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Implementation of the CHARMM Force Field in GROMACS: Analysis of Protein Stability Effects from Correction Maps, Virtual Interaction Sites, and Water Models
Theoretical and Computational Biophysics, Department of Theoretical Physics, Royal Institute of Technology. (Erik Lindahl)
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
Swiss Institute of Bioinformatics.
Stockholm University, Faculty of Science, Department of Biochemistry and Biophysics.
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2010 (English)In: Journal of Chemical Theory and Computation, ISSN 1549-9618, E-ISSN 1549-9626, Vol. 6, no 2, 459-466 p.Article in journal (Refereed) Published
Abstract [en]

CHARMM27 is a widespread and popular force field for biomolecular simulation, and several recent algorithms such as implicit solvent models have been developed specifically for it. We have here implemented the CHARMM force field and all necessary extended functional forms in the GROMACS molecular simulation package, to make CHARMM-specific features available and to test them in combination with techniques for extended time steps, to make all major force fields available for comparison studies in GROMACS, and to test various solvent model optimizations, in particular the effect of Lennard-Jones interactions on hydrogens. The implementation has full support both for CHARMM-specific features such as multiple potentials over the same dihedral angle and the grid-based energy correction map on the , ψ protein backbone dihedrals, as well as all GROMACS features such as virtual hydrogen interaction sites that enable 5 fs time steps. The medium-to-long time effects of both the correction maps and virtual sites have been tested by performing a series of 100 ns simulations using different models for water representation, including comparisons between CHARMM and traditional TIP3P. Including the correction maps improves sampling of near native-state conformations in our systems, and to some extent it is even able to refine distorted protein conformations. Finally, we show that this accuracy is largely maintained with a new implicit solvent implementation that works with virtual interaction sites, which enables performance in excess of 250 ns/day for a 900-atom protein on a quad-core desktop computer.

Place, publisher, year, edition, pages
Washington: American Chemical Society , 2010. Vol. 6, no 2, 459-466 p.
National Category
Chemical Sciences
Identifiers
URN: urn:nbn:se:su:diva-38245DOI: 10.1021/ct900549rISI: 000274838800012OAI: oai:DiVA.org:su-38245DiVA: diva2:308381
Available from: 2010-04-06 Created: 2010-04-06 Last updated: 2017-12-12Bibliographically approved
In thesis
1. Prediction, modeling, and refinement of protein structure
Open this publication in new window or tab >>Prediction, modeling, and refinement of protein structure
2010 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Accurate predictions of protein structure are important for understanding many processes in cells. The interactions that govern protein folding and structure are complex, and still far from completely understood. However, progress is being made in many areas. Here, efforts to improve the overall quality of protein structure models are described. From a pure evolutionary perspective, in which proteins are viewed in the light of gradually accumulated mutations on the sequence level, it is shown how information from multiple sources helps to create more accurate models. A very simple but surprisingly accurate method for assigning confidence measures for protein structures is also tested. In contrast to models based on evolution, physics based methods view protein structures as the result of physical interactions between atoms. Newly implemented methods are described that both increase the time-scales accessible for molecular dynamics simulations almost 10-fold, and that to some extent might be able to refine protein structures. Finally, I compare the efficiency and properties of different techniques for protein structure refinement.

Place, publisher, year, edition, pages
Stockholm: Department of Biochemistry and Biophysics, Stockholm University, 2010. 64 p.
Keyword
Protein structure prediction, Multiple alignments, Quality assessment, Molecular dynamics, Implicit solvent, Refinement
National Category
Bioinformatics and Systems Biology Bioinformatics (Computational Biology) Theoretical Chemistry
Research subject
Biochemistry
Identifiers
urn:nbn:se:su:diva-38253 (URN)978-91-7447-036-9 (ISBN)
Public defence
2010-05-12, Magnélisalen, Kemiska övningslaboratoriet, Svante Arrhenius väg 16 B, Stockholm, 10:00 (English)
Opponent
Supervisors
Note
At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 4: In press. Paper 5: Manuscript. Available from: 2010-04-20 Created: 2010-04-06 Last updated: 2010-04-09Bibliographically approved
2. Modeling of voltage-gated ion channels
Open this publication in new window or tab >>Modeling of voltage-gated ion channels
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The recent determination of several crystal structures of voltage-gated ion channels has catalyzed computational efforts of studying these remarkable molecular machines that are able to conduct ions across biological membranes at extremely high rates without compromising the ion selectivity.

Starting from the open crystal structures, we have studied the gating mechanism of these channels by molecular modeling techniques. Firstly, by applying a membrane potential, initial stages of the closing of the channel were captured, manifested in a secondary-structure change in the voltage-sensor. In a follow-up study, we found that the energetic cost of translocating this 310-helix conformation was significantly lower than in the original conformation. Thirdly, collaborators of ours identified new molecular constraints for different states along the gating pathway. We used those to build new protein models that were evaluated by simulations. All these results point to a gating mechanism where the S4 helix undergoes a secondary structure transformation during gating.

These simulations also provide information about how the protein interacts with the surrounding membrane. In particular, we found that lipid molecules close to the protein diffuse together with it, forming a large dynamic lipid-protein cluster. This has important consequences for the understanding of protein-membrane interactions and for the theories of lateral diffusion of membrane proteins.

Further, simulations of the simple ion channel antiamoebin were performed where different molecular models of the channel were evaluated by calculating ion conduction rates, which were compared to experimentally measured values. One of the models had a conductance consistent with the experimental data and was proposed to represent the biological active state of the channel.

Finally, the underlying methods for simulating molecular systems were probed by implementing the CHARMM force field into the GROMACS simulation package. The implementation was verified and specific GROMACS-features were combined with CHARMM and evaluated on long timescales. The CHARMM interaction potential was found to sample relevant protein conformations indifferently of the model of solvent used.

Place, publisher, year, edition, pages
Stockholm: Department of Biochemistry and Biophysics. Stockholm University, 2011. 65 p.
Keyword
Molecular modeling, Molecular dynamics, Voltage-gating, Ion channels, Protein structure prediction
National Category
Theoretical Chemistry Bioinformatics (Computational Biology)
Research subject
Biochemistry with Emphasis on Theoretical Chemistry
Identifiers
urn:nbn:se:su:diva-63437 (URN)978-91-7447-336-0 (ISBN)
Public defence
2011-12-16, Magnélisalen, Kemiska övningslaboratoriet, Svante Arrhenius väg 16 B, Stockholm, 10:00 (English)
Opponent
Supervisors
Note
At the time of the doctoral defense, the following paper was unpublished and had a status as follows: Paper 3: Manuscript.Available from: 2011-11-24 Created: 2011-10-18 Last updated: 2011-11-23Bibliographically approved

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