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Computational Study of Calmodulin’s Ca2+-dependent Conformational Ensembles
KTH, School of Engineering Sciences (SCI), Applied Physics, Biophysics. (Molecular biophysics)ORCID iD: 0000-0003-2288-5711
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 [en]
Molecular dynamics, Calmodulin, Free energy estimation, Gaussian mixture models, Spectral clustering, conformational selection
National Category
Biophysics
Research subject
Biological Physics
Identifiers
URN: urn:nbn:se:kth:diva-234888ISBN: 978-91-7729-890-8 (print)OAI: oai:DiVA.org:kth-234888DiVA, id: diva2:1247435
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
List of papers
1. Inference of Calmodulin's Ca2+-Dependent Free Energy Landscapes via Gaussian Mixture Model Validation
Open this publication in new window or tab >>Inference of Calmodulin's Ca2+-Dependent Free Energy Landscapes via Gaussian Mixture Model Validation
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
Keywords
Exchange Molecular-Dynamics, Calculating Free-Energies, Replica-Exchange, Biological-Systems, Simulations, Transitions, Algorithm, Mechanism, Efficient, Proteins
National Category
Other Chemistry Topics
Identifiers
urn:nbn:se:kth:diva-221690 (URN)10.1021/acs.jctc.7b00346 (DOI)000419998300007 ()29144736 (PubMedID)2-s2.0-85040344833 (Scopus ID)
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
2. Effect of Ca2+on the promiscuous target-protein binding of calmodulin
Open this publication in new window or tab >>Effect of Ca2+on the promiscuous target-protein binding of calmodulin
2018 (English)In: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 14, no 4, article id e1006072Article in journal (Refereed) Published
Abstract [en]

Calmodulin (CaM) is a calcium sensing protein that regulates the function of a large number of proteins, thus playing a crucial part in many cell signaling pathways. CaM has the ability to bind more than 300 different target peptides in a Ca2+-dependent manner, mainly through the exposure of hydrophobic residues. How CaM can bind a large number of targets while retaining some selectivity is a fascinating open question. Here, we explore the mechanism of CaM selective promiscuity for selected target proteins. Analyzing enhanced sampling molecular dynamics simulations of Ca2+-bound and Ca2+-free CaM via spectral clustering has allowed us to identify distinct conformational states, characterized by interhelical angles, secondary structure determinants and the solvent exposure of specific residues. We searched for indicators of conformational selection by mapping solvent exposure of residues in these conformational states to contacts in structures of CaM/target peptide complexes. We thereby identified CaM states involved in various binding classes arranged along a depth binding gradient. Binding Ca2+modifies the accessible hydrophobic surface of the two lobes and allows for deeper binding. Apo CaM indeed shows shallow binding involving predominantly polar and charged residues. Furthermore, binding to the C-terminal lobe of CaM appears selective and involves specific conformational states that can facilitate deep binding to target proteins, while binding to the N-terminal lobe appears to happen through a more flexible mechanism. Thus the long-ranged electrostatic interactions of the charged residues of the N-terminal lobe of CaM may initiate binding, while the short-ranged interactions of hydrophobic residues in the C-terminal lobe of CaM may account for selectivity. This work furthers our understanding of the mechanism of CaM binding and selectivity to different target proteins and paves the way towards a comprehensive model of CaM selectivity.

Place, publisher, year, edition, pages
Public Library of Science, 2018
National Category
Bioinformatics (Computational Biology)
Identifiers
urn:nbn:se:kth:diva-228941 (URN)10.1371/journal.pcbi.1006072 (DOI)000432169600018 ()29614072 (PubMedID)2-s2.0-85046377207 (Scopus ID)
Funder
Science for Life Laboratory - a national resource center for high-throughput molecular bioscience
Note

QC 20180530

Available from: 2018-05-30 Created: 2018-05-30 Last updated: 2018-09-12Bibliographically approved

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