Login Register Cart 0
Generic placeholder image

Letters in Drug Design & Discovery

Editor-in-Chief

ISSN (Print): 1570-1808
ISSN (Online): 1875-628X

Back
Research Article

The 3D-QSAR Study, Molecular Docking, and ADMET Analysis of Darunavir Derivatives of HIV-1 Protease Inhibitors

Author(s): Rui-Jing Fang, Yan-Jun Zhang, Wei-Xian Wang, Tian-Le Wu, Shuai-Jun Zhang, Yi-Yang He, Fei Xiong* and Zhong-Hua Wang*

Volume 21, Issue 13, 2024

Published on: 26 September, 2023

Page: [2590 - 2603] Pages: 14

DOI: 10.2174/1570180820666230818100059

Price: $65

Abstract

Background: Acquired Immunodeficiency Syndrome (AIDS) is one of most prevalent infectious diseases in the world , and HIV-1 protease (PR) is a vital target of drug design. Nowadays, threedimensional quantitative structure-activity relationships (3D-QSAR) are applied to help design new protease inhibitions (PIs).

Objective: The primary objective of this study is to apply the 3D-QSAR study to a series of 42 derivatives of Darunavir (DRV) and to design new molecules possessing high antivirus activity.

Methods: Partial Least Squares (PLS) were used to cross-validate the dataset of compounds, and the optimal number of principal components (ONC), cross-validate coefficient (q²), standard error of estimate (SEE), non-cross-validated correlation coefficient (R²) and fisher test value (F) were calculated to assess model robustness. In this study, the CoMSIA-DAH model (q²=0.754, r²= 0.988, rpred 2=0.57) possessed the highest predicted activity. Newly designed molecules were analyzed by docking studies with compound 25 taken as a template.

Results: Within eight newly designed drugs, compound N02 possessed the highest antivirus activity (IC50=0.00461 nM) predicted by the CoMSIA-DAH model. The Surflex-Dock module of SYBYL-X 2.0 was used to affirm the predicted anti-PR activity of the newly designed compounds and the results of docking complex structure could be visualized. All newly designed molecules were in agreement with CSore above four and the docking study revealed that Asp29, Asp30, Ile50, Asp124, Asp128, Asp129 and Ile149 were critical residues in the process of inhibiting PR.

Conclusion: One of the main aspects of this study is the successful design of a series of molecules with excellent investigatory values, which elucidates explicit quantitative structure-activity relationships of DRV derivatives and will provide significant suggestions for future pharmaceutical research.

