RESUMO
The pharmacophoric space of glycogen synthase kinase-3beta (GSK-3beta) was explored using two diverse sets of inhibitors. Subsequently, genetic algorithm and multiple linear regression analysis were employed to select optimal combination of pharmacophores and physicochemical descriptors that access self-consistent and predictive quantitative structure-activity relationship (QSAR) against 132 training compounds ( r (2) 123 = 0.663, F = 24.6, r (2) LOO = 0.592, r (2) PRESS against 29 external test inhibitors = 0.695). Two orthogonal pharmacophores emerged in the QSAR, suggesting the existence of at least two distinct binding modes accessible to ligands within GSK-3beta binding pocket. The validity of the QSAR equation and the associated pharmacophores was established by the identification of three nanomolar GSK-3beta inhibitors retrieved from our in-house-built structural database of established drugs, namely, hydroxychloroquine, cimetidine, and gemifloxacin. Docking studies supported the binding modes suggested by the pharmacophore/QSAR analysis. In addition to being excellent leads for subsequent optimization, the anti-GSK-3beta activities of these drugs should have significant clinical implications.
Assuntos
Cimetidina/farmacologia , Simulação por Computador , Fluoroquinolonas/farmacologia , Quinase 3 da Glicogênio Sintase/antagonistas & inibidores , Hidroxicloroquina/farmacologia , Naftiridinas/farmacologia , Relação Quantitativa Estrutura-Atividade , Algoritmos , Sítios de Ligação , Cimetidina/química , Inibidores Enzimáticos/química , Inibidores Enzimáticos/farmacologia , Fluoroquinolonas/química , Gemifloxacina , Glicogênio Sintase Quinase 3 beta , Hidroxicloroquina/química , Modelos Lineares , Modelos Moleculares , Estrutura Molecular , Naftiridinas/química , Valor Preditivo dos Testes , Análise de Sequência de Proteína/métodos , SoftwareRESUMO
The pharmacophoric space of streptococcal MurF was explored using a set of 39 known inhibitors. Subsequently, genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of pharmacophoric models and physicochemical descriptors that access self-consistent quantitative structure-activity relationship (QSAR) (r(2)=0.93,F=56.9,r(LOO)(2)=0.91,r(PRESS)(2) against eight external test inhibitors=0.75). Two orthogonal pharmacophores (of cross-correlation r(2)=0.26) emerged in the QSAR equation suggesting the existence of at least two distinct binding modes accessible to ligands within MurF binding pocket. The validity of the QSAR equation and the associated pharmacophore models was experimentally established by the identification of three promising new MurF inhibitors retrieved from the NCI database. Docking studies conducted on active hits supported the binding modes suggested by the pharmacophore/QSAR analysis.
Assuntos
Biologia Computacional , Avaliação Pré-Clínica de Medicamentos/métodos , Modelos Moleculares , Proteínas Musculares/antagonistas & inibidores , Proteínas Musculares/química , Relação Quantitativa Estrutura-Atividade , Bases de Dados Genéticas , Ligantes , Proteínas Musculares/metabolismo , Estrutura Terciária de Proteína , Pseudomonas aeruginosa/genética , Pseudomonas aeruginosa/metabolismo , SoftwareRESUMO
A pharmacophoric model was developed for human protein tyrosine phosphatase 1B (h-PTP 1B) inhibitors utilizing the HipHop-REFINE module of CATALYST software. Subsequently, genetic algorithm and multiple linear regression analysis were employed to select an optimal combination of physicochemical descriptors and pharmacophore hypothesis that yield consistent QSAR equation of good predictive potential (r = 0.87,F-statistic = 69.13,r(BS)2 = 0.76,r(LOO)2 = 0.68). The validity of the QSAR equation and the associated pharmacophoric hypothesis was experimentally established by the identification of five new h-PTP 1B inhibitors retrieved from the National Cancer Institute (NCI) database.
