Literature DB >> 10956210

DoMCoSAR: a novel approach for establishing the docking mode that is consistent with the structure-activity relationship. Application to HIV-1 protease inhibitors and VEGF receptor tyrosine kinase inhibitors.

M Vieth1, D J Cummins.   

Abstract

DoMCoSAR is a novel approach for statistically determining the docking mode that is consistent with a structure-activity relationship. The approach establishes the binding mode for the compounds in a chemical series with the assumption that all molecules exhibit the same binding mode. It involves three stages. In the first stage all molecules that belong to a given chemical series are docked to the active site of the protein target. The only bias used in the docking at this stage involves the location of the protein binding site. Coordinates of the common substructure (CS) that results from the unbiased docking are then clustered to establish the major substructure docking modes. In the second stage all molecules are docked to the major docking modes (MDMs) with constraints based on the common substructure. The third stage generates, for the major docking modes, interaction-based descriptors that include electrostatic, VDW, strain, and solvation contributions. The problem of docking mode evaluation is now reduced to the question of which descriptor set is more predictive. To establish a quantitative comparison of the descriptor sets associated with the major docking modes, we use 50 instances of random 4-fold cross-validation. For each 4-fold cross-validation the predictive squared correlation coefficient (R(2)) is computed. t-Tests are applied to establish significance of the differences in mean R(2) for one docking mode versus another. We test the methodology on two test cases: HIV-1 protease inhibitors (Holloway et al. J. Med. Chem. 1995, 38, 305-317) and vascular endothelial growth factor (VEGF) receptor tyrosine kinase oxoindoles (Sun et al. J. Med. Chem. 1998, 41, 2588-2603). For both test cases there is statistically significant preference for the binding mode consistent with the X-ray structure. The appeal of this methodology is that researchers gain the objectivity of statistical justification for the selected docking mode. The methodology is relatively insensitive to subtle variations of the protein structure that include, but are not limited to, side chain and small backbone rearrangement during binding. In addition, predictive models that result from the approach can be used to further optimize chemical series.

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Year:  2000        PMID: 10956210     DOI: 10.1021/jm990609e

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  9 in total

1.  CoMFA and docking study of novel estrogen receptor subtype selective ligands.

Authors:  Peter Wolohan; David E Reichert
Journal:  J Comput Aided Mol Des       Date:  2003 May-Jun       Impact factor: 3.686

2.  Development of biologically active compounds by combining 3D QSAR and structure-based design methods.

Authors:  Wolfgang Sippl
Journal:  J Comput Aided Mol Des       Date:  2002-11       Impact factor: 3.686

Review 3.  Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go.

Authors:  N Moitessier; P Englebienne; D Lee; J Lawandi; C R Corbeil
Journal:  Br J Pharmacol       Date:  2007-11-26       Impact factor: 8.739

4.  Conformational analysis and intramolecular hydrogen bonding of cis-3-aminoindan-1-ol: a quantum chemical study.

Authors:  Djaffar Kheffache; Hind Guemmour; Azzedine Dekhira; Ahmed Benaboura; Ourida Ouamerali
Journal:  J Mol Model       Date:  2013-09-13       Impact factor: 1.810

5.  Comparative residue interaction analysis (CoRIA): a 3D-QSAR approach to explore the binding contributions of active site residues with ligands.

Authors:  Prasanna A Datar; Santosh A Khedkar; Alpeshkumar K Malde; Evans C Coutinho
Journal:  J Comput Aided Mol Des       Date:  2006-09-29       Impact factor: 4.179

6.  Synthesis and biological evaluation of novel indole-2-one and 7-aza-2-oxindole derivatives as anti-inflammatory agents.

Authors:  Gaozhi Chen; Lili Jiang; Lili Dong; Zhe Wang; Fengli Xu; Ting Ding; Lili Fu; Qilu Fang; Zhiguo Liu; Xiaoou Shan; Guang Liang
Journal:  Drug Des Devel Ther       Date:  2014-10-13       Impact factor: 4.162

7.  Docking Based 3D-QSAR Study of Tricyclic Guanidine Analogues of Batzelladine K As Anti-Malarial Agents.

Authors:  Nafees Ahmed; Sirajudheen Anwar; Thet Thet Htar
Journal:  Front Chem       Date:  2017-06-15       Impact factor: 5.221

8.  Leveraging nonstructural data to predict structures and affinities of protein-ligand complexes.

Authors:  Joseph M Paggi; Julia A Belk; Scott A Hollingsworth; Nicolas Villanueva; Alexander S Powers; Mary J Clark; Augustine G Chemparathy; Jonathan E Tynan; Thomas K Lau; Roger K Sunahara; Ron O Dror
Journal:  Proc Natl Acad Sci U S A       Date:  2021-12-21       Impact factor: 11.205

9.  Sanjeevini: a freely accessible web-server for target directed lead molecule discovery.

Authors:  B Jayaram; Tanya Singh; Goutam Mukherjee; Abhinav Mathur; Shashank Shekhar; Vandana Shekhar
Journal:  BMC Bioinformatics       Date:  2012-12-13       Impact factor: 3.169

  9 in total

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