« Previous Next »
[1]
Mohamed, A.A.; Lu, X.; Mounmin, F.A. Diagnosis and treatment of esophageal candidiasis: Current updates. Can. J. Gastroenterol. Hepatol., 2019, 2019, 3585136.
[http://dx.doi.org/10.1155/2019/3585136] [PMID: 31772927]
[2]
van Veen, K.E.B.; Brouwer, M.C.; van der Ende, A.; van de Beek, D. Bacterial meningitis in patients using immunosuppressive medication: A population-based prospective nationwide study. J. Neuroimmune. Pharmacol., 2017, 12(2), 213-218.
[http://dx.doi.org/10.1007/s11481-016-9705-6] [PMID: 27613024]
[3]
Wordell, C.J.; Hauptman, S.P. Treatment of pneumocystis carinii pneumonia in patients with AIDS. Clin. Pharm., 1988, 7(7), 514-527.
[PMID: 3138063]
[4]
Heath, K.; Levi, J.; Hill, A. The joint united nations programme on HIV/AIDS 95–95–95 targets: Worldwide clinical and cost benefits of generic manufacture. AIDS., 2021, 35(S2), S197-S203.
[http://dx.doi.org/10.1097/QAD.0000000000002983] [PMID: 34115649]
[5]
Kress, J.; Vermeulen, M.; Chudy, M.; Reissinger, A.; Hanschmann, K.M.; Saville, A.; Nübling, C.M. Reliability of CE-marked NATs for HIV-1 subtype C detection and quantitation. J. Clin. Virol., 2020, 132, 104649.
[http://dx.doi.org/10.1016/j.jcv.2020.104649] [PMID: 33027700]
[6]
Tompa, D.R.; Immanuel, A.; Srikanth, S.; Kadhirvel, S. Trends and strategies to combat viral infections: A review on FDA approved antiviral drugs. Int. J. Biol. Macromol., 2021, 172, 524-541.
[http://dx.doi.org/10.1016/j.ijbiomac.2021.01.076] [PMID: 33454328]
[7]
Veselovsky, A.V.; Zharkova, M.S.; Poroikov, V.V.; Nicklaus, M.C. Computer-aided design and discovery of protein–protein interaction inhibitors as agents for anti-HIV therapy. SAR QSAR Environ. Res., 2014, 25(6), 457-471.
[http://dx.doi.org/10.1080/1062936X.2014.898689] [PMID: 24716798]
[8]
Huff, J.R. HIV protease: A novel chemotherapeutic target for AIDS. J. Med. Chem., 1991, 34(8), 2305-2314.
[http://dx.doi.org/10.1021/jm00112a001] [PMID: 1875332]
[9]
Olczak, A. Darunavir, promising option in therapy multi-experience HIV-infected patients. HIV AIDS Rev., 2008, 7(1), 5-9.
[http://dx.doi.org/10.1016/S1730-1270(10)60059-8]
[10]
Rolle, C.P.; Marquez, O.; Nguyen, V.; Hinestrosa, F.; DeJesus, E. Clinical outcomes of once-daily darunavir in treatment-experienced patients with darunavir resistance-associated mutations through 48 weeks of treatment. Int. J. STD AIDS, 2020, 31(10), 958-966.
[http://dx.doi.org/10.1177/0956462420926405] [PMID: 32698728]
[11]
Ma, L.; Wen, J.; Dong, B.; Zhou, J.; Hu, S.; Wang, J.; Wang, Y.; Zhu, M.; Cen, S. Design and evaluation of novel HIV-1 protease inhibitors containing phenols or polyphenols as P2 ligands with high activity against DRV-resistant HIV-1 variants. Int. J. Mol. Sci., 2022, 23(22), 14178.
[http://dx.doi.org/10.3390/ijms232214178] [PMID: 36430656]
[12]
Zhu, M.; Shan, Q.; Ma, L.; Wen, J.; Dong, B.; Zhang, G.; Wang, M.; Wang, J.; Zhou, J.; Cen, S.; Wang, Y. Design and biological evaluation of cinnamic and phenylpropionic amide derivatives as novel dual inhibitors of HIV-1 protease and reverse transcriptase. Eur. J. Med. Chem., 2021, 220, 113498.
[http://dx.doi.org/10.1016/j.ejmech.2021.113498] [PMID: 33933756]
[13]
Shaker, B.; Ahmad, S.; Lee, J.; Jung, C.; Na, D. In silico methods and tools for drug discovery. Comput. Biol. Med., 2021, 137, 104851.
