In silico discrimination of nsSNPs in hTERT gene by means of local DNA sequence context and regularity

Comprehensive Characterization of the Coding and Non-Coding Single Nucleotide Polymorphisms in the Tumor Protein p63 (TP63) Gene Using In Silico Tools

Single nucleotide polymorphisms (SNPs) help to understand the phenotypic variations in humans. Genome-wide association studies (GWAS) have identified SNPs located in the tumor protein 63 (TP63) locus to be associated with the genetic susceptibility of cancers. However, there is a lack of in-depth characterization of the structural and functional impacts of the SNPs located at the TP63 gene. The current study was designed for the comprehensive characterization of the coding and non-coding SNPs in the human TP63 gene for their functional and structural significance. The functional and structural effects of the SNPs were investigated using a wide variety of computational tools and approaches, including molecular dynamics (MD) simulation. The deleterious impact of eight nonsynonymous SNPs (nsSNPs) affecting protein stability, structure, and functions was measured by using 13 bioinformatics tools. These eight nsSNPs are in highly conserved positions in protein and were predicted to decrease protein stability and have a deleterious impact on the TP63 protein function. Molecular docking analysis showed five nsSNPs to reduce the binding affinity of TP63 protein to DNA with significant results for three SNPs (R319H, G349E, and C347F). Further, MD simulations revealed the possible disruption of TP63 and DNA binding, hampering the essential protein function. PolymiRTS study found five non-coding SNPs in miRNA binding sites, and the GTEx portal recognized five eQTLs SNPs in single tissue of the lung, heart (LV), and cerebral hemisphere (brain). Characterized nsSNPs and non-coding SNPs will help researchers to focus on TP63 gene loci and ascertain their association with certain diseases.

Prediction of Deleterious Non-synonymous SNPs of Human STK11 Gene by Combining Algorithms, Molecular Docking, and Molecular Dynamics Simulation

Serine-threonine kinase11 (STK11) is a tumor suppressor gene which plays a key role in regulating cell growth and apoptosis. It is widely known as a multitasking kinase and engaged in cell polarity, cell cycle arrest, chromatin remodeling, energy metabolism, and Wnt signaling. The substitutions of single amino acids in highly conserved regions of the STK11 protein are associated with Peutz-Jeghers syndrome (PJS), which is an autosomal dominant inherited disorder. The abnormal function of the STK11 protein is still not well understood. In this study, we classified disease susceptible single nucleotide polymorphisms (SNPs) in STK11 by using different computational algorithms. We identified the deleterious nsSNPs, constructed mutant protein structures, and evaluated the impact of mutation by employing molecular docking and molecular dynamics analysis. Our results show that W239R and W308C variants are likely to be highly deleterious mutations found in the catalytic kinase domain, which may destabilize structure and disrupt the activation of the STK11 protein as well as reduce its catalytic efficiency. The W239R mutant is likely to have a greater impact on destabilizing the protein structure compared to the W308C mutant. In conclusion, these mutants can help to further realize the large pool of disease susceptibilities linked with catalytic kinase domain activation of STK11 and assist to develop an effective drug for associated diseases.

Computational biophysical, biochemical, and evolutionary signature of human R-spondin family proteins, the member of canonical Wnt/β-catenin signaling pathway

In human, Wnt/β-catenin signaling pathway plays a significant role in cell growth, cell development, and disease pathogenesis. Four human (Rspo)s are known to activate canonical Wnt/β-catenin signaling pathway. Presently, (Rspo)s serve as therapeutic target for several human diseases. Henceforth, basic understanding about the molecular properties of (Rspo)s is essential. We approached this issue by interpreting the biochemical and biophysical properties along with molecular evolution of (Rspo)s thorough computational algorithm methods. Our analysis shows that signal peptide length is roughly similar in (Rspo)s family along with similarity in aa distribution pattern. In Rspo3, four N-glycosylation sites were noted. All members are hydrophilic in nature and showed alike GRAVY values, approximately. Conversely, Rspo3 contains the maximum positively charged residues while Rspo4 includes the lowest. Four highly aligned blocks were recorded through Gblocks. Phylogenetic analysis shows Rspo4 is being rooted with Rspo2 and similarly Rspo3 and Rspo1 have the common point of origin. Through phylogenomics study, we developed a phylogenetic tree of sixty proteins (n = 60) with the orthologs and paralogs seed sequences. Protein-protein network was also illustrated. Results demonstrated in our study may help the future researchers to unfold significant physiological and therapeutic properties of (Rspo)s in various disease models.

DNA barcoding to map the microbial communities: current advances and future directions

During the last two decades, the DNA barcode development towards microbial community has increased dramatically. DNA barcode development is related to error-free and quick species identification which aid in understanding the microbial biodiversity, as well as the diseases related to microbial species. Here, we seek to evaluate the so-called barcoding initiatives for the microbial communities and the emerging trends in this field. In this paper, we describe the development of DNA marker-based DNA barcoding system, comparison between routine species identification and DNA barcode, and microbial biodiversity and DNA barcode for microbial communities. Two major topics, such as the molecular diversity of viruses and barcode for viruses have been discussed at the same time. We demonstrate the current status and the maker of DNA barcode for bacteria, algae, fungi, and protozoa. Furthermore, we argue about the promises, limitations, and present and future challenges of microbial barcode development.

In silico profiling and structural insights of missense mutations in RET protein kinase domain by molecular dynamics and docking approach

A major challenge remaining in drug design efforts towards protein kinase is due to the development of drug resistance initiated by the missense mutations in the kinase catalytic domain. Gain or loss of function mutations in the REarranged during Transfection (RET) tyrosine kinase gene have been associated with the development of a wide range of human associated cancers and Hirschsprung's disease. However, to what extent these mutations might affect bio-molecular functions remains unclear. In this article, the functionally significant mutations in RET were screened with the aid of various sequence and structure based in silico prediction methods. We mapped the deleterious mutants, modelled mutant proteins and deciphered the impact of mutations on drug binding mechanisms in the RET crystal structure of PDB ID: with the potential inhibitor vandetanib by docking analysis. Furthermore, molecular dynamics simulations were undertaken to understand the mechanistic action of cancer associated mutations in altering the protein kinase structure, dynamics, and stability. According to our results, the overall effect of V804M, M918T and S922Y were destabilizing and mostly alter the electrostatic component of the binding energy. Specifically, the mutation of gatekeeper residue valine 804 present in the ATP binding pocket affects the protein stability and confers resistance to the drug vandetanib, which was consistent with previously published experimental results. Overall, our findings may provide useful structural insights for in-depth understanding of the molecular mechanism underlying RET mutation and developing effective drugs.