Computational screening and analysis of deleterious nsSNPs in human p14ARF (CDKN2A gene) protein using molecular dynamic simulation approach

Cyclin-dependent kinase inhibitor 2 A (CDKN2A) gene belongs to the cyclin-dependent kinase family that code for two transcripts (p16INK4A and p14ARF), both work as tumor suppressors proteins. The mutation that occurs in the p14ARF protein can lead to different types of cancers. Single nucleotide polymorphisms (SNPs) are an important type of genetic alteration that can lead to different types of diseases. In this study, we applied the computational strategy on human p14ARF protein to identify the potential deleterious nsSNPs and check their impact on the structure, function, and protein stability. We applied more than ten prediction tools to screen the retrieved 288 nsSNPs, consequently extracting four deleterious nsSNPs i.e., rs139725688 (R10G), rs139725688 (R21W), rs374360796 (F23L) and rs747717236 (L124R). Homology modeling, conservation and conformational analysis of mutant models were performed to examine the divergence of these variants from the native p14ARF structure. All-atom molecular dynamics simulation revealed a significant impact of these mutations on protein stability, compactness, globularity, solvent accessibility and secondary structure elements. Protein-protein interactions indicated that p14ARF operates as a hub linking clusters of different proteins and that changes in p14ARF may result in the disassociation of numerous signal cascades. Our current study is the first survey of computational analysis on p14ARF protein that determines the association of these nsSNPs with the altered function of p14ARF protein and leads to the development of various types of cancers. This research proposes the described functional SNPs as possible targets for proteomic investigations, diagnostic procedures, and treatments. Communicated by Ramaswamy H. Sarma.