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dhr. dr. T. (Tristan) Bereau

Van 't Hoff Institute for Molecular Sciences and Informatics Institute
Faculteit der Natuurwetenschappen, Wiskunde en Informatica
Van 't Hoff Institute for Molecular Sciences

Bezoekadres
  • Science Park 904
  • Kamernummer:C3.232
Postadres
  • Postbus 94157
    1090 GD Amsterdam
Contactgegevens
  • Research interests

    My research focuses on the development and application of multiscale molecular simulations methods for soft-condensed-matter materials. Current activities revolve around the development of computational high-throughput screening methods from molecular dynamics, aimed at the generation of large databases of free energies. Interfaces with recent machine-learning architectures help streamline and accelerate the process. Further activities aim at improving dynamical properties of coarse-grained models.

    Group webpage

  • Publicaties

    2020

    • Barnett, J. W., Bilchak, C. R., Wang, Y., Benicewicz, B. C., Murdock, L. A., Bereau, T., & Kumar, S. K. (2020). Designing exceptional gas-separation polymer membranes using machine learning. Science Advances, 6(20), [eaaz4301]. https://doi.org/10.1126/sciadv.aaz4301
    • Centi, A., Dutta, A., Parekh, S. H., & Bereau, T. (2020). Inserting Small Molecules across Membrane Mixtures: Insight from the Potential of Mean Force. Biophysical Journal. https://doi.org/10.1016/j.bpj.2020.01.039
    • Girard, M., & Bereau, T. (2020). Regulating Lipid Composition Rationalizes Acyl Tail Saturation Homeostasis in Ectotherms. Biophysical Journal. https://doi.org/10.1016/j.bpj.2020.07.024
    • Hoffmann, C., Centi, A., Menichetti, R., & Bereau, T. (2020). Molecular dynamics trajectories for 630 coarse-grained drug-membrane permeations. Scientific Data, 7(1). https://doi.org/10.1038/s41597-020-0391-0
    • Koch, A. H. R., Morsbach, S., Bereau, T., Lévêque, G., Butt, H. J., Deserno, M., ... Fytas, G. (2020). Probing Nanoparticle/Membrane Interactions by Combining Amphiphilic Diblock Copolymer Assembly and Plasmonics. The journal of Physical Chemistry. B, 124(5), 742-750. https://doi.org/10.1021/acs.jpcb.9b10469
    • Rauer, C., & Bereau, T. (2020). Hydration free energies from kernel-based machine learning: Compound-database bias. Journal of Chemical Physics, 153(1), [014101]. https://doi.org/10.1063/5.0012230
    • Scherer, C., Scheid, R., Andrienko, D., & Bereau, T. (2020). Kernel-Based Machine Learning for Efficient Simulations of Molecular Liquids. Journal of Chemical Theory and Computation, 16(5), 3194-3204. https://doi.org/10.1021/acs.jctc.9b01256

    2019

    • Bause, M., Wittenstein, T., Kremer, K., & Bereau, T. (2019). Microscopic reweighting for nonequilibrium steady-state dynamics. Physical Review E, 100(6), [060103]. https://doi.org/10.1103/PhysRevE.100.060103
    • Girard, M., Ehlen, A., Shakya, A., Bereau, T., & de la Cruz, M. O. (2019). Hoobas: A highly object-oriented builder for molecular dynamics. Computational materials science, 167, 25-33. https://doi.org/10.1016/j.commatsci.2019.05.003
    • Hoffmann, C., Menichetti, R., Kanekal, K. H., & Bereau, T. (2019). Controlled exploration of chemical space by machine learning of coarse-grained representations. Physical Review E, 100(3), [033302]. https://doi.org/10.1103/PhysRevE.100.033302
    • Kanekal, K. H., & Bereau, T. (2019). Resolution limit of data-driven coarse-grained models spanning chemical space. Journal of Chemical Physics, 151(16), [164106]. https://doi.org/10.1063/1.5119101
    • Menichetti, R., & Bereau, T. (2019). Revisiting the Meyer-Overton rule for drug-membrane permeabilities. Molecular Physics, 117(20), 2900-2909. https://doi.org/10.1080/00268976.2019.1601787
    • Menichetti, R., Kanekal, K. H., & Bereau, T. (2019). Drug-Membrane Permeability across Chemical Space. ACS Central Science, 5(2), 290-298. https://doi.org/10.1021/acscentsci.8b00718
    • Rudzinski, J. F., Radu, M., & Bereau, T. (2019). Automated detection of many-particle solvation states for accurate characterizations of diffusion kinetics. Journal of Chemical Physics, 150(2), [024102]. https://doi.org/10.1063/1.5064808
    • Schilling, C., Mack, T., Lickfett, S., Sieste, S., Ruggeri, F. S., Sneideris, T., ... Knöll, B. (2019). Sequence-Optimized Peptide Nanofibers as Growth Stimulators for Regeneration of Peripheral Neurons. Advanced Functional Materials, 29(24), [1809112]. https://doi.org/10.1002/adfm.201809112
    • Wörner, S. J., Bereau, T., Kremer, K., & Rudzinski, J. F. (2019). Direct route to reproducing pair distribution functions with coarse-grained models via transformed atomistic cross correlations. Journal of Chemical Physics, 151(24), [244110]. https://doi.org/10.1063/1.5131105

