Showing papers by "R. Rajasekaran published in 2013"

In silico analysis of drug-resistant mutant of neuraminidase (N294S) against oseltamivir.

Abstract: The recent H1N1 influenza pandemic has attracted worldwide attention due to the high infection rate. Oseltamivir is a new class of anti-viral agent approved for the treatment and prevention of influenza infections. The principal target for this drug is a virus surface glycoprotein, neuraminidase (NA), which facilitates the release of nascent virus and thus spreads infection. Until recently, only a low prevalence of neuraminidase inhibitor (NAI) resistance (<1 %) had been detected in circulating viruses. However, there have been reports of significant numbers of A (H1N1) influenza strains with a N294S neuraminidase mutation that was highly resistant to the NAI, oseltamivir. Hence, in the present study, we highlight the effect of point mutation-induced oseltamivir resistance in H1N1 subtype neuraminidases by molecular simulation approach. The docking analysis reveals that mutation (N294S) significantly affects the binding affinity of oseltamivir with mutant type NA. This is mainly due to the decrease in the flexibility of binding site residues and the difference in prevalence of hydrogen bonds in the wild and mutant structures. This study throws light on the possible effects of drug-resistant mutations on the large functionally important collective motions in biological systems.

Identification of Potential Inhibitors of H5N1 Influenza A Virus Neuraminidase by Ligand-Based Virtual Screening Approach

Abstract: The neuraminidase (NA) of the influenza virus is the target of antiviral drug, oseltamivir. Recently, cases were reported that influenza virus becoming resistant to oseltamivir, necessitating the development of new long-acting antiviral compounds. In this report, a novel class of lead molecule with potential NA inhibitory activity was identified using a combination of virtual screening (VS), molecular docking, and molecular dynamic approach. The PubChem database was used to perform the VS analysis by employing oseltamivir as query. Subsequently, the data reduction was carried out by employing molecular docking study. Furthermore, the screened lead molecules were analyzed with respect to the Lipinski rule of five, drug-likeness, toxicity profiles, and other physico-chemical properties of drugs by suitable software program. Final screening was carried out by normal mode analysis and molecular dynamic simulation approach. The result indicates that CID 25145634, deuterium-enriched oseltamivir, become a promising lead compound and be effective in treating oseltamivir sensitive as well as resistant influenza virus strains.

In Silico Analysis of Prion Protein Mutants: A Comparative Study by Molecular Dynamics Approach

Abstract: Polymorphisms in the human prion proteins lead to amino acid substitutions by the conversion of PrPC to PrPSc and amyloid formation, resulting in prion diseases such as familial Creutzfeldt–Jakob disease, Gerstmann–Straussler–Scheinker disease and fatal familial insomnia. Cation–π interaction is a non-covalent binding force that plays a significant role in protein stability. Here, we employ a novel approach by combining various in silico tools along with molecular dynamics simulation to provide structural and functional insight into the effect of mutation on the stability and activity of mutant prion proteins. We have investigated impressions of prevalent mutations including 1E1S, 1E1P, 1E1U, 1E1P, 1FKC and 2K1D on the human prion proteins and compared them with wild type. Structural analyses of the models were performed with the aid of molecular dynamics simulation methods. According to our results, frequently occurred mutations were observed in conserved sequences of human prion proteins and the most fluctuation values appear in the 2K1D mutant model at around helix 4 with residues ranging from 190 to 194. Our observations in this study could help to further understand the structural stability of prion proteins.

In silico analysis of detrimental mutations in ADD domain of chromatin remodeling protein ATRX that cause ATR-X syndrome: X-linked disorder

Abstract: Many biological functions involve specific interactions of proteins. Mutations in ATRX gene can change the sequence and structure of a protein thereby impairing its function. Thus, the dysfunction of chromatin remodeling protein ATRX as a result of amino acid substitution in ADD domain often underlies the human disease, ATR-X syndrome. In general, it is mainly caused by amino acid substitution that interfered with the interactions of interest at the interface level. Hence, the study of protein–protein interactions and the interface that mediate the interactions stand important for understanding of biological function. In this work, we address the loss of function in chromatin remodeling protein ATRX due to loss of structural stability that affect the functional activity in mutant ADD domain by 17 missense mutations viz., G175E, N179S, P190A, P190L, P190S, L192F, V194I, C200S, Q219P, C220R, C220Y, W222S, C243F, R246C, R246L, G249C, and G249D. Furthermore, the loss of binding affinity of ADD domain with their interacting partner namely histone H3-peptide were investigated by (1) computing the RMSD (root mean square deviation) for the ADD domain of native with all the 17 mutants, (2) computing intra-molecular interactions in ADD domain of native with all the mutants, (3) computing binding affinity of native and mutant structures of ADD domain with histone H3-peptide through docking studies, and (4) cross validating the loss of function on binding affinity through inter-molecular interactions and normal mode analysis. Finally, as from our computational result, we concluded that all the parameters mentioned above used for studying ADD domain of mutant structures showed the decreased potential values compared to native structure that underlie ATR-X syndrome.

