Improving Protein Structure Determination by Integrating Ensemble-Driven Molecular Dynamics with Chemical Shift-Based Restraints

We present a protocol for nuclear magnetic resonance (NMR) chemical shift-based structure determination that employs ensemble-driven molecular dynamics (EDMD) for structure refinement. Here, specifically, Chemical-Shift-Rosetta (CS-Rosetta) was applied, followed by EDMD. EDMD eliminates the need to predict chemical shifts at every molecular dynamics (MD) step by defining continuous, differentiable potential energy functions (PEFs) based on dihedral angle distributions from CS-Rosetta models while incorporating the measurement temperature. This yielded a thermodynamically realistic, experiment-based custom force field for each studied system. We benchmarked EDMD against 5 proteins (13.1-19.2 kDa), focusing on systems with nonprotein components and demonstrated its consistent improvement of backbone root-mean-square deviation (RMSD) relative to known reference structures over the original CS-Rosetta ensemble. Moreover, EDMD enhanced the fulfillment of NOE-derived (nuclear Overhauser effect) distance restraints compared to the results of CS-Rosetta and unrestrained MD simulations. EDMD also improved NOE-RASREC-Rosetta (resolution-adapted structural recombination Rosetta protocol supplemented with NOE-based distance restraints) models and maintained the correct protein-ligand conformations. This approach provides an opportunity to refine nonconverged CS-Rosetta structure calculations, where the results would not be interpretable otherwise. EDMD can be generalized to any ensemble with scoring information, enabling refined exploration of the φ/ψ phase space and accurate reinsertion of nonprotein moieties.

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Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2026-02-16
DOI
https://doi.org/10.1021/acs.jcim.5c02358
Primary Topic
Protein Structure and Dynamics
Type
article
Field-Weighted Citation Impact
0.00

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article

Improving Protein Structure Determination by Integrating Ensemble-Driven Molecular Dynamics with Chemical Shift-Based Restraints

Zsolt Fazekas, Márton Gadanecz, Dóra K. Menyhárd, András Perczel
Journal of Chemical Information and Modeling
Protein Structure and Dynamics
article

Improving Protein Structure Determination by Integrating Ensemble-Driven Molecular Dynamics with Chemical Shift-Based Restraints

Zsolt Fazekas, Márton Gadanecz, Dóra K. Menyhárd, András Perczel
article en

Abstract

We present a protocol for nuclear magnetic resonance (NMR) chemical shift-based structure determination that employs ensemble-driven molecular dynamics (EDMD) for structure refinement. Here, specifically, Chemical-Shift-Rosetta (CS-Rosetta) was applied, followed by EDMD. EDMD eliminates the need to predict chemical shifts at every molecular dynamics (MD) step by defining continuous, differentiable potential energy functions (PEFs) based on dihedral angle distributions from CS-Rosetta models while incorporating the measurement temperature. This yielded a thermodynamically realistic, experiment-based custom force field for each studied system. We benchmarked EDMD against 5 proteins (13.1-19.2 kDa), focusing on systems with nonprotein components and demonstrated its consistent improvement of backbone root-mean-square deviation (RMSD) relative to known reference structures over the original CS-Rosetta ensemble. Moreover, EDMD enhanced the fulfillment of NOE-derived (nuclear Overhauser effect) distance restraints compared to the results of CS-Rosetta and unrestrained MD simulations. EDMD also improved NOE-RASREC-Rosetta (resolution-adapted structural recombination Rosetta protocol supplemented with NOE-based distance restraints) models and maintained the correct protein-ligand conformations. This approach provides an opportunity to refine nonconverged CS-Rosetta structure calculations, where the results would not be interpretable otherwise. EDMD can be generalized to any ensemble with scoring information, enabling refined exploration of the φ/ψ phase space and accurate reinsertion of nonprotein moieties.

Journal of Chemical Information and ModelingVol. 66(5)
Eötvös Loránd University (HU)
European Commission, Innovációs és Technológiai Minisztérium, Nemzeti Kutatási, Fejlesztési és Innovaciós Alap, National Research, Development and Innovation Office
Affordable and clean energy
Openalex Percentile: Top 54%
Protein Structure and Dynamics
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