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Kovačević SZ, Karadžić MŽ, Vukić DV, Vukić VR, Podunavac-Kuzmanović SO, Jevrić LR, Ajduković JJ. Toward steroidal anticancer drugs: Non-parametric and 3D-QSAR modeling of 17-picolyl and 17-picolinylidene androstanes with antiproliferative activity on breast adenocarcinoma cells. J Mol Graph Model 2018; 87:240-249. [PMID: 30594032 DOI: 10.1016/j.jmgm.2018.12.010] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2018] [Revised: 12/11/2018] [Accepted: 12/13/2018] [Indexed: 02/08/2023]
Abstract
The present study is aimed to analyze lipophilicity and ADMET profiles, and to develop field based 3D-QSAR and ligand-based pharmacophore hypothesis for a series of 17α-picolyl and 17(E)-picolinylidene androstane derivatives in order to give detailed structural insights and to highlight important binding features of novel androstane derivatives, as compounds with antiproliferative activity toward breast adenocarcinoma cells. This study can provide guidelines for the rational design of novel potent compounds. Sum of ranking differences (SRD), as a non-parametric method, was applied for compounds ranking. 3D-QSAR methods, including comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA), were applied to predict the antiproliferative effect on breast adenocarcinoma cells and provide the regions in space where interactive fields may influence the activity. The compounds are ranked so the compounds with the most favorable ADME and lipophilicity features together with significant anticancer activity can be distinguished. The established 3D-QSAR model could be used for design of new compounds with antiproliferative activity on the human ER- breast adenocarcinoma cells. The pharmacophore model is able to accurately predict antiproliferative activity. Generally, the present study provides significant guidelines for further selection, synthesis and rational design of new highly potential androstane derivatives as anticancer drugs.
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Affiliation(s)
- Strahinja Z Kovačević
- University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21000, Novi Sad, Serbia.
| | - Milica Ž Karadžić
- University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21000, Novi Sad, Serbia
| | - Dajana V Vukić
- University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21000, Novi Sad, Serbia
| | - Vladimir R Vukić
- University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21000, Novi Sad, Serbia
| | | | - Lidija R Jevrić
- University of Novi Sad, Faculty of Technology Novi Sad, Bulevar cara Lazara 1, 21000, Novi Sad, Serbia
| | - Jovana J Ajduković
- University of Novi Sad, Faculty of Sciences, Department of Chemistry, Biochemistry and Environmental Protection, Trg Dositeja Obradovića 3, 21000, Novi Sad, Serbia
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Toward the identification of a reliable 3D-QSAR model for the protein tyrosine phosphatase 1B inhibitors. J Mol Struct 2018. [DOI: 10.1016/j.molstruc.2018.01.011] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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3
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Atomic 3D-QSAR study based on pharmacophore modeling of resveratrol derivatives as selective COX-2 inhibitors. Med Chem Res 2017. [DOI: 10.1007/s00044-017-1830-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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4
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Chandra S, Pandey J, Tamrakar AK, Siddiqi MI. Multiple machine learning based descriptive and predictive workflow for the identification of potential PTP1B inhibitors. J Mol Graph Model 2016; 71:242-256. [PMID: 28006676 DOI: 10.1016/j.jmgm.2016.10.020] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2016] [Revised: 09/27/2016] [Accepted: 10/25/2016] [Indexed: 12/21/2022]
Abstract
In insulin and leptin signaling pathway, Protein-Tyrosine Phosphatase 1B (PTP1B) plays a crucial controlling role as a negative regulator, which makes it an attractive therapeutic target for both Type-2 Diabetes (T2D) and obesity. In this work, we have generated classification models by using the inhibition data set of known PTP1B inhibitors to identify new inhibitors of PTP1B utilizing multiple machine learning techniques like naïve Bayesian, random forest, support vector machine and k-nearest neighbors, along with structural fingerprints and selected molecular descriptors. Several models from each algorithm have been constructed and optimized, with the different combination of molecular descriptors and structural fingerprints. For the training and test sets, most of the predictive models showed more than 90% of overall prediction accuracies. The best model was obtained with support vector machine approach and has Matthews Correlation Coefficient of 0.82 for the external test set, which was further employed for the virtual screening of Maybridge small compound database. Five compounds were subsequently selected for experimental assay. Out of these two compounds were found to inhibit PTP1B with significant inhibitory activity in in-vitro inhibition assay. The structural fragments which are important for PTP1B inhibition were identified by naïve Bayesian method and can be further exploited to design new molecules around the identified scaffolds. The descriptive and predictive modeling strategy applied in this study is capable of identifying PTP1B inhibitors from the large compound libraries.
