Biology subjects

Weber, K. C.

Publications and source records attributed to Weber, K. C..

5 recordsLinked to original sources

bioRxiv2026

Bidirectional allosteric ligand regulation in a central glycolytic enzyme

Allosteric regulation enables fine-tuned control of enzyme activity in response to cellular signals, yet its molecular basis often remains unclear. Phosphofructokinase-1 (PFK), the rate-limiting enzyme of glycolysis, is a paradigmatic, well-conserved system whose reaction kinetics conform to the Monod-Wyman-Changeux model of allostery. However, X-ray crystal structures of bacterial PFK orthologs in distinct ligand-bound states do not show the consistent, concerted structural rearrangements expected for classical "relaxed" and "tense" states, revealing a decades-long disconnect between structure and function. We resolve this paradox by integrating biophysical and computational approaches to show that activator and inhibitor binding to the same allosteric pocket differentially reweight the conformational ensemble of Escherichia coli PFK. Activator binding stabilizes conformational substates that preorganize the catalytic site, whereas inhibitor binding upweights apo-like, catalytically incompetent substates. These findings establish an ensemble-based mechanism for PFK regulation and provide an energetic framework for understanding the expanded allosteric architecture of higher PFK orthologs.

biophysics↗

bioRxiv2025

A machine learning method for calculating highly localized protein stabilities

The residue-level free energy of opening ({Delta}Gop) is the ultimate thermodynamic descriptor of localized protein stability, providing valuable information about the protein ensemble at physiologically relevant timescales and conditions. PFNet instantly determines {Delta}Gop for arbitrarily large proteins and complexes from conventional peptide-level hydrogen exchange/mass spectrometry (HX/MS) datasets. It unlocks the full potential of HX/MS, democratizing the method and establishing quantitative, scalable and accessible analysis (https://github.com/glasgowlab/PFNet).

biophysics↗

bioRxiv2025

HXMS: a standardized file format for HX/MS data

MotivationHydrogen/deuterium exchange-mass spectrometry (HX-MS) is a rapidly expanding technique used to investigate protein conformational ensembles. The growing popularity and utility of HX-MS has driven the development of diverse instrumentation and software, resulting in inconsistent, non-standardized data analysis and representation. Most HX-MS data formats also employ only mean deuteration representations of the data rather than full isotopic mass spectra, which reduces the information content of the data and limits downstream quantitative analysis. ResultsInspired by reliable protein structure and genomics data formats, we present HXMS, a unified, lightweight, scalable, and human-readable file format for HX-MS data. The HXMS format preserves the isotopic mass envelopes for all peptides, captures the full experimental time-course including fully deuterated control samples, and contains all other key information. It supports multimodal distributions, post-translational modifications (PTMs), and experimental replicates. To promote compatibility with existing HX-MS workflows, we also developed PFLink, a Python package that converts exported data files from commonly used HX-MS software to the HXMS format. PFLink and the HXMS format will enable more quantitative, higher-resolution data processing, improved data sharing and storage among HX-MS practitioners, future machine learning applications, and further developments in HX-MS analysis. Availability and implementationPFLink is publicly available to install locally on HuggingFace, alongside documentation, or use online at HuggingFace (https://huggingface.co/spaces/glasgow-lab/PFlink). The supplemental information includes sample input files, sample HXMS files, and a generic unfilled PFlink custom CSV file that users may populate with key experimental conditions and results, which can then be read and converted into the HXMS format.

biophysics↗

bioRxiv2025

Conserved energetic changes drive function in an ancient protein fold

While the ongoing revolution in structural biology offers an unprecedented understanding of the relationship between protein structure and function, it also confirms a puzzling, widely applicable principle: protein domains with highly conserved three-dimensional folds can perform radically disparate biochemical functions. To gain insight to this fundamental structural enigma, we mapped the energetic landscapes of a family of bacterial transcription factors and their anciently diverged structural homologs, the periplasmic binding proteins. Using hydrogen exchange/mass spectrometry, bioinformatics, X-ray crystallography, and molecular dynamics, we uncovered an unexpected contrast: despite binding the same sugars, the two families evolved unique "energetic blueprints" to support their distinct functional requirements. To test if differences in energetic ensembles have functional consequences, we rationally redesigned the protein fold for tunable ligand-driven transcriptional responses. Strikingly, energy-driven protein engineering produced synthetic transcription factors with the theoretically anticipated ligand-induced transcriptional outputs. Thus, decoding energetic blueprints among conserved protein folds provides a novel explanation for diverse functional adaptations, paves an alternative roadmap for protein design, and offers a new approach for engineering challenging drug targets.

biophysics↗

bioRxiv2023

MAGPIE: an interactive tool for visualizing and analyzing many simultaneous protein interactions with a binding partner

Quantitative tools to compile and analyze biomolecular interactions among chemically diverse binding partners would improve therapeutics design and aid in the study of molecular evolution. Here we present MAGPIE (Mapping Areas of Genetic Parsimony In Epitopes), a publicly available software package for simultaneously visualizing and analyzing thousands of interactions between a single protein or small molecule ligand (the "target") and all of its protein binding partners ("binders"). MAGPIE generates an interactive 3D visualization from a set of protein complex structures that share the target ligand, as well as sequence logo-style amino acid frequency graphs that show all the amino acids from the set of protein binders that interact with user-defined target ligand positions or chemical groups. MAGPIE highlights all the salt bridge and hydrogen bond interactions made by the target in the visualization and as separate amino acid frequency graphs. Finally, MAGPIE collates the most common target-binder interactions as a list of "hotspots," which can be used to analyze trends or guide the de novo design of protein binders. As an example of the utility of the program, we used MAGPIE to probe how two ligands bind orthologs of a well-conserved glycolytic enzyme for a detailed understanding of evolutionarily conserved interactions involved in its activation and inhibition. MAGPIE is implemented in Python 3 and freely available at https://github.com/glasgowlab/MAGPIE, along with sample datasets, usage examples, and helper scripts to prepare input structures.

bioinformatics↗