Investigating the function of single nucleotide polymorphisms in the CTSB gene: a computational approach

Computational refinement identifies functional destructive single nucleotide polymorphisms associated with human retinoid X receptor gene

Alterations in the nuclear retinoid X receptor (RXRs) signalling have been implicated in neurodegenerative disorders such as Alzheimer's disease, Parkinson's disease, stroke, multiple sclerosis and glaucoma. Single nucleotide polymorphisms (SNPs) are the main cause underlying single nucleic acid variations which in turn determine heterogeneity within various populations. These genetic polymorphisms have been suggested to associate with various degenerative disorders in population-wide analysis. This bioinformatics study was designed to investigate, search, retrieve and identify deleterious SNPs which may affect the structure and function of various RXR isoforms through a computational and molecular modelling approach. Amongst the 1,813 retrieved SNPs several were found to be deleterious with rs140464195_G139R, rs368400425_R358W and rs368586400_L383F RXRα mutant variants being the most detrimental ones causing changes in the interatomic interactions and decreasing the flexibility of the mutant proteins. Molecular genetics analysis identified seven missense mutations in RXRα/β/γ isoforms. Two novel mutations SNP IDs (rs1588299621 and rs1057519958) were identified in RXRα isoform. We used several in silico prediction tools such as SIFT, PolyPhen, I-Mutant, Protein Variation Effect Analyzer (PROVEAN), PANTHER, SNP&Go, PhD-SNP and SNPeffect to predict pathogenicity and protein stability associated with RXR mutations. The structural assessment by DynaMut tool revealed that hydrogen bonds were affected along with hydrophobic and carbonyl interactions resulting in reduced flexibility at the mutated residue positions but ultimately stabilizing the molecule as a whole. Summarizing, analysis of the missense mutations in RXR isoforms showed a mix of conclusive and inconclusive genotype-phenotype correlations suggesting the use of sophisticated computational analysis tools for studying RXR variants.Communicated by Ramaswamy H. Sarma.

Identification of Novel Cathepsin B Inhibitors with Implications in Alzheimer's Disease: Computational Refining and Biochemical Evaluation

Amyloid precursor protein (APP), upon proteolytic degradation, forms aggregates of amyloid β (Aβ) and plaques in the brain, which are pathological hallmarks of Alzheimer’s disease (AD). Cathepsin B is a cysteine protease enzyme that catalyzes the proteolytic degradation of APP in the brain. Thus, cathepsin B inhibition is a crucial therapeutic aspect for the discovery of new anti-Alzheimer’s drugs. In this study, we have employed mixed-feature ligand-based virtual screening (LBVS) by integrating pharmacophore mapping, docking, and molecular dynamics to detect small, potent molecules that act as cathepsin B inhibitors. The LBVS model was generated by using hydrophobic (HY), hydrogen bond acceptor (HBA), and hydrogen bond donor (HBD) features, using a dataset of 24 known cathepsin B inhibitors of both natural and synthetic origins. A validated eight-feature pharmacophore hypothesis (Hypo III) was utilized to screen the Maybridge chemical database. The docking score, MM-PBSA, and MM-GBSA methodology was applied to prioritize the lead compounds as virtual screening hits. These compounds share a common amide scaffold, and showed important interactions with Gln23, Cys29, His110, His111, Glu122, His199, and Trp221. The identified inhibitors were further evaluated for cathepsin-B-inhibitory activity. Our study suggests that pyridine, acetamide, and benzohydrazide compounds could be used as a starting point for the development of novel therapeutics.

Evolving geographic diversity in SARS-CoV2 and in silico analysis of replicating enzyme 3CLpro targeting repurposed drug candidates

Background

Severe acute respiratory syndrome (SARS) has been initiating pandemics since the beginning of the century. In December 2019, the world was hit again by a devastating SARS episode that has so far infected almost four million individuals worldwide, with over 200,000 fatalities having already occurred by mid-April 2020, and the infection rate continues to grow exponentially. SARS coronavirus 2 (SARS-CoV-2) is a single stranded RNA pathogen which is characterised by a high mutation rate. It is vital to explore the mutagenic capability of the viral genome that enables SARS-CoV-2 to rapidly jump from one host immunity to another and adapt to the genetic pool of local populations.

Methods

For this study, we analysed 2301 complete viral sequences reported from SARS-CoV-2 infected patients. SARS-CoV-2 host genomes were collected from The Global Initiative on Sharing All Influenza Data (GISAID) database containing 9 genomes from pangolin-CoV origin and 3 genomes from bat-CoV origin, Wuhan SARS-CoV2 reference genome was collected from GeneBank database. The Multiple sequence alignment tool, Clustal Omega was used for genomic sequence alignment. The viral replicating enzyme, 3-chymotrypsin-like cysteine protease (3CL^pro) that plays a key role in its pathogenicity was used to assess its affinity with pharmacological inhibitors and repurposed drugs such as anti-viral flavones, biflavanoids, anti-malarial drugs and vitamin supplements.

Results

Our results demonstrate that bat-CoV shares > 96% similar identity, while pangolin-CoV shares 85.98% identity with Wuhan SARS-CoV-2 genome. This in-depth analysis has identified 12 novel recurrent mutations in South American and African viral genomes out of which 3 were unique in South America, 4 unique in Africa and 5 were present in-patient isolates from both populations. Using state of the art in silico approaches, this study further investigates the interaction of repurposed drugs with the SARS-CoV-2 3CL^pro enzyme, which regulates viral replication machinery.

Conclusions

Overall, this study provides insights into the evolving mutations, with implications to understand viral pathogenicity and possible new strategies for repurposing compounds to combat the nCovid-19 pandemic.

Simulation Based Investigation of Deleterious nsSNPs in ATXN2 Gene and Its Structural Consequence Toward Spinocerebellar Ataxia

Spinocerebellar degeneration, termed as ataxia is a neurological disorder of central nervous system, characterized by limb in-coordination and a progressive gait. The patient also demonstrates specific symptoms of muscle weakness, slurring of speech, and decreased vibration senses. Expansion of polyglutamine trinucleotide (CAG) within ATXN2 gene with 35 or more repeats, results in spinocerebellar ataxia type-2. Protein ataxin-2 coded by ATXN2 gene has been reported to have a crucial role in translation of the genetic information through sequestering the histone acetyl transferases (HAT) resulting in a state of hypo-acetylation. In the present study, we have evaluated the outcome for 122 non synonymous single nucleotide polymorphisms (nsSNPs) reported within ATXN2 gene through computational tools such as SIFT, PolyPhen 2.0, PANTHER, I-mutant 2.0, Phd-SNP, Pmut, MutPred. The apo and mutant (L305V and Q339L) form of structures for the ataxin-2 protein were modeled for gaining insights toward 3D spatial arrangement. Further, molecular dynamics simulations and structural analysis were performed to observe the brunt of disease associated nsSNPs toward the strength and secondary properties of ataxin-2 protein structure. Our results showed that, L305V is a highly deleterious and disease causing point substitution. Analysis based on RMSD, RMSF, Rg, SASA, number of hydrogen bonds (NH bonds), covariance matrix trace, projection analysis for eigen vector demonstrated a significant instability and conformation along with rise in mutant flexibility values in comparison to the apo form of ataxin-2 protein. The study provides a blue print of computational methodologies to examine the ataxin-blend SNPs. J. Cell. Biochem. 119: 499-510, 2018. © 2017 Wiley Periodicals, Inc.