Integrating Hydrogen Exchange with Molecular Dynamics for Improved Ligand Binding Predictions
Year: 2025
Type: article
Abstract: We introduce Hydrogen-Exchange Experimental Structure Prediction (HX-ESP), a method that integrates hydrogen exchange (HX) data with molecular dynamics (MD) simulations to accurately predict ligand binding modes, even for targets requiring significant conformational changes. Benchmarking HX-ESP by fitting two ligands to PAK1 and four ligands to MAP4K1 (HPK1), and comparing the results to X-ray crystallography structures, demonstrated that HX-ESP successfully identified binding modes across a range of affinities significantly outperforming flexible docking for ligands necessitating large conformational adjustments. By objectively guiding simulations with experimental HX data, HX-ESP overcomes the long timescales required for binding predictions using traditional MD. This advancement promises to enhance the accuracy of computational modeling in drug discovery, potentially accelerating the development of effective therapeutics.
Institution: Genentech
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,500
Funders: U.S. Department of Energy, Roche, Georgia Research Alliance, Salt Science Research Foundation, National Institutes of Health, Genentech, Office of Science, National Institute of General Medical Sciences, Basic Energy Sciences, Biological and Environmental Research, Argonne National Laboratory
Awards: G102163711, G107546177, G1286236842, G1286251239, G1313983767, G1337544421, G1633006425, G1664757510, G1800737955, G1911902306, Phase II SER-CAT Optimization: Acquisition of a next generation area detector, G223002938, G2287611682, G262962599, G2638771445, G2857925935, G30714459, G3075337988, G3083819904, G3338542329, Acquisition of a High Precision Micro Diffractometer to Support NIH funded Research at SER-CAT, G419881185, G426311843, G42916606, G434509735, G4501827968, G498139845, G5387317844, G5921955326, G650090426, G6800544485, G6848031779, G6918803902, G7583137537, G760289873, G7787287669, G7932540327, G8229677252, G8868651796, ALS Efficiently Networking Advanced Beam Line Experiments (ALS-ENABLE), G969889393, G993149817
OpenAlex ID: W4411216764