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Predicting the topology of transmembrane helical proteins using mean burial propensity and a hidden-Markov-model-based method

Howard Hughes Medical Institute Center for Single Molecule Biophysics, Department of Physiology & Biophysics, State University of New York at Buffalo, Buffalo, New York 14214, USA

Reprint requests to: Yaoqi Zhou, Howard Hughes Medical Institute Center for Single Molecule Biophysics and Department of Physiology & Biophysics, State University of New York at Buffalo, 124 Sherman Hall, Buffalo, NY 14214, USA; e-mail: yqzhou{at}buffalo.edu; fax: 716-829-2344.

Helices in membrane spanning regions are more tightly packed than the helices in soluble proteins. Thus, we introduce a method that uses a simple scale of burial propensity and a new algorithm to predict transmembrane helical (TMH) segments and a positive-inside rule to predict amino-terminal orientation. The method (the topology predictor of transmembrane helical proteins using mean burial propensity [THUMBUP]) correctly predicted the topology of 55 of 73 proteins (or 75%) with known three-dimensional structures (the 3D helix database). This level of accuracy can be reached by MEMSAT 1.8 (a 200-parameter model-recognition method) and a new HMM-based method (a 111-parameter hidden Markov model, UMDHMM^TMHP) if they were retrained with the 73-protein database. Thus, a method based on a physiochemical property can provide topology prediction as accurate as those methods based on more complicated statistical models and learning algorithms for the proteins with accurately known structures. Commonly used HMM-based methods and MEMSAT 1.8 were trained with a combination of the partial 3D helix database and a 1D helix database of TMH proteins in which topology information were obtained by gene fusion and other experimental techniques. These methods provide a significantly poorer prediction for the topology of TMH proteins in the 3D helix database. This suggests that the 1D helix database, because of its inaccuracy, should be avoided as either a training or testing database. A Web server of THUMBUP and UMDHMM^TMHP is established for academic users at http://www.smbs.buffalo.edu/phys_bio/service.htm. The 3D helix database is also available from the same Web site.

Keywords: Transmembrane protein topology; burial propensity; topology prediction; hydrophobicity scale

Abbreviations: THUMBUP, topology predictor of transmembrane helical proteins using mean burial propensity • UMDHMM^TMHP, University of Maryland hidden Markov model for transmembrane helical protein • MSR, membrane spanning regions

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