Prasanth Chikungunya Viral nsP4
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Exploring the Polymerase Activity of Chikungunya Viral non structural Protein 4 (nsP4) using Molecular Modeling, e-Pharmacophore and Docking Studies S. Prasanth Kumar, Ravi G. Kapopara, Yogesh T. Jasrai and Himanshu A. Pandya Department of Bioinformatics, ABC, Gujarat University, Ahmedabad- 380009.
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S. prasanth kumar young scientist awarded presentation
The document summarizes research on the coat protein of the Tomato yellow leaf curl viral (TYLCV) disease, which causes significant damage to tomato crops in India. Key findings include:
1) Sequence analysis found mutations in the coat protein that provide insights into the evolutionary divergence of Indian virus isolates and their ability to systematically infect plants.
2) Structural modeling predicted the coat protein binds double-stranded DNA through interactions facilitated by surface loops and neutral patches on the protein.
3) Docking simulations showed the coat protein binds plant DNA through electrostatic and van der Waals interactions, helping the virus infect tomato and other plants.
Soft copy of abstracts
These are the abstracts indexed with my name in the Proceedings of the National Symposium on Evolving Paradigm to Improve Productivity from Dynamic Management and Value Addition for Plant Genetic Resources.
Protein stability manual
This document provides a manual for using the Protein Stability Program developed by S. Prasanth Kumar. The program takes a protein sequence as input and outputs kinetic and thermodynamic parameters to analyze protein stability. It serves to help understand protein stability from sequence alone without 3D structure. Key steps include downloading the program, preparing an input sequence file, running the program from the command line, and interpreting the results to identify amino acids contributing most to stability.
ORVIL Manual
ORganic VIrtual Library (ORVIL) –A COMBINATORIAL LIBRARY CONSTRUCTION BASED ON ORGANIC CONSTITUENTS AND WITHOUT SCAFFOLD HOPPING
2 d qsar model of dihydrofolate reductase (dhfr) inhibitors with activity in ...
The document describes a 2D-QSAR model developed to predict the biological activity of dihydrofolate reductase inhibitors in Toxoplasma gondii and Lactobacillus casei. 31 inhibitors with known activity values were used to generate the model, with 16 molecules in the training set and 15 in the test set. The model relates biological activity to various molecular descriptors including surface area, logP, molecular weight, polarizability, and refractivity. The model was able to accurately predict activity for many compounds in both the training and test sets, demonstrating its ability to quantify structure-activity relationships for this class of inhibitors.
Epitope prediction and its algorithms
The document summarizes epitope prediction and its algorithms. It discusses that epitopes are the portions of antigens responsible for antigen-antibody specificity. There are two main types of epitopes: sequential/continuous epitopes recognized by T helper cells and conformational/discontinuous epitopes recognized by both T and B cells. It then describes several computational algorithms used for predicting B-cell and T-cell epitopes, including Hopp & Woods, Welling's method, Karplus & Schultz parameters, and Kolaskar & Tongaonkar's method. Finally, it lists several databases and servers that can be used for epitope prediction, such as SYFPEITHI, MHCPEP, and EPIM
Gene order
The document discusses gene order, or synteny, between species and how it changes over evolutionary time due to chromosomal rearrangements. It explains that closely related species tend to share similar gene orders and clusters of functionally related genes, but gene orders become randomized in more distant species due to breaks and rejoinings of chromosomes. Computational methods can be used to analyze and compare gene orders between species to estimate how many and what types of rearrangements have occurred.
The mechanism of protein folding
The document summarizes the mechanism of protein folding in 3 sentences:
Protein folding is the physical process by which a polypeptide folds into its characteristic three-dimensional structure, driven by hydrophobic amino acids forming a core shielded from water and polar residues interacting with surrounding water. Key factors that stabilize the folded state include intramolecular hydrogen bonds and hydrophobic interactions. Molecular chaperones assist in protein folding in the crowded intracellular environment to prevent misfolding and aggregation.
Sequence alignments complete coverage
The document discusses algorithms for optimal sequence alignment using dynamic programming. It describes the Needleman-Wunsch algorithm for global alignment and the Smith-Waterman algorithm for local alignment. Both algorithms use dynamic programming to find the highest scoring alignment between two sequences by dividing the problem into independent subproblems. The Needleman-Wunsch algorithm allows gaps across the entire length of the sequences, while Smith-Waterman only considers local regions with high similarity.
