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Fragment optimization for GPCRs by molecular dynamics free energy calculations: Probing druggable subpockets of the A(2A) adenosine receptor binding site
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics. Stockholm University, Science for Life Laboratory (SciLifeLab).
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Number of Authors: 122017 (English)In: Scientific Reports, ISSN 2045-2322, E-ISSN 2045-2322, Vol. 7, article id 6398Article in journal (Refereed) Published
Abstract [en]

Fragment-based lead discovery is becoming an increasingly popular strategy for drug discovery. Fragment screening identifies weakly binding compounds that require optimization to become high-affinity leads. As design of leads from fragments is challenging, reliable computational methods to guide optimization would be invaluable. We evaluated using molecular dynamics simulations and the free energy perturbation method (MD/FEP) in fragment optimization for the A(2A) adenosine receptor, a pharmaceutically relevant G protein-coupled receptor. Optimization of fragments exploring two binding site subpockets was probed by calculating relative binding affinities for 23 adenine derivatives, resulting in strong agreement with experimental data (R-2 = 0.78). The predictive power of MD/FEP was significantly better than that of an empirical scoring function. We also demonstrated the potential of the MD/FEP to assess multiple binding modes and to tailor the thermodynamic profile of ligands during optimization. Finally, MD/FEP was applied prospectively to optimize three nonpurine fragments, and predictions for 12 compounds were evaluated experimentally. The direction of the change in binding affinity was correctly predicted in a majority of the cases, and agreement with experiment could be improved with rigorous parameter derivation. The results suggest that MD/FEP will become a powerful tool in structure-driven optimization of fragments to lead candidates.

Place, publisher, year, edition, pages
2017. Vol. 7, article id 6398
National Category
Biological Sciences Chemical Sciences
Research subject
Biochemistry towards Bioinformatics
Identifiers
URN: urn:nbn:se:su:diva-145886DOI: 10.1038/s41598-017-04905-0ISI: 000406279200005OAI: oai:DiVA.org:su-145886DiVA, id: diva2:1135057
Available from: 2017-08-22 Created: 2017-08-22 Last updated: 2018-04-10Bibliographically 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 and 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)
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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: 2018-05-03Bibliographically approved

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