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Articles by Gül H. Zerze
Nucleation Landscape of Biomolecular Condensates in the Grand Canonical Ensemble via Monte Carlo Simulations
Abstract We present a Monte Carlo framework for simulating the nucleation of biomolecular condensates in the grand canonical ensemble, which overcomes the limitations of fixed particle number and allows direct control of the dilute-phase concentration. Our approach combines conformation sampling with bias-enhanced cluster size sampling, enabling accurate sampling of individual cluster sizes in various conformations.
A Deep Learning-Driven Sampling Technique to Explore the Phase Space of an RNA Stem-Loop
Abstract The folding and unfolding of RNA stem-loops are critical biological processes; however, their computational studies are often hampered by the ruggedness of their folding landscape, necessitating long simulation times at the atomistic scale. Here, we adapted DeepDriveMD (DDMD), an advanced deep learning-driven sampling technique originally developed for protein folding, to address the challenges of RNA stem-loop folding.
Second critical point in two realistic models of water
Report View ORCID ProfilePablo G. Debenedetti1,*,†, View ORCID ProfileFrancesco Sciortino2,†, View ORCID ProfileGül H. Zerze1,† 1Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ, USA. 2Department of Physics, Sapienza University of Rome, Rome, Italy. ↵*Corresponding author. Email: pdebene{at}princeton.edu ↵† These authors contributed equally to this work. See allHide authors and affiliations Science 17 Jul 2020: Vol. 369, Issue 6501, pp.
TDP-43 α-helical structure tunes liquid-liquid phase separation and function
TDP-43 α-helical structure tunes liquid–liquid phase separation and function Alexander E. Conicella, Gregory L. Dignon, Gül H. Zerze, Hermann Broder Schmidt, Alexandra M. D’Ordine, Young C. Kim, Rajat Rohatgi, Yuna M. Ayala, Jeetain Mittal, Nicolas L. Fawzi Proceedings of the National Academy of Sciences Mar 2020, 201912055; DOI: 10.1073/pnas.1912055117
Mechanistic View of hnRNPA2 Low-Complexity Domain Structure, Interactions, and Phase Separation Altered by Mutation and Arginine Methylation
hnRNPA2, a component of RNA-processing membraneless organelles, forms inclusions when mutated in a syndrome characterized by the degeneration of neurons (bearing features of amyotrophic lateral sclerosis [ALS] and frontotemporal dementia), muscle, and bone. Here we provide a unified structural view of hnRNPA2 self-assembly, aggregation, and interaction and the distinct effects of small chemical changes—disease mutations and arginine methylation—on these assemblies.
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