School Of Basic And Applied Sciences

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Subject: search.filters.subject.dipeptidyl peptidase-4

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    Structure-based Virtual Screening and Molecular Dynamic Simulation Approach for the Identification of Terpenoids as Potential DPP-4 Inhibitors
    (Bentham Science Publishers, 2023-05-16T00:00:00) Pulikkottil, Ajay Aravind; Kumar, Amit; Jangid, Kailash; Kumar, Vinod; Jaitak, Vikas
    Background: Diabetes mellitus is a metabolic disorder where insulin secretion is compromised, leading to hyperglycemia. DPP-4 is a viable and safer target for type 2 diabetes mellitus. Computational tools have proven to be an asset in the process of drug discovery. Objective: In the present study, tools like structure-based virtual screening, MM/GBSA, and pharmacokinetic parameters were used to identify natural terpenoids as potential DPP-4 inhibitors for treating diabetes mellitus. Methods: Structure-based virtual screening, a cumulative mode of elimination technique, was adopted, identifying the top five potent hit compounds depending on the docking score and nonbonding interactions. Results: According to the docking data, the most important contributors to complex stability are hydrogen bonding, hydrophobic interactions, and Pi-Pi stacking interactions. The dock scores ranged from-6.492 to-5.484 kcal/mol, indicating robust ligand-protein interactions. The pharmacokinetic characteristics of top-scoring hits (CNP0309455, CNP0196061, CNP0122006, CNP0 221869, CNP0297378) were also computed in this study, confirming their safe administration in the human body. Also, based on the synthetic accessibility score, all top-scored hits are easily synthesizable. Compound CNP0309455 was quite stable during molecular dynamic simulation studies. Conclusion: Virtual database screening yielded new leads for developing DPP-4 inhibitors. As a result, the findings of this study can be used to design and develop natural terpenoids as DPP-4 inhibitors for the medication of diabetes mellitus. � 2024 Bentham Science Publishers.
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    Assessment of risk conferred by coding and regulatory variations of TMPRSS2 and CD26 in susceptibility to SARS-CoV-2 infection in human
    (Springer, 2020) Senapati, S; Kumar, S; Singh, A.K; Banerjee, P; Bhagavatula, S.
    At present, more than 200 countries and territories are directly affected by the coronavirus disease-19 (COVID-19) pandemic. Incidence and case fatality rate are significantly higher among elderly individuals (age > 60 years), type 2 diabetes and hypertension patients. Cellular receptor ACE2, serine protease TMPRSS2 and exopeptidase CD26 (also known as DPP4) are the three membrane bound proteins potentially implicated in SARS-CoV-2 infection. We hypothesised that common variants from TMPRSS2 and CD26 may play critical role in infection susceptibility of predisposed population or group of individuals. Coding (missense) and regulatory variants from TMPRSS2 and CD26 were studied across 26 global populations. Two missense and five regulatory SNPs were identified to have differential allelic frequency. Significant linkage disequilibrium (LD) signature was observed in different populations. Modelled protein?protein interaction (PPI) predicted strong molecular interaction between these two receptors and SARS-CoV-2 spike protein (S1 domain). However, two missense SNPs, rs12329760 (TMPRSS2) and rs1129599 (CD26), were not found to be involved physically in the said interaction. Four regulatory variants (rs112657409, rs11910678, rs77675406 and rs713400) from TMPRSS2 were found to influence the expression of TMPRSS2 and pathologically relevant MX1. rs13015258 a 5? UTR variant from CD26 have significant role in regulation of expression of key regulatory genes that could be involved in SARS-CoV-2 internalization. Overexpression of CD26 through epigenetic modification at rs13015258-C allele was found critical and could explain the higher SARS-CoV-2 infected fatality rate among type 2 diabetes. 2020, Indian Academy of Sciences.