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      Identification of potential human pancreatic α-amylase inhibitors from natural products by molecular docking, MM/GBSA calculations, MD simulations, and ADMET analysis

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          Abstract

          Human pancreatic α-amylase (HPA), which works as a catalyst for carbohydrate hydrolysis, is one of the viable targets to control type 2 diabetes. The inhibition of α-amylase lowers blood glucose levels and helps to alleviate hyperglycemia complications. Herein, we systematically screened the potential HPA inhibitors from a library of natural products by molecular modeling. The modeling encompasses molecular docking, MM/GBSA binding energy calculations, MD simulations, and ADMET analysis. This research identified newboulaside B, newboulaside A, quercetin-3-O- β-glucoside, and sasastilboside A as the top four potential HPA inhibitors from the library of natural products, whose Glide docking scores and MM/GBSA binding energies range from -9.191 to -11.366 kcal/mol and -19.38 to -77.95 kcal/mol, respectively. Based on the simulation, among them, newboulaside B was found as the best HPA inhibitor. Throughout the simulation, with the deviation of 3Å (acarbose = 3Å), it interacted with ASP356, ASP300, ASP197, THR163, ARG161, ASP147, ALA106, and GLN63 via hydrogen bonding. Additionally, the comprehensive ADMET analysis revealed that it has good pharmacokinetic properties having not acutely toxic, moderately bioavailable, and non-inhibitor nature toward cytochrome P450. All the results suggest that newboulaside B might be a promising candidate for drug discovery against type 2 diabetes.

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          Most cited references41

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          SwissADME: a free web tool to evaluate pharmacokinetics, drug-likeness and medicinal chemistry friendliness of small molecules

          To be effective as a drug, a potent molecule must reach its target in the body in sufficient concentration, and stay there in a bioactive form long enough for the expected biologic events to occur. Drug development involves assessment of absorption, distribution, metabolism and excretion (ADME) increasingly earlier in the discovery process, at a stage when considered compounds are numerous but access to the physical samples is limited. In that context, computer models constitute valid alternatives to experiments. Here, we present the new SwissADME web tool that gives free access to a pool of fast yet robust predictive models for physicochemical properties, pharmacokinetics, drug-likeness and medicinal chemistry friendliness, among which in-house proficient methods such as the BOILED-Egg, iLOGP and Bioavailability Radar. Easy efficient input and interpretation are ensured thanks to a user-friendly interface through the login-free website http://www.swissadme.ch. Specialists, but also nonexpert in cheminformatics or computational chemistry can predict rapidly key parameters for a collection of molecules to support their drug discovery endeavours.
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            Protein and ligand preparation: parameters, protocols, and influence on virtual screening enrichments.

            Structure-based virtual screening plays an important role in drug discovery and complements other screening approaches. In general, protein crystal structures are prepared prior to docking in order to add hydrogen atoms, optimize hydrogen bonds, remove atomic clashes, and perform other operations that are not part of the x-ray crystal structure refinement process. In addition, ligands must be prepared to create 3-dimensional geometries, assign proper bond orders, and generate accessible tautomer and ionization states prior to virtual screening. While the prerequisite for proper system preparation is generally accepted in the field, an extensive study of the preparation steps and their effect on virtual screening enrichments has not been performed. In this work, we systematically explore each of the steps involved in preparing a system for virtual screening. We first explore a large number of parameters using the Glide validation set of 36 crystal structures and 1,000 decoys. We then apply a subset of protocols to the DUD database. We show that database enrichment is improved with proper preparation and that neglecting certain steps of the preparation process produces a systematic degradation in enrichments, which can be large for some targets. We provide examples illustrating the structural changes introduced by the preparation that impact database enrichment. While the work presented here was performed with the Protein Preparation Wizard and Glide, the insights and guidance are expected to be generalizable to structure-based virtual screening with other docking methods.
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              Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes.

