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Comparison of Charge Derivation Methods Applied to Amino Acid Parameterization
[Image: see text] When using non-natural amino acids in computational simulations of proteins, it is necessary to ensure appropriate parameterization of the new amino acids toward the creation of appropriate input files. In particular, the charges on the atoms may have to be derived de novo and ad h...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6641686/ https://www.ncbi.nlm.nih.gov/pubmed/31458687 http://dx.doi.org/10.1021/acsomega.8b00438 |
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author | Aronica, Pietro G. A. Fox, Stephen J. Verma, Chandra S. |
author_facet | Aronica, Pietro G. A. Fox, Stephen J. Verma, Chandra S. |
author_sort | Aronica, Pietro G. A. |
collection | PubMed |
description | [Image: see text] When using non-natural amino acids in computational simulations of proteins, it is necessary to ensure appropriate parameterization of the new amino acids toward the creation of appropriate input files. In particular, the charges on the atoms may have to be derived de novo and ad hoc for the new species. As there are many variables in the charge derivation process, an investigation was devised to compare different approaches and determine their effect on simulations. This was done with the purpose to identify the methods which produced results compatible with the existing parameters. It was found in this study that all analyzed charge derivation methods reproduce with sufficient accuracy the literature values and can be used with confidence when parameterizing novel species. |
format | Online Article Text |
id | pubmed-6641686 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-66416862019-08-27 Comparison of Charge Derivation Methods Applied to Amino Acid Parameterization Aronica, Pietro G. A. Fox, Stephen J. Verma, Chandra S. ACS Omega [Image: see text] When using non-natural amino acids in computational simulations of proteins, it is necessary to ensure appropriate parameterization of the new amino acids toward the creation of appropriate input files. In particular, the charges on the atoms may have to be derived de novo and ad hoc for the new species. As there are many variables in the charge derivation process, an investigation was devised to compare different approaches and determine their effect on simulations. This was done with the purpose to identify the methods which produced results compatible with the existing parameters. It was found in this study that all analyzed charge derivation methods reproduce with sufficient accuracy the literature values and can be used with confidence when parameterizing novel species. American Chemical Society 2018-04-27 /pmc/articles/PMC6641686/ /pubmed/31458687 http://dx.doi.org/10.1021/acsomega.8b00438 Text en Copyright © 2018 American Chemical Society This is an open access article published under an ACS AuthorChoice License (http://pubs.acs.org/page/policy/authorchoice_termsofuse.html) , which permits copying and redistribution of the article or any adaptations for non-commercial purposes. |
spellingShingle | Aronica, Pietro G. A. Fox, Stephen J. Verma, Chandra S. Comparison of Charge Derivation Methods Applied to Amino Acid Parameterization |
title | Comparison of Charge Derivation Methods Applied to
Amino Acid Parameterization |
title_full | Comparison of Charge Derivation Methods Applied to
Amino Acid Parameterization |
title_fullStr | Comparison of Charge Derivation Methods Applied to
Amino Acid Parameterization |
title_full_unstemmed | Comparison of Charge Derivation Methods Applied to
Amino Acid Parameterization |
title_short | Comparison of Charge Derivation Methods Applied to
Amino Acid Parameterization |
title_sort | comparison of charge derivation methods applied to
amino acid parameterization |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6641686/ https://www.ncbi.nlm.nih.gov/pubmed/31458687 http://dx.doi.org/10.1021/acsomega.8b00438 |
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