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

Sheetal Dagar , Anil Panwar , Dushyant Gahalyan , Neeru Redhu , Mukesh Kumar , Sunil Kumar , Varruchi Sharma , Heera Ram , Ravikant Verma , Anil Sharma
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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 −8.48 kcal/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.
利用计算机方法在计算机上鉴定植物化学物质作为抑制HMG-CoA还原酶活性的潜在治疗剂
植物化学物质长期以来一直被研究用于各种严重的代谢性疾病和退行性疾病,如心脏病和癌症,因为它们具有显著的治疗作用。在动物细胞中,胆固醇作为细胞膜的组成部分起着至关重要的作用,对某些类固醇激素的前体细胞的正常功能至关重要。3-羟基-3-甲基戊二酰辅酶A (HMG-CoA)通过HMG-CoA还原酶(HMGCR)转化为甲羟戊酸盐产生胆固醇。然而,当胆固醇水平过高时,可能会导致动脉粥样硬化。他汀类药物,也被称为降低胆固醇的合成药物,因此被设计成针对这种酶起作用。对于患有血脂异常的患者,过量他汀类药物治疗的副作用已被证明是令人担忧的,因此使用天然植物抑制剂是一个很有前途的选择。计算方法有助于确定许多靶向HMG-CO A还原酶的药物。本研究采用自动对接的硅基分子对接技术,通过深入的文献研究,筛选出20种药用植物中含有120种植物化学物质的HMG-CoA还原酶抑制剂。虚拟分子对接结果显示5种生物活性化合物;对HMG-CO - A还原酶的结合能分别为- 9.33、- 8.99、- 8.87、- 8.58和- 8.48 kcal/mol,其中皂苷酮、古古酮、植物甾醇、威纳醇A和巴西罗酮具有较高的结合亲和力。用瑞士adme工具分析了所选化合物的ADMET性质。结果表明,五种化合物中有三种符合Lipinski法则,具有ADMET性质。通过RMSD、RMSF、Rg、氢键结果和主成分分析验证了HMG-CoA还原酶-配体复合物的稳定性。在MM-P/G/BSA计算中进一步利用所得的MD收敛周期轨迹,得到了结合自由能的精确估计。因此,Sominone、Guggulsterone、Phytosterol、Withanolide A和Basilol这5种植物化学物质可能是调控HMGCR功能的潜在抑制剂,有助于开发有效的抗高脂血症药物。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Aspects of molecular medicine
Aspects of molecular medicine Molecular Biology, Molecular Medicine
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