Literature DB >> 9986707

Three-dimensional quantitative structure-activity relationship of interleukin 1-beta converting enzyme inhibitors: A comparative molecular field analysis study.

S S Kulkarni1, V M Kulkarni.   

Abstract

A three-dimensional quantitative structure-activity relationship (QSAR) study using the comparative molecular field analysis (CoMFA) method was performed on a series of interleukin 1-beta converting enzyme (ICE) inhibitors. The compounds studied have been reported to be time-dependent inhibitors of ICE. This study was performed using 49 compounds, in which the CoMFA models were developed using a training set of 39 compounds. All the compounds were modeled using the X-ray crystal structure of tetrapeptide aldehyde inhibitor/ICE complex. The inhibitor compounds were considered both as neutral species and as P1 carboxylate ionized species. Superimpositions were performed using two alignment rules, namely, an alignment of the structures based on RMS fitting of the backbone heavy atoms of each structure to compound 2 and an alignment based on SYBYL QSAR rigid body field fit of the steric and electrostatic fields of the molecules to the fields of compound 2. Use of LUMO energies or ClogP as additional descriptors in the QSAR table did not improve the significance of the CoMFA models. Steric and electrostatic fields of the inhibitors were found to be the relevant descriptors for structure-activity relationships. The predictive ability of the CoMFA model was evaluated by using a test set of 10 compounds (r2pred as high as 0.859). Further comparison of the coefficient contour maps with the steric and electrostatic properties of the receptor show a high level of compatibility.

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Year:  1999        PMID: 9986707     DOI: 10.1021/jm9708442

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


  8 in total

1.  3D-QSAR and molecular modeling of HIV-1 integrase inhibitors.

Authors:  Mahindra T Makhija; Vithal M Kulkarni
Journal:  J Comput Aided Mol Des       Date:  2002-03       Impact factor: 3.686

2.  Development of quantitative structure-binding affinity relationship models based on novel geometrical chemical descriptors of the protein-ligand interfaces.

Authors:  Shuxing Zhang; Alexander Golbraikh; Alexander Tropsha
Journal:  J Med Chem       Date:  2006-05-04       Impact factor: 7.446

3.  Quantitative Series Enrichment Analysis (QSEA): a novel procedure for 3D-QSAR analysis.

Authors:  Bernd Wendt; Richard D Cramer
Journal:  J Comput Aided Mol Des       Date:  2008-02-27       Impact factor: 3.686

4.  Probing the opportunities for designing anthelmintic leads by sub-structural topology-based QSAR modelling.

Authors:  Prabodh Ranjan; Mohd Athar; Prakash Chandra Jha; Kari Vijaya Krishna
Journal:  Mol Divers       Date:  2018-04-02       Impact factor: 2.943

5.  Molecular electrostatic potentials as input for the alignment of HIV-1 integrase inhibitors in 3D QSAR.

Authors:  M T Makhija; V M Kulkarni
Journal:  J Comput Aided Mol Des       Date:  2001-11       Impact factor: 3.686

6.  Virtual screening to identify Leishmania braziliensis N-myristoyltransferase inhibitors: pharmacophore models, docking, and molecular dynamics.

Authors:  Juliana Cecília de Carvalho Gallo; Larissa de Mattos Oliveira; Janay Stefany Carneiro Araújo; Isis Bugia Santana; Manoelito Coelho Dos Santos Junior
Journal:  J Mol Model       Date:  2018-08-29       Impact factor: 1.810

7.  Comparative molecular field analysis (coMFA) study of epothilones-tubulin depolymerization inhibitors: pharmacophore development using 3D QSAR methods.

Authors:  K W Lee; J M Briggs
Journal:  J Comput Aided Mol Des       Date:  2001-01       Impact factor: 3.686

8.  Docking and 3D-QSAR studies on isatin sulfonamide analogues as caspase-3 inhibitors.

Authors:  Qi Wang; Robert H Mach; David E Reichert
Journal:  J Chem Inf Model       Date:  2009-08       Impact factor: 4.956

  8 in total

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