News

Research from the Schlick Group published this month in the journal Proceedings of the National Academy of Sciences has been selected to appear in the PNAS Showcase on Kudos.  The findings will provide insights in developing anti-viral therapeutics for a broad spectrum of coronaviruses.

Schlick writes: “It was rewarding to see how pure math, namely graph theory, can be used here so crucially to generate conformational landscapes of coronaviruses and propose RNA mutations that suppress key RNA structural transitions important to viral propagation. The RNA-As-Graphs (RAG) framework we have developed for years has relevant medical utility.”

Schlick postdoc Shuting Yan adds, “Studying RNA structures via mathematical modeling helps understand RNA structural evolution. The design of minimal mutations via our graph-based inverse folding algorithm can serve as potential therapeutic avenues.”

Reference

Yan, S., Zhu, Q., Hohl J., Dong, A., and Schlick, T., Evolution of Coronavirus Frameshifting Elements: Competing Stem Networks Explain Conservation and Variability, Proc. Nat. Acad. Sci., 120 (20) e2221324120 (2023)

A new study published this week in the journal Proceedings of the National Academy of Sciences, explains why cancers not only stop responding to kinase inhibitors but come back stronger, a finding that could inform which drugs oncologists use as a first-line treatment. 

“When a kinase is switched into the active state, it can lead to processes like cells dividing, a hallmark of cancer,” said Alida Besch, a joint PhD student in the Traaseth group and the Simons Center’s Zhang group, and the study’s first author. “This increased activity is why we hypothesize that cancers come back even stronger, but exactly how gatekeeper mutations increase kinase activity is not well understood.”

Using a multipronged approach, including experiments and computer simulations, the researchers studied FGFR kinases harboring two distinct gatekeeper mutations to determine how the kinase is made more active by the gatekeeper mutations.

Reference

Beach, A., Marsiglia, W.M., Mohammadi, M., Zhang, Y., and Traaseth, N.J., Gatekeeper mutations activate FGF receptor tyrosine kinases by destabilizing the autoinhibited state, Proc. Nat. Acad. Sci. 120 (8) e2213090120 (2023)

In collaboration with the Molecular Sciences Software Institute (MolSSI), the Simons Center presents an introductory, scientific programming workshop designed for students and faculty who are interested in using computational tools in science instruction and research.  The Friday, April 28, all-day workshop is offered free of charge.  It will be held on the Washington Square campus of NYU and focuses on building practical programming skills. NO prior programming experience is required. Details and registration instructions are on the Simons Center’s Events page.

The Simons Center for Computational Physical Chemistry at NYU invites applications from outstanding young scientists, who are within three months of, or three years beyond completing their PhD, for independent three-year Simons Center Fellowships. Fellows are selected on the basis of their exceptional accomplishments to-date, evidence of strong intellectual drive, and the promise of the research they plan to undertake in the broad areas of theoretical and computational chemistry.

Fellows are appointed for a three-year term and receive an annual stipend of $85,000, benefits, plus research and travel funds of up to $10,000, per year including up to $2000 of relocation costs. Women and members of groups currently underrepresented in computational physical chemistry are especially encouraged to apply.  Fellowships are open to all nationalities.

Applications for this latest round are due April 4, 2023. Application details may be found here.  

Congratulations to Simons Graduate Fellowship recipient, Subarna Sasmal.  Subarna is the lead author on a paper that demonstrates that Linear Discriminant Analysis (LDA) applied to atomic positions in two different states of a biomolecule produces a good reaction coordinate between those two states.

Reference:

Sasmal, S., McCullagh, M., and Hocky, G.M., Reaction Coordinates for Conformational Transitions using Linear Discriminant Analysis on Positions.  arXiv preprint arXiv:2301.03479 (2023) 

https://wp.nyu.edu/sccpc/2023/01/10/947/

Sunghan Ro of the Technion-Israel Institute of Technology, Buming Guo of New York University, and colleagues — in an effort led by NYU Simons Center’s Stefano Martiniani — have devised a method for measuring local entropy production rate in active matter systems. In the image above, active Brownian particles are driven toward the center of the ring structure via a series of funnels.  Local entropy production is largest at the funnel tips (shown in yellow) where the particle trajectories bifurcate, and contributions to the entropy production from particle collisions is higher in regions with higher particle density. Hence, the region within the inner ring is brightest, and the region outside the outer ring is darkest.

This work is published as the cover article in Physical Review Letters and has been selected for a Viewpoint in Physics magazine. The method, which involves comparing forward and time-reversed particle trajectories, could allow researchers to reveal the impact of local entropy production rates on the global dynamics of complex systems.

Reference:

Model-Free measurement of local entropy production and extractable work in active matter

Sunghan Ro, Buming Guo, Aaron Shih, Trung V. Phan, Robert H. Austin, Dov Levine, Paul M. Chaikin, and Stefano Martiniani
Phys. Rev. Lett. 129, 220601 – Published 21 November 2022
DOI: 10.1103/PhysRevLett.129.220601

Researchers in the Tuckerman group, in collaboration with scientists at the biopharmaceutical company AbbVie, have developed a new computational tool that can quickly and efficiently map the position of water molecules within crystal structures. The findings could be used during the drug development and discovery process to predict which crystals are likely to include water and anticipate the different possible structures of a given drug formulation.

Reference:

A data-driven and topological mapping approach for the a priori prediction of stable molecular crystalline hydrates

Richard S. Hong, Alessandra Mattei, Ahmad Y. Sheikh, and Mark E. Tuckerman
Proceedings of the National Academy of Science, October, 2022
DOI: 10.1073/pnas.2204414119

In collaboration with ESCIP (Enhancing Science Courses by Integrating Python) and MolSSI (Molecular Sciences Software Institute), the Simons Center will host a faculty workshop at New York University Apr 29-30, 2023.  This event will be a combination writing (develop course materials) plus training program (learn new skills and discuss best practices for using Python in undergraduate science courses).  An optional, introductory Python programming course for faculty and students will be held on Friday, April 28.   If you may wish to attend, please complete our expression of interest form.