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A quantum mechanical computational method for modeling electrostatic and solvation effects of protein

An efficient computational approach for modeling protein electrostatic is developed according to static point-charge model distributions based on the linear-scaling EE-GMFCC (electrostatically embedded generalized molecular fractionation with conjugate caps) quantum mechanical (QM) method. In this a...

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Autores principales: Wang, Xianwei, Li, Yang, Gao, Ya, Yang, Zejin, Lu, Chenhui, Zhu, Tong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5882933/
https://www.ncbi.nlm.nih.gov/pubmed/29615707
http://dx.doi.org/10.1038/s41598-018-23783-8
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author Wang, Xianwei
Li, Yang
Gao, Ya
Yang, Zejin
Lu, Chenhui
Zhu, Tong
author_facet Wang, Xianwei
Li, Yang
Gao, Ya
Yang, Zejin
Lu, Chenhui
Zhu, Tong
author_sort Wang, Xianwei
collection PubMed
description An efficient computational approach for modeling protein electrostatic is developed according to static point-charge model distributions based on the linear-scaling EE-GMFCC (electrostatically embedded generalized molecular fractionation with conjugate caps) quantum mechanical (QM) method. In this approach, the Electrostatic-Potential atomic charges are obtained from ab initio calculation of protein, both polarization and charge transfer effect are taken into consideration. This approach shows a significant improvement in the description of electrostatic potential and solvation energy of proteins comparing with current popular molecular mechanics (MM) force fields. Therefore, it has gorgeous prospect in many applications, including accurate calculations of electric field or vibrational Stark spectroscopy in proteins and predicting protein-ligand binding affinity. It can also be applied in QM/MM calculations or electronic embedding method of ONIOM to provide a better electrostatic environment.
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spelling pubmed-58829332018-04-09 A quantum mechanical computational method for modeling electrostatic and solvation effects of protein Wang, Xianwei Li, Yang Gao, Ya Yang, Zejin Lu, Chenhui Zhu, Tong Sci Rep Article An efficient computational approach for modeling protein electrostatic is developed according to static point-charge model distributions based on the linear-scaling EE-GMFCC (electrostatically embedded generalized molecular fractionation with conjugate caps) quantum mechanical (QM) method. In this approach, the Electrostatic-Potential atomic charges are obtained from ab initio calculation of protein, both polarization and charge transfer effect are taken into consideration. This approach shows a significant improvement in the description of electrostatic potential and solvation energy of proteins comparing with current popular molecular mechanics (MM) force fields. Therefore, it has gorgeous prospect in many applications, including accurate calculations of electric field or vibrational Stark spectroscopy in proteins and predicting protein-ligand binding affinity. It can also be applied in QM/MM calculations or electronic embedding method of ONIOM to provide a better electrostatic environment. Nature Publishing Group UK 2018-04-03 /pmc/articles/PMC5882933/ /pubmed/29615707 http://dx.doi.org/10.1038/s41598-018-23783-8 Text en © The Author(s) 2018 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Wang, Xianwei
Li, Yang
Gao, Ya
Yang, Zejin
Lu, Chenhui
Zhu, Tong
A quantum mechanical computational method for modeling electrostatic and solvation effects of protein
title A quantum mechanical computational method for modeling electrostatic and solvation effects of protein
title_full A quantum mechanical computational method for modeling electrostatic and solvation effects of protein
title_fullStr A quantum mechanical computational method for modeling electrostatic and solvation effects of protein
title_full_unstemmed A quantum mechanical computational method for modeling electrostatic and solvation effects of protein
title_short A quantum mechanical computational method for modeling electrostatic and solvation effects of protein
title_sort quantum mechanical computational method for modeling electrostatic and solvation effects of protein
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5882933/
https://www.ncbi.nlm.nih.gov/pubmed/29615707
http://dx.doi.org/10.1038/s41598-018-23783-8
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