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DMS/NIGMS 2: Predicting rare events in biomolecular systems with machine learning and short molecular dynamics trajectories

Award Number: R01GM169399
ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 08/10/2026
PERIOD OF PERFORMANCE END DATE: 05/31/2030

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DMS/NIGMS 2: Predicting rare events in biomolecular systems with machine learning and short molecular dynamics trajectories - PROJECT SUMMARY (See instructions): Molecular dynamics simulations allow molecular mechanisms to be studied with atomistic detail. By averaging over long trajectories, one can estimate dynamical statistics such as mean first-passage times or committors. These quantities are integral to rate theories. However, events of interest are rare, often occurring on timescales several orders of magnitude longer than the timescales of microscopic fluctuations. For example, the dissociation of the insulin dimer, a prerequisite for insulin to bind its cellular receptor to initiate signaling, can take hours to days even though its bond vibrations demand a femtosecond integration time step. In such cases, collecting chemical-kinetic statistics by integrating the system's equations of motion and directly computing averages (sample means) requires prohibitive amounts of computational resources. This project will develop schemes capable of characterizing a rare event under study using a dataset of short trajectories, bypassing the need to generate trajectories long enough to exhibit the event. These short-trajectory samples can be generated either using rare-event sampling schemes of the type developed by the team in the past, or they can be generated by directly seeding initial conditions throughout the state space. The proposed approach provides approximations of the functions needed to represent key quantities like transition rates as well as a strategy to adapt the simulation model to better match experimentally obtained estimates of such quantities.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2026 ( Subtotal = $185,462 )
2026	2026	NEW YORK UNIVERSITY	70 WASHINGTON SQ S FL 11	NEW YORK	NY	10012	NEW YORK	USA	Biomedical Research and Research Training	000	1	8/7/2026	NEW	$185,462
														Subtotal = $185,462

Grand Total All Awards = $185,462

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DMS/NIGMS 2: Predicting rare events in biomolecular systems with machine learning and short molecular dynamics trajectories

Award Number: R01GM169399

ORGANIZATION: NATIONAL INSTITUTE OF GENERAL MEDICAL SCIENCES

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 08/10/2026

PERIOD OF PERFORMANCE END DATE: 05/31/2030

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