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Inference of Calmodulin's Ca2+-Dependent Free Energy Landscapes via Gaussian Mixture Model Validation
KTH, School of Engineering Sciences (SCI), Physics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
KTH, School of Engineering Sciences (SCI), Physics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
KTH, School of Engineering Sciences (SCI), Physics. KTH, Centres, Science for Life Laboratory, SciLifeLab.
2018 (English)In: Journal of Chemical Theory and Computation, ISSN 1549-9618, E-ISSN 1549-9626, Vol. 14, no 1, p. 63-71Article in journal (Refereed) Published
Abstract [en]

A free energy landscape estimation method based on the well-known Gaussian mixture model (GMM) is used to compare the efficiencies of thermally enhanced sampling methods with respect to regular molecular dynamics. The simulations are carried out on two binding states of calmodulin, and the free energy estimation method is compared with other estimators using a toy model. We show that GMM with cross-validation provides a robust estimate that is not subject to overfitting. The continuous nature of Gaussians provides better estimates on sparse data than canonical histogramming. We find that diffusion properties determine the sampling method effectiveness, such that diffusion-dominated apo calmodulin is most efficiently sampled by regular molecular dynamics, while holo calmodulin, with its rugged free energy landscape, is better sampled by enhanced sampling methods.

Place, publisher, year, edition, pages
American Chemical Society (ACS), 2018. Vol. 14, no 1, p. 63-71
Keywords [en]
Exchange Molecular-Dynamics, Calculating Free-Energies, Replica-Exchange, Biological-Systems, Simulations, Transitions, Algorithm, Mechanism, Efficient, Proteins
National Category
Other Chemistry Topics
Identifiers
URN: urn:nbn:se:kth:diva-221690DOI: 10.1021/acs.jctc.7b00346ISI: 000419998300007PubMedID: 29144736Scopus ID: 2-s2.0-85040344833OAI: oai:DiVA.org:kth-221690DiVA, id: diva2:1176306
Funder
Knut and Alice Wallenberg Foundation, 1484505Carl Tryggers foundation , CTS-15:298Science for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 20180122

Available from: 2018-01-22 Created: 2018-01-22 Last updated: 2018-09-12Bibliographically approved
In thesis
1. Computational Study of Calmodulin’s Ca2+-dependent Conformational Ensembles
Open this publication in new window or tab >>Computational Study of Calmodulin’s Ca2+-dependent Conformational Ensembles
2018 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Ca2+ and calmodulin play important roles in many physiologically crucial pathways. The conformational landscape of calmodulin is intriguing. Conformational changes allow for binding target-proteins, while binding Ca2+ yields population shifts within the landscape. Thus, target-proteins become Ca2+-sensitive upon calmodulin binding. Calmodulin regulates more than 300 target-proteins, and mutations are linked to lethal disorders. The mechanisms underlying Ca2+ and target-protein binding are complex and pose interesting questions. Such questions are typically addressed with experiments which fail to provide simultaneous molecular and dynamics insights. In this thesis, questions on binding mechanisms are probed with molecular dynamics simulations together with tailored unsupervised learning and data analysis.

In Paper 1, a free energy landscape estimator based on Gaussian mixture models with cross-validation was developed and used to evaluate the efficiency of regular molecular dynamics compared to temperature-enhanced molecular dynamics. This comparison revealed interesting properties of the free energy landscapes, highlighting different behaviors of the Ca2+-bound and unbound calmodulin conformational ensembles.

In Paper 2, spectral clustering was used to shed light on Ca2+ and target protein binding. With these tools, it was possible to characterize differences in target-protein binding depending on Ca2+-state as well as N-terminal or C-terminal lobe binding. This work invites data-driven analysis into the field of biomolecule molecular dynamics, provides further insight into calmodulin’s Ca2+ and targetprotein binding, and serves as a stepping-stone towards a complete understanding of calmodulin’s Ca2+-dependent conformational ensembles.

Place, publisher, year, edition, pages
Stockholm: Kungliga Tekniska högskolan, 2018. p. 36
Series
TRITA-SCI-FOU ; 2018:33
Keywords
Molecular dynamics, Calmodulin, Free energy estimation, Gaussian mixture models, Spectral clustering, conformational selection
National Category
Biophysics
Research subject
Biological Physics
Identifiers
urn:nbn:se:kth:diva-234888 (URN)978-91-7729-890-8 (ISBN)
Presentation
2018-10-03, Milky Way, Tomtebodavägen 23B, Solna, 09:30 (English)
Opponent
Supervisors
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 20180912

Available from: 2018-09-12 Created: 2018-09-12 Last updated: 2018-09-12Bibliographically approved

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