In-silico identification of phytochemicals as potential therapeutic agents to inhibit the HMG-CoA reductase activity using computational approach

Phytochemicals, have long been studied for various severe metabolic illnesses and degenerative diseases like heart disease and cancer because of their significant therapeutic effects. In animal cells, cholesterol serves a critical role being a component of cell membranes and essential for the normal functioning of precursor cells to some steroid hormones. Three-hydroxy-3-methyl glutaryl coenzyme A (HMG-CoA) is converted into mevalonate by the HMG-CoA Reductase (HMGCR) enzyme to produce cholesterol. However, when cholesterol levels are high, it may result in atherosclerosis. Statins, also known as synthetic drugs which decrease cholesterol, are therefore designed to work by targeting this enzyme. For patients with dyslipidemia, the side effects of excessive statin therapy have proven alarming hence using natural plant-based inhibitors is a promising alternative. Computational approach helps to identified many drugs that can target HMG-CO A Reductase. In this study, using in-silico molecular docking via auto-dock, 20 medicinal plants with 120 phytochemicals, reported as having antihyperlipidemic activity through deep literature study, were screened as HMG-CoA reductase enzyme inhibitors. The virtual molecular docking results reveals that five bioactive compounds; Sominone, Guggulsterone, Phytosterol, Withanolide A and Basilol, had higher binding affinities towards the HMG-CO A Reductase having binding energies of -9.33, -8.99, -8.87, -8.58, and -8.48kcal/mol, respectively. ADMET properties of selected compounds were analysed using swiss adme tool. Results showed that out of five compounds three follow Lipinski rule of five, having ADMET properties. The HMG-CoA reductase-ligand complex's stability was validated by RMSD, RMSF, Rg, H-bond results 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. This leads one to the conclusion that five phytochemicals, Sominone, Guggulsterone, Phytosterol, Withanolide A and Basilol can serve as potential inhibitors in regulating HMGCR’s function may assist the development of effective anti-hyperlipedemic drugs.

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Publication Details

Journal
Aspects of Molecular Medicine
Published
2025-05-09
DOI
https://doi.org/10.1016/j.amolm.2025.100086
Citations
2
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
3.01

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article

In-silico identification of phytochemicals as potential therapeutic agents to inhibit the HMG-CoA reductase activity using computational approach

Heera Ram, Ravikant Verma, Sumit Singh Dagar, Anil Panwar et al.
2 citations
Aspects of Molecular Medicine
Computational Drug Discovery Methods
3.01
article

In-silico identification of phytochemicals as potential therapeutic agents to inhibit the HMG-CoA reductase activity using computational approach

Heera Ram, Ravikant Verma, Sumit Singh Dagar, Anil Panwar, Neeru Singh Redhu, Mukesh Kumar, Anil Kumar Sharma, Sunil Kumar, Dushyant Gahalyan
article en
2 citations

Abstract

Phytochemicals, have long been studied for various severe metabolic illnesses and degenerative diseases like heart disease and cancer because of their significant therapeutic effects. In animal cells, cholesterol serves a critical role being a component of cell membranes and essential for the normal functioning of precursor cells to some steroid hormones. Three-hydroxy-3-methyl glutaryl coenzyme A (HMG-CoA) is converted into mevalonate by the HMG-CoA Reductase (HMGCR) enzyme to produce cholesterol. However, when cholesterol levels are high, it may result in atherosclerosis. Statins, also known as synthetic drugs which decrease cholesterol, are therefore designed to work by targeting this enzyme. For patients with dyslipidemia, the side effects of excessive statin therapy have proven alarming hence using natural plant-based inhibitors is a promising alternative. Computational approach helps to identified many drugs that can target HMG-CO A Reductase. In this study, using in-silico molecular docking via auto-dock, 20 medicinal plants with 120 phytochemicals, reported as having antihyperlipidemic activity through deep literature study, were screened as HMG-CoA reductase enzyme inhibitors. The virtual molecular docking results reveals that five bioactive compounds; Sominone, Guggulsterone, Phytosterol, Withanolide A and Basilol, had higher binding affinities towards the HMG-CO A Reductase having binding energies of -9.33, -8.99, -8.87, -8.58, and -8.48kcal/mol, respectively. ADMET properties of selected compounds were analysed using swiss adme tool. Results showed that out of five compounds three follow Lipinski rule of five, having ADMET properties. The HMG-CoA reductase-ligand complex's stability was validated by RMSD, RMSF, Rg, H-bond results 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. This leads one to the conclusion that five phytochemicals, Sominone, Guggulsterone, Phytosterol, Withanolide A and Basilol can serve as potential inhibitors in regulating HMGCR’s function may assist the development of effective anti-hyperlipedemic drugs.

Aspects of Molecular MedicineVol. 5
Chaudhary Charan Singh Haryana Agricultural University (IN), Guru Gobind Singh Medical College and Hospital (IN), Department of Biotechnology (IN), Amity University (AE), Institute of Botany (AM), Jai Narain Vyas University (IN)
Haryana State Council for Science and Technology
Openalex Percentile: Top 9%
Computational Drug Discovery Methods
3.01
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