Abstract
Knowledge of the atomic structure of biomolecules, such as proteins, is paramount to understanding their function and interactions in the human body. For example, knowledge of the atomic structure of a target protein is crucial for developing drugs that bind strongly to it and thus help cure diverse diseases.
Macromolecular crystallography is the forefront method for determining the atomic structure of proteins, especially through X-ray diffraction experiments. However, the data obtained from these experiments are not the atomic structure but need to be processed and interpreted before arriving at the individual positions of atoms in a protein. This intepretation is done through computational techniques that share some of the algorithms and problems with computational chemistry.
In this thesis, we use several methods that combine computational chemistry and macromolecular crystallography for the study of multiple important proteins. Crystallographic refinement combined with quantum mechanical calculations (quantum refinement) is used to improve the X-ray structures of three metalloenzymes. Furthermore, a quantum refinement procedure for neutron structures is developed and applied to two important enzymes. We also investigate how to use and improve the existing information on dynamics from crystallography experiments. To this end, we test whether conformational entropy can be calculated directly from B-factors. Additionally, ensemble refinement is used to explore ligand dynamics in the binding site of galectin-3 and reveals hidden conformations that were not apparent in traditional crystallographic refinement methods. Finally, we study the modeling of water molecules in protein X-ray and neutron crystal structures. We show that molecular dynamics simulations can reproduce crystal water molecules, if protein movements are correctly taken into account. Moreover, we have developed a method to automatically improve the orientation of water molecules in neutron structures.
Macromolecular crystallography is the forefront method for determining the atomic structure of proteins, especially through X-ray diffraction experiments. However, the data obtained from these experiments are not the atomic structure but need to be processed and interpreted before arriving at the individual positions of atoms in a protein. This intepretation is done through computational techniques that share some of the algorithms and problems with computational chemistry.
In this thesis, we use several methods that combine computational chemistry and macromolecular crystallography for the study of multiple important proteins. Crystallographic refinement combined with quantum mechanical calculations (quantum refinement) is used to improve the X-ray structures of three metalloenzymes. Furthermore, a quantum refinement procedure for neutron structures is developed and applied to two important enzymes. We also investigate how to use and improve the existing information on dynamics from crystallography experiments. To this end, we test whether conformational entropy can be calculated directly from B-factors. Additionally, ensemble refinement is used to explore ligand dynamics in the binding site of galectin-3 and reveals hidden conformations that were not apparent in traditional crystallographic refinement methods. Finally, we study the modeling of water molecules in protein X-ray and neutron crystal structures. We show that molecular dynamics simulations can reproduce crystal water molecules, if protein movements are correctly taken into account. Moreover, we have developed a method to automatically improve the orientation of water molecules in neutron structures.
| Original language | English |
|---|---|
| Qualification | Doctor |
| Supervisors/Advisors |
|
| Award date | 2019 Dec 6 |
| Publisher | |
| ISBN (Print) | 978-91-7422-702-4 |
| ISBN (electronic) | 978-91-7422-703-1 |
| Publication status | Published - 2019 |
Bibliographical note
Defence detailsDate: 2019-12-06
Time: 09:00
Place: Kemicentrum, Lecture Hall F, Naturvetarvägen 14, Lund
External reviewer(s)
Name: Murshudov, Garib
Title: Dr.
Affiliation: MRC Laboratory of Molecular Biology, Cambridge, UK
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UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Subject classification (UKÄ)
- Theoretical Chemistry (including Computational Chemistry)
Free keywords
- Protein structure, X-ray crystallography, Neutron crystallography, Quantum mechanics, QM/MM, Quantum refinement, Ensemble refinement, Water structure
Fingerprint
Dive into the research topics of 'Bridging the gap between computational chemistry and macromolecular crystallography'. Together they form a unique fingerprint.Research output
- 7 Article
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Exploring ligand dynamics in protein crystal structures with ensemble refinement
Caldararu, O., Ekberg, V., Logan, D. T., Oksanen, E. & Ryde, U., 2021, In: Acta Crystallographica Section D: Structural Biology. 77, p. 1099-1115 17 p.Research output: Contribution to journal › Article › peer-review
Open Access -
Water structure in solution and crystal molecular dynamics simulations compared to protein crystal structures
Caldararu, O., Misini Ignjatovic, M., Oksanen, E. & Ryde, U., 2020 Feb 18, In: RSC Advances. 10, p. 8435-8443Research output: Contribution to journal › Article › peer-review
Open AccessFile113 Downloads (Pure) -
Are crystallographic: B-factors suitable for calculating protein conformational entropy?
Caldararu, O., Kumar, R., Oksanen, E., Logan, D. T. & Ryde, U., 2019, In: Physical Chemistry Chemical Physics. 21, 33, p. 18149-18160 12 p.Research output: Contribution to journal › Article › peer-review
Open AccessFile136 Downloads (Pure)
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