Gajendra P S Raghava | Institute of Microbial Technology (original) (raw)

Papers by Gajendra P S Raghava

Tuberculosis is a global menace, caused by Mycobacterium tuberculosis, responsible for millions o... more Tuberculosis is a global menace, caused by Mycobacterium tuberculosis, responsible for millions of premature deaths every year. In the era of drug-resistant tuberculosis, peptide-based therapeutics may provide alternate to small molecule based drugs. In order to create knowledgebase, AntiTbPdb (http://webs.iiitd.edu.in/raghava/antitbpdb/), experimentally validated anti-tubercular and anti-mycobacterial peptides were compiled from literature. We curate 10 652 research articles and 35 patents to extract anti-tubercular peptides and annotate these peptides manually. This knowledgebase has 1010 entries, each entry provides extensive information about an anti-tubercular peptide such as sequence, chemical modification, chirality, nature and source of origin. The ter-tiary structure of these anti-tubercular peptides containing natural as well as chemically modified residues was predicted using PEPstrMOD and I-TASSER. In addition to structural information, database maintains other properties of peptides like physiochemical properties. Numerous web-based tools have been integrated for data retrieval, browsing, sequence similarity search and peptide mapping. In order to assist wide range of user, we developed a responsive website suitable for smartphone, tablet and desktop.

Side chain prediction plays an important role in the accuracy of protein structure prediction. Th... more Side chain prediction plays an important role in the accuracy of protein structure prediction. The distribution of Chi1 torsion angles are not random but occupy only certain range of values. In this work we analysed distribution of chi1 dihedral angle of all amino acids (except ALA and GLY) in peptides and proteins separately. 1819/7995 peptide/protein chains were obtained from PDB respectively after filtering data at resolution <=2, redundancy 30% and peptide/protein length <= 22/80 respectively. The distribution of Chi1 torsion angle for each amino acid in both the datasets shows a Gaussian distribution within selected range of angles in the Chi1 conformational space making a clear cut 4 regions (except PRO which has one region from 42˚ to -38˚) where majority of Chi1 values fall. These regions are defined as: R1 from 179˚ to 161˚, R2 from 77˚ to 51˚, R3 from -42˚ to -96˚ and R4 from -152˚ to -179˚. A step further, calculation of Chi1 percentage of each residue in each regio...

Methods in Molecular Biology, 2015

Cell-penetrating peptides (CPPs) have proven their potential as versatile drug delivery vehicles.... more Cell-penetrating peptides (CPPs) have proven their potential as versatile drug delivery vehicles. Last decade has witnessed an unprecedented growth in CPP-based research, demonstrating the potential of CPPs as therapeutic candidates. In the past, many in silico algorithms have been developed for the prediction and screening of CPPs, which expedites the CPP-based research. In silico screening/prediction of CPPs followed by experimental validation seems to be a reliable, less time-consuming, and cost-effective approach. This chapter describes the prediction, screening, and designing of novel efficient CPPs using &amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot;CellPPD,&amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;amp;quot; an in silico tool.

Scientific Reports, 2015

High blood pressure or hypertension is an affliction that threatens millions of lives worldwide. ... more High blood pressure or hypertension is an affliction that threatens millions of lives worldwide. Peptides from natural origin have been shown recently to be highly effective in lowering blood pressure. In the present study, we have framed a platform for predicting and designing novel antihypertensive peptides. Due to a large variation found in the length of antihypertensive peptides, we divided these peptides into four categories (i) Tiny peptides, (ii) small peptides, (iii) medium peptides and (iv) large peptides. First, we developed SVM based regression models for tiny peptides using chemical descriptors and achieved maximum correlation of 0.701 and 0.543 for dipeptides and tripeptides, respectively. Second, classification models were developed for small peptides and achieved maximum accuracy of 76.67%, 72.04% and 77.39% for tetrapeptide, pentapeptide and hexapeptides, respectively. Third, we have developed a model for medium peptides using amino acid composition and achieved maximum accuracy of 82.61%. Finally, we have developed a model for large peptides using amino acid composition and achieved maximum accuracy of 84.21%. Based on the above study, a web-based platform has been developed for locating antihypertensive peptides in a protein, screening of peptides and designing of antihypertensive peptides.

