Biology subjects

Glasgow, A.

Publications and source records attributed to Glasgow, A..

12 recordsLinked to original sources

bioRxiv2026

Manganese availability determines insulin sensitivity by enhancing Akt activity

Insulin signaling is a critical determinant of metabolic health, and impairments in insulin action contribute to the development of type 2 diabetes. The kinase Akt is a central mediator of insulin signaling and is required for insulin's suppression of hepatic glucose output. Although the regulation of Akt by the insulin receptor-PI3K pathway is well understood, there are instances in which signaling downstream of Akt is dissociated from proximal insulin signaling, for example in insulin resistance. Nonetheless, little is known about PI3K-independent mechanisms of Akt regulation. Here, we discovered that hepatocyte manganese concentrations are a key determinant of PI3K-independent Akt function in vivo. We further demonstrated that manganese increases Akt's catalytic efficiency, and quantitative phosphoproteomics revealed that manganese and insulin act additively to enhance Akt activity. Moreover, we uncovered that hepatic manganese concentrations fluctuate during fasting and feeding via carbohydrate-dependent transcriptional regulation of the manganese efflux transporter Slc30a10. This dynamic metal-signaling axis provides a mechanistic link between nutrient status and Akt activation, and suggests a molecular explanation for the glucose-lowering effects of manganese observed in humans. Our findings establish manganese as a physiologically regulated cofactor for Akt and position metal bioavailability as a previously unrecognized layer of insulin signaling control.

physiology↗

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

A Hotspot Phosphorylation Site on SHP2 Drives Oncoprotein Activation and Drug Resistance

SHP2 is a phosphatase and a critical mediator of receptor tyrosine kinase (RTK)-driven RAS/mitogen-activated protein kinase (MAPK) signaling. Despite promising preclinical data, SHP2 inhibitors have shown minimal clinical efficacy, with no defined clinical mechanisms of primary resistance. Here, we elucidate phosphorylation of SHP2 at tyrosine 62 (pY62) as a hotspot phosphorylation site in the proteome and RTK-driven tumor types in patients. We demonstrate that SRC family kinases directly phosphorylate SHP2 at Y62, downstream of but not directly phosphorylated by RTKs. Using biochemical and biophysical analyses, we show that SHP2 Y62D enforces an open, active conformation, resulting in constitutive phosphatase activation that is sufficient to activate MAPK signaling and confer resistance to allosteric SHP2 inhibitors. These findings establish that SHP2 pY62 is a phosphorylation hotspot phenocopying mutational activation, a mechanism of primary resistance to SHP2 inhibitors, and a cancer drug target distinct from wildtype SHP2. Statement of significanceThis study identifies phosphorylation of SHP2 at tyrosine 62 (pY62) as a conserved mechanism of resistance to allosteric SHP2 inhibitors. By stabilizing an open, active SHP2 conformation, pY62 phenocopies oncogenic PTPN11 mutations and sustains MAPK signaling across cancer types. These findings redefine SHP2 inhibitor resistance as a phosphorylation-driven, target-intrinsic process, nominate pY62 as a potential biomarker for therapeutic response, and propose phosphorylated SHP2 as a distinct drug target.

cancer biology↗

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↗

bioRxiv2024

Site-resolved energetic information from HX/MS experiments

High-resolution energetic information about protein conformational ensembles is essential for understanding protein function, yet remains challenging to obtain. We present PIGEON-FEATHER, a method for calculating ensemble free energies of opening ({Delta}Gop) at single- or near-single-amino acid resolution for proteins of all sizes from hydrogen exchange/mass spectrometry (HX/MS) data. PIGEON-FEATHER disambiguates and reconstructs all experimentally measured HX/MS isotopic mass envelopes using a Bayesian Monte Carlo sampling approach. We applied PIGEON-FEATHER to reveal how E. coli and human dihydrofolate reductases (ecDHFR, hDHFR) have evolved distinct ensembles. We show how two competitive inhibitors bind these orthologs differently, solving the longstanding mystery of why both therapeutic molecules inhibit hDHFR, but only one inhibits ecDHFR. Extending PIGEON-FEATHER to a large protein-DNA complex, we mapped ligand-induced ensemble reweighting in the E. coli lac repressor to describe the functional switching mechanism crucial for transcriptional regulation.

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↗

bioRxiv2023

An evolutionarily conserved strategy for ribosome binding and inhibition by β-coronavirus non-structural protein 1

