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Charge-Transfer Knowledge Graph among Amino Acids Derived from High-Throughput Electronic Structure Calculations for Protein Database

[Image: see text] The charge-transfer coupling is an important component in tight-binding methods. Because of the highly complex chemical structure of biomolecules, the anisotropic feature of charge-transfer couplings in realistic proteins cannot be ignored. In this work, we have performed the first...

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Autores principales: Wang, Hongwei, Liu, Fang, Dong, Tiange, Du, Likai, Zhang, Dongju, Gao, Jun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2018
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6641752/
https://www.ncbi.nlm.nih.gov/pubmed/31458645
http://dx.doi.org/10.1021/acsomega.8b00336
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author Wang, Hongwei
Liu, Fang
Dong, Tiange
Du, Likai
Zhang, Dongju
Gao, Jun
author_facet Wang, Hongwei
Liu, Fang
Dong, Tiange
Du, Likai
Zhang, Dongju
Gao, Jun
author_sort Wang, Hongwei
collection PubMed
description [Image: see text] The charge-transfer coupling is an important component in tight-binding methods. Because of the highly complex chemical structure of biomolecules, the anisotropic feature of charge-transfer couplings in realistic proteins cannot be ignored. In this work, we have performed the first large-scale quantitative assessment of charge-transfer preference by calculating the charge-transfer couplings in all 20 × 20 possible amino acid side-chain combinations, which are extracted from available high-quality structures of thousands of protein complexes. The charge-transfer database quantitatively shows distinct features of charge-transfer couplings among millions of amino acid side-chain combinations. The overall distribution of charge-transfer couplings reveals that only one average or representative structure cannot be regarded as the typical charge-transfer preference in realistic proteins. This work provides us an alternative route to comprehensively understand the charge-transfer couplings for the overall distribution of realistic proteins in the foreseen big data scenario.
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spelling pubmed-66417522019-08-27 Charge-Transfer Knowledge Graph among Amino Acids Derived from High-Throughput Electronic Structure Calculations for Protein Database Wang, Hongwei Liu, Fang Dong, Tiange Du, Likai Zhang, Dongju Gao, Jun ACS Omega [Image: see text] The charge-transfer coupling is an important component in tight-binding methods. Because of the highly complex chemical structure of biomolecules, the anisotropic feature of charge-transfer couplings in realistic proteins cannot be ignored. In this work, we have performed the first large-scale quantitative assessment of charge-transfer preference by calculating the charge-transfer couplings in all 20 × 20 possible amino acid side-chain combinations, which are extracted from available high-quality structures of thousands of protein complexes. The charge-transfer database quantitatively shows distinct features of charge-transfer couplings among millions of amino acid side-chain combinations. The overall distribution of charge-transfer couplings reveals that only one average or representative structure cannot be regarded as the typical charge-transfer preference in realistic proteins. This work provides us an alternative route to comprehensively understand the charge-transfer couplings for the overall distribution of realistic proteins in the foreseen big data scenario. American Chemical Society 2018-04-11 /pmc/articles/PMC6641752/ /pubmed/31458645 http://dx.doi.org/10.1021/acsomega.8b00336 Text en Copyright © 2018 American Chemical Society This is an open access article published under a Creative Commons Attribution (CC-BY) License (http://pubs.acs.org/page/policy/authorchoice_ccby_termsofuse.html) , which permits unrestricted use, distribution and reproduction in any medium, provided the author and source are cited.
spellingShingle Wang, Hongwei
Liu, Fang
Dong, Tiange
Du, Likai
Zhang, Dongju
Gao, Jun
Charge-Transfer Knowledge Graph among Amino Acids Derived from High-Throughput Electronic Structure Calculations for Protein Database
title Charge-Transfer Knowledge Graph among Amino Acids Derived from High-Throughput Electronic Structure Calculations for Protein Database
title_full Charge-Transfer Knowledge Graph among Amino Acids Derived from High-Throughput Electronic Structure Calculations for Protein Database
title_fullStr Charge-Transfer Knowledge Graph among Amino Acids Derived from High-Throughput Electronic Structure Calculations for Protein Database
title_full_unstemmed Charge-Transfer Knowledge Graph among Amino Acids Derived from High-Throughput Electronic Structure Calculations for Protein Database
title_short Charge-Transfer Knowledge Graph among Amino Acids Derived from High-Throughput Electronic Structure Calculations for Protein Database
title_sort charge-transfer knowledge graph among amino acids derived from high-throughput electronic structure calculations for protein database
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6641752/
https://www.ncbi.nlm.nih.gov/pubmed/31458645
http://dx.doi.org/10.1021/acsomega.8b00336
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