    2018

    • Bereau, T., & Rudzinski, J. F. (2018). Accurate Structure-Based Coarse Graining Leads to Consistent Barrier-Crossing Dynamics. Physical Review Letters, 121(25), [256002]. https://doi.org/10.1103/PhysRevLett.121.256002
    • Bereau, T., DiStasio, R. A., Tkatchenko, A., & Von Lilienfeld, O. A. (2018). Non-covalent interactions across organic and biological subsets of chemical space: Physics-based potentials parametrized from machine learning. Journal of Chemical Physics, 148(24), [241706]. https://doi.org/10.1063/1.5009502
    • Liu, C., Kremer, K., & Bereau, T. (2018). Polymorphism of Syndiotactic Polystyrene Crystals from Multiscale Simulations. Advanced Theory and Simulations, 1(7), [1800024]. https://doi.org/10.1002/adts.201800024
    • Menichetti, R., Kremer, K., & Bereau, T. (2018). Efficient potential of mean force calculation from multiscale simulations: Solute insertion in a lipid membrane. Biochemical and Biophysical Research Communications, 498(2), 282-287. https://doi.org/10.1016/j.bbrc.2017.08.095
    • Morsbach, S., Gonella, G., Mailänder, V., Wegner, S., Wu, S., Weidner, T., ... Landfester, K. (2018). Engineering Proteins at Interfaces: From Complementary Characterization to Material Surfaces with Designed Functions. Angewandte Chemie - International Edition, 57(39), 12626-12648. https://doi.org/10.1002/anie.201712448
    • Rudzinski, J. F., & Bereau, T. (2018). Structural-kinetic-thermodynamic relationships identified from physics-based molecular simulation models. Journal of Chemical Physics, 148(20), [204111]. https://doi.org/10.1063/1.5025125
    • Rudzinski, J. F., & Bereau, T. (2018). The role of conformational entropy in the determination of structural-kinetic relationships for helix-coil transitions. Computation, 6(1), [21]. https://doi.org/10.3390/computation6010021

    2017

    • Franz, J., Bereau, T., Pannwitt, S., Anbazhagan, V., Lehr, A., Nubbemeyer, U., ... Schneider, D. (2017). Nitrated Fatty Acids Modulate the Physical Properties of Model Membranes and the Structure of Transmembrane Proteins. Chemistry - A European Journal, 23(40), 9690-9697. https://doi.org/10.1002/chem.201702041
    • Menichetti, R., Kanekal, K. H., Kremer, K., & Bereau, T. (2017). In silico screening of drug-membrane thermodynamics reveals linear relations between bulk partitioning and the potential of mean force. Journal of Chemical Physics, 147(12), [125101]. https://doi.org/10.1063/1.4987012

    2016

    • Bereau, T., & Kremer, K. (2016). Protein-Backbone Thermodynamics across the Membrane Interface. Journal of Physical Chemistry B, 120(26), 6391-6400. https://doi.org/10.1021/acs.jpcb.6b03682
    • Bereau, T., & Meuwly, M. (2016). Multipolar force fields for atomistic simulations. In Many-Body Effects and Electrostatics in Biomolecules (pp. 233-268). Pan Stanford Publishing Pte. Ltd.. https://doi.org/10.4032/9789814613934
    • Bereau, T., Andrienko, D., & Kremer, K. (2016). Research Update: Computational materials discovery in soft matter. APL Materials, 4(5), [053101]. https://doi.org/10.1063/1.4943287
    • El Hage, K., Bereau, T., Jakobsen, S., & Meuwly, M. (2016). Impact of quadrupolar electrostatics on atoms adjacent to the sigma-hole in condensed-phase simulations. Journal of Chemical Theory and Computation, 12(7), 3008-3019. https://doi.org/10.1021/acs.jctc.6b00202
    • Rudzinski, J. F., & Bereau, T. (2016). Concurrent parametrization against static and kinetic information leads to more robust coarse-grained force fields. European Physical Journal: Special Topics, 225(8-9), 1373-1389. https://doi.org/10.1140/epjst/e2016-60114-5
    • Rudzinski, J. F., Kremer, K., & Bereau, T. (2016). Communication: Consistent interpretation of molecular simulation kinetics using Markov state models biased with external information. Journal of Chemical Physics, 144(5), [051102]. https://doi.org/10.1063/1.4941455
    • Xiao, Q., Chen, Y., Bereau, T., & Shi, Y. (2016). An in-silico walker. Chemical Physics Letters, 659, 6-9. https://doi.org/10.1016/j.cplett.2016.06.019

