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Haga CL, Le CN, Yang XD, Phinney DG. Py-CoMSIA: An Open-Source Implementation of Comparative Molecular Similarity Indices Analysis in Python. Pharmaceuticals (Basel) 2025; 18:440. [PMID: 40143216 PMCID: PMC11945924 DOI: 10.3390/ph18030440] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2025] [Revised: 03/16/2025] [Accepted: 03/17/2025] [Indexed: 03/28/2025] Open
Abstract
Background/Objectives: The progression of three-dimensional (3D) quantitative structure-activity relationship (QSAR) methodologies has significantly contributed to the advancement of medicinal chemistry and pharmaceutical discovery. Comparative Molecular Similarity Indices Analysis (CoMSIA) is a widely used 3D-QSAR technique. However, its reliance on discontinued proprietary software creates accessibility challenges. This work aims to develop an open-source Python library to address these limitations and broaden access to grid-based 3D-QSAR methods. Methods: Py-CoMSIA was developed in Python using RDKit and NumPy for calculations and PyVista for visualizations. Results: Py-CoMSIA provides a functional open-source alternative to proprietary CoMSIA software. It successfully implements the core CoMSIA algorithm and generates comparable similarity indices, as demonstrated by testing several benchmarking datasets including the original CoMSIA steroid dataset. Conclusions: The Py-CoMSIA library addresses the accessibility issues associated with proprietary 3D-QSAR software by providing an open-source Python implementation of CoMSIA. This tool broadens access to complex grid-based 3D-QSAR methodologies and offers a flexible platform for integrating advanced statistical and machine learning techniques.
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Affiliation(s)
- Christopher L. Haga
- Department of Molecular Medicine, The Herbert Wertheim UF Scripps Institute for Biomedical Innovation & Technology, Jupiter, FL 33458, USA; (C.N.L.); (X.D.Y.); (D.G.P.)
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2
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Edache EI, Uzairu A, Mamza PA, Shallangwa GA. Structure-based simulated scanning of rheumatoid arthritis inhibitors: 2D-QSAR, 3D-QSAR, docking, molecular dynamics simulation, and lipophilicity indices calculation. SCIENTIFIC AFRICAN 2022. [DOI: 10.1016/j.sciaf.2021.e01088] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022] Open
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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; 33:855-864. [DOI: 10.1007/s10822-019-00231-x] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2019] [Accepted: 09/28/2019] [Indexed: 11/28/2022]
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Senra JD, Viana GM, Malta LFB, Simas ABC, Aguiar LCS. Selectivity Studies Towards the Synthesis of Novel Biaryl Ureas by (Hetero)Nanocatalysis: Size Control and Support Effects. ChemCatChem 2015. [DOI: 10.1002/cctc.201500889] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
Affiliation(s)
- Jaqueline D. Senra
- Chemistry Institute; Universidade do Estdo do Rio de Janeiro; Rio de Janeiro, RJ 20550-900 Brazil
| | - Gil M. Viana
- Faculty of Pharmacy; Universidade Federal do Rio de Janeiro; Rio de Janeiro, RJ 21941-614 Brazil
| | - Luiz Fernando B. Malta
- Chemistry Institute; Universidade Federal do Rio de Janeiro; Rio de Janeiro, RJ 21941-903 Brazil
| | - Alessandro B. C. Simas
- Walter Mors Institute of Research on Natural Products; Universidade Federal do Rio de Janeiro; Rio de Janeiro, RJ 21941-614 Brazil
| | - Lucia C. S. Aguiar
- Chemistry Institute; Universidade Federal do Rio de Janeiro; Rio de Janeiro, RJ 21941-903 Brazil
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Bai Q, Zhang Y, Li X, Chen W, Liu H, Yao X. Computational study on the interaction between CCR5 and HIV-1 entry inhibitor maraviroc: insight from accelerated molecular dynamics simulation and free energy calculation. Phys Chem Chem Phys 2015; 16:24332-8. [PMID: 25296959 DOI: 10.1039/c4cp03331k] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
C-C chemokine receptor type 5 (CCR5) is the co-receptor of human immunodeficiency virus type 1 (HIV-1) and plays an important role in HIV-1 virus infection. Maraviroc has been proved to be effective for anti-HIV-1 by targeting CCR5. Understanding the detailed interaction mechanism between CCR5 and Maraviroc will be of great help to the rational design of a more potential inverse agonist to block HIV-1 infection. Here, we performed molecular dynamics (MD) simulation and accelerated MD simulation (aMD) to study the interaction mechanism between CCR5 and Maraviroc based on a recently reported crystal structure. The results of MD simulation demonstrate that Maraviroc can form stable hydrogen bonds with residues Tyr37(1.39), Tyr251(6.51) and Glu283(7.39). The results of aMD simulation indicate that the carboxamide moiety is more flexible than the tropane group of Maraviroc in the pocket of CCR5. The electrostatic potential analysis proves that Maraviroc can escape from the pocket of CCR5 along the negative electrostatic potential pathway during the dissociation process. The free energy calculation illustrates that there exist three binding pockets during the dissociation process of Maraviroc. Our results will be useful for understanding the interaction mechanism between CCR5 and Maraviroc as well as for the rational design of a more potent inverse agonist.