[http://dx.doi.org/10.1016/j.compbiomed.2021.104851] [PMID: 34520990]
[14]
Cramer, R.D.; Patterson, D.E.; Bunce, J.D. Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. J. Am. Chem. Soc., 1988, 110(18), 5959-5967.
[http://dx.doi.org/10.1021/ja00226a005] [PMID: 22148765]
[15]
Matayoshi, E.D.; Wang, G.T.; Krafft, G.A.; Erickson, J. Novel fluorogenic substrates for assaying retroviral proteases by resonance energy transfer. Science., 1990, 247(4945), 954-958.
[http://dx.doi.org/10.1126/science.2106161] [PMID: 2106161]
[16]
Volpe, D.A.; Hamed, S.S.; Zhang, L.K. Use of different parameters and equations for calculation of IC50 values in efflux assays: Potential sources of variability in IC50 determination. AAPS J., 2014, 16(1), 172-180.
[http://dx.doi.org/10.1208/s12248-013-9554-7] [PMID: 24338112]
[17]
Gramatica, P. On the development and validation of QSAR models. Methods. Mol. Biol., 2013, 930, 499-526.
[http://dx.doi.org/10.1007/978-1-62703-059-5_21] [PMID: 23086855]
[18]
Leemans, E.; Mahasenan, K.V.; Kumarasiri, M.; Spink, E.; Ding, D.; O’Daniel, P.I.; Boudreau, M.A.; Lastochkin, E.; Testero, S.A.; Yamaguchi, T.; Lee, M.; Hesek, D.; Fisher, J.F.; Chang, M.; Mobashery, S. Three-dimensional QSAR analysis and design of new 1,2,4-oxadiazole antibacterials. Bioorg. Med. Chem. Lett., 2016, 26(3), 1011-1015.
[http://dx.doi.org/10.1016/j.bmcl.2015.12.041] [PMID: 26733473]
[19]
Zhang, Y.J.; Chen, L.; Xu, J.; Jiang, H.F.; Zhu, Y.R.; Wang, Z.H.; Xiong, F. Evaluation of novel HIV-1 protease inhibitors with DRV-resistance by utilizing 3D-QSAR molecular docking and molecular dynamics simulation. New J. Chem., 2022, 46(45), 21885-21897.
[http://dx.doi.org/10.1039/D2NJ04492G]
[20]
Böhm, M.; Stürzebecher, J.; Klebe, G. Three-dimensional quantitative structure-activity relationship analyses using comparative molecular field analysis and comparative molecular similarity indices analysis to elucidate selectivity differences of inhibitors binding to trypsin, thrombin, and factor Xa. J. Med. Chem., 1999, 42(3), 458-477.
[http://dx.doi.org/10.1021/jm981062r] [PMID: 9986717]
[21]
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), 4130-4146.
[http://dx.doi.org/10.1021/jm00050a010] [PMID: 7990113]
[22]
Wold, S.; Ruhe, A.; Wold, H.; Dunn, W.J., III The collinearity problem in linear regression. The partial least squares (PLS) approach to generalized inverses. SIAM J. Sci. Statist. Comput., 1984, 5(3), 735-743.
[http://dx.doi.org/10.1137/0905052]
[23]
Xu, X.; Zhang, W.; Huang, C.; Li, Y.; Yu, H.; Wang, Y.; Duan, J.; Ling, Y. A novel chemometric method for the prediction of human oral bioavailability. Int. J. Mol. Sci., 2012, 13(6), 6964-6982.
[http://dx.doi.org/10.3390/ijms13066964] [PMID: 22837674]
[24]
Singh, K.P.; Gupta, S. Nano-QSAR modeling for predicting biological activity of diverse nanomaterials. RSC Adv., 2014, 4(26), 13215-13230.
[http://dx.doi.org/10.1039/C4RA01274G]
[25]
Khalid, T.; White, P.; De Lacy Costello, B.; Persad, R.; Ewen, R.; Johnson, E.; Probert, C.S.; Ratcliffe, N. A pilot study combining a GC-sensor device with a statistical model for the identification of bladder cancer from urine headspace. PLoS One, 2013, 8(7), e69602.
[http://dx.doi.org/10.1371/journal.pone.0069602] [PMID: 23861976]
[26]
