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2020 - 20222
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Subject: Bioinformatics × End date: 2022 × Start date: 2020 ×
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    ThesisItemOpen Access
    Computational analysis of potential phytochemicals interaction with COVID-19 main protease
    (CCSHAU Hisar, 2022-07) Nisha; Ahalawat, Navjeet
    The global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in 2020 has affected almost every country with around 543 million confirmed cases worldwide. Currently to fight against the infection, multiple vaccines and several types of drugs alone or with combination have been used in many countries for emergency use. Some severe side effects of repositioned drugs are a cause for concern and their efficacy is still under evaluation. Antiviral therapeutics based on phytochemicals that have been reported to have more tolerable side effects can serve as a reliable alternative to synthetic antiviral drugs for the inhibition of viral replication and penetration. The main protease of SARS-CoV-2 is one of the highly potent and vital targets to design and develop antiviral drugs for the inhibition of COVID-19 contamination. Computational approach helps to identified many drugs that can target viral proteins Mpro. We generated a phytochemical library containing 2453 phytochemicals which have been reported as having antiviral activity through deep literature study.The virtual molecular docking results reveals that five bioactive compounds; theaflavate C, theaflavin-3,3-O-digallate, amentoflavone, hinokiflavone, theaflavin3-gallate have a higher binding affinity toward COVID-19 main protease (MPro) with the binding energy of -10.1, -9.9, -9.7, -9.7 and -9.7 Kcal/mol. But these phytochemicals didn’t follow Lipinski rule of five, so we selected more four phytochemicals having ADMET properties. The main protease docked complexes with phytochemicals; theaflavate C, theaflavin-3,3-O-digallate, amentoflavone, hinokiflavone, theaflavin3-gallate, 10-methoxycamptothecin, caribine, sesamin and licoisoflavanone were used for MD simulation of 20 ns time period using Gromacs package. The MD results were analysed with respect to RMSD, RMSF, Rg, SASA, hydrogen bond and principal component analysis. The resulting trajectories of converged period of MD were further exploited in MM-P/G/BSA calculations to derive accurate estimates of binding free energies. The study provides a basic foundation and suggests that the seven phytochemicals, viz. theaflavate C, theaflavin-3,3-O-digallate, amentoflavone, hinokiflavone, theaflavin3-gallate, caribine, and licoisoflavanone serve as potential inhibitors in regulating the Mpro protein’s function and controlling viral replication and may assist the development of effective anti-COVID-19 drugs.
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    ThesisItemOpen Access
    In-silico identification of miRNA in Rice (Oryza sativa L.)
    (CCSHAU,HiSAR, 2020) Bhavya; Sudhir Kumar
    Rice (Oryza sativa L.) is the world’s single most important and essential crop and a primary food source for half of the world’s populace. An aggregate of 49% calories consumed by the human population come from rice. Micro RNAs (miRNA) are single-stranded non coding RNA molecules of about 21-23 nucleotides in length which regulate gene expression. The main function of miRNAs is to down-regulate the gene expression. The twelve chromosomes of Oryza sativa was downloaded from the International Rice Genome Sequencing Project (IRGSP), after that they transcribed into RNA and then they were cut into fragments by using split command. The output of split command was subjected as input for palindrome finding in palindrome.pl script. Only four mismatches were allowed. The secondary structures and MFE of output of palindrome.pl script were predicted using RNAfold program. The sequences whose energy were less than -40kcal were sorted and identified as putative miRNA. These putative miRNA were compared against miRNA database in miRBase. Total 61 miRNAs and their 255 putative targets were identified. These target genes have regulatory functions in some certain biological processes.