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Affiliation(s)
- Qifeng Bai
- College of Chemistry and Chemical Engineering, Lanzhou University, Lanzhou, Gansu 730000, P. R. China.
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6
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Moonsamy S, Dash RC, Soliman MES. Integrated computational tools for identification of CCR5 antagonists as potential HIV-1 entry inhibitors: homology modeling, virtual screening, molecular dynamics simulations and 3D QSAR analysis. Molecules 2014; 19:5243-65. [PMID: 24762964 PMCID: PMC6270745 DOI: 10.3390/molecules19045243] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2014] [Revised: 04/01/2014] [Accepted: 04/09/2014] [Indexed: 11/16/2022] Open
Abstract
Using integrated in-silico computational techniques, including homology modeling, structure-based and pharmacophore-based virtual screening, molecular dynamic simulations, per-residue energy decomposition analysis and atom-based 3D-QSAR analysis, we proposed ten novel compounds as potential CCR5-dependent HIV-1 entry inhibitors. Via validated docking calculations, binding free energies revealed that novel leads demonstrated better binding affinities with CCR5 compared to maraviroc, an FDA-approved HIV-1 entry inhibitor and in clinical use. Per-residue interaction energy decomposition analysis on the averaged MD structure showed that hydrophobic active residues Trp86, Tyr89 and Tyr108 contributed the most to inhibitor binding. The validated 3D-QSAR model showed a high cross-validated rcv2 value of 0.84 using three principal components and non-cross-validated r2 value of 0.941. It was also revealed that almost all compounds in the test set and training set yielded a good predicted value. Information gained from this study could shed light on the activity of a new series of lead compounds as potential HIV entry inhibitors and serve as a powerful tool in the drug design and development machinery.
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Affiliation(s)
- Suri Moonsamy
- School of Health Sciences, University of KwaZulu-Natal, Westville, Durban 4001, South Africa
| | - Radha Charan Dash
- School of Health Sciences, University of KwaZulu-Natal, Westville, Durban 4001, South Africa
| | - Mahmoud E S Soliman
- School of Health Sciences, University of KwaZulu-Natal, Westville, Durban 4001, South Africa.