              A novel scoring function to estimate protein-ligand binding affinities has been developed and implemented as the Glide 4.0 XP scoring function and docking protocol. In addition to unique water desolvation energy terms, protein-ligand structural motifs leading to enhanced binding affinity are included: (1) hydrophobic enclosure where groups of lipophilic ligand atoms are enclosed on opposite faces by lipophilic protein atoms, (2) neutral-neutral single or correlated hydrogen bonds in a hydrophobically enclosed environment, and (3) five categories of charged-charged hydrogen bonds. The XP scoring function and docking protocol have been developed to reproduce experimental binding affinities for a set of 198 complexes (RMSDs of 2.26 and 1.73 kcal/mol over all and well-docked ligands, respectively) and to yield quality enrichments for a set of fifteen screens of pharmaceutical importance. Enrichment results demonstrate the importance of the novel XP molecular recognition and water scoring in separating active and inactive ligands and avoiding false positives.
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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: ResourcesRole: SoftwareRole: ValidationRole: VisualizationRole: Writing – original draft
                Role: Formal analysisRole: ResourcesRole: Writing – review & editing
                Role: Formal analysisRole: VisualizationRole: Writing – review & editing
                Role: Formal analysisRole: ResourcesRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Project administrationRole: ResourcesRole: SoftwareRole: SupervisionRole: Writing – review & editing
                Role: Editor
                Journal
                PLoS One
                PLoS One
                plos
                PLOS ONE
                Public Library of Science (San Francisco, CA USA )
                1932-6203
                16 March 2023
                2023
                : 18
                : 3
                Affiliations
                [1 ] Central Department of Chemistry, Tribhuvan University, Kirtipur, Kathmandu, Nepal
                [2 ] Central Department of Physics, Tribhuvan University, Kirtipur, Kathmandu, Nepal
                [3 ] Department of Physics, Kathmandu University, Dhulikhel, Nepal
                University of Botswana, BOTSWANA
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Article
                PONE-D-22-26420
                10.1371/journal.pone.0275765
                10019617
                36928801
                6cae6cff-ecfc-450d-9a7d-4c5ba2afd249
                © 2023 Basnet et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 23 September 2022
                : 21 February 2023
                Page count
                Figures: 4, Tables: 1, Pages: 13
                Product
                Funding
                Funded by: http://www.ugcnepal.edu.np/uploads/notice/csmNgT.pdf
                Award ID: MRS-77/78-S&T-36
                Award Recipient :
                This work was supported by the University Grants Commission, Bhaktapur, Nepal, as part of a thesis grant fellowship award (MRS-77/78-S&T-36). The funder detail is in the following links ( http://www.ugcnepal.edu.np/uploads/notice/csmNgT.pdf). When the proposal was submitted to the UGC Nepal, it was proposed under the title of “In-Silico Evaluation of Different Natural Products as Inhibitors of α-Amylase Enzyme”. UGC provided funding (funding number: MRS-77/78-S&T-36) as dissertation support, but the title has been modified to “Identification of potential human pancreatic α-amylase inhibitors from natural products by molecular docking, MM/GBSA calculations, MD simulations, and ADMET analysis” during journal submission to give more emphasis on finding.
                Categories
                Research Article
                Biology and Life Sciences
                Biochemistry
                Biochemical Simulations
                Biology and Life Sciences
                Computational Biology
                Biochemical Simulations
                Physical Sciences
                Chemistry
                Physical Chemistry
                Chemical Bonding
                Hydrogen Bonding
                Physical Sciences
                Chemistry
                Computational Chemistry
                Molecular Docking
                Physical Sciences
                Chemistry
                Computational Chemistry
                Molecular Dynamics
                Medicine and Health Sciences
                Endocrinology
                Endocrine Disorders
                Diabetes Mellitus
                Type 2 Diabetes
                Medicine and Health Sciences
                Medical Conditions
                Metabolic Disorders
                Diabetes Mellitus
                Type 2 Diabetes
                Medicine and Health Sciences
                Endocrinology
                Endocrine Disorders
                Diabetes Mellitus
                Medicine and Health Sciences
                Medical Conditions
                Metabolic Disorders
                Diabetes Mellitus
                Biology and Life Sciences
                Toxicology
                Toxicity
                Medicine and Health Sciences
                Pathology and Laboratory Medicine
                Toxicology
                Toxicity
                Biology and Life Sciences
                Biochemistry
                Proteins
                Protein Interactions
                Custom metadata
                All relevant data are within the paper and its Supporting information files.

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