Restraining Interproton Angular and Distance Dynamics with KEnRef

Despite the increase in computational power, traditional NMR structure determination remains semiquantitative or even qualitative, especially because of the complicated mathematics involved in modeling the nuclear dipole-dipole interactions in nuclear Overhauser effect (NOE) spectra. Even advanced exact NOE (eNOE) and residual dipolar coupling (RDC) methods neglect the effects of interproton angular motion, limiting the physical realism of generated ensembles. We present KEnRef, an open-source C++ library implementing the Kinetic Ensemble approach to refine multistate protein structures using restraints that rigorously account for interproton distance and angular fluctuation. We introduce a loss function, using fractional exponents, that balances sensitivity across the target distance range. KEnRef interfaces with GROMACS to introduce forces calculated at each molecular dynamics time step. On synthetic ubiquitin data sets, single-structure simulations with a fractional exponent of 0.25 achieved an interproton RMSD of ∼0.2 Å and convergence time down to 2 ns. Two-structure ensembles showed 100-fold restraint energy decreases at high force constants and reproduced both rigid and dynamic behaviors with distance and angular fluctuation highly correlated to reference data (<i>R</i> > 0.85), validating KEnRef's capacity to capture localized motions. KEnRef enables integrated refinement of distance and angular fluctuations, yielding ensembles that faithfully model both structural and dynamic properties. Its performance on synthetic benchmark tests and modular design lay the foundation for ultraquantitative NMR-based ensemble refinement.

Authors

Institutions

Publication Details

Journal
The Journal of Physical Chemistry B
Published
2026-03-09
DOI
https://doi.org/10.1021/acs.jpcb.5c08554
Primary Topic
Advanced NMR Techniques and Applications
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Restraining Interproton Angular and Distance Dynamics with KEnRef

Amr Alhossary, Colin A. Smith
The Journal of Physical Chemistry B
Advanced NMR Techniques and Applications
article

Restraining Interproton Angular and Distance Dynamics with KEnRef

Amr Alhossary, Colin A. Smith
article en

Abstract

Despite the increase in computational power, traditional NMR structure determination remains semiquantitative or even qualitative, especially because of the complicated mathematics involved in modeling the nuclear dipole-dipole interactions in nuclear Overhauser effect (NOE) spectra. Even advanced exact NOE (eNOE) and residual dipolar coupling (RDC) methods neglect the effects of interproton angular motion, limiting the physical realism of generated ensembles. We present KEnRef, an open-source C++ library implementing the Kinetic Ensemble approach to refine multistate protein structures using restraints that rigorously account for interproton distance and angular fluctuation. We introduce a loss function, using fractional exponents, that balances sensitivity across the target distance range. KEnRef interfaces with GROMACS to introduce forces calculated at each molecular dynamics time step. On synthetic ubiquitin data sets, single-structure simulations with a fractional exponent of 0.25 achieved an interproton RMSD of ∼0.2 Å and convergence time down to 2 ns. Two-structure ensembles showed 100-fold restraint energy decreases at high force constants and reproduced both rigid and dynamic behaviors with distance and angular fluctuation highly correlated to reference data (<i>R</i> > 0.85), validating KEnRef's capacity to capture localized motions. KEnRef enables integrated refinement of distance and angular fluctuations, yielding ensembles that faithfully model both structural and dynamic properties. Its performance on synthetic benchmark tests and modular design lay the foundation for ultraquantitative NMR-based ensemble refinement.

The Journal of Physical Chemistry BVol. 130(11)
Wesleyan University (US)
Affordable and clean energy
Openalex Percentile: Top 30%
Advanced NMR Techniques and Applications
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.