oalib

Publish in OALib Journal

ISSN: 2333-9721

APC: Only $99

Submit

Any time

2019 ( 18 )

2018 ( 17 )

2017 ( 23 )

2016 ( 41 )

Custom range...

Search Results: 1 - 10 of 3954 matches for " Bhartendu Nath Mishra "
All listed articles are free for downloading (OA Articles)
Page 1 /3954
Display every page Item
Ranking of binding and nonbinding peptides to MHC class I molecules using inverse folding approach: Implications for vaccine design
Satarudra Prakash Singh,Bhartendu Nath Mishra
Bioinformation , 2008,
Abstract: T cell recognition of the peptide–MHC complex initiates a cascade of immunological events necessary for immune responses. Accurate T-cell epitope prediction is an important part of the vaccine designing. Development of predictive algorithms based on sequence profile requires a very large number of experimental binding peptide data to major histocompatibility complex (MHC) molecules. Here we used inverse folding approach to study the peptide specificity of MHC class I molecule with the aim of obtaining a better differentiation between binding and nonbinding peptides. Overlapping peptides, spanning the entire protein sequence, are threaded through the backbone coordinates of a known peptide fold in the MHC groove, and their interaction energies are evaluated using statistical pairwise contact potentials. We used the Miyazawa & Jernigan and Betancourt & Thirumalai tables for pairwise contact potentials, and two distance criteria (Nearest atom < 4.0 & C-beta< 7.0 ) for ranking the peptides in an ascending order according to their energy values, and in most cases, known antigenic peptides are highly ranked. The predictions from threading improved when used multiple templates and average scoring scheme. In general, when structural information about a protein-peptide complex is available, the current application of the threading approach can be used to screen a large library of peptides for selection of the best binders to the target protein. The proposed scheme may significantly reduce the number of peptides to be tested in wet laboratory for epitope based vaccine design.
Identification and characterization of merozoite surface protein 1 epitope
Satarudra Prakash Singh,Bhartendu Nath Mishra
Bioinformation , 2009,
Abstract: Malaria is an important tropical infection which urgently requires intervention of an effective vaccine. Antigenic variations of the parasite and allelic diversity of the host are main problems in the development of an effective malaria vaccine. Cytotoxic T lymphocytes (CTL) directed against Plasmodium falciparum-derived antigens are shown to play an important role for the protection against malaria. The merozoite surface protein 1 (MSP1) is expressed in all the four life-cycle stages of Plasmodium falciparum and did not find any sequence similarity to human and mouse reference proteins. MSP1 is a known target of the immune response and a single CTL epitope binding to the HLA-A*0201 is available for merozoite form. Here, we report the results from the computational characterization of MSP1, precursor (1720 residue) and screening of highest scoring potential CTL epitopes for 1712 overlapping peptides binding to thirty four HLA class-I alleles and twelve HLA class-I supertypes (5 HLA-A and 7 HLA-B) using bioinformatics tools. Supertypes are the clustered groups of HLA class-I molecules, representing a sets of molecules that share largely overlapping peptide binding specificity. The prediction results for MSP1 as adhesin and adhesin-like in terms of probability is 1.0. Results also show that MSP1 has orthologs to other related species as well as having non allergenicity and single transmembrane properties demonstrating its suitability as a vaccine candidate. The predicted peptides are expected to be useful in the design of multi-epitope vaccines without compromising the human population coverage.
Prediction of MHC binding peptide using Gibbs motif sampler, weight matrix and artificial neural network
Satarudra Prakash Singh,Bhartendu Nath Mishra
Bioinformation , 2008,
Abstract: The identification of MHC restricted epitopes is an important goal in peptide based vaccine and diagnostic development. As wet lab experiments for identification of MHC binding peptide are expensive and time consuming, in silico tools have been developed as fast alternatives, however with low performance. In the present study, we used IEDB training and blind validation datasets for the prediction of peptide binding to fourteen human MHC class I and II molecules using Gibbs motif sampler, weight matrix and artificial neural network methods. As compare to MHC class I predictor based on sequence weighting (Aroc=0.95 and CC=0.56) and artificial neural network (Aroc=0.73 and CC=0.25), MHC class II predictor based on Gibbs sampler did not perform well (Aroc=0.62 and CC=0.19). The predictive accuracy of Gibbs motif sampler in identifying the 9-mer cores of a binding peptide to DRB1 alleles are also limited (40%), however above the random prediction (14%). Therefore, the size of dataset (training and validation) and the correct identification of the binding core are the two main factors limiting the performance of MHC class-II binding peptide prediction. Overall, these data suggest that there is substantial room to improve the quality of the core predictions using novel approaches that capture distinct features of MHC-peptide interactions than the current approaches.
CoMFA and CoMSIA 3D-QSAR analysis of DMDP derivatives as anti-cancer agents
