Validation of DBFOLD: An efficient algorithm for computing folding pathways of complex proteins.

Atomistic simulations can provide valuable, experimentally-verifiable insights into protein folding mechanisms, but existing ab initio simulation methods are restricted to only the smallest proteins due to severe computational speed limits. The folding of larger proteins has been studied using nativ...

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Autores principales:	Amir Bitran, William M Jacobs, Eugene Shakhnovich
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2020
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/79d3cb9b47984e72b76d137ec0dbec12
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spelling	oai:doaj.org-article:79d3cb9b47984e72b76d137ec0dbec122021-12-02T19:57:35ZValidation of DBFOLD: An efficient algorithm for computing folding pathways of complex proteins.1553-734X1553-735810.1371/journal.pcbi.1008323https://doaj.org/article/79d3cb9b47984e72b76d137ec0dbec122020-11-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1008323https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Atomistic simulations can provide valuable, experimentally-verifiable insights into protein folding mechanisms, but existing ab initio simulation methods are restricted to only the smallest proteins due to severe computational speed limits. The folding of larger proteins has been studied using native-centric potential functions, but such models omit the potentially crucial role of non-native interactions. Here, we present an algorithm, entitled DBFOLD, which can predict folding pathways for a wide range of proteins while accounting for the effects of non-native contacts. In addition, DBFOLD can predict the relative rates of different transitions within a protein's folding pathway. To accomplish this, rather than directly simulating folding, our method combines equilibrium Monte-Carlo simulations, which deploy enhanced sampling, with unfolding simulations at high temperatures. We show that under certain conditions, trajectories from these two types of simulations can be jointly analyzed to compute unknown folding rates from detailed balance. This requires inferring free energies from the equilibrium simulations, and extrapolating transition rates from the unfolding simulations to lower, physiologically-reasonable temperatures at which the native state is marginally stable. As a proof of principle, we show that our method can accurately predict folding pathways and Monte-Carlo rates for the well-characterized Streptococcal protein G. We then show that our method significantly reduces the amount of computation time required to compute the folding pathways of large, misfolding-prone proteins that lie beyond the reach of existing direct simulation. Our algorithm, which is available online, can generate detailed atomistic models of protein folding mechanisms while shedding light on the role of non-native intermediates which may crucially affect organismal fitness and are frequently implicated in disease.Amir BitranWilliam M JacobsEugene ShakhnovichPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 16, Iss 11, p e1008323 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Amir Bitran William M Jacobs Eugene Shakhnovich Validation of DBFOLD: An efficient algorithm for computing folding pathways of complex proteins.
description	Atomistic simulations can provide valuable, experimentally-verifiable insights into protein folding mechanisms, but existing ab initio simulation methods are restricted to only the smallest proteins due to severe computational speed limits. The folding of larger proteins has been studied using native-centric potential functions, but such models omit the potentially crucial role of non-native interactions. Here, we present an algorithm, entitled DBFOLD, which can predict folding pathways for a wide range of proteins while accounting for the effects of non-native contacts. In addition, DBFOLD can predict the relative rates of different transitions within a protein's folding pathway. To accomplish this, rather than directly simulating folding, our method combines equilibrium Monte-Carlo simulations, which deploy enhanced sampling, with unfolding simulations at high temperatures. We show that under certain conditions, trajectories from these two types of simulations can be jointly analyzed to compute unknown folding rates from detailed balance. This requires inferring free energies from the equilibrium simulations, and extrapolating transition rates from the unfolding simulations to lower, physiologically-reasonable temperatures at which the native state is marginally stable. As a proof of principle, we show that our method can accurately predict folding pathways and Monte-Carlo rates for the well-characterized Streptococcal protein G. We then show that our method significantly reduces the amount of computation time required to compute the folding pathways of large, misfolding-prone proteins that lie beyond the reach of existing direct simulation. Our algorithm, which is available online, can generate detailed atomistic models of protein folding mechanisms while shedding light on the role of non-native intermediates which may crucially affect organismal fitness and are frequently implicated in disease.
format	article
author	Amir Bitran William M Jacobs Eugene Shakhnovich
author_facet	Amir Bitran William M Jacobs Eugene Shakhnovich
author_sort	Amir Bitran
title	Validation of DBFOLD: An efficient algorithm for computing folding pathways of complex proteins.
title_short	Validation of DBFOLD: An efficient algorithm for computing folding pathways of complex proteins.
title_full	Validation of DBFOLD: An efficient algorithm for computing folding pathways of complex proteins.
title_fullStr	Validation of DBFOLD: An efficient algorithm for computing folding pathways of complex proteins.
title_full_unstemmed	Validation of DBFOLD: An efficient algorithm for computing folding pathways of complex proteins.
title_sort	validation of dbfold: an efficient algorithm for computing folding pathways of complex proteins.
publisher	Public Library of Science (PLoS)
publishDate	2020
url	https://doaj.org/article/79d3cb9b47984e72b76d137ec0dbec12
work_keys_str_mv	AT amirbitran validationofdbfoldanefficientalgorithmforcomputingfoldingpathwaysofcomplexproteins AT williammjacobs validationofdbfoldanefficientalgorithmforcomputingfoldingpathwaysofcomplexproteins AT eugeneshakhnovich validationofdbfoldanefficientalgorithmforcomputingfoldingpathwaysofcomplexproteins
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Validation of DBFOLD: An efficient algorithm for computing folding pathways of complex proteins.

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