Literature DB >> 31557013

Ligand-Binding-Site Structure Refinement Using Molecular Dynamics with Restraints Derived from Predicted Binding Site Templates.

Hugo Guterres1, Hui Sun Lee1, Wonpil Im1,2.   

Abstract

Accurate modeling of ligand-binding-site structures plays a critical role in structure-based virtual screening. However, the structures of the ligand-binding site in most predicted protein models are generally of low quality and need refinements. In this work, we present a ligand-binding-site structure refinement protocol using molecular dynamics simulation with restraints derived from predicted binding site templates. Our benchmark validation shows great performance for 40 diverse sets of proteins from the Astex list. The ligand-binding sites on modeled protein structures are consistently refined using our method with an average Cα RMSD improvement of 0.90 Å. Comparison of ligand binding modes from ligand docking to initial unrefined and refined structures shows an average of 1.97 Å RMSD improvement in the refined structures. These results demonstrate a promising new method of structure refinement for protein ligand-binding-site structures.

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Year:  2019        PMID: 31557013      PMCID: PMC6884403          DOI: 10.1021/acs.jctc.9b00751

Source DB:  PubMed          Journal:  J Chem Theory Comput        ISSN: 1549-9618            Impact factor:   6.006


  53 in total

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4.  I-TASSER: a unified platform for automated protein structure and function prediction.

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5.  Identification of ligand templates using local structure alignment for structure-based drug design.

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Journal:  J Chem Inf Model       Date:  2012-09-28       Impact factor: 4.956

6.  How to choose relevant multiple receptor conformations for virtual screening: a test case of Cdk2 and normal mode analysis.

Authors:  Olivier Sperandio; Liliane Mouawad; Eulalie Pinto; Bruno O Villoutreix; David Perahia; Maria A Miteva
Journal:  Eur Biophys J       Date:  2010-03-18       Impact factor: 1.733

7.  Computational protein structure refinement: Almost there, yet still so far to go.

Authors:  Michael Feig
Journal:  Wiley Interdiscip Rev Comput Mol Sci       Date:  2017-03-28

8.  Refinement of protein structure homology models via long, all-atom molecular dynamics simulations.

Authors:  Alpan Raval; Stefano Piana; Michael P Eastwood; Ron O Dror; David E Shaw
Journal:  Proteins       Date:  2012-05-15

9.  In pursuit of virtual lead optimization: the role of the receptor structure and ensembles in accurate docking.

Authors:  Erin S D Bolstad; Amy C Anderson
Journal:  Proteins       Date:  2008-11-15

10.  Exploring the composition of protein-ligand binding sites on a large scale.

Authors:  Nickolay A Khazanov; Heather A Carlson
Journal:  PLoS Comput Biol       Date:  2013-11-21       Impact factor: 4.475

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  6 in total

1.  Ligand-Binding-Site Refinement to Generate Reliable Holo Protein Structure Conformations from Apo Structures.

Authors:  Hugo Guterres; Sang-Jun Park; Wei Jiang; Wonpil Im
Journal:  J Chem Inf Model       Date:  2020-12-18       Impact factor: 4.956

2.  Improving Protein-Ligand Docking Results with High-Throughput Molecular Dynamics Simulations.

Authors:  Hugo Guterres; Wonpil Im
Journal:  J Chem Inf Model       Date:  2020-04-10       Impact factor: 4.956

3.  Mining for Ligandable Cavities in RNA.

Authors:  Jingru Xie; Aaron T Frank
Journal:  ACS Med Chem Lett       Date:  2021-06-01       Impact factor: 4.632

4.  Improved Sampling Strategies for Protein Model Refinement Based on Molecular Dynamics Simulation.

Authors:  Lim Heo; Collin F Arbour; Giacomo Janson; Michael Feig
Journal:  J Chem Theory Comput       Date:  2021-02-09       Impact factor: 6.006

Review 5.  Structure of fish Toll-like receptors (TLR) and NOD-like receptors (NLR).

Authors:  Bikash Ranjan Sahoo
Journal:  Int J Biol Macromol       Date:  2020-08-02       Impact factor: 6.953

Review 6.  Exploring the computational methods for protein-ligand binding site prediction.

Authors:  Jingtian Zhao; Yang Cao; Le Zhang
Journal:  Comput Struct Biotechnol J       Date:  2020-02-17       Impact factor: 7.271

  6 in total

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