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Bringing Clarity to the Prediction of Protein–Ligand Binding Free Energies via “Blurring”

[Image: see text] We present a method to evaluate the free energies of ligand binding utilizing a Monte Carlo estimation of the configuration integrals concomitant with uncertainty quantification. Ensembles for integration are built through systematically perturbing an initial ligand conformation in...

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Autores principales: Ucisik, Melek N., Zheng, Zheng, Faver, John C., Merz, Kenneth M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2014
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4006398/
https://www.ncbi.nlm.nih.gov/pubmed/24803861
http://dx.doi.org/10.1021/ct400995c
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author Ucisik, Melek N.
Zheng, Zheng
Faver, John C.
Merz, Kenneth M.
author_facet Ucisik, Melek N.
Zheng, Zheng
Faver, John C.
Merz, Kenneth M.
author_sort Ucisik, Melek N.
collection PubMed
description [Image: see text] We present a method to evaluate the free energies of ligand binding utilizing a Monte Carlo estimation of the configuration integrals concomitant with uncertainty quantification. Ensembles for integration are built through systematically perturbing an initial ligand conformation in a rigid binding pocket, which is optimized separately prior to incorporation of the ligand. We call the procedure producing the ensembles “blurring”, and it is carried out using an in-house developed code. The Boltzmann factor contribution of each pose to the configuration integral is computed and from there the free energy is obtained. Potential function uncertainties are estimated using a fragment-based error propagation method. This method has been applied to a set of small aromatic ligands complexed with T4 Lysozyme L99A mutant. Microstate energies have been determined with the force fields ff99SB and ff94, and the semiempirical method PM6DH2 in conjunction with continuum solvation models including Generalized Born (GB), the Conductor-like Screening Model (COSMO), and SMD. Of the methods studied, PM6DH2-based scoring gave binding free energy estimates, which yielded a good correlation to the experimental binding affinities (R(2) = 0.7). All methods overestimated the calculated binding affinities. We trace this to insufficient sampling, the single static protein structure, and inaccuracies in the solvent models we have used in this study.
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spelling pubmed-40063982015-02-07 Bringing Clarity to the Prediction of Protein–Ligand Binding Free Energies via “Blurring” Ucisik, Melek N. Zheng, Zheng Faver, John C. Merz, Kenneth M. J Chem Theory Comput [Image: see text] We present a method to evaluate the free energies of ligand binding utilizing a Monte Carlo estimation of the configuration integrals concomitant with uncertainty quantification. Ensembles for integration are built through systematically perturbing an initial ligand conformation in a rigid binding pocket, which is optimized separately prior to incorporation of the ligand. We call the procedure producing the ensembles “blurring”, and it is carried out using an in-house developed code. The Boltzmann factor contribution of each pose to the configuration integral is computed and from there the free energy is obtained. Potential function uncertainties are estimated using a fragment-based error propagation method. This method has been applied to a set of small aromatic ligands complexed with T4 Lysozyme L99A mutant. Microstate energies have been determined with the force fields ff99SB and ff94, and the semiempirical method PM6DH2 in conjunction with continuum solvation models including Generalized Born (GB), the Conductor-like Screening Model (COSMO), and SMD. Of the methods studied, PM6DH2-based scoring gave binding free energy estimates, which yielded a good correlation to the experimental binding affinities (R(2) = 0.7). All methods overestimated the calculated binding affinities. We trace this to insufficient sampling, the single static protein structure, and inaccuracies in the solvent models we have used in this study. American Chemical Society 2014-02-07 2014-03-11 /pmc/articles/PMC4006398/ /pubmed/24803861 http://dx.doi.org/10.1021/ct400995c Text en Copyright © 2014 American Chemical Society
spellingShingle Ucisik, Melek N.
Zheng, Zheng
Faver, John C.
Merz, Kenneth M.
Bringing Clarity to the Prediction of Protein–Ligand Binding Free Energies via “Blurring”
title Bringing Clarity to the Prediction of Protein–Ligand Binding Free Energies via “Blurring”
title_full Bringing Clarity to the Prediction of Protein–Ligand Binding Free Energies via “Blurring”
title_fullStr Bringing Clarity to the Prediction of Protein–Ligand Binding Free Energies via “Blurring”
title_full_unstemmed Bringing Clarity to the Prediction of Protein–Ligand Binding Free Energies via “Blurring”
title_short Bringing Clarity to the Prediction of Protein–Ligand Binding Free Energies via “Blurring”
title_sort bringing clarity to the prediction of protein–ligand binding free energies via “blurring”
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4006398/
https://www.ncbi.nlm.nih.gov/pubmed/24803861
http://dx.doi.org/10.1021/ct400995c
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