Biology subjects

Yen, H.-Y.

Publications and source records attributed to Yen, H.-Y..

5 recordsLinked to original sources

bioRxiv2024

Ligand-induced conformational changes in the β1-Adrenergic Receptor Revealed by Hydrogen-Deuterium Exchange Mass Spectrometry

G-Protein Coupled Receptors (GPCRs) constitute the largest family of signalling proteins responsible for translating extracellular stimuli into intracellular functions. When dysregulated, GPCRs drive numerous diseases and are the most targeted proteins in drug discovery. GPCR structural dynamics and activity can be modulated by a wide range of drugs, including full/partial agonists and antagonists. While crucial for developing novel therapeutics targeting GPCRs, the structural dynamics of the receptors associated with their activity upon drug interactions are not yet fully understood. Here, we employ Hydrogen Deuterium Exchange Mass Spectrometry (HDX-MS), to characterise the structural dynamics of turkey {beta}1-adrenergic receptor (t{beta}1AR) in complex with nine ligands, including agonists, partial agonists and antagonists. We show that dynamic signatures across the GPCR structure can be grouped by compound modality. Surprisingly, we discovered repeated destabilisation of the intracellular loop 1 (ICL1) upon full agonist binding and stabilisation upon antagonist binding, suggesting that increased dynamics in this region are an essential component for G-protein recruitment. Multiple sequence alignments and molecular dynamics simulations indicate that L72 in ICL1 plays important structural role. Differential HDX-MS experiment of t{beta}1AR and t{beta}1AR L72A construct in complex with miniGs, in response to various ligands, suggests involvement of ICL1 in stabilising the GDP bound state by influencing the stability of HG helix of miniGs. Overall, our results provide a platform for determining drug modality and highlight how HDX-MS can be used to dissect receptor ligand interaction properties and GPCR mechanism. Significance statementRecent advances in hydrogen-deuterium exchange mass spectrometry have allowed probing conformational signatures of challenging membrane protein assemblies. We studied the structural dynamics of a class A GPCR, namely t{beta}1AR, in response to diverse ligands including agonists, antagonists and partial agonists. We demonstrate that the functional effect of compounds can be discerned by simply profiling the dynamics induced across the receptor, without the need for downstream interaction partners. We showed that ICL1 undergoes a significant change in dynamics between activated and inhibited states consistent with a role in downstream signaling pathways in class A GPCRs.

biophysics↗

bioRxiv2024

Structural Basis of How MGME1 Processes DNA 5' Ends to Maintain Mitochondrial Genome Integrity

Mitochondrial genome maintenance exonuclease 1 (MGME1) helps to ensure mitochondrial DNA (mtDNA) integrity by serving as an ancillary 5' exonuclease for DNA polymerase {gamma}. Curiously, MGME1 exhibits unique bidirectionality in vitro, being capable of degrading DNA from either the 5' or 3' end. The structural basis of this bidirectionally and, particularly, how it processes DNA from the 5' end to assist in mtDNA maintenance remains unclear. Here, we present a crystal structure of human MGME1 in complex with a 5'-overhang DNA, revealing that MGME1 functions as a rigid DNA clamp equipped with a single-strand-(ss)-selective arch, allowing it to slide on single-stranded DNA in either the 5'-to-3' or 3'-to-5' direction. Using a nuclease activity assay, we have dissected the structural basis of MGME1-derived DNA cleavage patterns in which the arch serves as a ruler to determine the cleavage site. We also reveal that MGME1 displays partial DNA-unwinding ability that helps it to better resolve 5'-DNA flaps, providing insights into MGME1-mediated 5'-end processing of nascent mtDNA. Our study builds on previously solved MGME1-DNA complex structures, finally providing the comprehensive functional mechanism of this bidirectional, ss-specific exonuclease.

biochemistry↗

bioRxiv2020

Correlating glycoforms of DC-SIGN with stability using a combination of enzymatic digestion and ion mobility MS