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Gadhe CG, Kothandan G, Cho SJ. Computational modeling of human coreceptor CCR5 antagonist as a HIV-1 entry inhibitor: using an integrated homology modeling, docking, and membrane molecular dynamics simulation analysis approach. J Biomol Struct Dyn 2013; 31:1251-76. [DOI: 10.1080/07391102.2012.732342] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
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8
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Gadhe CG, Kothandan G, Cho SJ. Binding site exploration of CCR5 using in silico methodologies: a 3D-QSAR approach. Arch Pharm Res 2013; 36:6-31. [DOI: 10.1007/s12272-013-0001-1] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023]
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LIAO SIYAN, QIAN LI, MIAO TIFANG, SHEN YONG, ZHENG KANGCHENG. 3D-QSAR STUDIES OF SUBSTITUTED 4-ARYL/HETEROARYL-4H-CHROMENES AS APOPTOSIS INDUCERS USING CoMFA AND CoMSIA. JOURNAL OF THEORETICAL & COMPUTATIONAL CHEMISTRY 2011. [DOI: 10.1142/s0219633609004599] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Three-dimensional (3D) quantitative structure–activity relationships (QSARs) of 36 apoptosis inducers, substituted 4-aryl/heteroaryl-4H-chromenes with anticancer activity against human breast cancer cell lines T47D, have been studied by using methods of comparative molecular field analysis (CoMFA) and comparative molecular similarity analysis (CoMSIA). The established 3D-QSAR models in training set show not only significant statistical quality, but also predictive ability, with high correlation coefficient (R2) values and cross-validation coefficient (q2) values: CoMFA (R2, q2: 0.944, 0.747), CoMSIA (R2, q2: 0.944, 0.704). Moreover, the predictive abilities of the CoMFA and CoMSIA models were further confirmed by a test set, giving the predictive correlation coefficients ([Formula: see text] values) of 0.845 and 0.851, respectively. Based on the CoMFA and CoMSIA contour map analyses, some key factors responsible for anticancer activity of this series of compounds have been found as follows: the steric interaction plays a decisive role in determining the anticancer activities of these compounds; bulky groups as substituent R 1 are not tolerated; in addition to a steric moderation, higher degree of electropositivity and hydrophobicity on the terminal alkyl of substituent R 2 might be favorable to the activity; the substituent R 3 should be hydrophobic; bulky and strong electron withdrawing groups for the substituent R 4 are not advantageous to the activity; simultaneously introducing large electronegative atoms as hydrogen-acceptors to the first atoms of the substituents R 5 and R 6 may increase the activity, but substituents R 5 and R 6 with a linking group – OCH 2 O – may decrease the activity. Such results can offer some useful theoretical references for understanding the action mechanism, designing more potent derivatives, and predicting their activities prior to synthesis.
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Affiliation(s)
- SI YAN LIAO
- School of Chemistry and Chemical Engineering, Zhongshan (Sun Yat-Sen) University, Guangzhou 510275, P. R. China
| | - LI QIAN
- School of Chemistry and Chemical Engineering, Zhongshan (Sun Yat-Sen) University, Guangzhou 510275, P. R. China
| | - TI FANG MIAO
- School of Chemistry and Chemical Engineering, Zhongshan (Sun Yat-Sen) University, Guangzhou 510275, P. R. China
| | - YONG SHEN
- School of Chemistry and Chemical Engineering, Zhongshan (Sun Yat-Sen) University, Guangzhou 510275, P. R. China
| | - KANG CHENG ZHENG
- School of Chemistry and Chemical Engineering, Zhongshan (Sun Yat-Sen) University, Guangzhou 510275, P. R. China
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LIAO SIYAN, QIAN LI, CHEN JINCAN, SHEN YONG, ZHENG KANGCHENG. 2D/3D-QSAR STUDY ON ANALOGUES OF 2-METHOXYESTRADIOL WITH ANTICANCER ACTIVITY. JOURNAL OF THEORETICAL & COMPUTATIONAL CHEMISTRY 2011. [DOI: 10.1142/s0219633608003745] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
Two-dimensional (2D) and three-dimensional (3D) quantitative structure–activity relationships (QSARs) of 23 analogs of 2-Methoxyestradiol with anticancer activity (expressed as p GI50) against MCF-7 human breast cancer cells have been studied by using a combined method of the DFT, MM2 and statistics for 2D, as well as the comparative molecular field analysis (CoMFA) for 3D. The established 2D-QSAR model in training set shows not only significant statistical quality, but also predictive ability, with the square of adjusted correlation coefficient [Formula: see text] and the square of the cross-validation coefficient (q2= 0.779). The same model was further applied to predict p GI50values of the four compounds in the test set, and the resulting [Formula: see text] being as high as 0.827, further confirms that this 2D-QSAR model has high predictive ability for this kind of compound. The 3D-QSAR model also shows good correlative and predictive capabilities in terms of R2(0.927) and q2(0.786) obtained from CoMFA model. The results that 2D- and 3D-QSAR analyses accord with each other, suggest that the electrostatic interaction plays a decisive role in determining the anticancer activity of the studied compounds, and that increasing the negative charge of substituent R2and the positive charge of substituents linking to C17as well as decreasing the size of substituent R1are advantageous to improving the cytotoxicity. Such results can offer some useful theoretical references for directing the molecular design and understanding the action mechanism of this kind of compound with anticancer activity.
