Cargando…

Identifying medically relevant xenon protein targets by in silico screening of the structural proteome

In a previous study, in silico screening of the binding of almost all proteins in the Protein Data Bank to each of the five noble gases xenon, krypton, argon, neon, and helium was reported. This massive and rich data set requires analysis to identify the gas-protein interactions that have the best b...

Descripción completa

Detalles Bibliográficos
Autores principales: Winkler, David A., Katz, Ira, Warden, Andrew, Thornton, Aaron W., Farjot, Géraldine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Wolters Kluwer - Medknow 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9480358/
https://www.ncbi.nlm.nih.gov/pubmed/35946221
http://dx.doi.org/10.4103/2045-9912.333858
_version_ 1784791036249243648
author Winkler, David A.
Katz, Ira
Warden, Andrew
Thornton, Aaron W.
Farjot, Géraldine
author_facet Winkler, David A.
Katz, Ira
Warden, Andrew
Thornton, Aaron W.
Farjot, Géraldine
author_sort Winkler, David A.
collection PubMed
description In a previous study, in silico screening of the binding of almost all proteins in the Protein Data Bank to each of the five noble gases xenon, krypton, argon, neon, and helium was reported. This massive and rich data set requires analysis to identify the gas-protein interactions that have the best binding strengths, those where the binding of the noble gas occurs at a site that can modulate the function of the protein, and where this modulation might generate clinically relevant effects. Here, we report a preliminary analysis of this data set using a rational, heuristic score based on binding strength and location. We report a partial prioritized list of xenon protein targets and describe how these data can be analyzed, using arginase and carbonic anhydrase as examples. Our aim is to make the scientific community aware of this massive, rich data set and how it can be analyzed to accelerate future discoveries of xenon-induced biological activity and, ultimately, the development of new “atomic” drugs.
format Online
Article
Text
id pubmed-9480358
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Wolters Kluwer - Medknow
record_format MEDLINE/PubMed
spelling pubmed-94803582022-09-17 Identifying medically relevant xenon protein targets by in silico screening of the structural proteome Winkler, David A. Katz, Ira Warden, Andrew Thornton, Aaron W. Farjot, Géraldine Med Gas Res Research Article In a previous study, in silico screening of the binding of almost all proteins in the Protein Data Bank to each of the five noble gases xenon, krypton, argon, neon, and helium was reported. This massive and rich data set requires analysis to identify the gas-protein interactions that have the best binding strengths, those where the binding of the noble gas occurs at a site that can modulate the function of the protein, and where this modulation might generate clinically relevant effects. Here, we report a preliminary analysis of this data set using a rational, heuristic score based on binding strength and location. We report a partial prioritized list of xenon protein targets and describe how these data can be analyzed, using arginase and carbonic anhydrase as examples. Our aim is to make the scientific community aware of this massive, rich data set and how it can be analyzed to accelerate future discoveries of xenon-induced biological activity and, ultimately, the development of new “atomic” drugs. Wolters Kluwer - Medknow 2022-08-04 /pmc/articles/PMC9480358/ /pubmed/35946221 http://dx.doi.org/10.4103/2045-9912.333858 Text en Copyright: © 2023 Medical Gas Research https://creativecommons.org/licenses/by-nc-sa/4.0/This is an open access journal, and articles are distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 4.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as appropriate credit is given and the new creations are licensed under the identical terms.
spellingShingle Research Article
Winkler, David A.
Katz, Ira
Warden, Andrew
Thornton, Aaron W.
Farjot, Géraldine
Identifying medically relevant xenon protein targets by in silico screening of the structural proteome
title Identifying medically relevant xenon protein targets by in silico screening of the structural proteome
title_full Identifying medically relevant xenon protein targets by in silico screening of the structural proteome
title_fullStr Identifying medically relevant xenon protein targets by in silico screening of the structural proteome
title_full_unstemmed Identifying medically relevant xenon protein targets by in silico screening of the structural proteome
title_short Identifying medically relevant xenon protein targets by in silico screening of the structural proteome
title_sort identifying medically relevant xenon protein targets by in silico screening of the structural proteome
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9480358/
https://www.ncbi.nlm.nih.gov/pubmed/35946221
http://dx.doi.org/10.4103/2045-9912.333858
work_keys_str_mv AT winklerdavida identifyingmedicallyrelevantxenonproteintargetsbyinsilicoscreeningofthestructuralproteome
AT katzira identifyingmedicallyrelevantxenonproteintargetsbyinsilicoscreeningofthestructuralproteome
AT wardenandrew identifyingmedicallyrelevantxenonproteintargetsbyinsilicoscreeningofthestructuralproteome
AT thorntonaaronw identifyingmedicallyrelevantxenonproteintargetsbyinsilicoscreeningofthestructuralproteome
AT farjotgeraldine identifyingmedicallyrelevantxenonproteintargetsbyinsilicoscreeningofthestructuralproteome