Uso da triagem virtual baseada na estrutura do receptor (SBVS) para o reposicionamento de fármacos no combate à COVID-19

Abstract

The efforts of the scientific community in seeking therapeutic options for the treatment of COVID-19 have become imperative due to the seriousness of the situation, with high case rates and high mortality rates around the world. Because of the absence of specific drugs, the clinical condition of many patients can be aggravated by lethal secondary infections caused by bacteria and fungi. In view of this, the use of medicinal chemistry strategies, such as virtual screening and drug repositioning, have become even more relevant in the fight against the pandemic, since tools such as these reduce the research time, the cost and the number of compounds to be synthesized and tested. In this work, a Structure-Based Virtual Screening (SBVS) methodology was used to identify approved or clinically developed drugs not reported in the literature as new therapeutic alternatives for COVID-19. The line of research that was explored is based on the strategy of repositioning inhibitor drugs that can covalently and irreversibly bind to the transmembrane serine protease enzyme 2 (TMPRSS2). Initially, a search for Michael acceptor drugs was conducted in databases such as NIH Chemical Genomics Center (NCGC), Pharmaceutical Collection (NPC), ChEMBL, DrugBank and PubChem. These drugs were designed and had structural energy minimization proceeded. With the three-dimensional structure of TMPRSS2 not yet reported by early April 2021, molecular homology modeling of this biologic target was performed using the serine protease hepisin as a template. With this, the sequence identity between the template and the target of interest was found to be 33.82%, with 70% coverage and a root mean square deviation (RMSD) equal to 0.111. It was also verified that the residues belonging to the catalytic triad of TMPRSS2 (Ser441, His296, and Asp345) were conserved, and by means of Ramachadran plot it was certified that 92.2% of all residues are in favorable regions, and 99.1% of all residues are in allowed regions. Next, validation of the virtual docking protocol was performed with several TMPRSS2 inhibitors, where both the homologous structure and the experimentally solved one were evaluated. After performing the docking with all molecules in the two .pdb files of the enzyme, it was observed that they presented more consistent results of interaction with the essential residues of the catalytic site when using the 3D structure built by homology. Thus, the latter was used for the execution of the molecular docking steps with visual inspection and obtaining the fitscore values, and also the covalent docking energy calculations of the potential drugs arising from the previous process. For the virtual screening, parameters were used as selection filters for potential TMPRSS2 inhibitor drugs, always comparing with camostat and nafamostat standard drugs: fitscore values, interaction with catalytic triad residues, angstrom distance between the oxygen of Ser441 and the electrophilic carbon of Michael acceptors, and covalent docking energy values. Thus, within the 230 ligands that were anchored to TMPRSS2 and matched the designated parameters, three drugs (two antibiotics and one with anticancer action) were identified as possible candidates for repositioning in the treatment of COVID-19.