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Affiliation(s)
- SI YAN LIAO
- School of Chemistry and Chemical Engineering, Zhongshan (Sun Yat-Sen) University, Guangzhou, 510275, P. R. China
| | - LI QIAN
- School of Chemistry and Chemical Engineering, Zhongshan (Sun Yat-Sen) University, Guangzhou, 510275, P. R. China
| | - JIN CAN CHEN
- School of Chemistry and Chemical Engineering, Zhongshan (Sun Yat-Sen) University, Guangzhou, 510275, P. R. China
| | - YONG SHEN
- School of Chemistry and Chemical Engineering, Zhongshan (Sun Yat-Sen) University, Guangzhou, 510275, P. R. China
| | - KANG CHENG ZHENG
- School of Chemistry and Chemical Engineering, Zhongshan (Sun Yat-Sen) University, Guangzhou, 510275, P. R. China
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Asadollahi T, Dadfarnia S, Shabani AMH, Ghasemi JB, Sarkhosh M. QSAR models for CXCR2 receptor antagonists based on the genetic algorithm for data preprocessing prior to application of the PLS linear regression method and design of the new compounds using in silico virtual screening. Molecules 2011; 16:1928-55. [PMID: 21358586 PMCID: PMC6259643 DOI: 10.3390/molecules16031928] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2011] [Revised: 01/31/2011] [Accepted: 02/15/2011] [Indexed: 11/24/2022] Open
Abstract
The CXCR2 receptors play a pivotal role in inflammatory disorders and CXCR2 receptor antagonists can in principle be used in the treatment of inflammatory and related diseases. In this study, quantitative relationships between the structures of 130 antagonists of the CXCR2 receptors and their activities were investigated by the partial least squares (PLS) method. The genetic algorithm (GA) has been proposed for improvement of the performance of the PLS modeling by choosing the most relevant descriptors. The results of the factor analysis show that eight latent variables are able to describe about 86.77% of the variance in the experimental activity of the molecules in the training set. Power prediction of the QSAR models developed with SMLR, PLS and GA-PLS methods were evaluated using cross-validation, and validation through an external prediction set. The results showed satisfactory goodness-of-fit, robustness and perfect external predictive performance. A comparison between the different developed methods indicates that GA-PLS can be chosen as supreme model due to its better prediction ability than the other two methods. The applicability domain was used to define the area of reliable predictions. Furthermore, the in silico screening technique was applied to the proposed QSAR model and the structure and potency of new compounds were predicted. The developed models were found to be useful for the estimation of pIC₅₀ of CXCR2 receptors for which no experimental data is available.
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Affiliation(s)
- Tahereh Asadollahi
- Department of Chemistry, Faculty of Science, Yazd University, Yazd 89195, Iran
| | | | | | - Jahan B. Ghasemi
- Department of Chemistry, Faculty of Science, K. N. Toosi University of Technology, Tehran, Iran
| | - Maryam Sarkhosh
- Department of Chemistry, Faculty of Science, K. N. Toosi University of Technology, Tehran, Iran
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Ai Y, Song FJ, Wang ST, Sun Q, Sun PH. Molecular modeling studies on 11H-dibenz[b,e]azepine and dibenz[b,f][1,4]oxazepine derivatives as potent agonists of the human TRPA1 receptor. Molecules 2010; 15:9364-79. [PMID: 21169885 PMCID: PMC6259276 DOI: 10.3390/molecules15129364] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2010] [Revised: 12/08/2010] [Accepted: 12/15/2010] [Indexed: 11/16/2022] Open
Abstract
A computational strategy based on comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) was performed on a series of the 11H-dibenz[b,e]azepine and dibenz[b,f][1,4]oxazepine derivatives as potent agonists of the human TRPA1 receptor. The CoMFA and CoMSIA models resulting from a 21 molecule training set gave r²(cv) values of 0.631 and 0.542 and r² values of 0.986 and 0.981, respectively. The statistically significant models were validated by a test set of five compounds with predictive r²(pred). values of 0.967 and 0.981 for CoMFA and CoMSIA, respectively. A systemic external validation was also performed on the established models. The information obtained from 3D counter maps could facilitate the design of more potent human TRPA1 receptor agonists.