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Affiliation(s)
- Sharat Chandra
- Academy of Scientific and Innovative Research (AcSIR), CSIR-Central Drug Resaerch Institute, Campus, Lucknow 226031, India; Molecular and Structural Biology Division, CSIR-Central Drug Research Institute, Lucknow 226031, India
| | - Jyotsana Pandey
- Biochemistry Division, CSIR-Central Drug Research Institute, Lucknow 226031, India
| | | | - Mohammad Imran Siddiqi
- Academy of Scientific and Innovative Research (AcSIR), CSIR-Central Drug Resaerch Institute, Campus, Lucknow 226031, India; Molecular and Structural Biology Division, CSIR-Central Drug Research Institute, Lucknow 226031, India.
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Novel cycloalkylthiophene-imine derivatives bearing benzothiazole scaffold: synthesis, characterization and antiviral activity evaluation. Bioorg Med Chem Lett 2013; 23:5131-4. [PMID: 23920438 DOI: 10.1016/j.bmcl.2013.07.023] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2013] [Revised: 06/23/2013] [Accepted: 07/15/2013] [Indexed: 11/20/2022]
Abstract
A series of novel cycloalkylthiophene-imine derivatives containing benzothiazole unit were designed, synthesized and evaluated for their anti-viral activities. The bio-evaluation results indicated that some of the target compounds (such as 5g, 5i, 5u) exhibited good to moderate antiviral effect on CVB5, ADV7 and EV71 viruses, however, these compounds did not have inhibition activity against H1N1 virus. Especially, the compounds 4c and 4d also exhibited high antiviral activities, which provide a new and efficient approach to evolve novel multi-functional antiviral agents by rational integration of active pharmacophores.
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Monga J, Khokra SL, Husain A. Pharmacophore modeling studies on N-hydroxyphenyl acrylamides and N-hydroxypyridin-2-yl-acrylamides as inhibitor of human cancer leukemia K562 cells. Med Chem Res 2012. [DOI: 10.1007/s00044-012-0182-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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7
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Bharate SB, Singh B, Bharate JB, Jain SK, Meena S, Vishwakarma RA. QSAR and pharmacophore modeling of N-acetyl-2-aminobenzothiazole class of phosphoinositide-3-kinase-α inhibitors. Med Chem Res 2012. [DOI: 10.1007/s00044-012-0081-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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8
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WITHDRAWN: Predicting substituted 2-butylbenzimidazoles derivatives as angiotensin II receptor antagonists: 3D-QSAR and pharmacophore modeling. JOURNAL OF SAUDI CHEMICAL SOCIETY 2011. [DOI: 10.1016/j.jscs.2011.09.001] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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9
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Bharate SB, Singh IP. Quantitative structure–activity relationship study of phloroglucinol-terpene adducts as anti-leishmanial agents. Bioorg Med Chem Lett 2011; 21:4310-5. [DOI: 10.1016/j.bmcl.2011.05.053] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2011] [Revised: 05/07/2011] [Accepted: 05/17/2011] [Indexed: 11/28/2022]
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Li Z, Chen K, Xie H, Wang Y, Dong F. Cluster Analysis and QSAR Study of Some Anti-hepatitis B Virus Agents Comprising 4-Aryl-6-chloro-quinolin-2-ones and 5-Aryl-7-chloro-1,4-benzodiazepines. CHINESE J CHEM 2009. [DOI: 10.1002/cjoc.201090007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
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Bag S, Tawari N, Degani M. Insight into Inhibitory Activity ofMycobacterialDihydrofolate Reductase Inhibitors byIn-silicoMolecular Modeling Approaches. ACTA ACUST UNITED AC 2009. [DOI: 10.1002/qsar.200860067] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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12
