4.5 Article

Computational Modeling of Molecular Structures Guided by Hydrogen-Exchange Data

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AMER CHEMICAL SOC
DOI: 10.1021/jasms.1c00328

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  1. University of Edinburgh and Medical Research Council [MC_UU_00009/2]
  2. Biotechnology and Biological Sciences Research Council [BB/R006792/1]

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Despite being used for several decades in structural studies of molecules, hydrogen-exchange monitoring data are often only qualitatively assessed in computational modeling. Various paradigms and prediction models have been proposed to link molecular structure and hydrogen exchange, but none have been widely accepted by the structural biology community. This paper aims to provide an exhaustive list of these models and hopes to guide research towards the development of better prediction models for improving synergies between hydrogen-exchange monitoring and molecular modeling.
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 macro molecular 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.

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