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Affiliation(s)
- Yong Ai
- College of Pharmacy, South Central University for Nationalities, 708 Minyuan Road, Wuhan 430074, China; E-Mails: (Y.A.); (S.-T.W.); (Q.S.)
| | - Fa-Jun Song
- College of Life Sciences, South Central University for Nationalities, 708 Minyuan Road, Wuhan 430074, China
- Author to whom correspondence should be addressed; E-Mail:
| | - Shao-Teng Wang
- College of Pharmacy, South Central University for Nationalities, 708 Minyuan Road, Wuhan 430074, China; E-Mails: (Y.A.); (S.-T.W.); (Q.S.)
| | - Qiang Sun
- College of Pharmacy, South Central University for Nationalities, 708 Minyuan Road, Wuhan 430074, China; E-Mails: (Y.A.); (S.-T.W.); (Q.S.)
| | - Ping-Hua Sun
- Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research, College of Pharmacy, Jinan University, Guangzhou 510632, China; E-Mail: (P-H.S.)
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Gadhe CG, Lee SH, Madhavan T, Kothandan G, Choi DB, Cho SJ. Ligand Based CoMFA, CoMSIA and HQSAR Analysis of CCR5 Antagonists. B KOREAN CHEM SOC 2010. [DOI: 10.5012/bkcs.2010.31.10.2761] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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Ai Y, Wang ST, Sun PH, Song FJ. Molecular modeling studies of 4,5-dihydro-1H-pyrazolo[4,3-h] quinazoline derivatives as potent CDK2/Cyclin a inhibitors using 3D-QSAR and docking. Int J Mol Sci 2010; 11:3705-24. [PMID: 21152296 PMCID: PMC2996803 DOI: 10.3390/ijms11103705] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2010] [Revised: 09/03/2010] [Accepted: 09/20/2010] [Indexed: 12/11/2022] Open
Abstract
CDK2/cyclin A has appeared as an attractive drug targets over the years with diverse therapeutic potentials. A computational strategy based on comparative molecular fields analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) followed by molecular docking studies were performed on a series of 4,5-dihydro-1H-pyrazolo[4,3-h]quinazoline derivatives as potent CDK2/cyclin A inhibitors. The CoMFA and CoMSIA models, using 38 molecules in the training set, gave r(2) (cv) values of 0.747 and 0.518 and r(2) values of 0.970 and 0.934, respectively. 3D contour maps generated by the CoMFA and CoMSIA models were used to identify the key structural requirements responsible for the biological activity. Molecular docking was applied to explore the binding mode between the ligands and the receptor. The information obtained from molecular modeling studies may be helpful to design novel inhibitors of CDK2/cyclin A with desired activity.
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Affiliation(s)
- Yong Ai
- Laboratory for Natural Product Chemistry, College of Pharmacy, South Central University for Nationalities, 708 Minyuan Road, Wuhan 430074, China; E-Mails: (Y.A.); (S.-T.W.)
| | - Shao-Teng Wang
- Laboratory for Natural Product Chemistry, College of Pharmacy, South Central University for Nationalities, 708 Minyuan Road, Wuhan 430074, China; E-Mails: (Y.A.); (S.-T.W.)