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Liu HY, Liu SS, Qin LT, Mo LY. CoMFA and CoMSIA analysis of 2,4-thiazolidinediones derivatives as aldose reductase inhibitors. J Mol Model 2009; 15:837-45. [PMID: 19132416 DOI: 10.1007/s00894-008-0439-0] [Citation(s) in RCA: 14] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/29/2008] [Accepted: 11/22/2008] [Indexed: 12/12/2022]
Abstract
Diabetes remains a life-threatening disease. The clinical profile of diabetic subjects is often worsened by the presence of several long-term complications, for example neuropathy, nephropathy, retinopathy, and cataract. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were performed on a series of 2,4-thiazolidinediones derivatives as aldose reductase (ALR2) inhibitors. Molecular ligand superimposition on a template structure was finished by the database alignment method. The 3D-QSAR models resulted from 44 molecules gave q (2) values of 0.773 and 0.817, r (2) values of 0.981 and 0.979 for CoMFA and CoMSIA, respectively. The contour maps from the models indicated that a large volume group next to the R-substituent will increase the ALR2 inhibitory activity. In fact, adding a -CH(2)COOH substituent at the R-position would generate a new compound with higher predicted activity.
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Affiliation(s)
- Hong-Yan Liu
- Department of Material and Chemical Engineering, Guilin University of Technology, 541004 Guilin, People's Republic of China
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Li ZG, Chen KX, Xie HY, Gao JR. Quantitative Structure-Activity Relationship Analysis of Some Thiourea Derivatives with Activities Against HIV-1 (IIIB). ACTA ACUST UNITED AC 2009. [DOI: 10.1002/qsar.200860097] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/08/2022]
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Chen KX, Xie HY, Li ZG, Gao JR. Quantitative structure-activity relationship studies on 1-aryl-tetrahydroisoquinoline analogs as active anti-HIV agents. Bioorg Med Chem Lett 2008; 18:5381-6. [PMID: 18835162 DOI: 10.1016/j.bmcl.2008.09.056] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2008] [Revised: 07/31/2008] [Accepted: 09/15/2008] [Indexed: 11/28/2022]
Abstract
Predictive quantitative structure-activity relationship analysis was developed for a diverse series of recently synthesized 1-aryl-tetrahydroisoquinoline analogs with anti-HIV activities in this study. The conventional 2D-QSAR models were developed by genetic function approximation (GFA) and stepwise multiple linear regression (MLR) with acceptable explanation of 94.9% and 95.5% and good predicted power of 91.7% and 91.7%, respectively. The results of the 2D-QSAR models were further compared with 3D-QSAR model generated by molecular field analysis (MFA), investigating the substitutional requirements for the favorable receptor-drug interaction and quantitatively indicating the important regions of molecules for their activities. The results obtained by combining these methodologies give insights into the key features for designing more potent analogs against HIV.
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Affiliation(s)
- Ke-xian Chen
- College of Chemical Engineering and Materials Science, Zhejiang University of Technology, 18, Chaowang Road, Hangzhou, Zhejiang 310014, China
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Tawari NR, Bag S, Degani MS. Pharmacophore mapping of a series of pyrrolopyrimidines, indolopyrimidines and their congeners as multidrug-resistance-associated protein (MRP1) modulators. J Mol Model 2008; 14:911-21. [DOI: 10.1007/s00894-008-0330-z] [Citation(s) in RCA: 36] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2008] [Accepted: 06/03/2008] [Indexed: 11/28/2022]
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