Prediction of membrane protein structures with complex topologies using limited constraints

Reliable structure-prediction methods for membrane proteins are important because the experimental determination of high-resolution membrane protein structures remains very difficult, especially for eukaryotic proteins. However, membrane proteins are typically longer than 200 aa and represent a formidable challenge for structure prediction. We have developed a method for predicting the structures of large membrane proteins by constraining helix–helix packing arrangements at particular positions predicted from sequence or identified by experiments. We tested the method on 12 membrane proteins of diverse topologies and functions with lengths ranging between 190 and 300 residues. Enforcing a single constraint during the folding simulations enriched the population of near-native models for 9 proteins. In 4 of the cases in which the constraint was predicted from the sequence, 1 of the 5 lowest energy models was superimposable within 4 Å on the native structure. Near-native structures could also be selected for heme-binding and pore-forming domains from simulations in which pairs of conserved histidine-chelating hemes and one experimentally determined salt bridge were constrained, respectively. These results suggest that models within 4 Å of the native structure can be achieved for complex membrane proteins if even limited information on residue-residue interactions can be obtained from protein structure databases or experiments.

[1]  Arne Elofsson,et al.  MaxSub: an automated measure for the assessment of protein structure prediction quality , 2000, Bioinform..

[2]  D. Baker,et al.  Toward high-resolution prediction and design of transmembrane helical protein structures , 2007, Proceedings of the National Academy of Sciences.

[3]  David Baker,et al.  Improved beta‐protein structure prediction by multilevel optimization of nonlocal strand pairings and local backbone conformation , 2006, Proteins.

[4]  D. Baker,et al.  Multipass membrane protein structure prediction using Rosetta , 2005, Proteins.

[5]  Arne Elofsson,et al.  OCTOPUS: improving topology prediction by two-track ANN-based preference scores and an extended topological grammar , 2008, Bioinform..

[6]  H. Kaback,et al.  A general method for determining helix packing in membrane proteins in situ: helices I and II are close to helix VII in the lactose permease of Escherichia coli. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[7]  O. Schueler‐Furman,et al.  Progress in Modeling of Protein Structures and Interactions , 2005, Science.

[8]  S H White,et al.  MPtopo: A database of membrane protein topology , 2001, Protein science : a publication of the Protein Society.

[9]  Ralf Zimmer,et al.  Profile-Profile Alignment: A Powerful Tool for Protein Structure Prediction , 2002, Pacific Symposium on Biocomputing.

[10]  Dmitrij Frishman,et al.  Co-evolving residues in membrane proteins , 2007, Bioinform..

[11]  W. Hubbell,et al.  Proximity between Glu126 and Arg144 in the lactose permease of Escherichia coli. , 1999, Biochemistry.

[12]  Alessandro Senes,et al.  Folding of helical membrane proteins: the role of polar, GxxxG-like and proline motifs. , 2004, Current opinion in structural biology.

[13]  Jie Liang,et al.  Prediction of transmembrane helix orientation in polytopic membrane proteins , 2006, BMC Structural Biology.

[14]  Thomas L. Madden,et al.  Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. , 1997, Nucleic acids research.

[15]  B. Honig,et al.  On the accuracy of homology modeling and sequence alignment methods applied to membrane proteins. , 2006, Biophysical journal.

[16]  Yang Zhang,et al.  Structure Modeling of All Identified G Protein–Coupled Receptors in the Human Genome , 2006, PLoS Comput. Biol..

[17]  G. von Heijne,et al.  Membrane protein structure: prediction versus reality. , 2007, Annual review of biochemistry.

[18]  W. DeGrado,et al.  Helix-packing motifs in membrane proteins , 2006, Proceedings of the National Academy of Sciences.

[19]  P. Bradley,et al.  High-resolution structure prediction and the crystallographic phase problem , 2007, Nature.