    2015

    • Bereau, T. (2015). Better Together: Lipopeptide Micelle Formation Enhances Antimicrobial Selectivity. Biophysical Journal, 109(4), 668-669. https://doi.org/10.1016/j.bpj.2015.07.012
    • Bereau, T. (2015). Multi-timestep Integrator for the Modified Andersen Barostat. Physics Procedia, 68, 7-15. https://doi.org/10.1016/j.phpro.2015.07.101
    • Bereau, T., & Deserno, M. (2015). Enhanced Sampling of Coarse-Grained Transmembrane-Peptide Structure Formation from Hydrogen-Bond Replica Exchange. Journal of Membrane Biology, 248(3), 395-405. https://doi.org/10.1007/s00232-014-9738-9
    • Bereau, T., & Kremer, K. (2015). Automated Parametrization of the Coarse-Grained Martini Force Field for Small Organic Molecules. Journal of Chemical Theory and Computation, 11(6), 2783-2791. https://doi.org/10.1021/acs.jctc.5b00056
    • Bereau, T., Andrienko, D., & Von Lilienfeld, O. A. (2015). Transferable Atomic Multipole Machine Learning Models for Small Organic Molecules. Journal of Chemical Theory and Computation, 11(7), 3225-3233. https://doi.org/10.1021/acs.jctc.5b00301
    • Bereau, T., Bennett, W. F. D., Pfaendtner, J., Deserno, M., & Karttunen, M. (2015). Folding and insertion thermodynamics of the transmembrane WALP peptide. Journal of Chemical Physics, 143(24), [243127]. https://doi.org/10.1063/1.4935487
    • Cazade, P. A., Tran, H., Bereau, T., Das, A. K., Kläsi, F., Hamm, P., & Meuwly, M. (2015). Solvation of fluoro-acetonitrile in water by 2D-IR spectroscopy: A combined experimental-computational study. Journal of Chemical Physics, 142(21), [212415]. https://doi.org/10.1063/1.4916630
    • Jakobsen, S., Bereau, T., & Meuwly, M. (2015). Multipolar force fields and their effects on solvent dynamics around simple solutes. Journal of Physical Chemistry B, 119(7), 3034-3045. https://doi.org/10.1021/jp508052q

    2014

    • Bereau, T., & Von Lilienfeld, O. A. (2014). Toward transferable interatomic van der Waals interactions without electrons: The role of multipole electrostatics and many-body dispersion. Journal of Chemical Physics, 141(3), [034101]. https://doi.org/10.1063/1.4885339
    • Bereau, T., Wang, Z. J., & Deserno, M. (2014). More than the sum of its parts: Coarse-grained peptide-lipid interactions from a simple cross-parametrization. Journal of Chemical Physics, 140(11), [115101]. https://doi.org/10.1063/1.4867465
    • Cazade, P. A., Bereau, T., & Meuwly, M. (2014). Computational two-dimensional infrared spectroscopy without maps: N-methylacetamide in water. Journal of Physical Chemistry B, 118(28), 8135-8147. https://doi.org/10.1021/jp5011692

    2013

    • Bereau, T., Kramer, C., & Meuwly, M. (2013). Leveraging symmetries of static atomic multipole electrostatics in molecular dynamics simulations. Journal of Chemical Theory and Computation, 9(12), 5450-5459. https://doi.org/10.1021/ct400803f
    • Bereau, T., Kramer, C., Monnard, F. W., Nogueira, E. S., Ward, T. R., & Meuwly, M. (2013). Scoring multipole electrostatics in condensed-phase atomistic simulations. Journal of Physical Chemistry B, 117(18), 5460-5471. https://doi.org/10.1021/jp400593c
    • Kramer, C., Bereau, T., Spinn, A., Liedl, K. R., Gedeck, P., & Meuwly, M. (2013). Deriving static atomic multipoles from the electrostatic potential. Journal of Chemical Information and Modeling, 53(12), 3410-3417. https://doi.org/10.1021/ci400548w

    2012

    • Bereau, T., Globisch, C., Deserno, M., & Peter, C. (2012). Coarse-grained and atomistic simulations of the salt-stable cowpea chlorotic mottle virus (SS-CCMV) subunit 26-49: β-barrel stability of the hexamer and pentamer geometries. Journal of Chemical Theory and Computation, 8(10), 3750-3758. https://doi.org/10.1021/ct200888u

    2011

    • Bereau, T., Deserno, M., & Bachmann, M. (2011). Structural basis of folding cooperativity in model proteins: Insights from a microcanonical perspective. Biophysical Journal, 100(11), 2764-2772. https://doi.org/10.1016/j.bpj.2011.03.056

    2010

    • Bereau, T., Bachmann, M., & Deserno, M. (2010). Interplay between secondary and tertiary structure formation in protein folding cooperativity. Journal of the American Chemical Society, 132(38), 13129-13131. https://doi.org/10.1021/ja105206w

    2009

    • Bereau, T., & Deserno, M. (2009). Generic coarse-grained model for protein folding and aggregation. Journal of Chemical Physics, 130(23), [235106]. https://doi.org/10.1063/1.3152842
    • Bereau, T., & Swendsen, R. H. (2009). Optimized convergence for multiple histogram analysis. Journal of computational Physics, 228(17), 6119-6129. https://doi.org/10.1016/j.jcp.2009.05.011
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  • Nevenwerkzaamheden
    • Max Planck Institute Polymer Research
      Supervision of PhD students