Chen, L.; Liu, W.G.; Xiong, F.; Ma, C.; Sun, C.; Zhu, Y.R.; Zhang, X.G.; Wang, Z.H. 3D-QSAR, molecular docking and molecular dynamics simulations analyses of a series of heteroaryldihydropyrimidine derivatives as hepatitis B virus capsid assembly inhibitors. New J. Chem., 2021, 45(47), 22062-22076.
[http://dx.doi.org/10.1039/D1NJ02542B]
[27]
Hartshorn, M.J.; Verdonk, M.L.; Chessari, G.; Brewerton, S.C.; Mooij, W.T.M.; Mortenson, P.N.; Murray, C.W. Diverse, high-quality test set for the validation of protein-ligand docking performance. J. Med. Chem., 2007, 50(4), 726-741.
[http://dx.doi.org/10.1021/jm061277y] [PMID: 17300160]
[28]
Ganguly, A.K.; Alluri, S.S.; Wang, C.H.; Antropow, A.; White, A.; Caroccia, D.; Biswas, D.; Kang, E.; Zhang, L.K.; Carroll, S.S.; Burlein, C.; Fay, J.; Orth, P.; Strickland, C. Structural optimization of cyclic sulfonamide based novel HIV-1 protease inhibitors to picomolar affinities guided by X-ray crystallographic analysis. Tetrahedron., 2014, 70(18), 2894-2904.
[http://dx.doi.org/10.1016/j.tet.2014.03.038]
[29]
Ruppert, J.; Welch, W.; Jain, A.N. Automatic identification and representation of protein binding sites for molecular docking. Protein Sci., 1997, 6(3)
[30]
Xiong, F.; Chen, L.; Zhang, Y.; Zhu, Y.; Sun, C.; Ma, C.; Zhang, S.; Wang, Z. Molecular modeling and docking studies of 2,4,5-trisubstituted pyrimidines as HIV-1 non-nucleoside reverse transcriptase inhibitors. Polycycl. Aromat. Compd., 2022, 1-20.
[http://dx.doi.org/10.1080/10406638.2022.2141274]
[31]
Yang, H.; Lou, C.; Sun, L.; Li, J.; Cai, Y.; Wang, Z.; Li, W.; Liu, G.; Tang, Y. admetSAR 2.0: Web-service for prediction and optimization of chemical ADMET properties. Bioinformatics., 2019, 35(6), 1067-1069.
[http://dx.doi.org/10.1093/bioinformatics/bty707] [PMID: 30165565]
[32]
Pires, D.E.V.; Blundell, T.L.; Ascher, D.B. pkCSM: Predicting small-molecule pharmacokinetic and toxicity properties using graph-based signatures. J. Med. Chem., 2015, 58(9), 4066-4072.
[http://dx.doi.org/10.1021/acs.jmedchem.5b00104] [PMID: 25860834]
[33]
Daina, A.; Michielin, O.; Zoete, V. SwissADME: A free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules. Sci. Rep., 2017, 7(1), 42717.
[http://dx.doi.org/10.1038/srep42717] [PMID: 28256516]
[34]
Zhou, S.F.; Zhou, Z.W.; Yang, L.P.; Cai, J.P. Substrates, inducers, inhibitors and structure-activity relationships of human Cytochrome P450 2C9 and implications in drug development. Curr. Med. Chem., 2009, 16(27), 3480-3675.
[http://dx.doi.org/10.2174/092986709789057635] [PMID: 19515014]
[35]
Escobar, P.A.; Kemper, R.A.; Tarca, J.; Nicolette, J.; Kenyon, M.; Glowienke, S.; Sawant, S.G.; Christensen, J.; Johnson, T.E.; McKnight, C.; Ward, G.; Galloway, S.M.; Custer, L.; Gocke, E.; O’Donovan, M.R.; Braun, K.; Snyder, R.D.; Mahadevan, B. Bacterial mutagenicity screening in the pharmaceutical industry. Mutat. Res. Rev. Mutat. Res., 2013, 752(2), 99-118.
[http://dx.doi.org/10.1016/j.mrrev.2012.12.002] [PMID: 23262374]
[36]
Araújo, M.O.; Freire Pessoa, H.L.; Lira, A.B.; Castillo, Y.P.; de Sousa, D.P. Synthesis, antibacterial evaluation, and QSAR of caffeic acid derivatives. J. Chem., 2019, 2019, 3408315.
[http://dx.doi.org/10.1155/2019/3408315]

Rights & Permissions Print Cite
© 2024 Bentham Science Publishers | Privacy Policy