Computational Biology of BRCA2 in Male Breast Cancer, through Prediction of Probable nsSNPs, and Hit Identification

Computational analysis of the functional and structural impact of the most deleterious missense mutations in the human Protein C

Protein C (PC) is a vitamin K-dependent factor that plays a crucial role in controlling anticoagulant processes and acts as a cytoprotective agent to promote cell survival. Several mutations in human PC are associated with decreased protein production or altered protein structure, resulting in PC deficiency. In this study, we conducted a comprehensive analysis of nonsynonymous single nucleotide polymorphisms in human PC to prioritize and confirm the most high-risk mutations predicted to cause disease. Of the 340 missense mutations obtained from the NCBI database, only 26 were classified as high-risk mutations using various bioinformatic tools. Among these, we identified that 12 mutations reduced the stability of protein, and thereby had the greatest potential to disturb protein structure and function. Molecular dynamics simulations revealed moderate alterations in the structural stability, flexibility, and secondary structural organization of the serine protease domain of human PC for five missense mutations (L305R, W342C, G403R, V420E, and W444C) when compared to the native structure that could maybe influence its interaction with other molecules. Protein-protein interaction analyses demonstrated that the occurrence of these five mutations can affect the regular interaction between PC and activated factor V. Therefore, our findings assume that these mutants can be used in the identification and development of therapeutics for diseases associated with PC dysfunction, although assessment the effect of these mutations need to be proofed in in-vitro.

Functional characterization of human genomic variation linked to polygenic diseases

The burden of human disease lies predominantly in polygenic diseases. Since the early 2000s, genome-wide association studies (GWAS) have identified genetic variants and loci associated with complex traits. These have ranged from variants in coding sequences to mutations in regulatory regions, such as promoters and enhancers, as well as mutations affecting mediators of mRNA stability and other downstream regulators, such as 5' and 3'-untranslated regions (UTRs), long noncoding RNA (lncRNA), and miRNA. Recent research advances in genetics have utilized a combination of computational techniques, high-throughput in vitro and in vivo screening modalities, and precise genome editing to impute the function of diverse classes of genetic variants identified through GWAS. In this review, we highlight the vastness of genomic variants associated with polygenic disease risk and address recent advances in how genetic tools can be used to functionally characterize them.