Sage technology
S.Prasanth Kumar describes the Serial Analysis of Gene Expression (SAGE) technology for quantitative and simultaneous analysis of large numbers of transcripts in cells or tissues. SAGE involves extracting short sequence tags from mRNA transcripts and concatenating them for sequencing. This allows identification and quantification of expressed genes from the sequenced tags by comparing them to genome databases. The procedure isolates 9-10 base pair tags from mRNA, concatenates them, and sequences the ditags to determine which genes are expressed and their relative abundances under different conditions.
Proteome databases
S.Prasanth Kumar is a bioinformatician who studies proteomics, 2D-PAGE, and proteome databases. Proteomics involves the study of proteins expressed by a genome through analysis of protein sequences, structures, modifications, and interactions. Major databases include Swiss-Prot, which contains annotated protein sequences, and TrEMBL, which contains automatically generated sequences. Other databases contain information on protein families and domains, nucleotide sequences, 2D-PAGE gel images, and post-translational modifications.
Protein protein interactions
S.Prasanth Kumar provides information on analyzing protein-protein interactions, specifically focusing on homodimers and heterodimers. Key analysis methods discussed include calculating the change in solvent accessible surface area between monomeric and multimeric states, assessing planarity and complementarity of interacting surfaces, and determining residue propensities at interfaces. The summary emphasizes that most homodimers only exist in multimeric states and hydrophobic and polar interactions between subunits are important for protein association.
Protein dna interaction practical
This document summarizes how to perform a protein-DNA interaction practical using online tools DNABindR and DP-Bind. It outlines submitting a query to DNABindR, viewing the results which identify potential DNA binding sites on a protein, and submitting the job to DP-Bind to get consensus predictions from multiple models on whether the protein is DNA binding or not. The document concludes by thanking the audience for their attention.
Protein dna interaction
The document discusses protein-DNA interactions and binding mechanisms. It covers several key points:
1) Specific binding of proteins to nucleic acids underlies gene expression processes like replication, repair, transcription and RNA metabolism.
2) Mechanisms of protein-DNA binding include the release of water molecules and ions, allowing the structures to conform and form hydrogen bonds and electrostatic interactions.
3) Recognition principles involve interactions with bases in the major/minor grooves, with certain amino acids preferring certain bases. Sequence-specific binding involves shape complementarity and electrostatic patches on the proteins.
Primary databases ncbi
S.Prasanth Kumar discusses primary databases at the National Center for Biotechnology Information (NCBI), including searching protein databases using various formats like GenPept and FASTA. He covers NCBI databases and services like the Conserved Domain Database and how search results differ depending on whether searching all databases or selecting specific ones. The presentation provides an overview of searching and viewing search results from NCBI databases.
Pharmacophore identification
The document discusses several key concepts in pharmacophore modeling:
1) A pharmacophore defines the important chemical features shared among active molecules, such as hydrogen bond donors/acceptors and hydrophobic regions.
2) Bioisosteres are atoms or groups with similar physical/chemical properties that produce similar biological effects.
3) 3D pharmacophores specify the spatial relationships between features as distance ranges and angles.
4) Constrained systematic searching and ensemble distance geometry are used to identify pharmacophores from a set of molecules while considering multiple conformations.
5) Clique detection identifies all possible combinations of pharmacophoric groups in molecules by finding "maximal completely connected subgraphs".
Pharmacogenomics
This document discusses how genetic polymorphisms can influence how individuals respond to drugs. It explains that genetics can account for 20-95% of variability in drug effects between people. Sequence variants in genes encoding drug-metabolizing enzymes, transporters, and targets can impact drug disposition and response. Specifically, it describes genetic polymorphisms that influence the cytochrome P450 enzyme CYP3A5 and the drug transporter P-glycoprotein, and how these affect the metabolism and transport of various medications. The document stresses that pharmacogenomic studies are helping to elucidate the inherited basis of differing drug responses.
Medline
MEDLINE is a biomedical database containing over 18 million references to journal articles in life sciences and biomedicine. It is maintained by the U.S. National Library of Medicine. Journal articles in MEDLINE are indexed with Medical Subject Headings (MeSH) terms arranged in a hierarchical structure to allow searching at different levels of specificity. MeSH consists of over 26,000 descriptors and 177,000 entry terms to assist in finding the appropriate descriptor. MEDLINE covers biomedicine and health broadly from 1946 to present day, with citations added daily. It is the primary component of PubMed and is searched using MeSH vocabulary.
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