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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 University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
Number of Authors: 32018 (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
National Category
Biological Sciences Chemical Sciences
Research subject
Biochemistry towards Bioinformatics
Identifiers
URN: urn:nbn:se:su:diva-154606DOI: 10.1021/acs.jcim.7b00520ISI: 000426613800016PubMedID: 29308882OAI: oai:DiVA.org:su-154606DiVA, id: diva2:1195064
Available from: 2018-04-04 Created: 2018-04-04 Last updated: 2022-02-26Bibliographically approved
In thesis
1. Development and Application of Molecular Modeling Methods for Structure-Based Drug Discovery
Open this publication in new window or tab >>Development and Application of Molecular Modeling Methods for Structure-Based Drug Discovery
2018 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Molecular modeling is increasingly being integrated into the drug discovery process. Although computational methods are already an essential part of the process today, these techniques have vast potential to evolve and refine drug design in the future. The integration of modeling is further catalyzed by the rapidly growing computational power available to both academia and pharmaceutical companies. These resources extend the reach of the computational methods to new time scales in physics-based simulations of biomolecular systems and increase the number of molecules that is possible to dock to a receptor by several orders of magnitude. However, there is also a need for further development of methods that utilize the increased computational power to increase the level of detail in modeling of molecular interactions. The work presented in this thesis has contributed to method development in two different areas and demonstrated how virtual screening can be applied to identify ligands of proteins. The first main project investigated modeling of ordered water molecules in protein binding sites to understand the role of water in molecular recognition and the impact of ligands on hydration networks. In a second project, an approach for discovery and optimization of fragment-sized ligands based on virtual screening was developed and used to identify inhibitors of a cancer drug target. Finally, molecular docking was applied to assess proposed substrates of cytochrome b561, a recently crystallized membrane protein.

Place, publisher, year, edition, pages
Stockholm: Department of Biochemistry and Biophysics, Stockholm University, 2018. p. 56
National Category
Biochemistry Molecular Biology Bioinformatics (Computational Biology)
Research subject
Biochemistry towards Bioinformatics
Identifiers
urn:nbn:se:su:diva-154977 (URN)978-91-7797-226-6 (ISBN)978-91-7797-227-3 (ISBN)
Public defence
2018-05-25, Magnélisalen, Kemiska övningslaboratoriet, Svante Arrhenius väg 16 B, Stockholm, 13:00 (English)
Opponent
Supervisors
Note

At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 4: In press.

Available from: 2018-05-02 Created: 2018-04-09 Last updated: 2025-02-20Bibliographically approved

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Rudling, AxelCarlsson, Jens

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