Computational modeling of molecular structures guided by hydrogen-exchange data
Devaurs, Didier and Antunes, Dinler A. and Borysik, Antoni J. (2022) Computational modeling of molecular structures guided by hydrogen-exchange data. Journal of the American Society for Mass Spectrometry, 33 (2). pp. 215-237. ISSN 1044-0305 (https://doi.org/10.1021/jasms.1c00328)
Preview |
Text.
Filename: Devaurs-etal-JASMS-2022-Computational-modeling-of-molecular-structures.pdf
Final Published Version License: ![]() Download (6MB)| Preview |
Abstract
Data produced by hydrogen-exchange monitoring experiments have been used in structural studies of molecules for several decades. Despite uncertainties about the structural determinants of hydrogen exchange itself, such data have successfully helped guide the structural modeling of challenging molecular systems, such as membrane proteins or large macromolecular complexes. As hydrogen-exchange monitoring provides information on the dynamics of molecules in solution, it can complement other experimental techniques in so-called integrative modeling approaches. However, hydrogen-exchange data have often only been used to qualitatively assess molecular structures produced by computational modeling tools. In this paper, we look beyond qualitative approaches and survey the various paradigms under which hydrogen-exchange data have been used to quantitatively guide the computational modeling of molecular structures. Although numerous prediction models have been proposed to link molecular structure and hydrogen exchange, none of them has been widely accepted by the structural biology community. Here, we present as many hydrogen-exchange prediction models as we could find in the literature, with the aim of providing the first exhaustive list of its kind. From purely structure-based models to so-called fractional-population models or knowledge-based models, the field is quite vast. We aspire for this paper to become a resource for practitioners to gain a broader perspective on the field and guide research toward the definition of better prediction models. This will eventually improve synergies between hydrogen-exchange monitoring and molecular modeling.
-
-
Item type: Article ID code: 90231 Dates: DateEvent2 February 2022Published25 January 2022Published Online4 January 2022AcceptedSubjects:
Science > Chemistry
Science > Mathematics > Electronic computers. Computer scienceDepartment: Faculty of Science > Computer and Information Sciences Depositing user: Pure Administrator Date deposited: 13 Aug 2024 14:47 Last modified: 21 Aug 2024 14:17 URI: https://strathprints.strath.ac.uk/id/eprint/90231