In silico studies of bacterial derived fatty acid as a potential inhibitor of 1FGE and 1BQO
Thrombomodulin (TM) and matrix metalloproteinase (MMPs) are the major factors that are responsible for lung cancer. Hence, the identification of novel compounds inhibiting TM and MMPs is the challenging task for the scientists. Even though synthetic drugs were developed, their toxicity and offtarget limit their usage. The current study aims to investigate the molecular simulations for bacterial derived stearic acid to estimate the in silico anticancer activity against TM and MMPs protein as target compounds and the findings were correlated with the standard drug vorinostat. Using Lamarckian genetic algorithm, the TM and MMPs were energy minimized and docked with stearic acid and vorinostat using auto dock 4.2 and visualized in PyMol software. Protein and ligand binding analysis revealed that stearic acid interacts with the amino acids of MMPs residues of PHE83, SER212, ALA213 and ASN214. It interacts with the TMs with two amino acid residues i.e. CYS407 and GLU408. Hence, compared to vorinostat, stearic acid shows a higher binding affinity towards MMPs and slightly lower affinity towards TM proteinase. We conclude that the computational analysis of ligand binding interaction of stearic acid suggests that it could be a potential inhibitor of matrix metallo proteinase and is effective against thrombomodulin and can be considered as an anticancer agent by in vivo studies.