Literature DB >> 29959628

Insights into the interaction and binding mode of a set of antifungal azoles as inhibitors of potential fungal enzyme-based targets.

Camilo Guerrero-Perilla1, Freddy A Bernal1, Ericsson Coy-Barrera2.   

Abstract

Azole-containing compounds are a kind of chemical entities of natural and synthetic origin having a wide-range of activities. They are therefore considered as important moieties for fungicide development, mostly due to the possible action on several enzyme-based targets. As part of our research on fungicidal agents, the relationship between the ligand-enzyme affinities of several synthetic azole-containing compounds against a set of fungal enzyme-based targets was in silico evaluated through molecular docking. The affinity values of the test compounds were mostly higher than those of the respective test controls. Binding modes between enzymes and test compounds were firstly investigated through Vina scores and ligand-residue interactions. Furthermore, statistically relationships among docking scores were successfully found by multivariate analysis. They were mostly correlated with reported MIC80 values, so it denoted an evident discrimination of the test compounds. Strong electron withdrawing groups on phenylacrylamide moiety were responsible for establishing stronger complexes with the enzyme targets, being trichodiene synthase and α-L-fucosidase the most important ones. Moreover, stability of a set of representative protein/ligand complexes was also analyzed by 10 ns molecular dynamics simulations (MD). Significant differences into the MD runs were detected and directly correlated to docking performances. Finally, docking affinity scores and HOMO-LUMO energy gaps resulted well predicted by comparative molecular field analysis (CoMFA) models, demonstrating the structure type is particularly associated with those calculated properties and these results were thus consistent with the respective validation parameters.

Entities:  

Keywords:  Antifungal agents; Azole-containing compounds; CoMFA; Molecular docking; Molecular dynamics; Multivariate analysis

Mesh:

Substances:

Year:  2018        PMID: 29959628     DOI: 10.1007/s11030-018-9854-z

Source DB:  PubMed          Journal:  Mol Divers        ISSN: 1381-1991            Impact factor:   2.943


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