Amish Patel
University of Pennsylvania, PA·Biophysics
Proteins constantly bind other molecules, including short protein fragments, sugars and other proteins, and many diseases involve these interactions. Computers can now predict and even design protein structures.
- Fields
Biophysics
Chemistry
Engineering
- Topics
molecular simulation
enhanced sampling
protein hydration
- Grants
- 1 known grant, through May 2030
What they work on
- Develop hydration-based, enhanced-sampling molecular simulations that capture how water's hydrogen-bond network reorganizes when proteins change shape and bind, as a basis for predicting binding strength and speed.
- Characterize how reader proteins recognize methylated histone tails, chemically marked segments of DNA-packaging proteins, using the new simulations alongside experimental collaborators to explain binding specificity.
- Predict and modulate binding between galectins, carbohydrate-binding proteins, and their sugar partners, testing simulation predictions against collaborators' experiments.
- Model how single-domain antibodies bind the p38 MAP kinase, a signaling enzyme, to inform the design of tight-binding modulators of protein–protein interactions.
More about the research
A structure alone, however, does not reveal how tightly or how quickly two molecules will bind. Water is a major reason. When molecules bind, the surrounding water must rearrange its network of hydrogen bonds. Current drug-design methods handle this with simple additive rules and assume proteins are rigid.
Why it matters
Many potential therapies work by blocking or adjusting protein interactions, but designing tight binders from structure alone remains unreliable. Simulation methods that account for water and protein flexibility could help researchers predict binding strength more accurately. They could also help design better modulators of interactions with peptides, carbohydrates and other proteins, which play roles in many cellular processes and diseases.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
John Franck
Syracuse University, NY·Chemistry·Early-career
Build instrumentation and open-source analysis software that turn liquid-state Overhauser Dynamic Nuclear Polarization (ODNP) into a routine method for characterizing hydration water around macromolecules.
Ao Ma
University of Illinois Chicago, IL·Biophysics
Compute true reaction coordinates for ligand binding using energy flow theory and the generalized work functional method, then simulate natural, unbiased binding in HIV-1 protease and PDZ domains.
Alberto Perez
University of Florida, FL·Biophysics
Map the binding partners of the ET domain of BET proteins: identify candidates computationally, rank the strongest with machine learning and physics-based methods, and check top leads with NMR experiments.
The school
University of Pennsylvania: 90 labs on PI Pages, $2.2B a year on research, 750 research doctorates a year.
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