Tai-Sung Lee
Rutgers University-New Brunswick, NJ·Chemistry
Many questions in drug discovery and protein engineering come down to one number: how tightly a molecule binds its target. Computer simulations of moving atoms, called molecular dynamics (MD), can estimate this through "free energy" calculations.
- Fields
Chemistry
Biophysics
Computer Science
- Topics
molecular dynamics
MD simulation
free energy calculations
- Grants
- 1 known grant, through Mar 2027
What they work on
- Build a Python-based executing environment that connects AMBER's molecular dynamics engine, a free energy module and user workflow control, so new simulation methods can be added and prototyped quickly.
- Develop new MD and free energy modules that pair object-oriented C++ layers with high-performance GPU kernels, tuned by runtime managers for single-GPU speed and scaling across ensemble simulations.
- Make the simulation modules work with different force fields, the rule sets describing how atoms interact, and with emerging physical models.
- Create a tool that automatically deduces alchemical graphs, maps of which candidate molecules to transform into one another computationally, to show the new engine's scaling and versatility.
More about the research
Free energy measures how favorable binding or another molecular change is. Running these calculations quickly and cheaply on graphics processing units (GPUs) has made them practical. However, new methods, physical models and workflows are spread across many separate programs, including NAMD, CHARMM, Gromacs and OpenMM. No single package brings fast MD, free energy tools and new models together smoothly.
Why it matters
Faster, more accurate and more affordable free energy simulations could help researchers rank drug candidates by predicted binding strength, and could aid protein, nucleic acid and biomaterials design. Because AMBER has more than 30,000 users in academia and industry, a more extensible environment could let new algorithms reach many scientists quickly.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Jonah Vilseck
Indiana University-Purdue University-Indianapolis, IN·Chemistry
Use lambda dynamics free energy simulations to understand how missense mutations in a drug target cause drug resistance, and to identify drug modifications that overcome it.
Jay Ponder
Washington University in St Louis, MO·Chemistry
Develop the AMOEBA+ polarizable multipole force field for DNA and RNA, with parameters generated automatically by the Poltype2 software, to model nucleic acid structure, dynamics and interactions.
Michael Shirts
University of Colorado Boulder, CO·Chemistry
Build systematically improvable force fields with the Open Force Field Initiative, optimized and validated against new thermophysical data, with statistical tests of when added complexity improves accuracy.
The school
Rutgers University-New Brunswick: 57 labs on PI Pages, $837M a year on research, 713 research doctorates a year.
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