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  • 1.
    Fleetwood, Oliver
    et al.
    KTH, Skolan för teknikvetenskap (SCI), Tillämpad fysik, Biofysik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Kasimova, Marina A.
    KTH, Skolan för teknikvetenskap (SCI), Tillämpad fysik, Biofysik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Westerlund, Annie M.
    KTH, Skolan för teknikvetenskap (SCI), Tillämpad fysik, Biofysik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Delemotte, Lucie
    KTH, Skolan för teknikvetenskap (SCI), Tillämpad fysik, Biofysik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Molecular Insights from Conformational Ensembles via Machine Learning2020Ingår i: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 118, nr 3, s. 765-780Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Biomolecular simulations are intrinsically high dimensional and generate noisy data sets of ever-increasing size. Extracting important features from the data is crucial for understanding the biophysical properties of molecular processes, but remains a big challenge. Machine learning (ML) provides powerful dimensionality reduction tools. However, such methods are often criticized as resembling black boxes with limited human-interpretable insight. We use methods from supervised and unsupervised ML to efficiently create interpretable maps of important features from molecular simulations. We benchmark the performance of several methods, including neural networks, random forests, and principal component analysis, using a toy model with properties reminiscent of macromolecular behavior. We then analyze three diverse biological processes: conformational changes within the soluble protein calmodulin, ligand binding to a G protein-coupled receptor, and activation of an ion channel voltage-sensor domain, unraveling features critical for signal transduction, ligand binding, and voltage sensing. This work demonstrates the usefulness of ML in understanding biomolecular states and demystifying complex simulations.

  • 2.
    Westerlund, Annie M.
    KTH, Skolan för teknikvetenskap (SCI), Tillämpad fysik, Biofysik.
    Computational Study of Calmodulin’s Ca2+-dependent Conformational Ensembles2018Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
    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.

  • 3.
    Westerlund, Annie M.
    et al.
    KTH, Skolan för teknikvetenskap (SCI), Tillämpad fysik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Delemotte, Lucie
    KTH, Skolan för teknikvetenskap (SCI), Tillämpad fysik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Effect of Ca2+on the promiscuous target-protein binding of calmodulin2018Ingår i: PloS Computational Biology, ISSN 1553-734X, E-ISSN 1553-7358, Vol. 14, nr 4, artikel-id e1006072Artikel i tidskrift (Refereegranskat)
    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.

  • 4.
    Westerlund, Annie M.
    et al.
    KTH, Skolan för teknikvetenskap (SCI), Tillämpad fysik, Biofysik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    Delemotte, Lucie
    KTH, Skolan för teknikvetenskap (SCI), Tillämpad fysik, Biofysik. KTH, Centra, Science for Life Laboratory, SciLifeLab.
    InfleCS: Clustering Free Energy Landscapes with Gaussian Mixtures.2019Ingår i: Journal of Chemical Theory and Computation, ISSN 1549-9618, E-ISSN 1549-9626, Vol. 15, nr 12, s. 6752-6759Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Free energy landscapes provide insights into conformational ensembles of biomolecules. In order to analyze these landscapes and elucidate mechanisms underlying conformational changes, there is a need to extract metastable states with limited noise. This has remained a formidable task, despite a plethora of existing clustering methods. We present InfleCS, a novel method for extracting well-defined core states from free energy landscapes. The method is based on a Gaussian mixture free energy estimator and exploits the shape of the estimated density landscape. The core states that naturally arise from the clustering allow for detailed characterization of the conformational ensemble. The clustering quality is evaluated on three toy models with different properties, where the method is shown to consistently outperform other conventional and state-of-the-art clustering methods. Finally, the method is applied to a temperature enhanced molecular dynamics simulation of Ca2+-bound Calmodulin. Through the free energy landscape, we discover a pathway between a canonical and a compact state, revealing conformational changes driven by electrostatic interactions.

  • 5.
    Westerlund, Annie M.
    et al.
    KTH, Skolan för teknikvetenskap (SCI), Tillämpad fysik, Biofysik.
    Delemotte, Lucie
    KTH, Skolan för teknikvetenskap (SCI), Tillämpad fysik, Biofysik.
    On the Selective Promiscuity of Calmodulin2018Ingår i: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 114, nr 3, s. 7A-8AArtikel i tidskrift (Övrigt vetenskapligt)
  • 6.
    Westerlund, Annie M.
    et al.
    KTH, Skolan för teknikvetenskap (SCI), Tillämpad fysik, Biofysik.
    Harpole, Tyler J.
    KTH, Skolan för teknikvetenskap (SCI), Fysik.
    Blau, Christian
    Stockholm Univ, Biochem & Biophys, Stockholm, Sweden..
    Delemotte, Lucie
    KTH, Skolan för teknikvetenskap (SCI), Tillämpad fysik, Biofysik.
    Inference of Calmodulin's Ca2+: Dependent Free Energy Landscapes via Gaussian Mixture Model Validation2018Ingår i: Biophysical Journal, ISSN 0006-3495, E-ISSN 1542-0086, Vol. 114, nr 3, s. 675A-675AArtikel i tidskrift (Refereegranskat)
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