Modeling and Validation of Transmembrane Protein Structures

Abstract Gaining knowledge of the structural makeup of protein complexes is critical to advance our understanding of their formation and functions. This task is particularly challenging for transmembrane protein complexes, and grows ever more imposing with increasing size of these large macromolecular structures. The last 10 years have seen a steep increase in solved high-resolution membrane protein structures due to both new and improved methods in the field, but still most structures of large transmembrane complexes remain elusive. An important first step towards the structure elucidation of these difficult complexes is the determination of their stoichiometry, which we discuss in this review. Knowing the stoichiometry of complex components not only answers unresolved structural questions and is relevant for understanding the molecular mechanisms of macromolecular machines but also supports further attempts to obtain high-resolution structures by providing constraints for structure calculations.

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Site‒specific IR spectroscopy and molecular modelling combined towards solving transmembrane protein structure

Spectroscopy An International Journal ◽

10.1155/2005/297098 ◽

2005 ◽

Vol 19 (1) ◽

pp. 1-16 ◽

Cited By ~ 8

Author(s):

Andreas Kukol

Keyword(s):

Molecular Dynamics ◽

Mhc Class Ii ◽

Transmembrane Protein ◽

Protein Structures ◽

Critical Evaluation ◽

Dynamics Simulation ◽

Proton Channel ◽

Conformational Search ◽

Widespread Application ◽

Site Specific

Membrane protein structures are underrepresented in structural databases despite their abundance and biomedical importance. This review focuses on the novel method of site-specific infrared dichroism (SSID) combined with constraint molecular dynamics simulation, which has recently emerged as a powerful method to obtain structures of transmembrane α-helical bundles. The theory of SSID including its latest developments is reviewed with the aim to encourage widespread application of this method. This is followed by an outline of the conformational search using experimentally constraint molecular dynamics simulations. Finally a critical evaluation of recent applications, namely the Influenza M2 proton channel, the vpu ion channel of HIV-1 and the MHC-class II associated invariant chain, is conducted.

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Transmembrane protein structures without X-rays

Trends in Biochemical Sciences ◽

10.1016/j.tibs.2005.12.005 ◽

2006 ◽

Vol 31 (2) ◽

pp. 106-113 ◽

Cited By ~ 56

Author(s):

Sarel J. Fleishman ◽

Vinzenz M. Unger ◽

Nir Ben-Tal

Keyword(s):

Transmembrane Protein ◽

Protein Structures ◽

X Rays

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Kink Characterization and Modeling in Transmembrane Protein Structures

Journal of Chemical Information and Modeling ◽

10.1021/ci400236s ◽

2013 ◽

Vol 53 (11) ◽

pp. 2926-2936 ◽

Cited By ~ 6

Author(s):

Tim Werner ◽

W. Bret Church

Keyword(s):

Transmembrane Protein ◽

Protein Structures

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Residue centrality in alpha helical polytopic transmembrane protein structures

Journal of Theoretical Biology ◽

10.1016/j.jtbi.2012.06.002 ◽

2012 ◽

Vol 309 ◽

pp. 78-87 ◽

Cited By ~ 9

Author(s):

I. Arnold Emerson ◽

K.M. Gothandam

Keyword(s):

Transmembrane Protein ◽

Protein Structures

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THE USE OF FUNCTIONAL DOMAINS TO IMPROVE TRANSMEMBRANE PROTEIN TOPOLOGY PREDICTION

Journal of Bioinformatics and Computational Biology ◽

10.1142/s0219720006001722 ◽

2006 ◽

Vol 04 (01) ◽

pp. 109-123 ◽

Cited By ~ 6

Author(s):

EMILY W. XU ◽

PAUL KEARNEY ◽

DANIEL G. BROWN

Keyword(s):

Prediction Accuracy ◽

Transmembrane Protein ◽

Probabilistic Approach ◽

Protein Structures ◽

Transmembrane Proteins ◽

Functional Domains ◽

Functional Domain ◽

Protein Topology ◽

Transmembrane Protein Topology ◽

Topology Prediction

Transmembrane proteins affect vital cellular functions and pathogenesis, and are a focus of drug design. It is difficult to obtain diffraction quality crystals to study transmembrane protein structure. Computational tools for transmembrane protein topology prediction fill in the gap between the abundance of transmembrane proteins and the scarcity of known membrane protein structures. Their prediction accuracy is still inadequate: TMHMM, the current state-of-the-art method, has less than 52% accuracy in topology prediction on one set of transmembrane proteins of known topology. Based on the observation that there are functional domains that occur preferentially internal or external to the membrane, we have extended the model of TMHMM to incorporate functional domains, using a probabilistic approach originally developed for computational gene finding. Our extension is better than TMHMM in predicting the topology of transmembrane proteins. As prediction of functional domain improves, our system's prediction accuracy will likely improve as well.

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