Identi cation of droplet formation
No salt
Concentration Pro les with Salt:
50 mM
100 mM
d
d
100 mM
d
d
The Fundamental Compromise in Molecular
Simulations
MARTINI Force Field
50 mM
Condensed phase concentration comparisons:
No salt
*
200 mM
Brangwynne et al. (2009) Science 324:1729–32
Brangwynne, Tompa, Pappu (2015) Nat Phys 11:899–904
Molecular dynamics (MD) simulations at atomic resolution could,
in principle, monitor molecular interactions with a high accuracy,
however, their high computational costs still preclude their
widespread use for simulating LLPS. Coarse-grained simulations
using a reduced representation enable direct simulations of phase
behavior and can give a good description of effective molecular
Dignon, Zheng, and Mittal (2019)
interactions.
Curr Opin Chem Eng 23:92–98
= 1.025
= 1.03
1st cluster 2nd cluster 3rd cluster 1st+2nd+3rd
What are the intraand inter-molecular
interactions that hold
these assemblies
together?
Time (ns)
Di erent salt concentrations
(Probe r=10A)
Larsen et al. 2020 PLoS Comput Biol 16(4): e1007870
Inspired by the success of the work for sm properties, we tested
a range of scaled protein-water interactions for condensate
formation. We refer to the scaling parameter as ; the parameter
with which we multiply the ε of the LJ interactions between
protein and water beads. We presented the results where the
parameter varies between 1-1.04.
= 1.01
= 1.02
= 1.025
= 1.03
Experimental range
Experimental range
50 mM
So, the parameter to tune the protein-water interactions wasn’t able
to achieve the experimentally found** range of condensed phase
concentrations. Two major conclusions: 1) parameters that give
good agreement for single-molecule properties do not work for
condensate formation 2) adding salt doesn’t change it though it possible
has an interesting effect on morphology. *Benayad et al. 2020 JCTC 17(1):525-37
**Conicella et al. 2016 Structure 24(9): 1537-49, Murthy et al 2019 Nat Struc Mol Bio 26(7):637-48
ANNOUNCEMENTS
I’m actively looking for multiple postdocs/senior
scientists who are interested in joining my lab to work on
projects funded by Cancer Prevention and Research Institute
of Texas. We are studying transcriptional condensates using
the tools of computational biomolecular science. Please email
gzerze@uh.edu for more information!
200 mM
Single-molecule (sm) properties have been commonly used as
objective functions for force eld optimization. One of the most
commonly used parameter to tune for such force eld
optimizations is the protein-water interaction strength. This
parameter has been used for optimization of the MARTINI force
Thomasen et al. 2008 JCTC 18(4):2033-41
eld.
=1
No salt
Parameter set for re nement of the MARTINI 3.0
Force Field
Representative screenshots of droplets
100 mM
Among the CG models, the MARTINI force eld offers a
resolution that preserves molecular details with an explicit (CG)
solvent while being able to achieve condensate formation in
reasonable computing time. Souza et al (2021) Nature methods (18)4: 382-8
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Funding: Cancer Prevention and Research Institute of Texas, Computations: Terascale Infrastructure Groundbreaking Research at Princeton
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One mechanism that explains the intracellular condensation/
dissolution is LLPS, in which the two liquid-like phases are a
protein (and/or RNA)-rich (condensed) phase and a dilute phase.
=1
= 1.01
= 1.02
No condensation
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Cubic simulation boxes (L = 40 nm) that contained 100 copies of
FUS LC chains, 2.6 mM (44.5 mg/mL) protein concentration.
Intracellular liquid-liquid phase separation (LLPS)
n
No atio
s
en
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Concentration Pro les without Salt:
RESULTS AND DISCUSSION
BACKGROUND AND MOTIVATION
nd
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Gül H. Zerze
Department of Chemical and Biomolecular Engineering, University of Houston
co
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Biomolecular Condensate Formation via Scaled Protein-Water Interactions MARTINI 3