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      A combination of virtual screening, molecular dynamics simulation, MM/PBSA, ADMET, and DFT calculations to identify a potential DPP4 inhibitor

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          Abstract

          DPP4 inhibitors can control glucose homeostasis by increasing the level of GLP-1 incretins hormone due to dipeptidase mimicking. Despite the potent effects of DPP4 inhibitors, these compounds cause unwanted toxicity attributable to their effect on other enzymes. As a result, it seems essential to find novel and DPP4 selective compounds. In this study, we introduce a potent and selective DPP4 inhibitor via structure-based virtual screening, molecular docking, molecular dynamics simulation, MM/PBSA calculations, DFT analysis, and ADMET profile. The screened compounds based on similarity with FDA-approved DPP4 inhibitors were docked towards the DPP4 enzyme. The compound with the highest docking score, ZINC000003015356, was selected. For further considerations, molecular docking studies were performed on selected ligands and FDA-approved drugs for DPP8 and DPP9 enzymes. Molecular dynamics simulation was run during 200 ns and the analysis of RMSD, RMSF, Rg, PCA, and hydrogen bonding were performed. The MD outputs showed stability of the ligand–protein complex compared to available drugs in the market. The total free binding energy obtained for the proposed DPP4 inhibitor was more negative than its co-crystal ligand (N7F). ZINC000003015356 confirmed the role of the five Lipinski rule and also, have low toxicity parameter according to properties. Finally, DFT calculations indicated that this compound is sufficiently soft.

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          AutoDock Vina 1.2.0: New Docking Methods, Expanded Force Field, and Python Bindings

          AutoDock Vina is arguably one of the fastest and most widely used open-source programs for molecular docking. However, compared to other programs in the AutoDock Suite, it lacks support for modeling specific features such as macrocycles or explicit water molecules. Here, we describe the implementation of this functionality in AutoDock Vina 1.2.0. Additionally, AutoDock Vina 1.2.0 supports the AutoDock4.2 scoring function, simultaneous docking of multiple ligands, and a batch mode for docking a large number of ligands. Furthermore, we implemented Python bindings to facilitate scripting and the development of docking workflows. This work is an effort toward the unification of the features of the AutoDock4 and AutoDock Vina programs. The source code is available at https://github.com/ccsb-scripps/AutoDock-Vina.
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            End-Point Binding Free Energy Calculation with MM/PBSA and MM/GBSA: Strategies and Applications in Drug Design

            Molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) and molecular mechanics generalized Born surface area (MM/GBSA) are arguably very popular methods for binding free energy prediction since they are more accurate than most scoring functions of molecular docking and less computationally demanding than alchemical free energy methods. MM/PBSA and MM/GBSA have been widely used in biomolecular studies such as protein folding, protein-ligand binding, protein-protein interaction, etc. In this review, methods to adjust the polar solvation energy and to improve the performance of MM/PBSA and MM/GBSA calculations are reviewed and discussed. The latest applications of MM/GBSA and MM/PBSA in drug design are also presented. This review intends to provide readers with guidance for practically applying MM/PBSA and MM/GBSA in drug design and related research fields.
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              ZINC--a free database of commercially available compounds for virtual screening.

              A critical barrier to entry into structure-based virtual screening is the lack of a suitable, easy to access database of purchasable compounds. We have therefore prepared a library of 727,842 molecules, each with 3D structure, using catalogs of compounds from vendors (the size of this library continues to grow). The molecules have been assigned biologically relevant protonation states and are annotated with properties such as molecular weight, calculated LogP, and number of rotatable bonds. Each molecule in the library contains vendor and purchasing information and is ready for docking using a number of popular docking programs. Within certain limits, the molecules are prepared in multiple protonation states and multiple tautomeric forms. In one format, multiple conformations are available for the molecules. This database is available for free download (http://zinc.docking.org) in several common file formats including SMILES, mol2, 3D SDF, and DOCK flexibase format. A Web-based query tool incorporating a molecular drawing interface enables the database to be searched and browsed and subsets to be created. Users can process their own molecules by uploading them to a server. Our hope is that this database will bring virtual screening libraries to a wide community of structural biologists and medicinal chemists.
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                Author and article information

                Contributors
                aida.solhjoo86@gmail.com
                emamil@sums.ac.ir
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                2 April 2024
                2 April 2024
                2024
                : 14
                : 7749
                Affiliations
                [1 ]Department of Medicinal Chemistry, School of Pharmacy, Shiraz University of Medical Sciences, ( https://ror.org/01n3s4692) Shiraz, Iran
                [2 ]Medicinal and Natural Products Chemistry Research Center, Shiraz University of Medical Sciences, ( https://ror.org/01n3s4692) Shiraz, Iran
                [3 ]GRID grid.6936.a, ISNI 0000000123222966, Chair of Proteomics and Bioanalytics, , Technical University of Munich (TUM), ; 85354 Freising, Germany
                [4 ]Department of Quality Control of Drug Products, School of Pharmacy, Shiraz University of Medical Sciences, ( https://ror.org/01n3s4692) Shiraz, Iran
                [5 ]Pharmaceutical Sciences Research Center, Shiraz University of Medical Sciences, ( https://ror.org/01n3s4692) Shiraz, Iran
                Article
                58485
                10.1038/s41598-024-58485-x
                10987597
                38565703
                c918e0e8-ffc1-46ca-9875-3559815646ba
                © The Author(s) 2024

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 5 December 2023
                : 29 March 2024
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100006096, Shiraz Transplant Research Center, Shiraz University of Medical Sciences;
                Award ID: 27202
                Award Recipient :
                Categories
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                © Springer Nature Limited 2024

                Uncategorized
                dpp4 inhibitor,structure-based virtual screening,molecular dynamics simulation,mm/pbsa,dft,admet,computational biology and bioinformatics,drug discovery

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