Mpipi: a transferable coarse-grained model for biomolecular phase-separation with near-quantitative accuracy.
POSTER
Abstract
The formation of biomolecular condensates via liquid-liquid phase separation is one of the chief mechanisms used by cells for spatiotemporal organisation. Importantly, biomolecular phase separation has been directly linked to many biological functions such as heterochromatin organization and transcription, DNA repair and ribonucleoprotein formation, as well as dysfunction, via the formation of in terms of pathological aggregates.
Although experimental techniques are essential for studying the bulk phase behavior of biomolecules, computer simulations are able to provide more close-up views and intricate molecular details of this phenomenon.
Over the last few years, the scientific community has made great progress in developing computational models to study liquid-liquid phase separation, which has helped us link the biomolecular sequences to their macroscopic phase behavior and decipher the physicochemical determinants of these transitions. I will present Mpipi, a multiscale coarse-grained model built upon bioinformatics data and atomistic calculations [1]. The model is designed to capture the dominant role of π–π and cation–π interactions, and the stronger contribution of arginine vs. lysine in LLPS and to carefully balance out the contribution of each amino acid. Using the Mpipi model, we compute phase diagrams for a series of well-studied proteins with near quantitative accuracy.
I will describe the parameterization of the force field, the benchmarking against other coarse-grained models, and the validation of the Mpipi model against existing experimental and computational studies.
[1]J A Joseph, A Reinhardt et al., Physics driven coarse-grained model for biomolecular phase separation with near-quantitative accuracy, Nat. Comput. Sci., 2021 (in press).
Although experimental techniques are essential for studying the bulk phase behavior of biomolecules, computer simulations are able to provide more close-up views and intricate molecular details of this phenomenon.
Over the last few years, the scientific community has made great progress in developing computational models to study liquid-liquid phase separation, which has helped us link the biomolecular sequences to their macroscopic phase behavior and decipher the physicochemical determinants of these transitions. I will present Mpipi, a multiscale coarse-grained model built upon bioinformatics data and atomistic calculations [1]. The model is designed to capture the dominant role of π–π and cation–π interactions, and the stronger contribution of arginine vs. lysine in LLPS and to carefully balance out the contribution of each amino acid. Using the Mpipi model, we compute phase diagrams for a series of well-studied proteins with near quantitative accuracy.
I will describe the parameterization of the force field, the benchmarking against other coarse-grained models, and the validation of the Mpipi model against existing experimental and computational studies.
[1]J A Joseph, A Reinhardt et al., Physics driven coarse-grained model for biomolecular phase separation with near-quantitative accuracy, Nat. Comput. Sci., 2021 (in press).
*This project has received funding from the European Research Council under the EU's Horizon 2020 program and performed using resources provided by the Cambridge Tier-2 system of the University of Cambridge.
Publication: Jerelle A. Joseph, Aleks Reinhardt, Anne Aguirre, Kieran O. Russell, Jorge R. Espinosa, Adiran Garaizar, Pin Yu Chew, and Rosana Collepardo-Guevara., Physics driven coarse-grained model for biomolecular phase separation with near-quantitative accuracy, Nat. Comput. Sci., 2021 (in press).
Presenters
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Anne Aguirre
- University of Cambridge