Prediction of membrane-protein topology from first principles

Abstract

The current best membrane-protein topology-prediction methods are typically based on sequence statistics and contain hundreds of parameters that are optimized on known topologies of membrane proteins. However, because the insertion of transmembrane helices into the membrane is the outcome of molecular interactions among protein, lipids and water, it should be possible to predict topology by methods based directly on physical data, as proposed >20 years ago by Kyte and Doolittle. Here, we present two simple topology-prediction methods using a recently published experimental scale of position-specific amino acid contributions to the free energy of membrane insertion that perform on a par with the current best statistics-based topology predictors. This result suggests that prediction of membrane-protein topology and structure directly from first principles is an attainable goal, given the recently improved understanding of peptide recognition by the translocon.

Fig. 1.

Topology predictions by TopPred^ΔG and SCAMPI. Each image contains, from top to bottom, the crystal structure of the protein chain; the ΔG_app profile, with the TopPred^ΔG parameters ΔG_high and ΔG_low shown as dashed lines and the topology predicted by TopPred^ΔG indicated beneath the curve; and the path through the SCAMPI model, with the vertical position in the model (see y axis) plotted as a function of sequence position. A detailed description of the SCAMPI model is available in Fig. S1. The structure and predicted topologies are colored according to ΔG_app values, where residues with predicted ΔG_app above ΔG_high and below ΔG_low are colored blue and red, respectively. Locations of the TM helices as annotated in the OPM database (22) are shown as gray boxes. Lys and Arg residues are marked with plus signs. (A) Cytochrome c oxidase from Thermus thermophilus, PDB ID code 1ehkA. All 13 TM segments give distinct minima in the ΔG_app profile and are correctly located by both TopPred^ΔG and SCAMPI. (B) Methane monooxygenase from Methylococcus capsulatus, PDB ID code 1yewB. Helix 6 (to the right in the upper image) contains several charges and is missed by both SCAMPI and TopPred^ΔG.

Fig. 2.

ΔG_app correlates with TM helix environment. (A) Correlation between ΔG_app and TM helix surface accessibility. White bars, fraction of surface area in contact with the whole protein; black bars, fraction of surface area in contact with the same polypeptide chain. (B) Correlation between ΔG_app and number of TM helices. Mean ΔG_app of all TM helices in polypeptide chains with the topology given by the x axis. Error bars in both images show the standard error of the mean ΔG_app estimation within the set defined by the x axis.