ENHANCEMENT OF A MICROCYSTIN BIOSENSOR BY MUTANTS MOLECULAR SCREENING WITH VINA AND FOLDX.

GASULLA, JAVIER; BRUQUE, CARLOS DAVID; NADRA, ALEJANDRO D; ALBA POSSE, JORGE EZEQUIEL; CARRIQUIRIBORDE, PEDRO

Congreso; Reunión Conjunta SAIB SAMIGE 20202; 2020

SAIB - SAMIGE

Protein phosphatase 1 (PP1) is a serine-threonine phosphatase, recently implemented by our group for the chromogenic biodetection of the cyanobacterial hepatotoxin microcystin (MC) in water samples. The toxin selectively inhibits the phosphatase activity, modulating a chromogenic reaction that can be optically measured. An augmentation in the ligand-receptor interaction could enable more sensible detection systems. To find mutants that maximize this affinity, we developed an in silico screening pipeline based in AutoDock Vina and FoldX software. Starting from a crystallized structure of PP1 and MC, we selected every residue of the protein close to the toxin, in less than 5 Å (20 residues). In a first stage, every close residue was generated in silico in FoldX for all the 20 amino acids, and each resultant structure (400 in total) was docked with the rigid toxin in AutoDock Vina, with the mutated residue as flexible. Also, protein stability (ΔΔG in FoldX) was measured for each mutant in order to increment the amount of protein obtained in their purification and improve the preservation of the phosphatase activity. We compared each mutant to the control without mutation, and those variants with more stability (more negative values of stability ΔΔG) and more docking affinity (more negative values in the docking ΔG ) than control were selected. Finally, that resultant group of mutants (100 structures) was docked again, but including as flexible every residue of the protein close by less than 5 Å to the toxin (20 flexible residues). That stage was computationally very exhaustive and was the reason for the previous filtering. Mutants with more stability and docking affinity (with all close residues set as flexible) were individually analyzed in Pymol and some of them were selected as candidates for future in vitro verification. Multiple mutants between the highest scored candidates were also analyzed in silico, obtaining a pseudo additive improvement with respect to every single mutation.