Unraveling membrane properties at the organelle-level with LipidDyn

Cellular membranes are formed from many different lipids in various amounts and proportions depending on the subcellular localization. The lipid composition of membranes is sensitive to changes in the cellular environment, and their alterations are linked to several diseases, including cancer. Lipids not only form lipid-lipid interactions but also interact with other biomolecules, including proteins, profoundly impacting each other. Molecular dynamics (MD) simulations are a powerful tool to study the properties of cellular membranes and membrane-protein interactions on different timescales and at varying levels of resolution. Over the last few years, software and hardware for biomolecular simulations have been optimized to routinely run long simulations of large and complex biological systems. On the other hand, high-throughput techniques based on lipidomics provide accurate estimates of the composition of cellular membranes at the level of subcellular compartments. The community needs computational tools for lipidomics and simulation data effectively interacting to better understand how changes in lipid compositions impact membrane function and structure. Lipidomic data can be analyzed to design biologically relevant models of membranes for MD simulations. Similar applications easily result in a massive amount of simulation data where the bottleneck becomes the analysis of the data to understand how membrane properties and membrane-protein interactions are changing in the different conditions. In this context, we developed LipidDyn, an in silico pipeline to streamline the analyses of MD simulations of membranes of different compositions. Once the simulations are collected, LipidDyn provides average properties and time series for several membrane properties such as area per lipid, thickness, diffusion motions, the density of lipid bilayers, and lipid enrichment/depletion. The calculations exploit parallelization and the pipelines include graphical outputs in a publication-ready form. We applied LipidDyn to different case studies to illustrate its potential, including membranes from cellular compartments and transmembrane protein domains. LipidDyn is implemented in Python and relies on open-source libraries. LipidDyn is available free of charge under the GNU General Public License from https://github.com/ELELAB/LipidDyn.

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Predicting the Structure and Dynamics of Membrane Protein GerAB from Bacillus subtilis

International Journal of Molecular Sciences ◽

10.3390/ijms22073793 ◽

2021 ◽

Vol 22 (7) ◽

pp. 3793

Author(s):

Sophie Blinker ◽

Jocelyne Vreede ◽

Peter Setlow ◽

Stanley Brul

Keyword(s):

Bacillus Subtilis ◽

Membrane Protein ◽

Spore Germination ◽

Structural Information ◽

Transmembrane Protein ◽

Homology Modelling ◽

Water Channel ◽

Md Simulations ◽

Integral Membrane Protein ◽

Starting Point

Bacillus subtilis forms dormant spores upon nutrient depletion. Germinant receptors (GRs) in spore’s inner membrane respond to ligands such as L-alanine, and trigger spore germination. In B. subtilis spores, GerA is the major GR, and has three subunits, GerAA, GerAB, and GerAC. L-Alanine activation of GerA requires all three subunits, but which binds L-alanine is unknown. To date, how GRs trigger germination is unknown, in particular due to lack of detailed structural information about B subunits. Using homology modelling with molecular dynamics (MD) simulations, we present structural predictions for the integral membrane protein GerAB. These predictions indicate that GerAB is an α-helical transmembrane protein containing a water channel. The MD simulations with free L-alanine show that alanine binds transiently to specific sites on GerAB. These results provide a starting point for unraveling the mechanism of L-alanine mediated signaling by GerAB, which may facilitate early events in spore germination.

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Discovery of novel membrane binding structures and functions

Biochemistry and Cell Biology ◽

10.1139/bcb-2014-0074 ◽

2014 ◽

Vol 92 (6) ◽

pp. 555-563 ◽

Cited By ~ 17

Author(s):

Irina Kufareva ◽

Marc Lenoir ◽

Felician Dancea ◽

Pooja Sridhar ◽

Eugene Raush ◽

...