Computational analysis of cdh1 missense mutations in the cause of hereditary diffuse gastric cancer

Abstract: In this present study, we computationally identified the germline missense mutation in the E-cadherin (CDH1) gene causing hereditary diffuse gastric cancer (HDGC). The analysis was initiated with SIFT followed by PolyPhen and I-Mutant2.0 programs with the help of 68 CDH1 variants retrieved from dbSNP. The analysis indicates that 10 variants such as P201R, A298T, E336D, C695R, N751K, Y755C, D768N, G879S, D882N and R169H were commonly found to be less stable and damaging by SIFT, PolyPhen and I-Mutant2.0 programs. Furthermore, SNPs&GO was used to predict the disease related mutations from the protein sequence. Finally, the affinities for the cetuximab with CDH1 variants were examined by using molecular docking algorithm. The result showed that P201R, A298T, E336D and R169H variants were found to be highly significant than the other mutations considered in our analysis. We sincerely hope that these findings certainly helpful for the experimental biologist working in HDGC drug development. DOI: http://dx.doi.org/10.3329/bjp.v8i2.14679

A computational approach to explore the functional missense mutations in the spindle check point protein Mad1

Abstract: In this work, the most detrimental missense mutations of Mad1 protein that cause various types of cancer were identified computationally and the substrate binding efficiencies of those missense mutations were analyzed. Out of 13 missense mutations, IMutant 2.0, SIFTand PolyPhen programs identified 3 variants that were less stable, deleterious and damaging respectively. Subsequently, modeling of these 3 variants was performed to understand the change in their conformations with respect to the native Mad1 by computing their root mean squared deviation (RMSD). Furthermore, the native protein and the 3 mutants were docked with the binding partner Mad2 to explain the substrate binding efficiencies of those detrimental missense mutations. The docking studies identified that all the 3 mutants caused lower binding affinity for Mad2 than the native protein. Finally, normal mode analysis determined that the loss of binding affinity of these 3 mutants was caused by altered flexibility in the amino acids that bind to Mad2 compared with the native protein. Thus, the present study showed that majority of the substrate binding amino acids in those 3 mutants displayed loss of flexibility, which could be the theoretical explanation of decreased binding affinity between the mutant Mad1 and Mad2.

In silico prediction of functional loss of cst3 gene in hereditary cerebral amyloid angiopathy

Abstract: The computational identification of missense mutation in CST3 (CYSTATIN 3 or CYSTATIN C) gene has been done in the present study. The missense mutations in the CST3 gene will leads to hereditary cerebral amyloid angiopathy The initiation of the analysis was done with SIFT followed by POLYPHEN-2 and I-Mutant 2.0 using 24 variants of CST3 gene of Homo sapiens which were derived from dbSNP. The analysis showed that 5 variants (Y60C, C123Y, L19P, Y88C, L94Q) were found to be less stable and damaging by SIFT, POLYPHEN-2 and I-MUTANT2.0. Furthermore the outputs of SNP & GO are collaborated with PHD-SNP (Predictor of Human Deleterious-Single Nucleotide Polymorphism) and PANTHER to predict 5 variants (Y60C, Y88C, C123Y, L19P, and L94Q) having clinical impact in causing the disease. These findings will be certainly helpful for the present medical practitioners for the treatment of cerebral amyloid angiopathy. DOI: http://dx.doi.org/10.3329/bjp.v8i4.16524 Bangladesh Journal of Pharmacology Vol.8(4) 2013 390-394

Computational analysis of adverse missense mutations of HLA-B27 protein

Abstract: The detrimental missense mutations of HLA-B27 gene causing Ankylosing spondylitis were identified computationally and the substrate binding efficiencies of these mutations were analyzed. Out of 12 variants, IMutant 3.0, SIFT and PolyPhen programs identified 1 variant (Y83H) that was less stable, deleterious as well as damaging respectively. Modeling of this one variant was performed to understand the changes in their conformations with respect to the native HLA-B27 protein by computing their RMSD and Total energy. Furthermore the native and the variant were docked with beta-microglobulin to explain the binding efficiencies of those detrimental missense mutations.