Computational modeling for mutational analysis of nitrilase enzyme towards enhancement of binding empathy

Abstract

Nitrilase enzyme (a green catalyst) is an industrially important enzyme which hydrolyses various nitrile compounds (containing -CN functional group) into amides and corresponding carboxylic acids. The current study explored the binding affinity and a method to enhance the catalysis activity of the enzyme using computational approaches. Four mutants were generated using sequential site-directed mutagenesis aiming that an increase in hydrogen bonds that will further increase binding efficiency towards the ligand. Molecular dynamics simulation was rigorously performed to check the stability of those mutants followed by docking to verify its interaction with the ligand. Various statistical dynamics analyses were performed to validate the structure. All the studies predict that built mutants are stable. Mutants 2 and 3 showed a better affinity towards acrylamide by forming the highest number of hydrogen bonds implying better catalysis. The binding affinity values of the Mutant 2 and Mutant 3 with acrylamide are −7.44 kcal/mol and −7.17 kcal/mol, respectively. This study may prove useful for the industry to develop efficient nitrilase enzymes with improved catalytic activity. Communicated by Ramaswamy H. Sarma