The immune scavenger protein DC-SIGN interacts with glycosylated proteins and has a putative role in facilitating viral infection. How these recognition events take place with different viruses is not clear and the effects of glycosylation on the folding and stability of DC-SIGN have not been reported. Here, we develop and apply a mass spectrometry-based approach to both uncover and characterise the effects of O-glycans on the stability of DC-SIGN. We first quantify the Core 1 & 2 O-glycan structures on the carbohydrate recognition and extracellular domains of the protein via sequential exoglycosidase sequencing. We then use ion mobility mass spectrometry to show how specific O-glycans, and/or single monosaccharide substitutions, alter both the overall collision cross section and the gas-phase stability of the glycoprotein isoforms of DC-SIGN. We find that rather than the mass or length of glycoprotein modifications, the stability of DC-SIGN is better correlated with the number of glycosylation sites. Collectively, our results exemplify a combined multi-dimensional MS approach, proficient in evaluating protein stability in response to both glycoprotein macro- and micro-heterogeneity and adding structural detail to the infection enhancer DC-SIGN.

biophysics↗

bioRxiv2019

A machine learning algorithm predicts molecular subtypes in pancreatic ductal adenocarcinoma with differential response to gemcitabine-based versus FOLFIRINOX chemotherapy

PurposeDevelopment of a supervised machine-learning model capable of predicting clinically relevant molecular subtypes of pancreatic ductal adenocarcinoma (PDAC) from diffusion-weighted-imaging-derived radiomic features.\n\nMethodsThe retrospective observational study assessed 55 surgical PDAC patients. Molecular subtypes were defined by immunohistochemical staining of KRT81. Tumors were manually segmented and 1606 radiomic features were extracted with PyRadiomics. A gradient-boosted-tree algorithm (XGBoost) was trained on 70% of the patients (N=28) and tested on 30% (N=17) to predict KRT81+ vs. KRT81-tumor subtypes. The average sensitivity, specificity and ROC-AUC value were calculated. Chemotherapy response was assessed stratified by subtype. Radiomic feature importance was ranked.\n\nResultsThe mean{+/-}STDEV sensitivity, specificity and ROC-AUC were 0.90{+/-}0.07, 0.92{+/-}0.11, and 0.93{+/-}0.07, respectively. Patients with a KRT81+ subtype experienced significantly diminished median overall survival compared to KRT81-patients (7.0 vs. 22.6 months, HR 1.44, log-rank-test P=<0.001) and a significantly improved response to gemcitabine-based chemotherapy over FOLFIRINOX (10.14 vs. 3.8 months median overall survival, HR 0.85, P=0.037) compared to KRT81-patients, who responded significantly better to FOLFIRINOX over gemcitabine-based treatment (30.8 vs. 13.4 months median overall survival, HR 0.88, P=0.027).\n\nConclusionsThe machine-learning based analysis of radiomic features enables the prediction of subtypes of PDAC, which are highly relevant for overall patient survival and response to chemotherapy.

bioinformatics↗

bioRxiv2018

State-Dependent Lipid Interactions with the A2a Receptor Revealed by MD Simulations Using In Vivo-Mimetic Membranes

G protein-coupled receptors (GPCRs) are the largest family of integral membrane proteins and a major class of drug targets. Membranes are known to have modulatory effects on GPCRs via specific lipid interactions. However, the mechanisms of such modulations in cell membranes and how they influence GPCR functions remain unclear. Here we report coarse-grained MD simulations on the Adenosine A2a receptor embedded in an in vivo mimetic membrane model comprised of 10 different lipid species. Three conformational states of the receptor, i.e. the inactive state, the active state, and the active state with a mini-GS protein bound were simulated to study the impact of protein-lipid interactions on the receptor activation. The simulations revealed three specific lipids (GM3, cholesterol and PIP2) that form stable and preferential interactions with the receptor, differentiating these from bulk lipids such as PS, PE and PC. In total, nine specific lipid-binding sites were revealed. The strength of lipid interaction with these sites depends on the conformational state of the receptor, suggesting that these lipids may regulate the conformational dynamics of the receptor. In particular, we revealed a dual role of PIP2 in promoting A2aR activation, which involves stabilization of both the characteristic outward tilt of helix TM6 within receptor and also the association of A2aR and mini-Gs when the activated complex forms. Structural comparisons suggested that PIP2 may facilitate G activation. Our results reveal likely allosteric effects of bound lipids in regulating the functional behaviour of GPCRs, providing a springboard for design of allosteric modulators of these biomedically important receptors.

biophysics↗