PHENOMS: Open-Source Software for Rust-Accelerated Hydrogen-Bond Analysis in Molecular Dynamics Simulations
5 affiliations
- 1UNC Eshelman School of Pharmacy, Center for Integrative Chemical Biology and Drug Discovery, Division of Chemical Biology and Medicinal Chemistry, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- 2Department of Biochemistry and Biophysics, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
- 3Segal Cancer Proteomics Centre, Lady Davis Institute, Jewish General Hospital, McGill University, Montreal, Quebec H3T 1E2, Canada
- 4Department of Pharmacology, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA
- 5UNC Lineberger Comprehensive Cancer Center, The University of North Carolina at Chapel Hill, Chapel Hill, NC 27599, USA.
Abstract
Hydrogen-deuterium exchange mass spectrometry (HDX-MS) provides powerful insight into protein structure and dynamics, but interpretation of protection patterns at atomic resolution often requires complementary computational modeling. We present PHENOMS, an open-source Python package that integrates molecular dynamics trajectories with HDX-MS data to analyze backbone hydrogen-bond networks by tracking how individual hydrogen bonds and residue-residue contacts form, break, and reorganize throughout the simulations. This residue-level analysis can reveal local structural changes that may be missed by conventional global trajectory metrics. PHENOMS employs a multithreaded, Rust-accelerated computational engine that achieved an average 16-fold speedup (up to 100-fold) over widely used Python-based MD analysis packages in our benchmarks, while retaining individual hydrogen-bond resolution in every trajectory frame. We demonstrate PHENOMS through multiple retrospective case studies using published and in-house datasets, showing that it can recapitulate HDX-MS protection patterns, identify key residues that drive coordinated structural changes, and benchmark the computational efficiency of the approach. With automated quality-control workflows, PHENOMS provides a framework for integrating hydrogen-bond analysis with HDX-MS data or serves as a standalone, high-throughput tool for analyzing MD trajectories for broader applications in protein engineering, drug discovery, and structural biology.
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BibTeX
@misc{novy2026phenoms,
title = {{PHENOMS: Open-Source Software for Rust-Accelerated Hydrogen-Bond Analysis in Molecular Dynamics Simulations}},
author = {Brandon Novy and Shu-Hang Lin and Rishabh Dey and Brenda Temple and Nicole Hajicek and Evgeniy V. Petrotchenko and Christoph H. Borchers and John Sondek and Konstantin I. Popov},
howpublished = {bioRxiv},
year = {2026},
month = oct,
doi = {10.64898/2026.10.26.761768},
url = {https://www.biorxiv.org/content/10.64898/2026.10.26.761768v1},
note = {CC BY},
}
RIS
TY - UNPB
TI - PHENOMS: Open-Source Software for Rust-Accelerated Hydrogen-Bond Analysis in Molecular Dynamics Simulations
AU - Brandon Novy
AU - Shu-Hang Lin
AU - Rishabh Dey
AU - Brenda Temple
AU - Nicole Hajicek
AU - Evgeniy V. Petrotchenko
AU - Christoph H. Borchers
AU - John Sondek
AU - Konstantin I. Popov
PY - 2026
DA - 2026/10/26
PB - bioRxiv
DO - 10.64898/2026.10.26.761768
UR - https://www.biorxiv.org/content/10.64898/2026.10.26.761768v1
AB - Hydrogen-deuterium exchange mass spectrometry (HDX-MS) provides powerful insight into protein structure and dynamics, but interpretation of protection patterns at atomic resolution often requires complementary computational modeling. We present PHENOMS, an open-source Python package that integrates molecular dynamics trajectories with HDX-MS data to analyze backbone hydrogen-bond networks by tracking how individual hydrogen bonds and residue-residue contacts form, break, and reorganize throughout the simulations. This residue-level analysis can reveal local structural changes that may be missed by conventional global trajectory metrics. PHENOMS employs a multithreaded, Rust-accelerated computational engine that achieved an average 16-fold speedup (up to 100-fold) over widely used Python-based MD analysis packages in our benchmarks, while retaining individual hydrogen-bond resolution in every trajectory frame. We demonstrate PHENOMS through multiple retrospective case studies using published and in-house datasets, showing that it can recapitulate HDX-MS protection patterns, identify key residues that drive coordinated structural changes, and benchmark the computational efficiency of the approach. With automated quality-control workflows, PHENOMS provides a framework for integrating hydrogen-bond analysis with HDX-MS data or serves as a standalone, high-throughput tool for analyzing MD trajectories for broader applications in protein engineering, drug discovery, and structural biology.
SN - 2692-8205
ER -