Accurate Calculation of Barnase and SNase Folding Energetics Using Short Molecular Dynamics Simulations and an Atomistic Model of the Unfolded Ensemble: Evaluation of Force Fields and Water Models

Galano-Frutos, Juan José (Universidad de Zaragoza) ; Sancho, Javier (Universidad de Zaragoza)

Resumen: As proteins perform most cellular functions, quantitative understanding of protein energetics is required to gain control of biological phenomena. Accurate models of native proteins can be obtained experimentally, but the lack of equally fine models of unfolded ensembles impedes the calculation of protein folding energetics from first principles. Here, we show that an atomistic unfolded ensemble model, consisting of a few dozen conformations built from a protein sequence, can be used in conjunction with an X-ray structure of its native state to calculate accurately by difference the changes in enthalpy and heat capacity of the polypeptide upon folding. The calculation is done using molecular dynamics simulations, popular force fields, and water models, and for the two model proteins studied (barnase and SNase), the results agree within error or are very close to their experimentally determined properties. The enthalpy sampling of the unfolded ensemble is done through short 2 ns simulations that do not significantly modify the representative distribution of Rg of the starting conformations. The impressive accuracy obtained opens the possibility to investigate quantitatively systems or phenomena not amenable to experiment and paves the way for addressing the calculation of protein conformational stability (i.e., the change in Gibbs energy upon folding), a central goal of structural biology. So far, these calculated enthalpy and heat capacity changes, combined with the experimentally determined melting temperatures of the corresponding protein, allow us to reproduce the stability curves of both barnase and SNase.

Idioma: Inglés

DOI: 10.1021/acs.jcim.9b00430

Año: 2019

Publicado en: Journal of Chemical Information and Modeling (2019), [11 pp]
ISSN: 1549-9596

Factor impacto JCR: 4.549 (2019)

Categ. JCR: CHEMISTRY, MEDICINAL rank: 11 / 61 = 0.18 (2019) - Q1 - T1
Categ. JCR: COMPUTER SCIENCE, INFORMATION SYSTEMS rank: 28 / 155 = 0.181 (2019) - Q1 - T1
Categ. JCR: COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS rank: 17 / 109 = 0.156 (2019) - Q1 - T1
Categ. JCR: CHEMISTRY, MULTIDISCIPLINARY rank: 49 / 176 = 0.278 (2019) - Q2 - T1

Factor impacto SCIMAGO: 1.329 - Chemical Engineering (miscellaneous) (Q1) - Library and Information Sciences (Q1) - Computer Science Applications (Q1) - Chemistry (miscellaneous) (Q1)

Financiación: info:eu-repo/grantAgreement/ES/MINECO/BFU2016-78232-P

Tipo y forma: Article (PostPrint)

Área (Departamento): Área Bioquímica y Biolog.Mole. (Dpto. Bioq.Biolog.Mol. Celular)