Biology subjects

Le Huray, K. I. P.

Publications and source records attributed to Le Huray, K. I. P..

3 recordsLinked to original sources

bioRxiv2024

To 200,000 m/z and beyond: native electron capture charge reduction mass spectrometry deconvolves heterogeneous signals in large biopharmaceutical analytes

Great progress has been made in the detection of large biomolecular analytes by native mass spectrometry, however characterizing highly heterogeneous samples remains challenging due to the presence of many overlapping signals from complex ion distributions. Electron-capture charge reduction (ECCR), in which a protein cation captures free electrons without apparent dissociation, can dealign overlapping signals by shifting the ions to lower charge states. The concomitant shift to higher m/z also facilitates the exploration of instrument upper m/z limits if large complexes are used. Here we perform native ECCR on the bacterial chaperonin GroEL and megadalton scale adeno-associated virus (AAV) capsid assemblies on the Q Exactive UHMR mass spectrometer. Charge reduction of AAV8 capsids by up to 90% pushes signals well above 100,000 m/z and enables charge state resolution and mean mass determination of these highly heterogeneous samples, even for capsids loaded with genetic cargo. With minor instrument modifications the UHMR can detect charge reduced ion signals beyond 200,000 m/z. This work demonstrates the utility of ECCR for deconvolving heterogeneous signals in native mass spectrometry and presents the highest m/z signals ever recorded on an Orbitrap instrument, opening up the use of Orbitrap native mass spectrometry for heavier analytes than ever before.

molecular biology↗

bioRxiv2023

Rapid Prediction of Lipid Interaction Sites on Pleckstrin Homology Domains Using Deep Graph Neural Networks and Molecular Dynamics Simulations

Interactions between membrane proteins and specific lipid molecules play a major role in cellular biology, but characterizing these interactions can be challenging due to the complexity and physicochemical properties of membranes. Molecular dynamics (MD) simulations allow researchers to predict protein-lipid interaction sites and generate testable models. MD simulations are however computationally expensive and require specialist expertise. In this study, we demonstrate that graph neural networks trained on coarse-grained MD simulation data can predict phosphoinositide lipid interaction sites on Pleckstrin Homology (PH) domain structures, a large family of membrane binding domains. The predictions are comparable to the results of simulations and require only seconds to compute. Comparison with experimental data shows that the model can predict known phosphoinositide interaction sites and can be used to form hypotheses for PH domains for which there is no experimental data. This model is a next generation tool for predicting protein-lipid interactions of PH domains and offers a basis for further development of models applicable to other membrane protein classes.

biophysics↗

bioRxiv2021

Systematic simulation of the interactions of Pleckstrin homology domains with membranes

Pleckstrin homology (PH) domains can recruit proteins to membranes by recognition of phosphatidylinositol phosphates (PIPs). Here we report the systematic simulation of the interactions of 100 mammalian PH domains with PIP containing model membranes. Comparison with crystal structures of PH domains bound to PIP analogues demonstrates that our method correctly identifies interactions at known canonical and non-canonical sites, while revealing additional functionally important sites for interaction not observed in the crystal structure, such as for P-Rex1 and Akt1. At the family level, we find that the {beta}1 and {beta}2 strands and their connecting loop constitute the primary PIP interaction site for the majority of PH domains, but we highlight interesting exceptional cases. Simultaneous interaction with multiple PIPs and clustering of PIPs induced by PH domain binding are also observed. Our findings support a general paradigm for PH domain membrane association involving multivalent interactions with anionic lipids. TeaserSimulating the binding of 100 Pleckstrin homology domains to cell membranes reveals patterns in their lipid interactions.

biophysics↗