Literature DB >> 16107143

A combination of docking, QM/MM methods, and MD simulation for binding affinity estimation of metalloprotein ligands.

Akash Khandelwal1, Viera Lukacova, Dogan Comez, Daniel M Kroll, Soumyendu Raha, Stefan Balaz.   

Abstract

To alleviate the problems in the receptor-based design of metalloprotein ligands due to inadequacies in the force-field description of coordination bonds, a four-tier approach was devised. Representative ligand-metalloprotein interaction energies are obtained by subsequent application of (1) docking with metal-binding-guided selection of modes, (2) optimization of the ligand-metalloprotein complex geometry by combined quantum mechanics and molecular mechanics (QM/MM) methods, (3) conformational sampling of the complex with constrained metal bonds by force-field-based molecular dynamics (MD), and (4) a single point QM/MM energy calculation for the time-averaged structures. The QM/MM interaction energies are, in a linear combination with the desolvation-characterizing changes in the solvent-accessible surface areas, correlated with experimental data. The approach was applied to structural correlation of published binding free energies of a diverse set of 28 hydroxamate inhibitors to zinc-dependent matrix metalloproteinase 9 (MMP-9). Inclusion of steps 3 and 4 significantly improved both correlation and prediction. The two descriptors explained 90% of variance in inhibition constants of all 28 inhibitors, ranging from 0.08 to 349 nM, with the average unassigned error of 0.318 log units. The structural and energetic information obtained from the time-averaged MD simulation results helped understand the differences in binding modes of related compounds.

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Year:  2005        PMID: 16107143      PMCID: PMC2896055          DOI: 10.1021/jm049050v

Source DB:  PubMed          Journal:  J Med Chem        ISSN: 0022-2623            Impact factor:   7.446


  56 in total

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Journal:  J Med Chem       Date:  2002-06-20       Impact factor: 7.446

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Journal:  J Med Chem       Date:  1997-05-09       Impact factor: 7.446

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  29 in total

1.  Molecular simulation methods in drug discovery: a prospective outlook.

Authors:  Xavier Barril; F Javier Luque
Journal:  J Comput Aided Mol Des       Date:  2011-12-08       Impact factor: 3.686

Review 2.  Prediction of protein-ligand binding affinity by free energy simulations: assumptions, pitfalls and expectations.

Authors:  Julien Michel; Jonathan W Essex
Journal:  J Comput Aided Mol Des       Date:  2010-05-28       Impact factor: 3.686

3.  Improved estimation of ligand-macromolecule binding affinities by linear response approach using a combination of multi-mode MD simulation and QM/MM methods.

Authors:  Akash Khandelwal; Stefan Balaz
Journal:  J Comput Aided Mol Des       Date:  2007-02-28       Impact factor: 3.686

Review 4.  Towards the development of universal, fast and highly accurate docking/scoring methods: a long way to go.

Authors:  N Moitessier; P Englebienne; D Lee; J Lawandi; C R Corbeil
Journal:  Br J Pharmacol       Date:  2007-11-26       Impact factor: 8.739

5.  A QM/MM study of the binding of RAPTA ligands to cathepsin B.

Authors:  Antonella Ciancetta; Samuel Genheden; Ulf Ryde
Journal:  J Comput Aided Mol Des       Date:  2011-06-24       Impact factor: 3.686

6.  Transferable scoring function based on semiempirical quantum mechanical PM6-DH2 method: CDK2 with 15 structurally diverse inhibitors.

Authors:  Petr Dobeš; Jindřich Fanfrlík; Jan Rezáč; Michal Otyepka; Pavel Hobza
Journal:  J Comput Aided Mol Des       Date:  2011-02-01       Impact factor: 3.686

7.  How accurate is the description of ligand-protein interactions by a hybrid QM/MM approach?

Authors:  Jakub Kollar; Vladimir Frecer
Journal:  J Mol Model       Date:  2017-12-12       Impact factor: 1.810

8.  Quantitative three dimensional structure linear interaction energy model of 5'-O-[N-(salicyl)sulfamoyl]adenosine and the aryl acid adenylating enzyme MbtA.

Authors:  Nicholas P Labello; Eric M Bennett; David M Ferguson; Courtney C Aldrich
Journal:  J Med Chem       Date:  2008-11-27       Impact factor: 7.446

9.  Quantum chemical study of silanediols as metal binding groups for metalloprotease inhibitors.

Authors:  Igor S Ignatyev; Manuel Montejo; Pilar Gema Rodríguez Ortega; Juan Jesús López González
Journal:  J Mol Model       Date:  2013-01-15       Impact factor: 1.810

10.  Molecular Modeling of Geometries, Charge Distributions, and Binding Energies of Small, Drug-Like Molecules Containing Nitrogen Heterocycles and Exocyclic Amino Groups in the Gas Phase and Aqueous Solution.

Authors:  Brian R White; Carston R Wagner; Donald G Truhlar; Elizabeth A Amin
Journal:  J Chem Theory Comput       Date:  2008-10-14       Impact factor: 6.006

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