A Computational Approach for Mutational Analysis of KRAS Snps and Toxicity Prediction of Screened Compounds of Lethal G12R KRAS SNP

KRAS protein is vital for normal cell signaling and its single point mutations are linked with the development of numerous forms of malignancies. Despite of various reports available on SNPs of KRAS and its unresponsiveness to available drug therapies, there is an urgent need for the development of effective and potential drug target against it. In present study, a strategy is made with the combination of computational biology, cancer informatics and cheminformatics. Mutational analysis, structure based virtual screening (SBVS) and toxicity profiling of compounds have been performed for the prediction of therapeutic drug targets against KRAS detrimental mutations. Among 31 retrieved mutations from dbSNP and UniProt, 12 mutations were predicted to be lethal by PROVEAN and PolyPhen tools. The protein stability analysis was done by using I-Mutant tool, from the 12 mutations 8 mutations have destructive effect while 4 mutations have constructive effect on protein stability. 3D-structures of 12 identified mutated KRAS genes were modeled by the aid of DS-visualizer. Among the identified lethal mutations G12R was selected for SBVS, the KRAS protein was subjected as receptor while GDP as a ligand. The SBVS was performed by using idock server, among 11630 library of compounds the best conformation was obtained having lowest idock score (-11.389 Kcal/Mol). The protein and ligand interactions were examined by using Ligplot+ and toxicity profiling of top 5 compounds were performed by using Lazar and ProTox tools. This study will be helpful in the development of effective diagnostic methodologies and drug targeted therapy against G12R mutation.