Vivek Srivastava,Ashutosh Kumar,Bhartendu Nath Mishra,Mohammad Imran Siddiqi
Bioinformation , 2008,
Abstract: Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on three dimensional quantitative structure–activity relationship (3D-QSAR) studies were conducted on a series (78 compounds) of 2, 4-diamino-5-methyl-5-deazapteridine (DMDP) derivatives as potent anticancer agents. The best prediction were obtained with a CoMFA standard model (q2 = 0.530, r2 = 0.903) and with CoMSIA combined steric, electrostatic, hydrophobic and hydrogen bond donor fields (q2 = 0.548, r2 = 0.909). Both models were validated by a test set of ten compounds producing very good predictive r2 values of 0.935 and 0.842, respectively. CoMFA and CoMSIA contour maps were then used to analyze the structural features of ligands to account for the activity in terms of positively contributing physiochemical properties such as steric, electrostatic, hydrophobic and hydrogen bond donor fields. The resulting contour maps produced by the best CoMFA and CoMSIA models were used to identify the structural features relevant to the biological activity in this series of analogs. This study suggests that the highly electropositive substituents with low steric tolerance are required at 5 position of the pteridine ring and bulky electronegatve substituents are required at the meta-position of the phenyl ring. The information obtained from CoMFA and CoMSIA 3-D contour maps can be used for the design of deazapteridine-based analogs as anti - cancer agents.
Molecular docking studies on DMDP derivatives as human DHFR inhibitors
Vivek Srivastava,Ashutosh Kumar,Bhartendu Nath Mishra,Mohammad Imran Siddiqi
Bioinformation , 2008,
Abstract: Molecular docking is routinely used for understanding drug–receptor interaction in modern drug design. Here, we describe the docking of 2, 4-diamino-5-methyl-5-deazapteridine (DMDP) derivatives as inhibitors to human dihydrofolate reductase (DHFR). We docked 78 DMDP derivates collected from literature to DHFR and studied their specific interactions with DHFR. A new shape-based method, LigandFit, was used for docking DMDP derivatives into DHFR active sites. The result indicates that the molecular docking approach is reliable and produces a good correlation coefficient (r2 = 0.499) for the 73 compounds between docking score and IC50 values (Inhibitory Activity). The chloro substituted naphthyl ring of compound 63 makes significant hydrophobic contact with Leu 22, Phe 31 and Pro 61 of the DHFR active site leading to enhanced inhibition of the enzyme. The docked complexes provide better insights to design more potent DHFR inhibitors prior to their synthesis.
2D-QSAR model development and analysis on variant groups of anti -tuberculosis drugs
Neeraja Dwivedi*,Bhartendu Nath Mishra,Vishwa Mohan Katoch
Bioinformation , 2011,
Abstract: A quantitative structure activity relationship study was performed on different groups of anti-tuberculosis drug compound for establishing quantitative relationship between biological activity and their physicochemical /structural properties. In recent years, a large number of herbal drugs are promoted in treatment of tuberculosis especially due to the emergence of MDR (multi drug resistance) and XDR (extensive drug resistance) tuberculosis. Multidrug-resistant TB (MDR-TB) is resistant to front-line drugs (isoniazid and rifampicin, the most powerful anti-TB drugs) and extensively drug-resistant TB (XDR-TB) is resistant to front-line and second-line drugs. The possibility of drug resistance TB increases when patient does not take prescribed drugs for defined time period. Natural products (secondary metabolites) isolated from the variety of sources including terrestrial and marine plants and animals, and microorganisms, have been recognized as having antituberculosis action and have recently been tested preclinically for their growth inhibitory activity towards Mycobacterium tuberculosis or related organisms. A quantitative structure activity relationship (QSAR) studies were performed to explore the antituberculosis compound from the derivatives of natural products . Theoretical results are in accord with the in vitro experimental data with reported growth inhibitory activity towards Mycobacterium tuberculosis or related organisms. Antitubercular activity was predicted through QSAR model, developed by forward feed multiple linear regression method with leave-one-out approach. Relationship correlating measure of QSAR model was 74% (R2 = 0.74) and predictive accuracy was 72% (RCV2 = 0.72). QSAR studies indicate that dipole energy and heat of formation correlate well with anti-tubercular activity. These results could offer useful references for understanding mechanisms and directing the molecular design of new lead compounds with improved anti-tubercular activity. The generated QSAR model revealed the importance of structural, thermodynamic and electro topological parameters. The quantitative structure activity relationship provides important structural insight in designing of potent antitubercular agent.
Genetic transformation studies and scale up of hairy root culture of Glycyrrhiza glabra in bioreactor
Mehrotra,Shakti; Kumar Kukreja,Arun; Singh Khanuja,Suman Preet; Nath Mishra,Bhartendu;
Electronic Journal of Biotechnology , 2008,