Keyword(s):

Membrane Protein ◽

Lipid Bilayers ◽

Protein Interactions ◽

Membrane Binding ◽

Three Dimensional ◽

Intrinsic Activity ◽

Resonance Spectroscopy ◽

Pleckstrin Homology ◽

Lysobisphosphatidic Acid ◽

Membrane Interactive

The function of a protein is determined by its intrinsic activity in the context of its subcellular distribution. Membranes localize proteins within cellular compartments and govern their specific activities. Discovering such membrane-protein interactions is important for understanding biological mechanisms and could uncover novel sites for therapeutic intervention. We present a method for detecting membrane interactive proteins and their exposed residues that insert into lipid bilayers. Although the development process involved analysis of how C1b, C2, ENTH, FYVE, Gla, pleckstrin homology (PH), and PX domains bind membranes, the resulting membrane optimal docking area (MODA) method yields predictions for a given protein of known three-dimensional structures without referring to canonical membrane-targeting modules. This approach was tested on the Arf1 GTPase, ATF2 acetyltransferase, von Willebrand factor A3 domain, and Neisseria gonorrhoeae MsrB protein and further refined with membrane interactive and non-interactive FAPP1 and PKD1 pleckstrin homology domains, respectively. Furthermore we demonstrate how this tool can be used to discover unprecedented membrane binding functions as illustrated by the Bro1 domain of Alix, which was revealed to recognize lysobisphosphatidic acid (LBPA). Validation of novel membrane-protein interactions relies on other techniques such as nuclear magnetic resonance spectroscopy (NMR), which was used here to map the sites of micelle interaction. Together this indicates that genome-wide identification of known and novel membrane interactive proteins and sites is now feasible and provides a new tool for functional annotation of the proteome.

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Controlling transmembrane protein concentration and orientation in supported lipid bilayers

Chemical Communications ◽

10.1039/c7cc01023k ◽

2017 ◽

Vol 53 (30) ◽

pp. 4250-4253 ◽

Cited By ~ 7

Author(s):

P. Bao ◽

M. L. Cartron ◽

K. H. Sheikh ◽

B. R. G. Johnson ◽

C. N. Hunter ◽

...

Keyword(s):

Membrane Protein ◽

Lipid Bilayers ◽

Electric Fields ◽

Protein Concentration ◽

Transmembrane Protein ◽

Fold Increase ◽

Supported Lipid Bilayers

The trans-membrane protein–proteorhodopsin (pR) has been incorporated into supported lipid bilayers (SLB). In-plane electric fields have been used to manipulate the orientation and concentration of these proteins, within the SLB, through electrophoresis leading to a 25-fold increase concentration of pR.

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Reshaping biological membranes in endocytosis: crossing the configurational space of membrane-protein interactions

Biological Chemistry ◽

10.1515/hsz-2013-0242 ◽

2014 ◽

Vol 395 (3) ◽

pp. 275-283 ◽

Cited By ~ 11

Author(s):

Mijo Simunovic ◽

Patricia Bassereau

Keyword(s):

Membrane Protein ◽

Protein Interactions ◽

Molecular Mechanisms ◽

Full Range ◽

Biological Membranes ◽

Membrane Properties ◽

Physical Parameters ◽

Membrane Remodeling ◽

Experimental Conditions ◽

The Way

Abstract Lipid membranes are highly dynamic. Over several decades, physicists and biologists have uncovered a number of ways they can change the shape of membranes or alter their phase behavior. In cells, the intricate action of membrane proteins drives these processes. Considering the highly complex ways proteins interact with biological membranes, molecular mechanisms of membrane remodeling still remain unclear. When studying membrane remodeling phenomena, researchers often observe different results, leading them to disparate conclusions on the physiological course of such processes. Here we discuss how combining research methodologies and various experimental conditions contributes to the understanding of the entire phase space of membrane-protein interactions. Using the example of clathrin-mediated endocytosis we try to distinguish the question ‘how can proteins remodel the membrane?’ from ‘how do proteins remodel the membrane in the cell?’ In particular, we consider how altering physical parameters may affect the way membrane is remodeled. Uncovering the full range of physical conditions under which membrane phenomena take place is key in understanding the way cells take advantage of membrane properties in carrying out their vital tasks.

