Cardiovascular disease (CVD) is a group of diseases, affecting the human heart and accounting for 30% of deaths worldwide. Major CVDs include heart failure, hypertension, stroke, etc. Various therapeutics are available against CVD, still there is a dire need to find out potential protein drug targets to reduce economic burden and mortality rate. Goal of the current study was to utilize sequential computational techniques to find the best cardiovascular drug targets and their inhibitors. Common human cardiovascular targets of both databases (GeneCards and Uniprot) were subjected to bioinformatics analyses. Purpose was to validate putative therapeutic targets employing the structure-based bioinformatics methods to determine their physiochemical properties and biological processes. Three stable proteins, that have 0 transmembrane helices, and possess biological processes were screened as potential protein-based therapeutic targets: Hemoglobin subunit beta (HBB), Gamma-enolase (ENO2), and Cholesteryl ester transfer protein (CETP). Tertiary structures of target proteins were retrieved from PDB, and molecular docking technique was utilized to evaluate a library of 5000 phytochemicals against the interacting residues of the target protein as well as their respective standard drugs through MOE and Pyrx software. Top five phytochemicals (d-Sesamin, 1,3-benzodioxole, Sativanone, Thiamine, and Cajanol) were identified based on their RMSD and docking scores as compared to their standard drugs. The docking studies were also validated by MM-GBSA binding free energy and molecular dynamics simulations. According to the study's findings, these phytochemicals may eventually be used as drugs to treat CVD. Further in vitro testing is required to confirm their efficacy and drug potency.Communicated by Ramaswamy H. Sarma.
Keywords: Cardiovascular disease; MM-GBSA analysis; heart attacks; molecular docking; phytochemicals; strokes.