr Comput Aided Drug Des 2007; 3: 254-62.
[http://dx.doi.org/10.2174/157340907782799417]
[40]
Melo-Filho CC, Braga RC, AndradeCH. 3D-QSAR approaches in drug design: Perspectives to generate reliable CoMFA models. Curr Comput Aided Drug Des 2014; 10: 148-59.
[http://dx.doi.org/10.2174/1573409910666140410111043]
[41]
Verma J, Khedkar VM, Coutinho EC. 3D-QSAR in drug design-a review. Curr Top Med Chem 2010; 10(1): 95-115.
[http://dx.doi.org/10.2174/156802610790232260] [PMID: 19929826]
[42]
Bhatt HG, Patel PK. Pharmacophore modeling, virtual screening and 3D-QSAR studies of 5-tetrahydroquinolinylidine aminoguanidine derivatives as sodium hydrogen exchanger inhibitors. Bioorg Med Chem Lett 2012; 22(11): 3758-65.
[http://dx.doi.org/10.1016/j.bmcl.2012.04.012] [PMID: 22546667]
[43]
Zhang L, Keng-Chang T, Lupei D, Hao F, Minyong L, Wenfang X. How to generate reliable and predictive CoMFA Models. Curr Med 2011; 18: 923-30.
[44]
Debnath AK. Application of 3D-QSAR techniques in anti-HIV-1 drug design-an overview. Curr Pharm Des 2005; 11(24): 3091-110.
[http://dx.doi.org/10.2174/1381612054864902] [PMID: 16178747]
[45]
Hemmateenejad B, Javidnia K, Nematollahi M. QSAR studies on the antiviral compounds of natural origin. JICS 2009; 6: 420-35.
[http://dx.doi.org/10.1007/BF03245853]
[46]
Vanangamudi M, Poongavanam V, Namasivayam V. HIV-1 non-nucleoside reverse transcriptase inhibitors: sar and lead optimization using CoMFA and CoMSIA studies (1995-2016). Curr Med Chem 2017; 24(34): 3774-812.
[http://dx.doi.org/10.2174/0929867324666170705122851] [PMID: 28685686]
[47]
Saini V, Piplani S, Dang AS, Kumar A. CoMFA, CoMSIA and docking studies of saquinavir based peptidomimetic inhibitors of HIV-1 protease. Curr Enzym Inhib 2016; 12: 161-9.
[http://dx.doi.org/10.2174/1573408011666151020213100]
[48]
Brylinski M, Feinstein WP. eFindSite: improved prediction of ligand binding sites in protein models using meta-threading, machine learning and auxiliary ligands. J Comput Aided Mol Des 2013; 27(6): 551-67.
[http://dx.doi.org/10.1007/s10822-013-9663-5] [PMID: 23838840]
[49]
Adriano D. Andricopulo, Lívia B. Salum, Abraham DJ. Structure-based drug design strategies in medicinal chemistry. Curr Top Med Chem 2009; 9: 771-90.
[http://dx.doi.org/10.2174/156802609789207127]
[50]
Wang T, Wu M-B, Zhang R-H, et al. Advances in computational structure-based drug design and application in drug discovery. Curr Top Med Chem 2016; 16(9): 901-16.
[http://dx.doi.org/10.2174/1568026615666150825142002] [PMID: 26303430]
[51]
Macalino SJY, Gosu V, Hong S, Choi S. Role of computer-aided drug design in modern drug discovery. Arch Pharm Res 2015; 38(9): 1686-701.
[http://dx.doi.org/10.1007/s12272-015-0640-5] [PMID: 26208641]
[52]
Chen L, Morrow JK, Tran HT, Phatak SS, Du-Cuny L, Zhang S. From laptop to benchtop to bedside: structure-based drug design on protein targets. Curr Pharm Des 2012; 18(9): 1217-39.
[http://dx.doi.org/10.2174/138161212799436386] [PMID: 22316152]
[53]
Muegge I, Bergner A, Kriegl JM. Computer-aided drug design at Boehringer Ingelheim. J Comput Aided Mol Des 2017; 31(3): 275-85.
[http://dx.doi.org/10.1007/s10822-016-9975-3] [PMID: 27650777]
[54]
Kishan KV. Structural biology, protein conformations and drug designing. Curr Protein Pept Sci 2007; 8(4): 376-80.
[http://dx.doi.org/10.2174/138920307781369454] [PMID: 17696870]
[55]
Ghosh AK, Brindisi M, Nyalapatla PR, et al. Design of novel HIV-1 protease inhibitors incorporating isophthalamide-derived P2-P3 ligands: Synthesis, biological evaluation and X-ray structural studies of inhibitor-HIV-1 protease complex. Bioorg Med Chem 2017; 25(19): 5114-27.
[http://dx.doi.org/10.1016/j.bmc.2017.04.005] [PMID: 28434781]
[56]
Ghosh AK, Takayama J, Kassekert LA, et al. Structure-based design, synthesis, X-ray studies, and biological evaluation of novel HIV-1 protease inhibitors containing isophthalamide-derived P2-ligands. Bioorg Med Chem Lett 2015; 25(21): 4903-9.
[http://dx.doi.org/10.1016/j.bmcl.2015.05.052] [PMID: 26096678]
[57]
Takashiro E, Nakamura Y, Miyamoto S, Ozawa Y, Sugiyama A, Fujimoto K. Design and synthesis of a novel series of HIV-1 protease inhibitors. Bioorg Med Chem 1999; 7(9): 2105-14.
[http://dx.doi.org/10.1016/S0968-0896(99)00163-7] [PMID: 10530961]
[58]
Borisa A, Bhatt H. 3D-QSAR (CoMFA, CoMFA-RG, CoMSIA) and molecular docking study of thienopyrimidine and thienopyridine derivatives to explore structural requirements for aurora-B kinase inhibition. Eur J Pharm Sci 2015; 79: 1-12.
