Dataset Information

IAF, QGF, and QDF Peptides Exhibit Cholesterol-Lowering Activity through a Statin-like HMG-CoA Reductase Regulation Mechanism: In Silico and In Vitro Approach.

ABSTRACT: In this study, in silico approaches are employed to investigate the binding mechanism of peptides derived from cowpea β-vignin and HMG-CoA reductase. With the obtained information, we designed synthetic peptides to evaluate their in vitro enzyme inhibitory activity. In vitro, the total protein extract and <3 kDa fraction, at 5000 µg, support this hypothesis (95% and 90% inhibition of HMG-CoA reductase, respectively). Ile-Ala-Phe, Gln-Gly-Phe, and Gln-Asp-Phe peptides were predicted to bind to the substrate binding site of HMGCR via HMG-CoAR. In silico, it was established that the mechanism of HMG-CoA reductase inhibition largely entailed mimicking the interactions of the decalin ring of simvastatin and via H-bonding; in vitro studies corroborated the predictions, whereby the HMG-CoA reductase activity was decreased by 69%, 77%, and 78%, respectively. Our results suggest that Ile-Ala-Phe, Gln-Gly-Phe, and Gln-Asp-Phe peptides derived from cowpea β-vignin have the potential to lower cholesterol synthesis through a statin-like regulation mechanism.

SUBMITTER: Silva M

PROVIDER: S-EPMC8538380 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature

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IAF, QGF, and QDF Peptides Exhibit Cholesterol-Lowering Activity through a Statin-like HMG-CoA Reductase Regulation Mechanism: In Silico and In Vitro Approach.

Silva Mariana M Philadelpho Biane B Santos Johnnie J Souza Victória V Souza Caio C Santiago Victória V Silva Jaff J Souza Carolina C Azeredo Francine F Castilho Marcelo M Cilli Eduardo E Ferreira Ederlan E

International journal of molecular sciences 20211014 20

In this study, in silico approaches are employed to investigate the binding mechanism of peptides derived from cowpea β-vignin and HMG-CoA reductase. With the obtained information, we designed synthetic peptides to evaluate their in vitro enzyme inhibitory activity. In vitro, the total protein extract and <3 kDa fraction, at 5000 µg, support this hypothesis (95% and 90% inhibition of HMG-CoA reductase, respectively). Ile-Ala-Phe, Gln-Gly-Phe, and Gln-Asp-Phe peptides were predicted to bind to th ...[more]

PMID: 34681729

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Project description:HMG-CoA reductase (HMGR) is the target of statins, cholesterol-lowering drugs prescribed to millions of patients worldwide. More recent research indicates that HMGR could be a useful target in the development of antimicrobial agents. Over the last seven decades, researchers have proposed a series of increasingly complex reaction mechanisms for this biomedically important enzyme. The maturation of the mechanistic proposals for HMGR have paralleled advances in a diverse set of research areas, such as molecular biology and computational chemistry. Thus, the development of the HMGR mechanism provides a useful case study for following the advances in state-of-the-art methods in enzyme mechanism research. Similarly, the questions raised by these mechanism proposals reflect the limitations of the methods used to develop them. The mechanism of HMGR, a four-electron oxidoreductase, is unique and far more complex than originally thought. The reaction contains multiple chemical steps, coupled to large-scale domain motions of the homodimeric enzyme. The first proposals for the HMGR mechanism were based on kinetic and labeling experiments, drawing analogies to the mechanism of known dehydrogenases. Advances in molecular biology and bioinformatics enabled researchers to use site-directed mutagenesis experiments and protein sequencing to identify catalytically important glutamate, aspartate, and histidine residues. These studies, in turn, have generated new and more complicated mechanistic proposals. With the development of protein crystallography, researchers solved HMGR crystal structures to reveal an unexpected lysine residue at the center of the active site. The many crystal structures of HMGR led to increasingly complex mechanistic proposals, but the inherent limitations of the protein crystallography left a number of questions unresolved. For example, the protonation state of the glutamate residue within the active site cannot be clearly determined from the crystal structure. The differing protonation state of this residue leads to different proposed mechanisms for the enzyme. As computational analysis of large biomolecules has become more feasible, the application of methods such as hybrid quantum mechanics/molecular mechanics (QM/MM) calculations to the HMGR mechanism have led to the most detailed mechanistic proposal yet. As these methodologies continue to improve, they prove to be very powerful for the study of enzyme mechanisms in conjunction with protein crystallography. Nevertheless, even the most current mechanistic proposal for HMGR remains incomplete due to limitations of the current computational methodologies. Thus, HMGR serves as a model for how the combination of increasingly sophisticated experimental and computational methods can elucidate very complex enzyme mechanisms.

