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Implementation of Time-Averaged Restraints with UNRES Coarse-Grained Model of Polypeptide Chains
Nguyen Truong Co1, Cezary Czaplewski1, Emilia A Lubecka2
1Faculty of Chemistry, University of Gdańsk, Fahrenheit Union of Universities, ul. Wita Stwosza 63, 80-308 Gdańsk, Poland.
Journal of Chemical Theory and Computation
|January 24, 2025
Summary
This study introduces a new computational method using nuclear magnetic resonance (NMR) data to model protein structures. The approach enhances the accuracy of conformational ensemble determination for complex proteins like intrinsically disordered proteins (IDPs).
Area of Science:
- Computational biology
- Biophysics
- Structural biology
Background:
- Many essential proteins, including multistate proteins and intrinsically disordered proteins (IDPs) and proteins with intrinsically disordered regions (IDRs), possess dynamic and complex conformational ensembles.
- Accurately modeling these conformational ensembles is crucial for understanding their biological functions.
- Existing all-atom approaches can be computationally intensive and less effective for proteins with diffuse structures.
Purpose of the Study:
- To develop a data-assisted modeling tool for conformational ensembles of challenging protein types.
- To implement time-averaged restraints from nuclear magnetic resonance (NMR) measurements into the UNRES coarse-grained model.
- To improve the accuracy and efficiency of determining protein conformational ensembles.
Main Methods:
- Integration of time-averaged restraints from NMR measurements into the UNRES coarse-grained polypeptide model.
- Development of a numerically stable molecular dynamics variant with time-averaged restraints, conserving energy in microcanonical runs and maintaining temperature in canonical runs.
- Scaling of time-average-restraint-force components with memory window length to effectively influence simulated structures.
Main Results:
- The new approach successfully restores conformational ensembles used for generating ensemble-averaged distances, validated with synthetic restraints.
- Demonstrated improved fitting of ensemble-averaged interproton distances to experimentally determined values for multistate proteins and IDPs/IDRs.
- The method offers advantages over all-atom approaches for proteins with diffuse structures due to faster and more robust conformational searches.
Conclusions:
- The developed tool provides a powerful, data-assisted method for modeling conformational ensembles of proteins, particularly those with complex or disordered structures.
- This approach enhances the accuracy of structural ensemble determination by effectively integrating experimental NMR data.
- The method presents a significant advancement for studying the dynamics and function of challenging protein classes like IDPs and IDRs.
