# Free Energy Sampling of Long-Timescale Biomolecular Dynamics

> **NIH NIH R01** · FLORIDA STATE UNIVERSITY · 2020 · $300,607

## Abstract

Project Summary
Protein aimlessly fluctuates in its surrounding. In order for energy to be effectively channeled
through the complex interaction network and so accurately activate essential transitions, often
hundreds of microseconds, to milliseconds, even to tens of seconds of dynamics are required.
Several decades’ biophysical studies suggest that proteins likely possess characteristic energy
landscapes that encode specific functions. Although theoretical and computational studies have
greatly improved our understanding on protein energy landscape, the existing knowledge is
still very limited. Dominant concepts, such as conformation selection model and hierarchical
energy landscape (conformational slaving) model, have not been adequately understood at the
atomistic level. This is largely due to lack of robust “predictive” molecular dynamics sampling
technique that can enable adequate exploration of long-timescale protein conformational
changes.
The orthogonal space sampling (OSS) scheme, particularly its high order generalization, allows
for systematic acceleration of energy flow as required for thorough sampling enhancement.
Preliminary studies suggest that orders of magnitude of sampling enhancement are plausible.
However a major challenge for OSS has been lack of rigorous algorithmic solution to ensure
sampling robustness. Our recent innovation in the adaptive dynamic reporting (ADR) method
development sheds light on this challenge. In this project, we will systematically develop and
improve this novel “predictive” sampling strategy in the context of protein long-timescale
dynamics and employ to-be-developed methods to quantitatively explore protein large-scale
conformational dynamics and decipher biophysical principles underlying protein functional
dynamics.
This study includes three specific goals: (1) Developing high order orthogonal space tempering
(HOOST) method based on the adaptive dynamic reporting (ADR) kernel to enable robust
“predictive” free energy sampling of biomolecular long-timescale dynamics; (2) Understanding
roles of solvation fluctuation in protein dynamics; (3) Understanding the mechanistic basis of
human Glucokinase (hGK) regulation.

## Key facts

- **NIH application ID:** 9971993
- **Project number:** 1R01GM124621-01A1
- **Recipient organization:** FLORIDA STATE UNIVERSITY
- **Principal Investigator:** Wei Yang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $300,607
- **Award type:** 1
- **Project period:** 2020-05-10 → 2024-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9971993

## Citation

> US National Institutes of Health, RePORTER application 9971993, Free Energy Sampling of Long-Timescale Biomolecular Dynamics (1R01GM124621-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9971993. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*