Abstract: the study was undertaken to induce hairy roots in glycyrrhiza glabra in leaf explants and to optimize the nutritional requirement for its growth kinetics at shake flask and bioreactor level. pathogenecity of agrobacterium depends upon transformation ability of strain and age, type, and physiological state of explants. agrobacterium rhizogenes strain k599 was used to infect leaf explants of g. glabra. explants of different age groups were obtained from 2 to 5 weeks old in vitro grown cultures. bacterial strain k599 could induce hairy roots in 3 and 4 weeks old leaf explants cultured on b5, ms, nb and wp basal semi-solid medium. leaf explants of 2 and 5 weeks old culture were not responsive to bacterial infection in terms of hairy root induction. maximum transformation frequency (tf) of tested bacterial strain was 47% obtained in 3 weeks old explants after 25 days of incubation on ms basal semi solid medium. nb and b5 both media composition showed 20% of transformation frequency after 28 and 38 days respectively. wp medium did not support induction of roots in cultured leaf explants infected with a. rhizogenes strain k599even after 50 days of incubation. further, when all the four media combinations were tested for root growth it was found that though wp was not responsive for hairy root induction, yet all four basal media supported hairy root growth and a gradual increase in fresh weight biomass was observed with an increase in culture duration. however amongst all, the nb medium composition supported best growth of hairy roots followed by ms, b5 and wp media. about 20 times increase in root biomass on fresh weight basis was recorded after 45days of culture in nb medium. initial inoculum of roots (0.18 g. f.wt./ flask) containing 50 ml of liquid culture medium produced 3.59 g (f. wt.) biomass. a fast growing hairy root clone g6 was grown in a 5 l capacity mechanically agitated bioreactor provided with a nylon mesh septum. after 30 days of sterile run, 310 g of root b
Performance Evaluation of DNA MOTIF discovery programs
Chandra Prakash Singh,Feroz Khan,Bhartendu Nath Mishra,Durg Singh Chauhan
Bioinformation , 2008,
Abstract: Methods for the identification of transcription factor binding sites have proved to be useful for deciphering genetic regulatory networks. The strengths and weaknesses for a number of available web tools are not fully understood. Here, we designed a comprehensive set of performance measures and benchmarked sequence-based motif discovery tools using large scale datasets (derived from Escherichia coli genome and RegulonDB database). The benchmark study showed that nucleotide based and binding site based prediction accuracy is often low and activator binding site based prediction accuracy is high.
CSF tau and amyloid β42 levels in Alzheimer’s disease—A meta-analysis  [PDF]
Rachna Agarwal, Neelam Chhillar, Vijay Nath Mishra, Chandra Bhushan Tripathi
Advances in Alzheimer's Disease (AAD) , 2012, DOI: 10.4236/aad.2012.13005
Abstract: Alzheimer’s disease International (ADI) estimates that there are currently 30 million people with dementia in the world. The main objective was to perform meta-analysis of studies of CSF tau and Amyloid β42 (Aβ42) levels in Alzheimer’s disease (AD) patients and controls. In the present study MEDLINE was reviewed from 1995 to 2009, supplemented by citation analysis from retrieved articles to select case control studies. Descriptive statistics showed that median effect size (raw mean difference) of CSF tau and Aβ42 levels were 301 pg/ml (Range: 22 to 614 pg/ml) and –352 pg/ml (Range: –969 to 203 pg/ml) respectively. The pooled effect size CSF tau and Aβ42 was 289.14 pg/ml (95% CI 253.278 to 325.013 pg/ml) and –329.02 pg/ml (95% CI –387.740 to –270.445 pg/ml) respectively. Heterogeneity in effect size of selected studies was present for both parameters (CSF tau: Q statistics = 1816.596, DF = 40, P = 0.000 and CSF Aβ42: Q-statistics = 1259.358, DF = 24, p < 0.001). Based on the findings of meta-analysis in the present study, CSF tau and Aβ42 levels in AD and controls may be considered as potential biomarker along with the clinical phenotype to perform them during high quality diagnostic testing in dementia.
A graph-based clustering method applied to protein sequences
Pooja Mishra,Paras Nath Pandey
Bioinformation , 2011,
Abstract: The number of amino acid sequences is increasing very rapidly in the protein databases like Swiss-Prot, Uniprot, PIR and others, but the structure of only some amino acid sequences are found in the Protein Data Bank. Thus, an important problem in genomics is automatically clustering homologous protein sequences when only sequence information is available. Here, we use graph theoretic techniques for clustering amino acid sequences. A similarity graph is defined and clusters in that graph correspond to connected subgraphs. Cluster analysis seeks grouping of amino acid sequences into subsets based on distance or similarity score between pairs of sequences. Our goal is to find disjoint subsets, called clusters, such that two criteria are satisfied: homogeneity: sequences in the same cluster are highly similar to each other; and separation: sequences in different clusters have low similarity to each other. We tested our method on several subsets of SCOP (Structural Classification of proteins) database, a gold standard for protein structure classification. The results show that for a given set of proteins the number of clusters we obtained is close to the superfamilies in that set; there are fewer singeltons; and the method correctly groups most remote homologs.
Page 1 /3954
Display every page Item


Home
Copyright © 2008-2017 Open Access Library. All rights reserved.