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Membrane Protein–Lipid Interactions Probed Using Mass Spectrometry

Annual Review of Biochemistry ◽

10.1146/annurev-biochem-013118-111508 ◽

2019 ◽

Vol 88 (1) ◽

pp. 85-111 ◽

Cited By ~ 35

Author(s):

Jani Reddy Bolla ◽

Mark T. Agasid ◽

Shahid Mehmood ◽

Carol V. Robinson

Keyword(s):

Mass Spectrometry ◽

Membrane Protein ◽

Lipid Bilayers ◽

Protein Interactions ◽

Native Mass Spectrometry ◽

Lipid Interactions ◽

X Ray Crystallography ◽

Native Ms ◽

Molecular Aspects ◽

Lipid Protein Interactions

Membrane proteins that exist in lipid bilayers are not isolated molecular entities. The lipid molecules that surround them play crucial roles in maintaining their full structural and functional integrity. Research directed at investigating these critical lipid–protein interactions is developing rapidly. Advancements in both instrumentation and software, as well as in key biophysical and biochemical techniques, are accelerating the field. In this review, we provide a brief outline of structural techniques used to probe protein–lipid interactions and focus on the molecular aspects of these interactions obtained from native mass spectrometry (native MS). We highlight examples in which lipids have been shown to modulate membrane protein structure and show how native MS has emerged as a complementary technique to X-ray crystallography and cryo–electron microscopy. We conclude with a short perspective on future developments that aim to better understand protein–lipid interactions in the native environment.

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A bimolecular fluorescence complementation flow cytometry screen for membrane protein interactions

Scientific Reports ◽

10.1038/s41598-021-98810-2 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Florian Schmitz ◽

Jessica Glas ◽

Richard Neutze ◽

Kristina Hedfalk

Keyword(s):

Flow Cytometry ◽

Membrane Proteins ◽

Membrane Protein ◽

Protein Interactions ◽

Protein Complexes ◽

Bimolecular Fluorescence Complementation ◽

Cellular Environment ◽

Fluorescence Complementation ◽

Bimolecular Fluorescence

AbstractInteractions between membrane proteins within a cellular environment are crucial for all living cells. Robust methods to screen and analyse membrane protein complexes are essential to shed light on the molecular mechanism of membrane protein interactions. Most methods for detecting protein:protein interactions (PPIs) have been developed to target the interactions of soluble proteins. Bimolecular fluorescence complementation (BiFC) assays allow the formation of complexes involving PPI partners to be visualized in vivo, irrespective of whether or not these interactions are between soluble or membrane proteins. In this study, we report the development of a screening approach which utilizes BiFC and applies flow cytometry to characterize membrane protein interaction partners in the host Saccharomyces cerevisiae. These data allow constructive complexes to be discriminated with statistical confidence from random interactions and potentially allows an efficient screen for PPIs in vivo within a high-throughput setup.

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Landscapes of Membrane Protein Interactions from High-Throughput MD Simulations using the Daft Approach

Biophysical Journal ◽

10.1016/j.bpj.2014.11.2885 ◽

2015 ◽

Vol 108 (2) ◽

pp. 526a

Author(s):

Tsjerk A. Wassenaar ◽

Kristyna Pluhackova ◽

Anastassiia Moussatova ◽

Durba Sengupta ◽

Siewert J. Marrink ◽

...

Keyword(s):

Membrane Protein ◽

High Throughput ◽

Protein Interactions ◽

Md Simulations

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SNARE Complex Alters the Interactions of the Ca2+ sensor Synaptotagmin 1 with Lipid Bilayers

10.1101/2020.06.19.161752 ◽

2020 ◽

Author(s):

Maria Bykhovskaia

Keyword(s):

