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Local Disordered Region Sampling (LDRS) for Ensemble Modeling of Proteins with Experimentally Undetermined or Low Confidence Prediction Segments

The Local Disordered Region Sampling (LDRS, pronounced loaders) tool, developed for the IDPConformerGenerator platform (Teixeira et al. 2022), provides a method for generating all-atom conformations of intrinsically disordered regions (IDRs) at N- and C-termini of and in loops or linkers between fol...

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Autores principales: Liu, Zi Hao, Teixeira, João M.C., Zhang, Oufan, Tsangaris, Thomas E., Li, Jie, Gradinaru, Claudiu C., Head-Gordon, Teresa, Forman-Kay, Julie D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cold Spring Harbor Laboratory 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10402175/
https://www.ncbi.nlm.nih.gov/pubmed/37546943
http://dx.doi.org/10.1101/2023.07.25.550520
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author Liu, Zi Hao
Teixeira, João M.C.
Zhang, Oufan
Tsangaris, Thomas E.
Li, Jie
Gradinaru, Claudiu C.
Head-Gordon, Teresa
Forman-Kay, Julie D.
author_facet Liu, Zi Hao
Teixeira, João M.C.
Zhang, Oufan
Tsangaris, Thomas E.
Li, Jie
Gradinaru, Claudiu C.
Head-Gordon, Teresa
Forman-Kay, Julie D.
author_sort Liu, Zi Hao
collection PubMed
description The Local Disordered Region Sampling (LDRS, pronounced loaders) tool, developed for the IDPConformerGenerator platform (Teixeira et al. 2022), provides a method for generating all-atom conformations of intrinsically disordered regions (IDRs) at N- and C-termini of and in loops or linkers between folded regions of an existing protein structure. These disordered elements often lead to missing coordinates in experimental structures or low confidence in predicted structures. Requiring only a pre-existing PDB structure of the protein with missing coordinates or with predicted confidence scores and its full-length primary sequence, LDRS will automatically generate physically meaningful conformational ensembles of the missing flexible regions to complete the full-length protein. The capabilities of the LDRS tool of IDPConformerGenerator include modeling phosphorylation sites using enhanced Monte Carlo Side Chain Entropy (MC-SCE) (Bhowmick and Head-Gordon 2015), transmembrane proteins within an all-atom bilayer, and multi-chain complexes. The modeling capacity of LDRS capitalizes on the modularity, ability to be used as a library and via command-line, and computational speed of the IDPConformerGenerator platform.
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spelling pubmed-104021752023-08-05 Local Disordered Region Sampling (LDRS) for Ensemble Modeling of Proteins with Experimentally Undetermined or Low Confidence Prediction Segments Liu, Zi Hao Teixeira, João M.C. Zhang, Oufan Tsangaris, Thomas E. Li, Jie Gradinaru, Claudiu C. Head-Gordon, Teresa Forman-Kay, Julie D. bioRxiv Article The Local Disordered Region Sampling (LDRS, pronounced loaders) tool, developed for the IDPConformerGenerator platform (Teixeira et al. 2022), provides a method for generating all-atom conformations of intrinsically disordered regions (IDRs) at N- and C-termini of and in loops or linkers between folded regions of an existing protein structure. These disordered elements often lead to missing coordinates in experimental structures or low confidence in predicted structures. Requiring only a pre-existing PDB structure of the protein with missing coordinates or with predicted confidence scores and its full-length primary sequence, LDRS will automatically generate physically meaningful conformational ensembles of the missing flexible regions to complete the full-length protein. The capabilities of the LDRS tool of IDPConformerGenerator include modeling phosphorylation sites using enhanced Monte Carlo Side Chain Entropy (MC-SCE) (Bhowmick and Head-Gordon 2015), transmembrane proteins within an all-atom bilayer, and multi-chain complexes. The modeling capacity of LDRS capitalizes on the modularity, ability to be used as a library and via command-line, and computational speed of the IDPConformerGenerator platform. Cold Spring Harbor Laboratory 2023-07-27 /pmc/articles/PMC10402175/ /pubmed/37546943 http://dx.doi.org/10.1101/2023.07.25.550520 Text en https://creativecommons.org/licenses/by-nc/4.0/This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (https://creativecommons.org/licenses/by-nc/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format for noncommercial purposes only, and only so long as attribution is given to the creator.
spellingShingle Article
Liu, Zi Hao
Teixeira, João M.C.
Zhang, Oufan
Tsangaris, Thomas E.
Li, Jie
Gradinaru, Claudiu C.
Head-Gordon, Teresa
Forman-Kay, Julie D.
Local Disordered Region Sampling (LDRS) for Ensemble Modeling of Proteins with Experimentally Undetermined or Low Confidence Prediction Segments
title Local Disordered Region Sampling (LDRS) for Ensemble Modeling of Proteins with Experimentally Undetermined or Low Confidence Prediction Segments
title_full Local Disordered Region Sampling (LDRS) for Ensemble Modeling of Proteins with Experimentally Undetermined or Low Confidence Prediction Segments
title_fullStr Local Disordered Region Sampling (LDRS) for Ensemble Modeling of Proteins with Experimentally Undetermined or Low Confidence Prediction Segments
title_full_unstemmed Local Disordered Region Sampling (LDRS) for Ensemble Modeling of Proteins with Experimentally Undetermined or Low Confidence Prediction Segments
title_short Local Disordered Region Sampling (LDRS) for Ensemble Modeling of Proteins with Experimentally Undetermined or Low Confidence Prediction Segments
title_sort local disordered region sampling (ldrs) for ensemble modeling of proteins with experimentally undetermined or low confidence prediction segments
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10402175/
https://www.ncbi.nlm.nih.gov/pubmed/37546943
http://dx.doi.org/10.1101/2023.07.25.550520
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