An important pathogenicity factor of SARS-CoV-2 and related coronaviruses is Nsp1, which suppresses host gene expression and stunts antiviral signaling. SARS-CoV-2 Nsp1 binds the ribosome to inhibit translation through mRNA displacement and induces degradation of host mRNAs through an unknown mechanism. Here we show that Nsp1-dependent host shutoff is conserved in diverse coronaviruses, but only Nsp1 from {beta}-CoV inhibits translation through ribosome binding. The C-terminal domain of all {beta}-CoV Nsp1s confers high-affinity ribosome-binding despite low sequence conservation. Modeling of interactions of four Nsp1s to the ribosome identified few absolutely conserved amino acids that, together with an overall conservation in surface charge, form the {beta}-CoV Nsp1 ribosome-binding domain. Contrary to previous models, the Nsp1 ribosome-binding domain is an inefficient translation inhibitor. Instead, the Nsp1-CTD likely functions by recruiting Nsp1s N-terminal "effector" domain. Finally, we show that a viral cis-acting RNA element has co-evolved to fine-tune SARS-CoV-2 Nsp1 function, but does not provide similar protection against Nsp1 from related viruses. Together, our work provides new insight into the diversity and conservation of ribosome-dependent host-shutoff functions of Nsp1, knowledge that could aide future efforts in pharmacological targeting of Nsp1 from SARS-CoV-2, but also related human-pathogenic {beta}-coronaviruses. Our study also exemplifies how comparing highly divergent Nsp1 variants can help to dissect the different modalities of this multi-functional viral protein.

biochemistry↗

bioRxiv2022

Computational pipeline provides mechanistic understanding of Omicron variant of concern neutralizing engineered ACE2 receptor traps

The SARS-CoV-2 Omicron variant, with 15 mutations in Spike receptor binding domain (Spike-RBD), renders virtually all clinical monoclonal antibodies against WT SARS-CoV-2 ineffective. We recently engineered the SARS-CoV-2 host entry receptor, ACE2, to tightly bind WT-Spike-RBD and prevent viral entry into host cells ("receptor traps"). Here we determine cryo-EM structures of our receptor traps in complex with full length Spike. We develop a multi-model pipeline combining Rosetta protein modeling software and cryo-EM to allow interface energy calculations even at limited resolution and identify interface side chains that allow for high affinity interactions between our ACE2 receptor traps and Spike-RBD. Our structural analysis provides a mechanistic rationale for the high affinity (0.53 - 4.2nM) binding of our ACE2 receptor traps to Omicron-RBD confirmed with biolayer interferometry measurements. Finally, we show that ACE2 receptor traps potently neutralize Omicron- and Delta-pseudotyped viruses, providing alternative therapeutic routes to combat this evolving virus.

biochemistry↗

bioRxiv2021

Ligand-induced changes in dynamics mediate long-range allostery in the lac repressor

Allostery, broadly defined as a proteins functional response to distal perturbations, is fundamental to biological regulation. In classical models, allosteric ligand binding produces a defined set of structural changes in the protein, resulting in a different low-energy conformation. Proteins that undergo ligand-induced allostery with few observable structural changes therefore frustrate interpretations by classical models. Here we used hydrogen-deuterium exchange with mass spectrometry (HDX/MS) to map the allosteric effects in a paradigm ligand-responsive allosteric transcription factor, the lac repressor (LacI). X-ray crystal structures of the core domain of LacI bound to different small molecule ligands, or the DNA operator, show less than 1.5 [A] difference in the protein all-atom root-mean-square-deviation (RMSD) between any two structures. Despite this high degree of similarity among static structures, our HDX/MS experiments reveal widespread and unexpected differences in the flexibility of secondary structures in the LacI core domain in each functional state. We propose a model in which ligand binding allosterically switches the functional response of the repressor by selectively changing the dynamics of particular secondary structure elements relative to each other, shifting the conformational ensemble of the protein between mutually incompatible DNA-bound and inducer-bound states. Our model also provides a mechanistic context for the altered functions of thousands of documented LacI mutants. Furthermore, our approach provides a platform for characterizing and engineering allosteric responses in proteins.

biophysics↗

bioRxiv2020

Engineered ACE2 receptor traps potently neutralize SARS-CoV-2

An essential mechanism for SARS-CoV-1 and -2 infection begins with the viral spike protein binding to the human receptor protein angiotensin-converting enzyme II (ACE2). Here we describe a stepwise engineering approach to generate a set of affinity optimized, enzymatically inactivated ACE2 variants that potently block SARS-CoV-2 infection of cells. These optimized receptor traps tightly bind the receptor binding domain (RBD) of the viral spike protein and prevent entry into host cells. We first computationally designed the ACE2-RBD interface using a two-stage flexible protein backbone design process that improved affinity for the RBD by up to 12-fold. These designed receptor variants were affinity matured an additional 14-fold by random mutagenesis and selection using yeast surface display. The highest affinity variant contained seven amino acid changes and bound to the RBD 170-fold more tightly than wild-type ACE2. With the addition of the natural ACE2 collectrin domain and fusion to a human Fc domain for increased stabilization and avidity, the most optimal ACE2 receptor traps neutralized SARS-CoV-2 pseudotyped lentivirus and authentic SARS-CoV-2 virus with half-maximal inhibitory concentrations (IC50) in the 10-100 ng/ml range. Engineered ACE2 receptor traps offer a promising route to fighting infections by SARS-CoV-2 and other ACE2-utilizing coronaviruses, with the key advantage that viral resistance would also likely impair viral entry. Moreover, such traps can be pre-designed for viruses with known entry receptors for faster therapeutic response without the need for neutralizing antibodies isolated or generated from convalescent patients.

bioengineering↗