BioTechniques

Similarity searches are a powerful method for solving important biological problems such as datab... more Similarity searches are a powerful method for solving important biological problems such as database scanning, evolutionary studies, gene prediction, and protein structure prediction. FASTA is a widely used sequence comparison tool for rapid database scanning. Here we describe the GWFASTA server that was developed to assist the FASTA user in similarity searches against partially and/or completely sequenced genomes. GWFASTA consists of more than 60 microbial genomes, eight eukaryote genomes, and proteomes of annotatedgenomes. Infact, it provides the maximum number of databases for similarity searching from a single platform. GWFASTA allows the submission of more than one sequence as a single query for a FASTA search. It also provides integrated post-processing of FASTA output, including compositional analysis of proteins, multiple sequences alignment, and phylogenetic analysis. Furthermore, it summarizes the search results organism-wise for prokaryotes and chromosome-wise for eukaryo...

Biotech Software & Internet Report, 2002

Abstract In this study, in silica biology is used to elucidate the biochemical and spatial proper... more Abstract In this study, in silica biology is used to elucidate the biochemical and spatial properties of peptides interacting with class-II MHC molecules. An existing prediction method was used to detect the directionality in the HLA-DRB1* 0401 binding peptides. ...

Biotech Software & Internet Report, 2001

ABSTRACT

Genomics, 2015

The RNA-protein interactions play a diverse role in the cells, thus identification of RNA-protein... more The RNA-protein interactions play a diverse role in the cells, thus identification of RNA-protein interface is essential for the biologist to understand their function. In the past, several methods have been developed for predicting RNA interacting residues in proteins, but limited efforts have been made for the identification of protein-interacting nucleotides in RNAs. In order to discriminate protein-interacting and non-interacting nucleotides, we used various classifiers (NaiveBayes, NaiveBayesMultinomial, BayesNet, ComplementNaiveBayes, MultilayerPerceptron, J48, SMO, RandomForest, SMO and SVM(light)) for prediction model development using various features and achieved highest 83.92% sensitivity, 84.82 specificity, 84.62% accuracy and 0.62 Matthew's correlation coefficient by SVM(light) based models. We observed that certain tri-nucleotides like ACA, ACC, AGA, CAC, CCA, GAG, UGA, and UUU preferred in protein-interaction. All the models have been developed using a non-redunda...

BMC bioinformatics, Jan 2, 2014

In past number of methods have been developed for predicting post-translational modifications in ... more In past number of methods have been developed for predicting post-translational modifications in proteins. In contrast, limited attempt has been made to understand post-transcriptional modifications. Recently it has been shown that tRNA modifications play direct role in the genome structure and codon usage. This study is an attempt to understand kingdom-wise tRNA modifications particularly uridine modifications (UMs), as majority of modifications are uridine-derived. A three-steps strategy has been applied to develop an efficient method for the prediction of UMs. In the first step, we developed a common prediction model for all the kingdoms using a dataset from MODOMICS-2008. Support Vector Machine (SVM) based prediction models were developed and evaluated by five-fold cross-validation technique. Different approaches were applied and found that a hybrid approach of binary and structural information achieved highest Area under the curve (AUC) of 0.936. In the second step, we used new...

