Journal of Computer-Aided Molecular Design

, Volume 31, Issue 9, pp 855–865 | Cite as

TMDIM: an improved algorithm for the structure prediction of transmembrane domains of bitopic dimers

  • Han Cao
  • Marcus C. K. Ng
  • Siti Azma Jusoh
  • Hio Kuan Tai
  • Shirley W. I. Siu


\(\alpha\)-Helical transmembrane proteins are the most important drug targets in rational drug development. However, solving the experimental structures of these proteins remains difficult, therefore computational methods to accurately and efficiently predict the structures are in great demand. We present an improved structure prediction method TMDIM based on Park et al. (Proteins 57:577–585, 2004) for predicting bitopic transmembrane protein dimers. Three major algorithmic improvements are introduction of the packing type classification, the multiple-condition decoy filtering, and the cluster-based candidate selection. In a test of predicting nine known bitopic dimers, approximately 78% of our predictions achieved a successful fit (RMSD <2.0 Å) and 78% of the cases are better predicted than the two other methods compared. Our method provides an alternative for modeling TM bitopic dimers of unknown structures for further computational studies. TMDIM is freely available on the web at Website is implemented in PHP, MySQL and Apache, with all major browsers supported.


Structure prediction Bitopic dimer Helix packing Helix assembly Scwrl4 Bioinformatics 



We thank Yungki Park and Volkhard Helms for granting the use of their program for the development of TMDIM. This work was performed in part at the High Performance Computing Cluster which is supported by Information and Communication Technology Office (ICTO) of the University of Macau.


The funding was provided by University of Macau (Grant Number MYRG2014-00104-FST).


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Han Cao
    • 1
  • Marcus C. K. Ng
    • 1
  • Siti Azma Jusoh
    • 2
  • Hio Kuan Tai
    • 1
  • Shirley W. I. Siu
    • 1
  1. 1.Department of Computer and Information Science, Faculty of Science and TechnologyUniversity of MacauTaipaChina
  2. 2.Department of Pharmaceutical Life Sciences, Faculty of PharmacyUniversiti Teknologi MARA Cawangan SelangorSelangorMalaysia

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