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L-amino-acids as immunity booster against COVID-19: DFT, molecular docking and MD simulations.

ABSTRACT: There is great interest to explore the importance of different amino-acids on immunity of human. Immunity helps to protect us from the pathogenic infections. The amino-acids are being use to give energy and is also used as an important basic molecule for the making of cells, protecting cell and others. Still, a little information is known for their importance in the inhibition of main protease of SARS-CoV-2. As known, tens of billions of humans are infected due to the SARS-CoV-2 and about a million of deaths are reported due to it or COVID. As of now, no promising drug is available in the market to cure the patients from this infection. Even, the medicines beings used for the partial cure may have some side effects. Therefore, the focus is to explore the natural amino-acids against the Mpro of SARS-CoV-2 as using of amino-acids is not toxic to humans. In the present work, authors have studied the amino-acids using DFT calculations and then they were explored for their promising role in the inhibition of main protease of SARS-CoV-2 using molecular docking and molecular dynamics simulations. Out of the 20 amino-acids, arginine found to best against the main protease of SARS-CoV-2 using the molecular docking and the binding energy was -0.94 kcal/ mol. Further, molecular dynamics simulations for the main protease of SARS-CoV-2 with and without arginine was performed using the Amber and different thermodynamic parameters like ΔH and TΔS to get ΔG, comes out to be 2.74 kcal/mol. It is expected that arginine can boost the immunity.

SUBMITTER: Singh P

PROVIDER: S-EPMC8590830 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:BackgroundStructure-activity relationship (SAR) is considered to be an effective in silico approach when discovering potential antagonists for breast cancer due to gene mutation. Major challenges are faced by conventional SAR in predicting novel antagonists due to the discovery of diverse antagonistic compounds. Methodologyand Results: In predicting breast cancer antagonists, a multistep screening of phytochemicals isolated from the seeds of the Citrus sinensis plant was applied using feasible complementary methodologies. A three-dimensional quantitative structure-activity relationship (3D-QSAR) model was developed through the Flare project, in which conformational analysis, pharmacophore generation, and compound alignment were done. Ten hit compounds were obtained through the development of the 3D-QSAR model. For exploring the mechanism of action of active compounds against cocrystal inhibitors, molecular docking analysis was done through Molegro software (MVD) to identify lead compounds. Three new proteins, namely, 1T15, 3EU7, and 1T29, displayed the best Moldock scores. The quality of the docking study was assessed by a molecular dynamics simulation. Based on binding affinities to the receptor in the docking studies, three lead compounds (stigmasterol P8, epoxybergamottin P28, and nobiletin P29) were obtained, and they passed through absorption, distribution, metabolism, and excretion (ADME) studies via the SwissADME online service, which proved that P28 and P29 were the most active allosteric inhibitors with the lowest toxicity level against breast cancer. Then, density functional theory (DFT) studies were performed to measure the active compound's reactivity, hardness, and softness with the help of Gaussian 09 software.ConclusionsThis multistep screening of phytochemicals revealed high-reliability antagonists of breast cancer by 3D-QSAR using flare, docking analysis, and DFT studies. The present study helps in providing a proper guideline for the development of novel inhibitors of BRCA1 and BRCA2.

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L-amino-acids as immunity booster against COVID-19: DFT, molecular docking and MD simulations.

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