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Yao J, Hong H. Steric trapping strategy for studying the folding of helical membrane proteins. Methods 2024; 225:1-12. [PMID: 38428472 PMCID: PMC11107808 DOI: 10.1016/j.ymeth.2024.02.007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2023] [Revised: 02/11/2024] [Accepted: 02/18/2024] [Indexed: 03/03/2024] Open
Abstract
Elucidating the folding energy landscape of membrane proteins is essential to the understanding of the proteins' stabilizing forces, folding mechanisms, biogenesis, and quality control. This is not a trivial task because the reversible control of folding is inherently difficult in a lipid bilayer environment. Recently, novel methods have been developed, each of which has a unique strength in investigating specific aspects of membrane protein folding. Among such methods, steric trapping is a versatile strategy allowing a reversible control of membrane protein folding with minimal perturbation of native protein-water and protein-lipid interactions. In a nutshell, steric trapping exploits the coupling of spontaneous denaturation of a doubly biotinylated protein to the simultaneous binding of bulky monovalent streptavidin molecules. This strategy has been evolved to investigate key elements of membrane protein folding such as thermodynamic stability, spontaneous denaturation rates, conformational features of the denatured states, and cooperativity of stabilizing interactions. In this review, we describe the critical methodological advancement, limitation, and outlook of the steric trapping strategy.
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Affiliation(s)
- Jiaqi Yao
- Department of Chemistry, Michigan State University, East Lansing, MI 48824, USA
| | - Heedeok Hong
- Department of Chemistry, Michigan State University, East Lansing, MI 48824, USA; Department of Biochemistry & Molecular Biology, Michigan State University, East Lansing, MI 48824, USA.
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2
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Gaffney KA, Guo R, Bridges MD, Muhammednazaar S, Chen D, Kim M, Yang Z, Schilmiller AL, Faruk NF, Peng X, Jones AD, Kim KH, Sun L, Hubbell WL, Sosnick TR, Hong H. Lipid bilayer induces contraction of the denatured state ensemble of a helical-bundle membrane protein. Proc Natl Acad Sci U S A 2022; 119:e2109169119. [PMID: 34969836 PMCID: PMC8740594 DOI: 10.1073/pnas.2109169119] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/17/2021] [Indexed: 12/19/2022] Open
Abstract
Defining the denatured state ensemble (DSE) and disordered proteins is essential to understanding folding, chaperone action, degradation, and translocation. As compared with water-soluble proteins, the DSE of membrane proteins is much less characterized. Here, we measure the DSE of the helical membrane protein GlpG of Escherichia coli (E. coli) in native-like lipid bilayers. The DSE was obtained using our steric trapping method, which couples denaturation of doubly biotinylated GlpG to binding of two streptavidin molecules. The helices and loops are probed using limited proteolysis and mass spectrometry, while the dimensions are determined using our paramagnetic biotin derivative and double electron-electron resonance spectroscopy. These data, along with our Upside simulations, identify the DSE as being highly dynamic, involving the topology changes and unfolding of some of the transmembrane (TM) helices. The DSE is expanded relative to the native state but only to 15 to 75% of the fully expanded condition. The degree of expansion depends on the local protein packing and the lipid composition. E. coli's lipid bilayer promotes the association of TM helices in the DSE and, probably in general, facilitates interhelical interactions. This tendency may be the outcome of a general lipophobic effect of proteins within the cell membranes.
