Literature DB >> 26575904

Representative Amino Acid Side-Chain Interactions in Protein-DNA Complexes: A Comparison of Highly Accurate Correlated Ab Initio Quantum Mechanical Calculations and Efficient Approaches for Applications to Large Systems.

Jiří Hostaš1,2, Dávid Jakubec1,2, Roman A Laskowski3, Ramachandran Gnanasekaran1, Jan Řezáč1, Jiří Vondrášek1, Pavel Hobza1,4.   

Abstract

Representative pairs of amino acid side chains and nucleic acid bases extracted from available high-quality structures of protein-DNA complexes were analyzed using a range of computational methods. CCSD(T)/CBS interaction energies were calculated for the chosen 272 pairs. These reference interaction energies were used to test the MP2.5/CBS, MP2.X/CBS, MP2-F12, DFT-D3, PM6, and Amber force field methods. Method MP2.5 provided excellent agreement with reference data (root-mean-square error (RMSE) of 0.11 kcal/mol), which is more than 1 order of magnitude faster than the CCSD(T) method. When MP2-F12 and MP2.5 were combined, the results were within reasonable accuracy (0.20 kcal/mol), with a computational savings of almost 2 orders of magnitude. Therefore, this method is a promising tool for accurate calculations of interaction energies in protein-DNA motifs of up to ∼100 atoms, for which CCSD(T)/CBS benchmark calculations are not feasible. B3-LYP-D3 calculated with def2-TZVPP and def2-QZVP basis sets yielded sufficiently good results with a reasonably small RMSE. This method provided better results for neutral systems, whereas positively charged species exhibited the worst agreement with the benchmark data. The Amber force field yielded unbalanced results-performing well for systems containing nonpolar amino acids but severely underestimating interaction energies for charged complexes. The semiempirical PM6 method with corrections for hydrogen bonding and dispersion energy (PM6-D3H4) exhibited considerably smaller error than the Amber force field, which makes it an effective tool for modeling extended protein-ligand complexes (of up to 10,000 atoms).

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Year:  2015        PMID: 26575904     DOI: 10.1021/acs.jctc.5b00398

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


  3 in total

1.  The BioFragment Database (BFDb): An open-data platform for computational chemistry analysis of noncovalent interactions.

Authors:  Lori A Burns; John C Faver; Zheng Zheng; Michael S Marshall; Daniel G A Smith; Kenno Vanommeslaeghe; Alexander D MacKerell; Kenneth M Merz; C David Sherrill
Journal:  J Chem Phys       Date:  2017-10-28       Impact factor: 3.488

2.  Evaluating dispersion forces for optimization of van der Waals complexes using a non-empirical functional.

Authors:  Alya A Arabi
Journal:  Philos Trans A Math Phys Eng Sci       Date:  2016-11-13       Impact factor: 4.226

3.  Sequence-Specific Recognition of DNA by Proteins: Binding Motifs Discovered Using a Novel Statistical/Computational Analysis.

Authors:  David Jakubec; Roman A Laskowski; Jiri Vondrasek
Journal:  PLoS One       Date:  2016-07-06       Impact factor: 3.240

  3 in total

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