Advances in Computational Methods for Transmembrane Protein Structure Prediction



Transmembrane (TM) proteins fulfill many crucial cellular functions such as substrate transport, biogenesis and signalling, and make up a significant fraction of any given proteome. Estimates suggest that up to 30% of all human genes may encode α-helical TM proteins, while β-barrel TM proteins, which are found in the outer-membrane of gram-negative bacteria, mitochondria and chloroplast, are encoded by 2–3% of genes. However, relatively few high resolution TM protein structures are known, making it all the more important to extract as much structural information as possible from amino acid sequences. In this chapter, we review the existing methods for the identification, topology prediction and three-dimensional modelling of TM proteins, including a discussion of the recent advances in identifying residue-residue contacts from large multiple sequence alignments that have enabled impressive gains to be made in the field of TM protein structure prediction.


Transmembrane proteins Structure prediction 3D modelling 


Competing Interests

The authors declare that they have no competing interests.


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Copyright information

© Springer Science+Business Media B.V. 2017

Authors and Affiliations

  1. 1.Thomson Reuters, Corporate Research and DevelopmentLondonUK
  2. 2.Bioinformatics Group, Department of Computer ScienceUniversity College LondonLondonUK
  3. 3.Computational Biology Program, Memorial Sloan Kettering Cancer CenterNew York CityUSA

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