Biology subjects

Agrawal, P.

Publications and source records attributed to Agrawal, P..

6 recordsLinked to original sources

bioRxiv2018

Social isolation-induced epigenetic and transcriptional changes in Drosophila dopaminergic neurons

Epigenetic mechanisms play fundamental roles in brain function and behavior and stressors such as social isolation can alter animal behavior via epigenetic mechanisms. However, due to cellular heterogeneity, identifying cell-type-specific epigenetic changes in the brain is challenging. Here we report first use of a modified INTACT method in behavioral epigenetics of Drosophila: a method we call mini-INTACT. Using ChIP-seq on mini-INTACT purified dopaminergic nuclei, we identified epigenetic signatures in socially-isolated and socially-enriched Drosophila males. Social experience altered the epigenetic landscape in clusters of genes involved in transcription and neural function. Some of these alterations were predicted by expression changes of four transcription factors and the prevalence of their binding sites in several clusters. These transcription factors were previously identified as activity-regulated genes and their knockdown in dopaminergic neurons reduced the effects of social experience on sleep. Our work enables the use of Drosophila as a model for cell-type-specific behavioral epigenetics.

neuroscience↗

bioRxiv2017

Computer-aided prediction of antigen presenting cell modulators for designing peptide-based vaccine adjuvants

BackgroundEvidences in literature strongly advocate the potential of immunomodulatory peptides for use as vaccine adjuvants. All the mechanisms of vaccine adjuvants ensuing immunostimulatory effects directly or indirectly stimulate Antigen Presenting Cells (APCs). While numerous methods have been developed in the past for predicting B-cell and T-cell epitopes; no method is available for predicting the peptides that can modulate the APCs.\n\nMethodsWe named the peptides that can activate APCs as A-cell epitopes and developed methods for their prediction in this study. A dataset of experimentally validated A-cell epitopes was collected and compiled from various resources. To predict A-cell epitopes, we developed Support Vector Machine-based machine learning models using different sequence-based features.\n\nResultsA hybrid model developed on a combination of sequence-based features (dipeptide composition and motif occurrence), achieved the highest accuracy of 96.91% with Matthews Correlation Coefficient (MCC) value of 0.94 on the training dataset. We also evaluated the hybrid models on an independent dataset and achieved a comparable accuracy of 94.93% with MCC 0.90.\n\nConclusionThe models developed in this study were implemented in a web-based platform VaxinPAD to predict and design immunomodulatory peptides or A-cell epitopes. This web server available at http://webs.iiitd.edu.in/raghava/vaxinpad/ and http://crdd.osdd.net/raghava/vaxinpad/ will facilitate researchers in designing peptide-based vaccine adjuvants.

bioinformatics↗

bioRxiv2017

HumCFS: A database of fragile sites in human chromosomes

Genomic instability is the hallmark of cancer and several other pathologies, such as mental retardation; preferentially occur at specific loci in genome known as chromosomal fragile sites. HumCFS (http://webs.iiitd.edu.in/raghava/humcfs/) is a manually curated database provides comprehensive information on 118 experimentally characterized fragile sites present in human chromosomes. HumCFS comprises of 19068 entries with wide range of information such as nucleotide sequence of fragile sites, their length, coordinates on the chromosome, cytoband, their inducers and possibility of fragile site occurrence i.e. either rare or common etc. Each fragile region gene is further annotated to disease database DisGenNET, to understand its disease association. Protein coding genes are identified by annotating each fragile site to UCSC genome browser (GRCh38/hg38). To know the extent of miRNA lying in fragile site region, miRNA from miRBase has been mapped. Comprehensively, HumCFS encompasses mapping of 5010 genes with 19068 transcripts, 1104 miRNA and 3737 disease-associated genes on fragile sites. In order to facilitate users, we integrate standard web-based tools for easy data retrieval and analysis.

bioinformatics↗

bioRxiv2017

Evaluation of protein-ligand docking methods on peptide-ligand complexes for docking small ligands to peptides

In the past, many benchmarking studies have been performed on protein-protein and protein-ligand docking however there is no study on peptide-ligand docking. In this study, we evaluated the performance of seven widely used docking methods (AutoDock, AutoDock Vina, DOCK 6, PLANTS, rDock, GEMDOCK and GOLD) on a dataset of 57 peptide-ligand complexes. Though these methods have been developed for docking ligands to proteins but we evaluate their ability to dock ligands to peptides. First, we compared TOP docking pose of these methods with original complex and achieved average RMSD from 4.74[A] for AutoDock to 12.63[A] for GEMDOCK. Next we evaluated BEST docking pose of these methods and achieved average RMSD from 3.82[A] for AutoDock to 10.83[A] for rDock. It has been observed that ranking of docking poses by these methods is not suitable for peptide-ligand docking as performance of their TOP pose is much inferior to their BEST pose. AutoDock clearly shows better performance compared to the other six docking methods based on their TOP docking poses. On the other hand, difference in performance of different docking methods (AutoDock, AutoDock Vina, PLANTS and DOCK 6) was marginal when evaluation was based on their BEST docking pose. Similar trend has been observed when performance is measured in terms of success rate at different cut-off values. In order to facilitate scientific community a web server PLDbench has been developed (http://webs.iiitd.edu.in/raghava/pldbench/).

bioinformatics↗

bioRxiv2017

Safety evaluation of soy leghemoglobin protein preparation derived from Pichia pastoris, intended for use as a flavor catalyst in plant-based meat

The leghemoglobin protein (LegH) from soy (Glycine max) expressed in Pichia pastoris (LegH Prep) imparts a meat-like flavor profile onto plant-based food products. The safety of LegH Prep was evaluated through a series of in vitro and in vivo tests. The genotoxic potential of LegH Prep was assessed using the bacterial reverse mutation assay (Ames test) and the in vitro chromosome aberration test. LegH Prep was non-mutagenic and non-clastogenic in each test, respectively. Systemic and female reproductive toxicity were assessed in two separate 28-day dietary studies in Sprague Dawley rats. There were no mortalities associated with the administration of LegH Prep. There were no clinical observations, body weight, ophthalmological, clinical pathology, or histopathological changes attributable to LegH Prep administration. Female reproductive parameters were comparable between rats treated with LegH Prep and concurrent control rats. These studies establish an NOAEL of 750 mg/kg/day LegH, which is over 100 times greater than the 90th percentile estimated daily intake (EDI). Collectively, this work demonstrates that LegH Prep is safe for its intended use in ground beef analogue products at concentrations up to 0.8% LegH.\n\nAbbreviations

pharmacology and toxicology↗

bioRxiv2017

Prediction of residue-residue contacts in CASP12 targets from its predicted tertiary structures

One of the challenges in the field of structural proteomics is to predict residue-residue contacts in a protein. It is an integral part of CASP competitions due to its importance in the field of structural biology. This manuscript describes RRCPred 2.0 a method participated in CASP12 and predicted residue-residue contact in targets with high precision. In this approach, firstly 150 predicted protein structures were obtained from CASP12 Stage 2 tarball and ranked using clustering-based quality assessment software. Secondly, residue-residue contacts were assigned in top 10 protein structures based on distance between residues. Finally, residue-residue contacts were predicted in target protein based on consensus/average in top 10 predicted structures. This simple approach performs better than most of CASP12 methods in the categories of TBM and TBM/FM. It ranked 1st in following categories; i) TBM domain on list size L/5, ii) TBM/FM domain on list size L/5 and iii) TBM/FM domain on Top 10. These observations indicate that predicted tertiary structure of a protein can be used for predicting residue-residue contacts in protein with high accuracy.

bioinformatics↗