Improved 3D-QSAR prediction by multiple-conformational alignment: A case study on PTP1B inhibitors |
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| Affiliation: | 1. Key Laboratory of Structure-Based Drug Design & Discovery, Ministry of Education, Shenyang Pharmaceutical University, Shenyang 110016, China;2. Faculty of Pharmaceutical Sciences, Toho University, Miyama 2-2-1, Funabashi, Chiba, 274-8510, Japan;1. Department of Life Sciences, Faculty of Life and Environmental Sciences, Prefectural University of Hiroshima, 5562 Nanatsuka, Shobara, 727-0023, Japan;2. Program in Biological System Sciences, Graduate School of Comprehensive Scientific Research, Prefectural University of Hiroshima, 5562 Nanatsuka, Shobara, 727-0023, Japan;3. Graduate School of Engineering, Osaka Electro-Communication University, 18-8 Hatsu-cho, Neyagawa, 572-8530, Japan;4. Department of Pharmacy, Faculty of Pharmacy, Kindai University, 3-4-1 Kowakae, Higashiosaka, 577-8502, Japan;1. The Rowett Institute, University of Aberdeen, Aberdeen AB25 2ZD, United Kingdom;2. Department of Chemistry, Technical University of Denmark, DK-2800 Kongens Lyngby, Denmark;3. Department of Biochemistry, University of Cambridge, Tennis Court Road, Cambridge CB2 1GA, United Kingdom;1. Shanghai Engineering Research Center of Molecular Therapeutics and New Drug Development, School of Chemistry and Molecular Engineering, East China Normal University, 3663 North Zhongshan Rd., Shanghai 200062, China;2. National Center for Drug Screening, State Key Laboratory of Drug Research, Shanghai Institute of Materia Medica, Chinese Academy of Science, Shanghai 201203, China;1. Molecular Chemistry and Natural Substances Laboratory, Faculty of Science, Moulay Ismail University of Meknes, Morocco;2. EST Khenifra, Sultan Moulay Sliman University, Benimellal, Morocco;1. Key Laboratory of Structure-Based Drug Design & Discovery, Ministry of Education, Shenyang Pharmaceutical University, Shenyang 110016, China;2. Faculty of Pharmaceutical Sciences, Toho University, Chiba 274-8510, Japan;3. School of Pharmaceutical Engineering, Shenyang Pharmaceutical University, Shenyang 110016, China |
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| Abstract: | Three-dimension quantitative structure activity relationship (3D-QSAR) was one of the major statistical techniques to investigate the correlation of biological activity with structural properties of candidate molecules, and the accuracy of statistic greatly depended on molecular alignment methodology. Exhaustive conformational search and successful conformational superposition could extremely improve the predictive accuracy of QSAR modeling. In this work, we proposed a solution to optimize QSAR prediction by multiple-conformational alignment methods, with a set of 40 flexible PTP1B inhibitors as case study. Three different molecular alignment methods were used for the development of 3D-QSAR models listed as following: (1) docking-based alignment (DBA); (2) pharmacophore-based alignment (PBA) and (3) co-crystallized conformer-based alignment (CCBA). Among these three alignments, it was indicated that the CCBA was the best and the fastest strategy in 3D-QSAR development, with the square correlation coefficient (r2) and cross-validated squared correlation coefficient (q2) of comparative molecular field analysis (CoMFA) were 0.992 and 0.694; the r2 and q2 of comparative molecular similarity indices analysis (CoMSIA) were 0.972 and 0.603, respectively. The alignment methodologies used here not only generated a robust QSAR model with useful molecular field contour maps for designing novel PTP1B inhibitors, but also provided a solution for constructing accurate 3D-QSAR model for various disease targets. Undoubtedly, such attempt in QSAR analysis would greatly help us to understand essential structural features of inhibitors required by its target, and so as to discover more promising chemical derivatives. |
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| Keywords: | PTP1B 3D-QSAR Molecular docking Molecular alignment Conformational analysis |
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