Analysis of consequences of non-synonymous SNPs of USP9Y gene in human using bioinformatics tools

Unravelling the Relacatib activity against the CTSK proteins causing pycnodysostosis: a molecular docking and dynamics approach

Pycnodysostosis is an atypical autosomal recessive condition of Lysosomal storage disorder that originated due to the deficit of the enzyme Cathepsin K which is vital for normal osteoclast action in bone resorption. Abnormal degradation of type 1 collagen and accumulation of toxic undigested collagen fibers in lysosomes of the osteoclast cells resulting in high bone density, brittle bones, and a short stature is caused in CTSK protein-carrying individuals. The broad aim of this study is to identify the most significant variant through various computational pipelines. This study was initiated by retrieving a total number of thirty-six variants from NCBI, HGMD, and UniProt databases, and the Y283C variant was found to be more significant by various standard computational tools. A structural investigation was performed to understand and gain a better knowledge about the interaction profile for the native (1BY8) and variant (Y283C) with Relacatib (a small-molecule drug that blocks the function of Cathepsin K, an enzyme that has been linked to osteoporosis, osteoarthritis, and other bone-degrading diseases). The interaction profile was analyzed using molecular docking. Relacatib (ligand) had an average binding affinity for both native (-7.16 kcal/mol) and Y283C (-6.76 kcal/mol). Finally, Molecular dynamics simulations were done in duplicates to recognize the variant (Y283C) activity of the protein structure against Relacatib for 100 ns. This study assists in comprehending the most pathogenic amino-acid variant, the ligand interaction with the protein structure, and paves the way for understanding the steadiness of the ligand with the native and selected significant amino-acid variant.Communicated by Ramaswamy H. Sarma.

Genome-wide in silico analysis leads to identification of deleterious L290V mutation in RBBP5 gene in Bos indicus

Genome-wide deleterious mutations were identified in zebu cattle (Bos indicus) using in silico approach. The ddRAD sequence data of Sahiwal cattle were annotated and aligned with the cattle reference genome (ARS-UCD1.2). A total of 279,383 SNPs were identified at Read Depth10, which were further filtered to 692 missense SNPs. These SNPs were further analyzed, for functional consequences, by using Variant Effect Predictor, PolyPhen, PROVEAN, and PANTHER tools. A total of 18 SNPs, were finally identified as deleterious, and among these, 12 SNPs were mapped on nine different genes. ERRAT, ProSA-web, Project HOPE, TM-Align, and YASSARA tools, further confirmed the protein malfunctioning of one missense (L290V) mutation of Retinoblastoma binding protein-5 (RBBP5) gene, transcribing a cell cycle regulatory protein and associated with Retinoblastoma in human. This derived bioinformatics pipeline may be useful for preliminarily identifying the deleterious DNA mutations in livestock, specifically in absence of any genetic disease records.

Computational Analysis of High-Risk SNPs in Human DBY Gene Responsible for Male Infertility: A Functional and Structural Impact

BACKGROUND

DEAD-box helicase 3, Y-linked (DBY) is a candidate gene of the AZF region which is involved in spermatogenesis process. Mutations in the DBY gene may disrupt the spermatogenesis and lead to infertility in men. Identification of functionally neutral mutation from the disease-causing mutation is the biggest challenge in human genetic variation analysis. Owing to the importance of DBY in male infertility, functional analysis was carried out to reveal the association between genetic mutation and phenotypic variation through various in silico approaches.

METHODS

The present study analyzed the functional consequences of the nsSNPs in human DBY gene using SIFT, PolyPhen 2, PROVEAN, SNAP2, PMut, nsSNPAnalyzer, PhD-SNP and SNPs&GO along with stability analysis through I-Mutant2.0, MuPro and iPTREE-STAB. The conservational analysis of amino acid residues, biophysical properties and conserved domains of the DBY protein was analyzed using various computational tools. The 3D structure of the protein was generated using SPARKS-X and validated using RAMPAGE.

RESULTS

Out of 1130 SNPs reported in dbSNP, only one nsSNP (G300D) was found to have a functional effect on stability as well as the function of the DBY protein. The results showed the presence of G300 in the putative structure of DBY domain.

CONCLUSION

To the best of our knowledge, this is the first study to detect pathologically significant nsSNPs (G300D) through a computational approach in the DBY which can be useful for development in potent drug discovery studies.