Department of Chemistry

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Lillian Chong

Professor

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331 Eberly Hall
Chevron Science Center
219 Parkman Avenue

Pittsburgh, PA 15260
412-624-6026

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Research Overview

Computational Biophysics; Biomolecular simulations

Research in the Chong lab involves the development and application of molecular simulation approaches to model a variety of biophysical processes. A summary of some of our research directions is provided below.

Weighted ensemble approaches for sampling rare events

To enable the efficient simulation of rare events (e.g. protein folding and binding processes), we have been developing approaches based on “weighted ensemble” path sampling, which introduces no bias into the dynamics. Using our high-performance implementation of this approach (WESTPA), we and others have demonstrated that this approach can enhance the efficiency of generating pathways and rate constants for rare events by orders of magnitude

Simulation of protein binding pathways and kinetics

Obtaining atomically detailed views of protein binding (and unbinding) processes has been a grand challenge in the field of biomolecular simulation due to the long timescales required. To tackle this difficult problem, we have been using weighted ensemble algorithms to generate pathways and rate constants for various protein binding processes, including those that involve intrinsically disordered peptides that fold only upon binding their intended partner proteins.

Design of protein conformational switches

The process of designing protein conformational switches involves a significant amount of educated guesswork in the laboratory. To aid in the rational design of protein switches, we have been developing simulation approaches with various levels of coarse-graining to efficiently predict the dynamics of these protein switches. We have been focusing on a particular class of protein-based switches that are engineered using a "mutually exclusive folding" strategy in which two formerly independent protein domains are fused together in such a way that at any moment in time, only one or the other protein can be folded, but not both.

The Chong Lab is currently accepting new graduate students.

Awards

  • Gordon Bell Special Prize for HPC-Based COVID-19 Research, 2020
  • Silicon Therapeutics Open Science Fellow, 2020
  • University of Pittsburgh Arts & Sciences Bellet Teaching Excellence Award, 2017
  • National Science Foundation CAREER Award, 2009-2014
  • Carnegie Science Emerging Female Scientist Award, 2012
  • Hewlett-Packard Outstanding Junior Faculty Award, 2008
  • Frank M. Goyan Graduate Research Award in Physical Chemistry at UCSF, 2002
  • Burroughs Wellcome Graduate Research Fellowship, 2001-2002
  • National Science Foundation Graduate Research Fellowship, 1998-2001

