Interpreting Hydrogen-Deuterium Exchange Experiments with Molecular Simulations: Tutorials and Applications of the HDXer Ensemble Reweighting Software [Article v1.0].
Paul Suhwan LeeRichard T BradshawFabrizio MarinelliKyle C KihnAlly K SmithPatrick L WintrodeDaniel J DeredgeJosé D Faraldo-GómezLucy R ForrestPublished in: Living journal of computational molecular science (2022)
Hydrogen-deuterium exchange (HDX) is a comprehensive yet detailed probe of protein structure and dynamics and, coupled to mass spectrometry, has become a powerful tool for investigating an increasingly large array of systems. Computer simulations are often used to help rationalize experimental observations of exchange, but interpretations have frequently been limited to simple, subjective correlations between microscopic dynamical fluctuations and the observed macroscopic exchange behavior. With this in mind, we previously developed the HDX ensemble reweighting approach and associated software, HDXer, to aid the objective interpretation of HDX data using molecular simulations. HDXer has two main functions; first, to compute H-D exchange rates that describe each structure in a candidate ensemble of protein structures, for example from molecular simulations, and second, to objectively reweight the conformational populations present in a candidate ensemble to conform to experimental exchange data. In this article, we first describe the HDXer approach, theory, and implementation. We then guide users through a suite of tutorials that demonstrate the practical aspects of preparing experimental data, computing HDX levels from molecular simulations, and performing ensemble reweighting analyses. Finally we provide a practical discussion of the capabilities and limitations of the HDXer methods including recommendations for a user's own analyses. Overall, this article is intended to provide an up-to-date, pedagogical counterpart to the software, which is freely available at https://github.com/Lucy-Forrest-Lab/HDXer.
Keyphrases
- molecular dynamics
- monte carlo
- convolutional neural network
- mass spectrometry
- data analysis
- electronic health record
- single molecule
- high resolution
- neural network
- healthcare
- big data
- primary care
- physical activity
- deep learning
- binding protein
- liquid chromatography
- amino acid
- protein protein
- clinical practice
- capillary electrophoresis
- artificial intelligence
- high throughput
- living cells
- tandem mass spectrometry