COMPUTACIONAL STUDY OF 1H-IMIDAZOL-2-YL-PYRIMIDINE-4,6-DIAMINES FOR IDENTIFICATION OF POTENTIAL PARENT COMPOUNDS OF NEW ANTIMALARIAL AGENTS

Abstract

Recebido em 24/10/2015; aceito em 01/02/2016; publicado na web em 15/04/2016 COMPUTACIONAL STUDY OF 1H-IMIDAZOL-2-YL-PYRIMIDINE-4,6-DIAMINES FOR IDENTIFICATION OF POTENTIAL PARENT COMPOUNDS OF NEW ANTIMALARIAL AGENTS. The aim of this study was develop in silico studies with a data set of 1H-imidazol-2-yl-pyrimidine-4,6-diamines derivatives described as antimalarial agents with the intention of obtain data and tools useful in the development of new drugs of this class. A QSAR model was developed using topological, geometrical and electronic molecular descriptors with aid of the OPS/PLS approach. The data set was also used for pharmacophoric modeling, that was used in the ZINC database for found compounds that show good fit with the model. Due to the similarity between the four selected hits in the virtual screening with the data set, the obtained equation was used for predict the potential antimalarial activity. All hits were within the applicablity domain of the QSAR model, and showed adquates Monge's leadlikeness score and predicted safety profiles.

Identification of Potential COX-2 Inhibitors for the Treatment of Inflammatory Diseases Using Molecular Modeling Approaches

“…The best statistical parameters were obtained for the parametric tri and tetra models with R 2 values of 0.9599 and 0.9617, and variance ratios of 62.6373 and 46.2719, respectively. It is emphasized that the greater the number of equated scores, the greater the quality of the predictor model, although the values are statistically close [ 10 ].…”

“…Subsequently, the input was made to the PharmaGist Web Server 15 to determine the following characteristics: atoms (ATM), spatial characteristics (SF), characteristics (F), aromatic (ARO), hydrophobic (HYD), acceptor (ACC), and donor of hydrogen (DONN). The initial set presented 25 molecules, which were aligned according to the similarity with the selected pivot molecule, allowing the generation of pharmacophore models with the aid of the Discovery Studio ® v. 4.0 program, following the methodology developed by us [ 10 , 12 , 14 , 57 , 58 , 59 ].…”

“…Mathematical analyses accompany in silico studies in order to enable the reduction of costs and time to obtain positive results, observing the molecular structures and their possible affinities with the therapeutic target, using the quantitative structure–activity relationship (QSAR). This method aims to build parametric models for predicting inhibitory activity (IC 50 ) correlated with dependent variables such as physical–chemical, biological, and toxicological properties [ 10 ].…”

“…In these analyses, reduction filters are applied to the models used to predict inhibitory activity, correlating the molecule structures with their activity and toxicological potential, and comparing them with a positive control. In 2016, Brick et al [ 10 ] applied the QSAR analysis to identify new antimalarial inhibitors from 1H-Imidazol-2-IL-Pyrimidine-4,6-Diamines, with reducing filters to eliminate descriptors that did not show correlation or information relevant to the process of statistical and toxicological analysis, beginning the screening with 107 compounds from the ZINC database and ending with four more promising compounds.…”

“…In this context, one of the main types of studies in progress by the scientific community is the in silico and in vivo studies of inhibitors for the inflammatory processes to search for new selective molecules. In parallel, the QSAR study (quantitative structure–activity relationships) uses multiparametric models that interrelate biological activity with the physical–chemical properties of selected molecules in order to predict their inhibitory capacity against the inflammatory mechanism [ 10 ]. Therefore, the objective of this work is the virtual screening of analogs of rofecoxib (Vioox ® ), based on pharmacophore and QSAR analysis, understanding approaches and molecular modeling techniques through free software that is easily accessible by the scientific community, in parallel with the prediction of pharmacokinetic properties and toxicity that show the possible effectiveness of the selected structures, according to the methodological scheme presented in Figure 2 (see more details in the Materials and Methods section).…”