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Affiliation(s)
- Kristen A Gaffney
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824
| | - Ruiqiong Guo
- Department of Chemistry, Michigan State University, East Lansing, MI 48824
| | - Michael D Bridges
- Jules Stein Eye Institute, University of California, Los Angeles, CA 90095
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095
| | | | - Daoyang Chen
- Department of Chemistry, Michigan State University, East Lansing, MI 48824
| | - Miyeon Kim
- Department of Chemistry, Michigan State University, East Lansing, MI 48824
| | - Zhongyu Yang
- Department of Chemistry and Biochemistry, North Dakota State University, Fargo, ND 58108
| | - Anthony L Schilmiller
- Research Technology Support Facility Mass Spectrometry and Metabolomics Core, Michigan State University, East Lansing, MI 48824
| | - Nabil F Faruk
- Graduate Program in Biophysical Sciences, The University of Chicago, Chicago, IL 60637
| | - Xiangda Peng
- Department of Biochemistry & Molecular Biology, The University of Chicago, Chicago, IL 60637
- Institute for Biophysical Dynamics, The University of Chicago, Chicago, IL 60637
| | - A Daniel Jones
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824
- Research Technology Support Facility Mass Spectrometry and Metabolomics Core, Michigan State University, East Lansing, MI 48824
| | - Kelly H Kim
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824
| | - Liangliang Sun
- Department of Chemistry, Michigan State University, East Lansing, MI 48824
| | - Wayne L Hubbell
- Jules Stein Eye Institute, University of California, Los Angeles, CA 90095
- Department of Chemistry and Biochemistry, University of California, Los Angeles, CA 90095
| | - Tobin R Sosnick
- Department of Biochemistry & Molecular Biology, The University of Chicago, Chicago, IL 60637;
- Institute for Biophysical Dynamics, The University of Chicago, Chicago, IL 60637
| | - Heedeok Hong
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, MI 48824;
- Department of Chemistry, Michigan State University, East Lansing, MI 48824
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Basu S, Assaf SS, Teheux F, Rooman M, Pucci F. BRANEart: Identify Stability Strength and Weakness Regions in Membrane Proteins. FRONTIERS IN BIOINFORMATICS 2021; 1:742843. [PMID: 36303753 PMCID: PMC9581023 DOI: 10.3389/fbinf.2021.742843] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2021] [Accepted: 11/03/2021] [Indexed: 11/22/2022] Open
Abstract
Understanding the role of stability strengths and weaknesses in proteins is a key objective for rationalizing their dynamical and functional properties such as conformational changes, catalytic activity, and protein-protein and protein-ligand interactions. We present BRANEart, a new, fast and accurate method to evaluate the per-residue contributions to the overall stability of membrane proteins. It is based on an extended set of recently introduced statistical potentials derived from membrane protein structures, which better describe the stability properties of this class of proteins than standard potentials derived from globular proteins. We defined a per-residue membrane propensity index from combinations of these potentials, which can be used to identify residues which strongly contribute to the stability of the transmembrane region or which would, on the contrary, be more stable in extramembrane regions, or vice versa. Large-scale application to membrane and globular proteins sets and application to tests cases show excellent agreement with experimental data. BRANEart thus appears as a useful instrument to analyze in detail the overall stability properties of a target membrane protein, to position it relative to the lipid bilayer, and to rationally modify its biophysical characteristics and function. BRANEart can be freely accessed from http://babylone.3bio.ulb.ac.be/BRANEart.
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Affiliation(s)
- Sankar Basu
- Computational Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, Belgium
- Department of Microbiology, Austosh College, Under University of Calcutta, Kolkata, India
| | - Simon S. Assaf
- Computational Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, Belgium
| | - Fabian Teheux
- Computational Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, Belgium
| | - Marianne Rooman
- Computational Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, Brussels, Belgium
- *Correspondence: Marianne Rooman, ; Fabrizio Pucci,
| | - Fabrizio Pucci
- Computational Biology and Bioinformatics, Université Libre de Bruxelles, Brussels, Belgium
- Interuniversity Institute of Bioinformatics in Brussels, Brussels, Belgium
- *Correspondence: Marianne Rooman, ; Fabrizio Pucci,
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Tian W, Naveed H, Lin M, Liang J. GeTFEP: A general transfer free energy profile of transmembrane proteins. Protein Sci 2019; 29:469-479. [PMID: 31658402 DOI: 10.1002/pro.3763] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2019] [Revised: 10/20/2019] [Accepted: 10/23/2019] [Indexed: 01/06/2023]
Abstract
Free energy of transferring amino acid side-chains from aqueous environment into lipid bilayers, known as transfer free energy (TFE), provides important information on the thermodynamic stability of membrane proteins. In this study, we derived a TFE profile named General Transfer Free Energy Profile (GeTFEP) based on computation of the TFEs of 58 β-barrel membrane proteins (βMPs). The GeTFEP agrees well with experimentally measured and computationally derived TFEs. Analysis based on the GeTFEP shows that residues in different regions of the transmembrane (TM) segments of βMPs have different roles during the membrane insertion process. Results further reveal the importance of the sequence pattern of TM strands in stabilizing βMPs in the membrane environment. In addition, we show that GeTFEP can be used to predict the positioning and the orientation of βMPs in the membrane. We also show that GeTFEP can be used to identify structurally or functionally important amino acid residue sites of βMPs. Furthermore, the TM segments of α-helical membrane proteins can be accurately predicted with GeTFEP, suggesting that the GeTFEP is of general applicability in studying membrane protein.
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Affiliation(s)
- Wei Tian
- Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois
| | - Hammad Naveed
- Department of Computer Science, National University of Computer and Emerging Sciences (NUCES-FAST), Islamabad, Islamabad Capital Territory, Pakistan
| | - Meishan Lin
- Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois
| | - Jie Liang
- Department of Bioengineering, University of Illinois at Chicago, Chicago, Illinois
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