Multiple Sclerosis is a neurodegenerative disease associated to the demyelination of axons that currently has no cure. KLK-6 and PAR-1 are proteins that have been considered as potential targets for its treatment. Starting from the structure of known ligands of KLK-6 and PAR-1 and applying modification strategies like isosterism and scaffold-hopping, we designed a library of 211 compounds. The theoretical affinity to PAR-1 and KLK-6 was calculated using molecular docking and an <i>in silico</i> ADME/Tox profile was predicted, which we used to construct a chemoinformatic score (CIS). We applied a vector analysis, using as coordinates the CIS, and the docking score for PAR-1 and KLK-6. We interpreted the norm of the vector, G, as a parameter which summarized the evaluated properties; the ligands with largest values correspond to the most desirable in terms of dual binding and ADME/Tox properties. Molecular dynamics simulations helped us to understand the potential interaction of the best ligands to PAR-1 and KLK-6, allowing us to identify 2-benzoyl-2,3-dihydrobenzofuran as a potential dual scaffold. From this experience, vector analysis was found to be a helpful form of visualizing and analyzing results, particularly in the identification potential dual or multitarget ligands.

Implementation of vector analysis for the identification of potential KLK-6/PAR-1 dual inhibitors for the treatment of multiple sclerosis through molecular docking, molecular dynamics and chemoinformatic studies

2019 Spring National Meeting

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