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dynamics simulations. Their proposed machine learning-based models can be able to promote data-driven decision making and has the potential to speed up the drug discovery process and reduce failure rates in drug discovery and development. The identified potential repurposed drugs from this project will aid in facilitating the hunt of anti-COVID-19 drug discovery. Dr Manoj Kumar Yadav from SRM University, Sonepat, Haryana has successfully identified 75 compounds with an accuracy range of 70-100 per cent as active compounds against SARS- CoV-2 spike protein.
All the screened compounds will be further investigated using molecular docking protocols and MD simulation in the next part of their work.
Contact info:
manojiids@gmail.com
In-silico analysis of COVID-19 genome sequences of Indian origin for
identification of genetic variability and molecular targets
A researcher group from National Institute of Technical Teachers’ Training and Research, Kolkata was working on ‘in-silico analysis of 10,000 genomic sequences of COVID-19 around the world, including India to identify genetic variability and potential molecular targets in virus and humans’. The primary objectives of this project were to: (a) identify the genetic variability in SARS-CoV-2 genomes around the globe including India; (b) identify the number of virus strains using single nucleotide polymorphism (SNP) data; (c) identify the putative epitopes as candidates of synthetic vaccine, based on genomic conserved regions that is highly immunogenic and antigenic; and (d) identify the potential target proteins of the virus and human host, based on protein-protein interactions as well as by integrating the knowledge of genetic variability. In addition to these, other objectives like prediction of coronavirus from other pathogenic viruses using machine learning; and identification of virus miRNAs that are also involved in regulating human mRNA or vice-versa were also considered to explore the challenges of COVID-19 from multiple directions to give best possible answer to combat the spread of SARS-CoV-2.
This project addresses such needs by developing a pipeline for systemic analysis of virus genomes. Multiple sequence alignment of 10664 SARS-CoV-2 sequences/genomes from 73 countries including India was performed. Thereafter, a consensus sequence was built to analyse each genome to identify mutations points as substitutions, deletions, insertions and SNPs, thereby resulting in 7209, 11700, 119 and 53 such points, respectively in coding regions. Subsequently, hierarchical clustering was used on SNP data to identify virus strains. As a result, five major clusters or virus strains were identified. Furthermore, using entropy values corresponding to the genomic coordinates of the aligned sequences, conserved regions were also identified. After filtration of these conserved regions, on the basis of length, one conserved region was identified as target in the NSP6 gene and its primers and probes were identified to detect SARS-CoV-2. These refined conserved regions were then considered to identify highly immunogenic and antigenic T-cell and B-cell epitopes.
As a result of this project, 30 MHC-I and 24 MHC-II restricted T-cell epitopes with 14 and 13 unique HLA alleles and 21 B-cell epitopes were identified for the 17 filtered conserved regions.
Contact info:
indrajit@nitttrkol.ac.in
VOL. IV ISSUE 10
VIGYAN PRASAR 17
COVID-19 SCIENCE & TECHNOLOGY EFFORTS IN INDIA