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IAS-5/INM-9 team leaded an international collaboration contributing in the research for SARS-CoV-2 inhibitors

March 21, 2021 - An international collaboration leaded by an IAS-5/INM-9 team reported a method to predict more precisely which molecules inhibit “Mpro”, the main protease of SARS-CoV-2.

Fast, accurate prediction of ligand-target structure and affinity is a major goal of drug design. Several docking programs are available for this purpose and their prediction capabilities have been proven for a number of biological targets. However, when induced-fit effects are coupled to a high plasticity of the binding site, these procedures may fail. 

In a recent publication on the ACS Pharmacol. Transl. Sci. journal, the authors provide a new definition of druggability based on the blueprint in the chemical space, identified by an optimal binding site’s conformational ensemble upon ligand binding. The procedure creates a structure-based ‘active-pharmacophore’ able to predict affinity trends and binding poses of potential binders. When applied to screen molecules against the SARS-CoV-2 main protease, it reveals compounds here experimentally validated as nanomolar inhibitors and it predicts poses in agreement with X-ray studies. This approach is very general. It can be applied to all proteins whose ligand-induced features are difficult to predict a priori. The research was funded by E4C consortium and it was done in collaboration with HBP scientists

CoverCover of the ACS Pharmacol. Transl. Sci. 2021 issue where the method was published

Press release about this achievement can be found here.

The news was also picked up by regional radio station BRF, which interviewed one of the members of the IAS-5/INM-9 team.