Molecular description of α‐keto‐based inhibitors of cruzain with activity against Chagas disease combining 3D‐QSAR studies and molecular dynamics

Abstract

In this work, a group of α-keto-based inhibitors of the cruzain enzyme with anti-chagas activity was selected for a three-dimensional quantitative structure-activity relationship study (3D-QSAR) combined with molecular dynamics (MD). Firstly, statistical models based on Partial Least Square (PLS) regression were developed employing comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) descriptors. Validation parameters (q and r )for the models were, respectively, 0.910 and 0.997 (CoMFA) and 0.913 and 0.992 (CoMSIA). In addition, external validation for the models using a test group revealed r = 0.728 (CoMFA) and 0.971 (CoMSIA). The most relevant aspect in this study was the generation of molecular fields in both favorable and unfavorable regions based on the models developed. These fields are important to interpret modifications necessary to enhance the biological activities of the inhibitors. This analysis was restricted considering the inhibitors in a fixed conformation, not interacting with their target, the cruzain enzyme. Then, MD was employed taking into account important variables such as time and temperature. MD helped describe the behavior of the inhibitors and their properties showed similar results as those generated by QSAR-3D study.

Virtual Screening of 1,2-Diazoles Compounds for Chagas Disease: A Prediction Model

“…One way of achieving these results is to perform studies of the Quantitative Relationship between Chemical Structure and Biological Activity (QSAR) [6] , which use information on compounds with known activity values for the construction of predictive models, as well as conducting similarity research chemistry or based on receptor structure [7] . The objective of this study was to perform a virtual screening of 1,2-diazo compounds as potential therapeutic agents for Chagas' disease through the construction of a prediction model.…”

Estratégias em quimioinformática para uma série de compostos antichagásicos

“…87 Para a construção dos modelos CoMSIA, foram geradas grades reticuladas com diferentes espaçamentos (0,5 a 2 Å). 88,90 Os índices de similaridade foram calculados com a função gaussiana padrão do programa e um átomo de carbono sp 3 com carga líquida +1 como sonda molecular. Foi usado o fator de atenuação padrão de 0,3 para a função gausiana.…”

“…89 O método do coeficiente do desvio padrão (SDC, na sigla em inglês para Standard Deviation Coefficient) de focalização de região foi aplicado a todos os modelos CoMFA e CoMSIA para eliminar descritores redundantes a aumentar o peso dos descritores mais relevantes. 88,90 Os modelos foram validados através dos mesmos procedimentos descritos para os modelos de HQSAR. Os melhores modelos CoMFA e CoMSIA foram utilizados na análise dos mapas de contornos 3D.…”

Estudos em quimioinformática baseados na estrutura do ligante e do receptor de candidatos a agentes antichagásicos

“…Similarity Index Analysis). 114 Para construção do conjunto 2, foram selecionados os periódicos que possuíam estruturas químicas com valores de índice de seletividade (SI) determinado experimentalmente, permanecendo 26 artigos. 113,115,118,120-121,123,125-127, 130-134,136-139,142-144,146-148,150,153 fossem adicionados à margem do mapa.…”