Literature DB >> 12502357

Surface descriptors for protein-ligand affinity prediction.

Ismael Zamora1, Tudor Oprea, Gabriele Cruciani, Manuel Pastor, Anna-Lena Ungell.   

Abstract

Molecular descriptors calculated by the VolSurf program have been extensively used to model pharmacokinetic properties, e.g., passive permeability through the gastrointestinal tract or through the blood-brain barrier. These descriptors quantify steric, hydrophobic, and hydrogen bond interactions between model compounds and different environments. Since these interactions are the same as those involved in the ligand-receptor binding, VolSurf descriptors could potentially be relevant in modeling this process as well. We obtained a significant model (r(2) = 0.85, q(2) = 0.75) using VolSurf descriptors derived from the ligand, the protein, and the ligand-protein complex for a diverse set of 38 structures previously used in the VALIDATE (ref 23) training set. Furthermore, a statistically significant model (r(2) = 0.94, q(2) = 0.89) was obtained using the same type of descriptors for a homogeneous set of glycogen phosphorylase inhibitors (ref 25). Using the VolSurf computational framework, both ligand-receptor binding and the ligand's pharmacokinetic behavior can be modeled simultaneously during the preclinical aspects of drug discovery.

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Year:  2003        PMID: 12502357     DOI: 10.1021/jm011051p

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


  13 in total

1.  Use of alignment-free molecular descriptors in diversity analysis and optimal sampling of molecular libraries.

Authors:  Fabien Fontaine; Manuel Pastor; Hugo Gutiérrez-de-Terán; Juan J Lozano; Ferran Sanz
Journal:  Mol Divers       Date:  2003       Impact factor: 2.943

2.  3D QSAR studies on binding affinities of coumarin natural products for glycosomal GAPDH of Trypanosoma cruzi.

Authors:  Irwin R A Menezes; Julio C D Lopes; Carlos A Montanari; Glaucius Oliva; Fernando Pavão; Marcelo S Castilho; Paulo C Vieira; Mônica T Pupo
Journal:  J Comput Aided Mol Des       Date:  2003 May-Jun       Impact factor: 3.686

Review 3.  Molecular similarity and diversity in chemoinformatics: from theory to applications.

Authors:  Ana G Maldonado; J P Doucet; Michel Petitjean; Bo-Tao Fan
Journal:  Mol Divers       Date:  2006-02       Impact factor: 2.943

4.  VolSurf analysis of pharmacokinetic properties for several antifungal sesquiterpene lactones isolated from Greek Centaurea sp.

Authors:  Catherine Koukoulitsa; George D Geromichalos; Helen Skaltsa
Journal:  J Comput Aided Mol Des       Date:  2005-10-28       Impact factor: 3.686

5.  BDDCS class prediction for new molecular entities.

Authors:  Fabio Broccatelli; Gabriele Cruciani; Leslie Z Benet; Tudor I Oprea
Journal:  Mol Pharm       Date:  2012-02-07       Impact factor: 4.939

6.  Prediction of PKCθ inhibitory activity using the Random Forest Algorithm.

Authors:  Ming Hao; Yan Li; Yonghua Wang; Shuwei Zhang
Journal:  Int J Mol Sci       Date:  2010-09-20       Impact factor: 5.923

7.  Experimental methodologies and evaluations of computer-aided drug design methodologies applied to a series of 2-aminothiophene derivatives with antifungal activities.

Authors:  Luciana Scotti; Marcus Tullius Scotti; Edeltrudes de Oliveira Lima; Marcelo Sobral da Silva; Maria do Carmo Alves de Lima; Ivan da Rocha Pitta; Ricardo Olímpio de Moura; Jaismary Gonzaga Batista de Oliveira; Rayssa Marques Duarte da Cruz; Francisco Jaime Bezerra Mendonça Junior
Journal:  Molecules       Date:  2012-02-24       Impact factor: 4.411

8.  Chemometric studies on natural products as potential inhibitors of the NADH oxidase from Trypanosoma cruzi using the VolSurf approach.

Authors:  Luciana Scotti; Elizabeth Igne Ferreira; Marcelo Sobral da Silva; Marcus Tullius Scotti
Journal:  Molecules       Date:  2010-10-21       Impact factor: 4.411

9.  Molecular determinants of juvenile hormone action as revealed by 3D QSAR analysis in Drosophila.

Authors:  Denisa Liszeková; Maja Polakovicová; Milan Beno; Robert Farkas
Journal:  PLoS One       Date:  2009-06-23       Impact factor: 3.240

10.  Predicting the impacts of mutations on protein-ligand binding affinity based on molecular dynamics simulations and machine learning methods.

Authors:  Debby D Wang; Le Ou-Yang; Haoran Xie; Mengxu Zhu; Hong Yan
Journal:  Comput Struct Biotechnol J       Date:  2020-02-20       Impact factor: 7.271

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