Descoberta de novos inibidores para a UDP-N-Acetilglicosamina Pirofosforilase do Moniliophthora perniciosa por triagem virtual

Abstract

Pests are responsible for high losses in cocoa production in Brazil and other countries, among them the witches' broom (WB) is one of the most important and destructive to the cocoa, even causing losses of up to 95% of production. This plague has spread very easily in the state of Bahia due to environmental conditions that provided the spread of WB, caused by the fungus Moniliophthora pernicious. Several chemical compounds have been tested in order to prevent or eradicate WB, however it has not showed good results, so the present study aimed to perform in silico assays were obtained in order to identify inhibitors of UDP-N-acetylglucosamine pyrophosphorylase (UNAcP) of M. perniciosa. For achieve this goal, computational methods have been employed in the search for new inhibitors for UNAcP where different stages of research and evaluation were performed. The initial stage of virtual screening consisted of the choice of the scoring function, thus the following scoring functions were evaluated: Broyden Fletcher Goldfarb Shanno (BFGS) present in AutoDock VINA 1.1.2; Grid and Grid Score Score+Hawkins GB/SA both present in DOCK 6.5 and calculate the consensus score. The results were analyzed by calculating Enrichment Factor (EF) analysis of the ROC curve and its respective Area under an ROC curve (AUC). The Grid Score presented EF(5)=7.85. The ROC curve analysis allowed us to observe that the Grid Score function can identify almost 40% of active molecules with less than 10% of the database (false positive and active molecules), AUC analysis demonstrated that the Grid Score has greater accuracy (AUC=0.87). Thus, these results showed what the Grid Score was the best scoring function for this system. A database composed of molecules derived from natural sources was also used. The top ten results of virtual screening of the DOCK6.5 underwent online platform ChemGPS-NP, for the calculation of chemical descriptors. Thus, the molecules were re-categorized, based on the values of the Grid Score DOCK6.5 and chemical descriptors ChemGPS-NP. The results indicate the ZINC68592326 molecule his the best score and the analysis indicates that this has hydrophobic interactions with Ala380, Gln113, Gly112, Gly381, Ser168, Arg383, Pro221 and hydrogen bond interaction (3.32Å) with Asn224. The virtual screening database of molecules derived from natural products research allowed with a universe of structures with very different characteristics. It was possible to obtain molecules with great structural diversity between the top ranking, however, also found very similar to the reference molecules. The use of chemometric methods is considered very useful and allows a systematic and consistent choice of structures, mainly by taking into account chemical descriptors and molecular characteristics, allowing for a more detailed evaluation.