[http://dx.doi.org/10.1016/j.ejps.2015.08.017] [PMID: 26343315]
[59]
Sybyl X. Molecular modelling software. Tripos Certara,V.1.2, St. Louis 2011.
[60]
Patel S, Patel B, Bhatt H. 3D-QSAR studies on 5-hydroxy-6-oxo-1, 6-dihydropyrimidine-4-carboxamide derivatives as HIV-1 integrase inhibitors. J Taiwan Inst Chem Eng 2016; 59: 61-8.
[http://dx.doi.org/10.1016/j.jtice.2015.07.024]
[61]
Iang Y, Chen Y. Quantitative structure-activity relationship of 2-alkyl-4-(biphenylylmethoxy) pyridine derivatives with AT1 receptor antagonistic activity. J Cent South Univ Technol 2012; 19: 1212-8.
[http://dx.doi.org/10.1007/s11771-012-1131-1]
[62]
Matheus P. Freitas, Multivariate QSAR: From Classical Descriptors to New Perspectives. Curr Comput Aided Drug Des 2007; 3: 235-9.
[http://dx.doi.org/10.2174/157340907782799408]
[63]
Chaube U, Bhatt H. 3D-QSAR, molecular dynamics simulations, and molecular docking studies on pyridoaminotropanes and tetrahydroquinazoline as mTOR inhibitors. Mol Divers 2017; 21(3): 741-59.
[http://dx.doi.org/10.1007/s11030-017-9752-9] [PMID: 28577112]
[64]
Geethaavacini G, Poh GP, Yan LY, et al. QSAR and Pharmacophore Mapping Studies on Benzothiazinimines to Relate their Structural Features with anti-HIV Activity. Med Chem 2018; 14(7): 733-40.
[http://dx.doi.org/10.2174/1573406414666180529091618] [PMID: 29807521]
[65]
Ravichandran V, Rohini K, Harish R, et al. Insights into the key structural features of triazolothienopyrimidines as anti-HIV agents using QSAR, molecular docking, and pharmacophore modeling. Struct Chem 2019; 30: 1471-84.
[http://dx.doi.org/10.1007/s11224-019-01304-1]
[66]
Srivastava VK, Tiwari M. QSAR and docking studies of coumarin derivatives as potent HIV-1 integrase inhibitors. Arab J Chem 2017; 10: 1081-94.
[http://dx.doi.org/10.1016/j.arabjc.2013.01.015]
[67]
Nidhi , Siddiqi MI. Recent advances in QSAR-based identification and design of anti-tubercular agents. Curr Pharm Des 2014; 20(27): 4418-26.
[http://dx.doi.org/10.2174/1381612819666131118165059] [PMID: 24245761]
[68]
Ying H, Wu C, Hu C. The Docking Based 3D-QSAR Studies on Isoindolinone Derived Inhibitors of p53-MDM2 Binding. Lett Drug Des Discov 2014; 11: 50-8.
[http://dx.doi.org/10.2174/15701808113109990053]
[69]
Ragno R. www.3d-qsar.com: a web portal that brings 3-D QSAR to all electronic devices-the Py-CoMFA web application as tool to build models from pre-aligned datasets. J Comput Aided Mol Des 2019; 33(9): 855-64.www.3d-qsar.com
[http://dx.doi.org/10.1007/s10822-019-00231-x] [PMID: 31595406]
[70]
Cramer RD. Topomer CoMFA: a design methodology for rapid lead optimization. J Med Chem 2003; 46(3): 374-88.
[http://dx.doi.org/10.1021/jm020194o] [PMID: 12540237]
[71]
Cramer RD, Patterson DE, Bunce JD. Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. J Am Chem Soc 1988; 110(18): 5959-67.
[http://dx.doi.org/10.1021/ja00226a005] [PMID: 22148765]
[72]
Chaube U, Chhatbar D, Bhatt H. 3D-QSAR, molecular dynamics simulations and molecular docking studies of benzoxazepine moiety as mTOR inhibitor for the treatment of lung cancer. Bioorg Med Chem Lett 2016; 26(3): 864-74.
[http://dx.doi.org/10.1016/j.bmcl.2015.12.075] [PMID: 26764189]
[73]
Klebe G, Abraham U, Mietzner T. Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity. J Med Chem 1994; 37(24): 4130-46.
[http://dx.doi.org/10.1021/jm00050a010] [PMID: 7990113]
[74]
Patel P, Chintha C, Ghate M, et al. 3D QSAR study of 4H-chromen-1,2,3,4-tetrahydropyrimidine-5-carboxylate derivatives as potential anti-mycobacterial agents. Med Chem Res 2014; 23: 2955-63.
[http://dx.doi.org/10.1007/s00044-013-0881-0]
[75]
Vyas VK, Bhatt HG, Patel PK, et al. CoMFA and CoMSIA studies on C-aryl glucoside SGLT2 inhibitors as potential anti-diabetic agents. SAR QSAR Environ Res 2013; 24(7): 519-51.
[http://dx.doi.org/10.1080/1062936X.2012.751553] [PMID: 23305412]
[76]
Mohammadi AA, Taheri S, Amouzegar A, Ahdenov R, Halvagar MR, Sadr AS. Diastereoselective synthesis and molecular docking studies of novel fused tetrahydropyridine derivatives as new inhibitors of HIV protease. J Mol Struct 2017; 1139: 166-74.
[http://dx.doi.org/10.1016/j.molstruc.2017.03.029]

Rights & Permissions Print Cite
Article Metrics
29
1
World Immunization Week
© 2024 Bentham Science Publishers | Privacy Policy