Physics-driven coarse-grained models for understanding and engineering biomolecular condensates

ORAL  · Invited

Abstract

Biomolecular condensates are membraneless compartments within living cells, composed of proteins and nucleic acids. They play essential roles in cellular functions and dysfunctions and offer a promising platform for engineering novel cellular functions. However, several questions remain unanswered about the mechanisms by which the material properties of condensates are encoded and how their functions emerge. To address these challenges, experimental approaches have been developed to perturb and measure condensates. Molecular simulations have become an invaluable complement to these efforts, providing detailed, close-up views of condensates. I will discuss how we develop coarse-grained models that balance accuracy and computational efficiency and leverage these approaches to recapitulate condensates in silico at submolecular resolution. Collectively, our framework connects condensate composition to their emergent behaviors, uncovering design principles that can be harnessed to engineer condensates.

*J.A.J. acknowledges start-up funds provided by the Department of Chemical and Biological Engineering and the Omenn–Darling Bioengineering Institute at Princeton University. J.A.J. also acknowledges research support from the Chan Zuckerberg Initiative DAF (an advised fund of Silicon Valley Community Foundation; grant 2023-332391), the National Institute of General Medical Sciences of the National Institutes of Health under Award Number R35GM155259, the National Science Foundation (NSF) through the Princeton University (PCCM) Materials Research Science and Engineering Center DMR-2011750, and an Innovation Fund from the School of Engineering and Applied Sciences at Princeton University.

Publication: Joseph JA†*, Reinhardt A†*, Aguirre A, Chew PY, Russell KO, Espinosa JR, Garaizar A, and Collepardo‑Guevara R*. Physics‑driven coarse‑grained model for biomolecular phase separation with near-quantitative accuracy. Nature Computational Science, 1, 732–743 (2021).

Aierken D and Joseph JA*. Accelerated Simulations Reveal Physicochemical Factors Governing Stability and Composition of RNA Clusters. J. Chem. Theory Comput (2024).

Presenters

  • Jerelle A Joseph

    • Princeton University
    • Chemical & Biological Engineering Princeton University, Omenn-Darling Bioengineering Institute
    • Princeton

Authors

  • Jerelle A Joseph

    • Princeton University
    • Chemical & Biological Engineering Princeton University, Omenn-Darling Bioengineering Institute
    • Princeton