Bioinformática estrutural aplicada a bioprospecção alvo direcionada de compostos com potencial antitumoral

Abstract

Cancer is a complex disease that acts by the disordered proliferation of cells in various organs and its treatment can be invasive and nonspecific, in addition to running into tumor resistance. Research seeking potential treatments is spread throughout the brazilian territory, including marine ecosystems as a source of compounds. Thus, MicroMarin is a bank of marine microorganisms collected in the brazilian economic exclusivity zone, also known as the Blue Amazon. The molecules identified in the bacterial strains of MicroMarin are investigated from their cytotoxic activity, as possible candidates for anticancer drugs, by experimental and in silico methodologies. In the context of cancer treatment, bioinformatics can play an important role in drug screening and targeting, making further studies more assertive and reducing the costs and time of the drug development process. The present work is a study on the application of bioinformatics in the prospection of compounds with pharmacological potential for the treatment of cancer. The objective was the optimization of a series of staurosporine from the MicroMarin microorganism bank, through in silico structural bioinformatics approaches, in other words, considering three-dimensional aspects of the research objects. Considered molecules with exacerbated toxicity, the staurosporine present in MicroMarin had their physicochemical and pharmacokinetic properties characterized, and their structures were divided into subgroups, allowing in silico optimization by the exclusion of substructures. Both the identified and digitally optimized staurosporine were subjected to molecular docking assays and compared for toxicity and pharmacokinetic properties. The optimization of the structures resulted in twenty new staurosporines, of which five had a predicted Median Lethal Dose (LD-50) increased from 11-1000mg/Kg to 5000-12800mg/Kg, allowing greater safety in administration. In addition, systemic toxicity assays (using ProTox-II software) predict that these five highlighted structures present fewer toxic effects when compared to the prototype molecules. The in silico prospection of possible molecular targets (target fishing) for the optimized staurosporine led to the selection, for the molecular docking studies, of the RET tyrosine kinase, which when mutated promotes disordered cell proliferation in different tumor types, among them thyroid adenocarcinoma. When compared to model staurosporine, known as non-selective kinase inhibitors, the five optimized structures that showed lower toxicity, also have greater stability in the interaction with RET kinase, identified by the greater amount of hydrogen bridges between molecule and receptor. The results of this work shed light on optimization mechanisms of anticancer drug candidate molecules, decreasing toxicity and increasing the interaction between these and their molecular targets. However, experimental data are essential to corroborate and validate the results obtained by bioinformatics. Synthesis feasibility tests are also necessary to make it possible to obtain and test the optimized molecules.