Publications

“Effects of altered backbone composition on the folding kinetics and mechanism of an ultrafast-folding protein,” J. R. Santhouse, J. M. G. Leung, L. T. Chong*, W. S. Horne* Chem. Sci. 2024, 15, 675-682
“Direct observation of negative cooperativity in a detoxification enzyme at the atomic level by Electron Paramagnetic Resonance spectroscopy and simulation,” Xiaowei Bogetti, Anthony Bogetti, Joshua Casto, Gordon Rule, Lillian Chong, Sunil Saxena Protein Science 2023, 32 10, e4770
“LPATH: A semi-automated Python tool for clustering molecular pathways,” Anthony T Bogetti, Jeremy MG Leung, Lillian T Chong bioRxiv 2023, 8 17, 553774
“Structure-Based Experimental Datasets for Benchmarking of Protein Simulation Force Fields,” Chapin E Cavender, David A Case, Julian C-H Chen, Lillian T Chong, Daniel A Keedy, Kresten Lindorff-Larsen, David L Mobley, OH Ollila, Chris Oostenbrink, Paul Robustelli, Vincent A Voelz, Michael E Wall, David C Wych, Michael K Gilson arXiv 2023, 2303, 11056
“How does a ligand exit from a buried receptor cavity? Atomistic simulations of unbinding pathways with rigorous kinetics,” Marion L Silvestrini, Riccardo Solazzo, Matteo Masetti, Kevin H Gardner, Lillian T Chong Biophysical Journal 2023, 122 3, 20a
“Alternate conformational states of the HIV-1 capsid protein: Atomistic structures and dynamics of interconversion,” Darian T Yang, Angela M Gronenborn, Lillian T Chong Biophysical Journal 2023, 122 3, 308a
“Identification of Small Molecule Ligand Binding Sites On and In the ARNT PAS-B Domain,” Xingjian Xu, Leandro Pimentel Marcelino, Denize C Favaro, Marion L Silvestrini, Riccardo Solazzo, Lillian T Chong, Kevin H Gardner bioRxiv 2023, 11 3, 565595
“# COVIDisAirborne: AI-enabled multiscale computational microscopy of delta SARS-CoV-2 in a respiratory aerosol,” Abigail Dommer, Lorenzo Casalino, Fiona Kearns, Mia Rosenfeld, Nicholas Wauer, Surl-Hee Ahn, John Russo, Sofia Oliveira, Clare Morris, Anthony Bogetti, Anda Trifan, Alexander Brace, Terra Sztain, Austin Clyde, Heng Ma, Chakra Chennubhotla, Hyungro Lee, Matteo Turilli, Syma Khalid, Teresa Tamayo-Mendoza, Matthew Welborn, Anders Christensen, Daniel GA Smith, Zhuoran Qiao, Sai K Sirumalla, Michael O’Connor, Frederick Manby, Anima Anandkumar, David Hardy, James Phillips, Abraham Stern, Josh Romero, David Clark, Mitchell Dorrell, Tom Maiden, Lei Huang, John McCalpin, Christopher Woods, Alan Gray, Matt Williams, Bryan Barker, Harinda Rajapaksha, Richard Pitts, Tom Gibbs, John Stone, Daniel M Zuckerman, Adrian J Mulholland, Thomas Miller III, Shantenu Jha, Arvind Ramanathan, Lillian Chong, Rommie E Amaro The international journal of high performance computing applications 2023, 37 1, 28 - 44
“A Suite of Advanced Tutorials for the WESTPA 2.0 Rare-Events Sampling Software [Article v0.1],” Anthony T. Bogetti, Jeremy M.G. Leung, John D. Russo, She Zhang, Jeff P. Thompson, Ali S. Saglam, Dhiamn Ray, Rhea C. Abraham, James R. Faeder, Loan Andricioaei, Joshua L. Adelman, Matthew C. Zwier, David N. LeBard, Daniel M. Zuckerman, Lillian T. Chong bioRxiv 2022, 10 4, 510803
“Mechanistic Insights into Passive Membrane Permeability of Drug-Like Molecules from a Weighted Ensemble of Trajectories,” S Zhang, JP Thompson, J Xia, AT Bogetti, F York, AG Skillman, LT Chong, DN LeBard J. Chem. Inf. Model. 2022, 62 8, 1891 - 1904
“WESTPA 2.0: High-Performance Upgrades for Weighted Ensemble Simulations and Analysis of Longer-Timescale Applications,” JD Russo*, S Zhang*, JMG Leung*, AT Bogetti*, JP Thompson, AJ DeGrave, PA Torrillo, AJ Pratt, KF Wong, J Xia, J Copperman, JL Adelman, MC Zwier, DN LeBard, DM Zuckerman, LT Chong J. Chem. Theory Comput. 2022, 18 2, 638 - 649
“A glycan gate controls opening of the SARS-CoV-2 spike protein,” T Sztain, S Ahn, AT Bogetti, L Casalino, JA Goldsmith, E Seitz, RS McCool, FL Kearns, F Acosta-Reyes, S Maji, G Mashayekhi, JA McCammon, A Ourmazd, J Frankm, JS McLellan, LT Chong*, and RE Amaro Nat. Chem 2021, 13, 963 - 968
“A minimal, adaptive binning scheme for weighted ensemble simulations,” PA Torrillo*, AT Bogetti*, and LT Chong J. Phys. Chem. A 2021, 125 7, 1642 - 1649
“The RED scheme: Rate-constant estimation from pre-steady state weighted ensemble simulations,” AJ DeGrave*, AT Bogetti*, and LT Chong bioRxiv 2021, 154 11, 114111
“The Next Frontier for Designing Switchable Proteins: Rational Enhancement of Kinetics,” AT Bogetti, MF Presti, SN Loh, and LT Chong J. Phys. Chem. B 2021, 125 32, 9069 - 9077
“A twist in the road less traveled: The AMBER ff15ipq-m force field for protein mimetics,” AT Bogetti, HE Piston, JMG Leung, CC Cabalteja, DT Yang, AJ DeGrave, KT Debiec, DS Cerutti, DA Case, WS Horne, and LT Chong J. Chem. Phys. 2020, 153 6, 064101
“A suite of tutorials for the WESTPA rare-events sampling software,” AT Bogetti, B Mostofian, A Dickson, AJ Pratt, AS Saglam, PO Harrison, JL Adelman, M Dudek, PA Torrillo, AJ DeGrave, U Adhikari, MC Zwier, DM Zuckerman, and LT Chong,  LiveCoMS 2019, 1 2, 10607
“Large enhancement of response times of a protein conformational switch by computational design,” AJ DeGrave, JH Ha, SN Loh, and LT Chong, Nat. Commun. 2018, 9, 1013
“Links Between the Charge Model and Bonded Parameter Force Constants in Biomolecular Force Fields,” Ceruitt DS, Deibiec KT, Case DA, and Chong LT J. Chem. Phys. 2017, 147, 161730