Project description:BackgroundHypercholesterolemia has posed a serious threat of heart diseases and stroke worldwide. Xanthine oxidase (XO), the rate-limiting enzyme in uric acid biosynthesis, is regarded as the root of reactive oxygen species (ROS) that generate atherosclerosis and cholesterol crystals. β-Hydroxy β-methylglutaryl-coenzyme A reductase (HMGR) is a rate-limiting enzyme in cholesterol biosynthesis. Although some commercially available enzyme inhibiting drugs have effectively reduced cholesterol levels, most of them have failed to meet potential drug candidates' requirements. Here, we have carried out an in-silico analysis of secondary metabolites that have already shown good inhibitory activity against XO and HMGR in a wet lab setup.MethodsOut of 118 secondary metabolites reviewed, sixteen molecules inhibiting XO and HMGR were selected based on the IC50 values reported in in vitro assays. Further, receptor-based virtual screening was carried out against secondary metabolites using GOLD Protein-Ligand Docking Software, combined with subsequent post-docking, to study the binding affinities of ligands to the enzymes. In-silico ADMET analysis was carried out to explore their pharmacokinetic properties, followed by toxicity prediction through ProTox-II.ResultsThe molecular docking of amentoflavone (GOLD score 70.54, ∆G calc. = - 10.4 Kcal/mol) and ganomycin I (GOLD score 59.61, ∆G calc. = - 6.8 Kcal/mol) displayed that the drug has effectively bound at the competitive site of XO and HMGR, respectively. Besides, 6-paradol and selgin could be potential drug candidates inhibiting XO. Likewise, n-octadecanyl-O-α-D-glucopyranosyl (6' → 1″)-O-α-D-glucopyranoside could be potential drug candidates to maintain serum cholesterol. In-silico ADMET analysis has shown that these sixteen metabolites were optimal within the categorical range compared to commercially available XO and HMGR inhibitors, respectively. Toxicity analysis through ProTox-II revealed that 6-gingerol, ganoleucoin K, and ganoleucoin Z are toxic for human use.ConclusionThis computational analysis supports earlier experimental evidence towards the inhibition of XO and HMGR by natural products. Further study is necessary to explore the clinical efficacy of these secondary molecules, which might be alternatives for the treatment of hypercholesterolemia.

Project description:BackgroundStatins are first-line therapy for cardiovascular disease prevention, but their systemic effects across lipoprotein subclasses, fatty acids, and circulating metabolites remain incompletely characterized.ObjectivesThis study sought to determine the molecular effects of statin therapy on multiple metabolic pathways.MethodsMetabolic profiles based on serum nuclear magnetic resonance metabolomics were quantified at 2 time points in 4 population-based cohorts from the United Kingdom and Finland (N = 5,590; 2.5 to 23.0 years of follow-up). Concentration changes in 80 lipid and metabolite measures during follow-up were compared between 716 individuals who started statin therapy and 4,874 persistent nonusers. To further understand the pharmacological effects of statins, we used Mendelian randomization to assess associations of a genetic variant known to mimic inhibition of HMG-CoA reductase (the intended drug target) with the same lipids and metabolites for 27,914 individuals from 8 population-based cohorts.ResultsStarting statin therapy was associated with numerous lipoprotein and fatty acid changes, including substantial lowering of remnant cholesterol (80% relative to low-density lipoprotein cholesterol [LDL-C]), but only modest lowering of triglycerides (25% relative to LDL-C). Among fatty acids, omega-6 levels decreased the most (68% relative to LDL-C); other fatty acids were only modestly affected. No robust changes were observed for circulating amino acids, ketones, or glycolysis-related metabolites. The intricate metabolic changes associated with statin use closely matched the association pattern with rs12916 in the HMGCR gene (R(2) = 0.94, slope 1.00 ± 0.03).ConclusionsStatin use leads to extensive lipid changes beyond LDL-C and appears efficacious for lowering remnant cholesterol. Metabolomic profiling, however, suggested minimal effects on amino acids. The results exemplify how detailed metabolic characterization of genetic proxies for drug targets can inform indications, pleiotropic effects, and pharmacological mechanisms.

Project description:Dyslipidemia, an imbalance in blood lipid levels, is a frequent complication of type 2 diabetes mellitus (DM2) and heightens the risk of cardiovascular diseases (CVDs). Statins, which inhibit 3-hydroxy-3-methylglutaryl-CoA reductase, are potent competitive inhibitors that reduce plasma cholesterol levels. However, individual responses to statins can vary markedly, possibly due to genetic variations in the 3-hydroxy-3-methylglutaryl-CoA reductase (HMGCR) gene. This study aimed to investigate the pharmacogenetic relationship between the HMGCR gene and hypercholesterolemia in type 2 diabetes mellitus patients who respond differently to atorvastatin, as well as in healthy individuals. Ninety participants were involved, including sixty with type 2 diabetes mellitus and hypercholesterolemia, and thirty healthy individuals. They were randomly assigned to three groups: responsive (received atorvastatin 40 mg), non-responsive (also received atorvastatin 40 mg), and control. Both responsive and non-responsive groups underwent fasting. Biochemical tests were conducted, followed by genetic analysis to identify mutations in the HMGCR gene. The effects of statins in each group were assessed using analysis of variance (ANOVA) and post hoc Tukey's Honestly Significant Difference (HSD) analysis. Atorvastatin 40 mg was administered to assess its efficacy in reducing cholesterol levels in patients with hypercholesterolemia and type 2 diabetes mellitus. The control group exhibited similar cholesterol levels to the responsive group (cholesterol < 200 mg/dl). However, both control and responsive groups significantly differed from the non-responsive group, which had markedly elevated cholesterol levels (> 240 mg/dl). Genetic analysis revealed a cytosine nucleotide insertion in the catalytic domain of the HMGCR gene in only two non-responsive participants to atorvastatin 40 mg therapy. These two patients showed non-responsiveness to atorvastatin 40 mg due to a genetic mutation in the HMGCR gene. This mutation altered the amino acid sequence in the flap domain, replacing isoleucine with a stop codon. As a result, translation was prematurely terminated, leading to the production of truncated proteins.

Dataset Information

IAF, QGF, and QDF Peptides Exhibit Cholesterol-Lowering Activity through a Statin-like HMG-CoA Reductase Regulation Mechanism: In Silico and In Vitro Approach.

Publications

IAF, QGF, and QDF Peptides Exhibit Cholesterol-Lowering Activity through a Statin-like HMG-CoA Reductase Regulation Mechanism: In Silico and In Vitro Approach.

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