Lipid Bilayers ◽

Protein Complex ◽

Transmembrane Protein ◽

Md Simulations ◽

Snare Complex ◽

Presynaptic Membrane ◽

Lipid Complex ◽

C2 Domains ◽

Atom Model ◽

Synaptotagmin 1

AbstractRelease of neuronal transmitters from nerve terminals is triggered by the molecular Ca2+ sensor Synaptotagmin 1 (Syt1). Syt1 is a transmembrane protein attached to the synaptic vesicle (SV), and its cytosolic region comprises two domains, C2A and C2B, which are thought to penetrate into lipid bilayers upon Ca2+ binding. Prior to fusion, SVs become attached to the presynaptic membrane (PM) by the four-helical SNARE complex, which binds the C2B domain of Syt1. To understand how the interactions of Syt1 with lipid bilayers and the SNARE complex trigger fusion, we performed molecular dynamics (MD) simulations at a microsecond scale. The MD simulations showed that the C2AB tandem of Syt1 can either bridge SV and PM or immerse into PM, and that the latter configuration is more favorable energetically. Surprisingly, C2 domains did not cooperate in penetrating into PM, but instead mutually hindered the lipid penetration. To test whether the interaction of Syt1 with lipid bilayers could be affected by the C2B-SNARE attachment, we performed systematic conformational analysis of the Syt1-SNARE complex. Notably, we found that the C2B-SNARE interface precludes the coupling of C2 domains of Syt1 and promotes the immersion of both domains into the PM bilayer. Subsequently, we simulated this pre-fusion protein complex between lipid bilayers imitating PM and SV and found that the immersion of Syt1 into the PM bilayer within this complex promotes PM curvature and leads to lipid merging. Altogether, our MD simulations elucidated the role of the Syt1-SNARE interactions in the fusion process and produced the dynamic all-atom model of the prefusion protein-lipid complex.Statement of SignificanceNeuronal transmitters are packed in synaptic vesicles (SVs) and released by fusion of SVs with the presynaptic membrane (PM). SVs are attached to PM by the SNARE protein complex, and fusion is triggered by the Ca2+ sensor Synaptotagmin 1 (Syt1). Although Syt1 and SNARE proteins have been extensively studied, it is not yet fully understood how the interactions of Syt1 with lipids and the SNARE complex induce fusion. To address this fundamental problem, we took advantage of Anton2 supercomputer, a unique computational environment, which enables simulating the dynamics of molecular systems at a scale of microseconds. Our simulations produced a dynamic all-atom model of the prefusion protein-lipid complex and demonstrated in silico how the Syt1-SNARE complex triggers fusion.

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Nuclear magnetic resonance (NMR) applied to membrane–protein complexes

Quarterly Reviews of Biophysics ◽

10.1017/s003358351600010x ◽

2016 ◽

Vol 49 ◽

Cited By ~ 35

Author(s):

Mohammed Kaplan ◽

Cecilia Pinto ◽

Klaartje Houben ◽

Marc Baldus

Keyword(s):

Nuclear Magnetic Resonance ◽

Magnetic Resonance ◽

Membrane Protein ◽

Protein Interactions ◽

Protein Transport ◽

Isotope Labeling ◽

Protein Complexes ◽

Cellular Membranes ◽

Membrane Protein Complexes ◽

Nuclear Magnetic

AbstractIncreasing evidence suggests that most proteins occur and function in complexes rather than as isolated entities when embedded in cellular membranes. Nuclear magnetic resonance (NMR) provides increasing possibilities to study structure, dynamics and assembly of such systems. In our review, we discuss recent methodological progress to study membrane–protein complexes (MPCs) by NMR, starting with expression, isotope-labeling and reconstitution protocols. We review approaches to deal with spectral complexity and limited spectral spectroscopic sensitivity that are usually encountered in NMR-based studies of MPCs. We highlight NMR applications in various classes of MPCs, including G-protein-coupled receptors, ion channels and retinal proteins and extend our discussion to protein–protein complexes that span entire cellular compartments or orchestrate processes such as protein transport across or within membranes. These examples demonstrate the growing potential of NMR-based studies of MPCs to provide critical insight into the energetics of protein–ligand and protein–protein interactions that underlie essential biological functions in cellular membranes.

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