Current medicinal chemistry, 2014

Cancer is one of the leading causes of mortality worldwide, with more than 10 million new cases e... more Cancer is one of the leading causes of mortality worldwide, with more than 10 million new cases each year. Despite the presence of several anticancer agents, cancer treatment is still not very effective. Main reasons behind this high mortality rate are the lack of screening tests for early diagnosis, and non-availability of tumor specific drug delivery system. Most of the current anticancer drugs are unable to differentiate between cancerous and normal cells, leading to systemic toxicity, and adverse side effects. In order to tackle this problem, a considerable progress has been made over the years to identify peptides, which specifically bind to the tumor cells, and tumor vasculature (tumor homing peptides). With the advances in phage display technology, and combinatorial libraries like one-bead one-compound library, several hundreds of tumor homing peptides, and their derivatives, which have potential to detect tumor in vivo, and deliver anticancer agents specifically to the tumor...

Immunomic Discovery of Adjuvants and Candidate Subunit Vaccines, 2012

Methods in Molecular Biology, 2013

Genome announcements, 2013

We report the 5.0-Mb genome sequence of the type species of the genus Citrobacter, Citrobacter fr... more We report the 5.0-Mb genome sequence of the type species of the genus Citrobacter, Citrobacter freundii strain MTCC 1658, isolated from canal water. This draft genome sequence of C. freundii strain MTCC 1658(T) consists of 5,001,265 bp with a G+C content of 51.61%, 4,691 protein-coding genes, 70 tRNAs, and 10 rRNAs.

Vaccine is a substance that trains the host immune system to protect itself against a pathogen. V... more Vaccine is a substance that trains the host immune system to protect itself against a pathogen. Vaccine antigen databases are compilations of different types of resources directly or indirectly leading to the development of vaccines. In order to train, a variety of antigens are used to activate different arms of immune system such as B- and T-cell epitopes, and innate immune components. This entry describes databases of various components of the immune system used to design a vaccine.

Journal of Translational Toxicology, 2014

ABSTRACT Background: Toxicity Prediction is one of the crucial issues as various industrial chemi... more ABSTRACT Background: Toxicity Prediction is one of the crucial issues as various industrial chemicals are linked with acute and chronic human diseases like carcinogenicity, mutagenecity. Thus, there is a growing need to risk assessment of these chemicals. Tetrahymena pyriformis is used as a model organism to accessed the environmental fate of a chemical to address the toxicity potential of organic chemicals. Our study is based on large diverse dataset of 1208 compounds taken from an international open competition ICANN09 was organized for aqueous toxicity prediction of chemical molecules against Tetrahymena pyriformis. Results: This study described the development of Quantitative Structure Toxicity Relationship (QSTR) model for the prediction of aqueous toxicity against T. pyriformis. Firstly, model developed on 1002 V-life calculated molecular descriptors shows a R/R 20.874/0.76 with RMSE 0.523. Further, selection of relevant descriptors leads to only 9 descriptors, which shows a performance R/R 2 0.846/0.71 with RMSE 0.574 while on blind dataset 0.756/0.570 with RMSE 0.570 respectively. Second, model developed on CDK based 178 descriptors shows correlation (R) 0.876/0.85, R 2 0.77/0.72 with RMSE 0.518/0.556 on training and blind dataset respectively. Next, model developed on selected 6 descriptors from CDK shows nearly equal performance with R 0.866/0.823, R 2 0.75/0.66 with RMSE 0.541/0.609 on training and blind dataset respectively. Finally, a hybrid model based on selected 17 descriptors from both V-life and CDK shows significant improvement in performance on both training and blind dataset with R 0.89/0.85, R 2 0.79/0.72 with RMSE 0.491/0.557 respectively. It was also observed that Molecular mass (M.W.), and XLogP have very high correlation with toxicity of chemical molecules, it suggests that size and solubility of chemical molecules play major role in toxicity. Our results suggest that it is possible to develop web service for computing toxicity of chemicals using non-commercial software. Conclusions: Our present study demonstrates that performance of a QSTR model depends on the quality/quantity of descriptors as well as on used techniques. Based on these observations, we developed a web server ToxiPred (http://crdd.osdd.net/raghava/toxipred), for environmental risk assessment of small chemical compounds.