Literature DB >> 14632461

Multimode ligand binding in receptor site modeling: implementation in CoMFA.

Viera Lukacova1, Stefan Balaz.   

Abstract

Receptor site modeling methods usually use one binding mode (conformation and/or orientation) for each ligand in a 1:1 complex with receptor. Multiple modes should be considered instead because (1). they have frequently been observed experimentally; (2). in a series, ligands can bind in single yet different modes; and (3). a series may only exhibit one but unknown mode and a few plausible modes must be examined. For multimode binding, the observed ligand/receptor association constant is the sum of the association constants that characterize individual binding modes. This relation, when applied to Comparative Molecular Field Analysis (CoMFA), results in a dependence of the observed binding energy on the probe energies that is nonlinear in optimized parameters. The dependence was linearized to allow parameter optimization by the partial least-squares method that was used iteratively until self-consistency. In addition to the standard CoMFA output, the procedure objectively selects one or a few optimal binding modes out of a dozen or more modes that are considered for each ligand. The approach was applied to published data for binding of 34 polychlorinated dibenzofurans to the aryl hydrocarbon receptor. Descriptive and predictive abilities of the 16-mode model were significantly better than for the one-, two-, and four-mode models. Predominantly, edge-aligned modes were selected that are seldom used in CoMFA. Since inclusion of multimode binding only changes the form of the correlation equation and does not affect the number of optimized parameters, the improvement is believed to be due to a more realistic description.

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Year:  2003        PMID: 14632461     DOI: 10.1021/ci034100a

Source DB:  PubMed          Journal:  J Chem Inf Comput Sci        ISSN: 0095-2338


  8 in total

1.  Processing multimode binding situations in simulation-based prediction of ligand-macromolecule affinities.

Authors:  Akash Khandelwal; Viera Lukacova; Daniel M Kroll; Soumyendu Raha; Dogan Comez; Stefan Balaz
Journal:  J Phys Chem A       Date:  2005-07-28       Impact factor: 2.781

2.  Structural determinants of binding of aromates to extracellular matrix: a multi-species multi-mode CoMFA study.

Authors:  Yufen Zhang; Viera Lukacova; Vladimir Bartus; Stefan Balaz
Journal:  Chem Res Toxicol       Date:  2007-01       Impact factor: 3.739

Review 3.  Modeling kinetics of subcellular disposition of chemicals.

Authors:  Stefan Balaz
Journal:  Chem Rev       Date:  2009-05       Impact factor: 60.622

4.  Rigorous treatment of multispecies multimode ligand-receptor interactions in 3D-QSAR: CoMFA analysis of thyroxine analogs binding to transthyretin.

Authors:  Senthil Natesan; Tiansheng Wang; Viera Lukacova; Vladimir Bartus; Akash Khandelwal; Stefan Balaz
Journal:  J Chem Inf Model       Date:  2011-04-08       Impact factor: 4.956

5.  Development of improved models for phosphodiesterase-4 inhibitors with a multi-conformational structure-based QSAR method.

Authors:  Adetokunbo Adekoya; Xialan Dong; Jerry Ebalunode; Weifan Zheng
Journal:  Curr Chem Genomics       Date:  2009-12-31

6.  Binding of matrix metalloproteinase inhibitors to extracellular matrix: 3D-QSAR analysis.

Authors:  Yufen Zhang; Viera Lukacova; Vladimir Bartus; Xiaoping Nie; Guorong Sun; Ethirajan Manivannan; Sandeep R Ghorpade; Xiaomin Jin; Shankar Manyem; Mukund P Sibi; Gregory R Cook; Stefan Balaz
Journal:  Chem Biol Drug Des       Date:  2008-10       Impact factor: 2.817

Review 7.  Rigorous incorporation of tautomers, ionization species, and different binding modes into ligand-based and receptor-based 3D-QSAR methods.

Authors:  Senthil Natesan; Stefan Balaz
Journal:  Curr Pharm Des       Date:  2013       Impact factor: 3.116

8.  Cellular quantitative structure-activity relationship (Cell-QSAR): conceptual dissection of receptor binding and intracellular disposition in antifilarial activities of Selwood antimycins.

Authors:  Senthil Natesan; Tiansheng Wang; Viera Lukacova; Vladimir Bartus; Akash Khandelwal; Rajesh Subramaniam; Stefan Balaz
Journal:  J Med Chem       Date:  2012-04-11       Impact factor: 7.446

  8 in total

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