| | - Ping-Hua Sun
- Guangdong Province Key Laboratory of Pharmacodynamic Constituents of TCM and New Drugs Research, College of Pharmacy, Jinan University, Guangzhou 510632, China
| | - Fa-Jun Song
- College of Life Science/Key Laboratory for Biotechnology of the State Ethnic Affairs Commission, South Central University for Nationalities, 708 Minyuan Road, Wuhan 430074, China
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Tan JJ, Cong XJ, Hu LM, Wang CX, Jia L, Liang XJ. Therapeutic strategies underpinning the development of novel techniques for the treatment of HIV infection. Drug Discov Today 2010; 15:186-97. [PMID: 20096804 DOI: 10.1016/j.drudis.2010.01.004] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2009] [Revised: 11/21/2009] [Accepted: 01/14/2010] [Indexed: 11/28/2022]
Abstract
The HIV replication cycle offers multiple targets for chemotherapeutic intervention, including the viral exterior envelope glycoprotein, gp120; viral co-receptors CXCR4 and CCR5; transmembrane glycoprotein, gp41; integrase; reverse transcriptase; protease and so on. Most currently used anti-HIV drugs are reverse transcriptase inhibitors or protease inhibitors. The expanding application of simulation to drug design combined with experimental techniques have developed a large amount of novel inhibitors that interact specifically with targets besides transcriptase and protease. This review presents details of the anti-HIV inhibitors discovered with computer-aided approaches and provides an overview of the recent five-year achievements in the treatment of HIV infection and the application of computational methods to current drug design.
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Affiliation(s)
- Jian J Tan
- College of Life Science and Bio-engineering, Beijing University of Technology, Beijing 100124, China
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Chen JC, Chen LM, Liao SY, Qian L, Zheng KC. 3D-QSAR Study of 7,8-Dialkyl-1,3-diaminopyrrolo-[3,2-f] Quinazolines with Anticancer Activity as DHFR Inhibitors. CHINESE J CHEM PHYS 2009. [DOI: 10.1088/1674-0068/22/03/285-289] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Afantitis A, Melagraki G, Sarimveis H, Koutentis PA, Igglessi-Markopoulou O, Kollias G. A combined LS-SVM & MLR QSAR workflow for predicting the inhibition of CXCR3 receptor by quinazolinone analogs. Mol Divers 2009; 14:225-35. [DOI: 10.1007/s11030-009-9163-7] [Citation(s) in RCA: 43] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2009] [Accepted: 05/09/2009] [Indexed: 11/28/2022]
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Afantitis A, Melagraki G, Sarimveis H, Igglessi-Markopoulou O, Kollias G. A novel QSAR model for predicting the inhibition of CXCR3 receptor by 4-N-aryl-[1,4] diazepane ureas. Eur J Med Chem 2009; 44:877-84. [DOI: 10.1016/j.ejmech.2008.05.028] [Citation(s) in RCA: 45] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2007] [Revised: 03/12/2008] [Accepted: 05/23/2008] [Indexed: 11/30/2022]
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Zhuo Y, Kong R, Cong XJ, Chen WZ, Wang CX. Three-dimensional QSAR analyses of 1,3,4-trisubstituted pyrrolidine-based CCR5 receptor inhibitors. Eur J Med Chem 2008; 43:2724-34. [DOI: 10.1016/j.ejmech.2008.01.040] [Citation(s) in RCA: 13] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2007] [Revised: 01/14/2008] [Accepted: 01/14/2008] [Indexed: 11/28/2022]
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Predictive QSAR modeling of CCR5 antagonist piperidine derivatives using chemometric tools. J Enzyme Inhib Med Chem 2008; 24:205-23. [DOI: 10.1080/14756360802051297] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022] Open
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Dessalew N. QSAR Study on Piperidinecarboxamides as Antiretroviral Agents: An Insight Into the Structural Basis for HIV Coreceptor Antagonist Activity. ACTA ACUST UNITED AC 2008. [DOI: 10.1002/qsar.200760177] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Liao S, Qian L, Lu H, Shen Y, Zheng K. A Combined 2D‐ and 3D‐QSAR Study on Analogues of ARC‐111 with Antitumor Activity. ACTA ACUST UNITED AC 2008. [DOI: 10.1002/qsar.200730154] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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