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Prediction of Ordered Water Molecules in Protein Binding Sites from Molecular Dynamics Simulations: The Impact of Ligand Binding on Hydration Networks
Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, SE-10691 Stockholm, Sweden..
Stockholm Univ, Dept Biochem & Biophys, Sci Life Lab, SE-10691 Stockholm, Sweden..
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Science and Technology, Biology, Department of Cell and Molecular Biology, Computational Biology and Bioinformatics.ORCID iD: 0000-0003-4623-2977
2018 (English)In: Journal of Chemical Information and Modeling, ISSN 1549-9596, E-ISSN 1549-960X, Vol. 58, no 2, p. 350-361Article in journal (Refereed) Published
Abstract [en]

Water plays a major role in ligand binding and is attracting increasing attention in structure-based drug design. Water molecules can make large contributions to binding affinity by bridging protein-ligand interactions or by being displaced upon complex formation, but these phenomena are challenging to model at the molecular level. Herein, networks of ordered water molecules in protein binding sites were analyzed by clustering of molecular dynamics (MD) simulation trajectories. Locations of ordered waters (hydration sites) were first identified from simulations of high resolution crystal structures of 13 protein-ligand complexes. The MD-derived hydration sites reproduced 73% of the binding site water molecules observed in the crystal structures. If the simulations were repeated without the cocrystallized ligands, a majority (58%) of the crystal waters in the binding sites were still predicted. In addition, comparison of the hydration sites obtained from simulations carried out in the absence of ligands to those identified for the complexes revealed that the networks of ordered water molecules were preserved to a large extent, suggesting that the locations of waters in a protein-ligand interface are mainly dictated by the protein. Analysis of >1000 crystal structures showed that hydration sites bridged protein-ligand interactions in complexes with different ligands, and those with high MD-derived occupancies were more likely to correspond to experimentally observed ordered water molecules. The results demonstrate that ordered water molecules relevant for modeling of protein-ligand complexes can be identified from MD simulations. Our findings could contribute to development of improved methods for structure-based virtual screening and lead optimization.

Place, publisher, year, edition, pages
2018. Vol. 58, no 2, p. 350-361
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Computer Sciences Chemical Sciences
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URN: urn:nbn:se:uu:diva-350543DOI: 10.1021/acs.jcim.7b00520ISI: 000426613800016PubMedID: 29308882OAI: oai:DiVA.org:uu-350543DiVA, id: diva2:1209084
Available from: 2018-05-21 Created: 2018-05-21 Last updated: 2018-05-21Bibliographically approved

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Carlsson, Jens

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