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Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda, Erik Gransetha and Arne Elofsson Journal of Molecular Biology 2006 Aug 18;361(3);591-603. Tim Nugent BugF 8 th March 2007

Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

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Page 1: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

Structural Classification and Prediction of Reentrant

Regions in Alpha-Helical Transmembrane Proteins:

Application to Complete Genomes

Håkan Viklunda, Erik Gransetha and Arne Elofsson

Journal of Molecular Biology 2006 Aug 18;361(3);591-603.

Tim Nugent

BugF 8th March 2007

Page 2: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

Structural regions of alpha-helical proteins

● Recently, the number of solved alpha-helical TM structures has increased rapidly.

● Structural complexity has been revealed to be equivalent of globular proteins.

● The most prominent features of TM proteins are membrane spanning alpha-helices.

● These are connected by loop regions.

Page 3: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

Substructures

● Several other functionally and structurally important substructures exists.

● One such substructure is the interface helix region, situated parallel with the membrane in the

membrane-water interface region.

● Another type is the reentrant region – part of the loop region which penetrates the membrane, but

enters and exits on the same side.

Page 4: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

Definition and properties or reentrant regions

● Reentrant regions are defined as sequences which start and end on the same side of the

membrane, and penetrate between 3 Å and 25 Å.

● Sequence stretches with a depth of between 1.5 Å and 3 Å are also defined as reentrant regions if

residue depth monotonically increase/decrease on the respective entrance/exit sides of the deepest

residue, and there is a clear turn in the membrane.

● Classification was performed by visual inspection.

● 79 transmembrane proteins with known 3D structure were attained from the Membrane Protein

Structure database and the Protein Data Bank. Homology reduced at 30% sequence similarity.

● Based on the definition:

– 36 reentrant regions

– 302 transmembrane regions

– 80 interface helix regions

Page 5: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,
Page 6: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

Region comparison

● Fraction of irregular secondary structure elements is larger in reentrant regions than in regular

TM helices.

● Average fraction of helical residues for reentrant regions is 57% with a clear correlation between

helical content and length of the region (correlation coefficient = 0.75).

Page 7: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

Three classes of reentrant regions can be identified

● Based on secondary structure - a helix must be at least 5 residues long; shorter helical regions are

defined as a coil.

● Helix-Coil-Helix:

Page 8: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

Three classes of reentrant regions can be identified

● Helix-Coil or Coil-Helix:

Page 9: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

Three classes of reentrant regions can be identified

● Coil / irregular secondary structure:

Page 10: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

Region length vs penetration depth

Page 11: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

Amino acid composition of reentrant regions and PCA

Page 12: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

Identification and prediction of reentrant regions

● Developed TOP-MOD - a hidden Markov model-based method to classify the residues of a TM

sequence into four structural classes – M, R, I and L.

Page 13: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

Distinguishing reentrant regions from loop and interface helix regions

● Believed that reentrant regions form relatively late in the overall folding dynamics, after the

initial translocation and formation of the membrane spanning helices.

● Their emergence can be visualised as a process in which parts of inter-TM regions are pulled into

the membrane.

● To test this, inter-TM parts from each sequence were cut out and TOP-MOD was used to make a

region classification on these subsequences.

Page 14: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

Distinguishing reentrant regions from loop and interface helix regions

Page 15: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

Predicting reentrant regions on whole sequence level

● So far, TOP-MOD has only been tested on sequences connecting TM helices.

● The possibility to distinguish between different types of structural region on a whole sequence level was evaluated.

● First, sequences where the approximate location of TM regions was considered to be know were analysed. Central residues of membrane regions were constrained to the HMM compartment modeling the membrane regions using sequence labels.

● Second, topology predictor PRODIV-TMHMM used as a pre-processor to predict location of TM helices.

Page 16: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

Scanning for reentrant regions in E. coli, S. cerevisiae and H. sapiens

● Using TOP-MOD and PRODIV-TMHMM, TM proteins of E. coli, S. cerevisiae and H.

sapiens were scanned to make a preliminary estimate of the occurrence of reentrant regions

in these genomes.

● Fraction is found to be at least 10% in all three genomes.

● To avoid false positives, sensitivity was set fairly low suggesting that the reentrant fraction

may be even higher.

Page 17: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

Scanning for reentrant regions in E. coli, S. cerevisiae and H. sapiens

● Fraction of proteins predicted with reentrant regions increases linearly with the number of

predicted TM regions.

● In two TM-number categories the fraction is lower: 7-TM GPCRs and 12-TM major

facilitator superfamily transporters.

Page 18: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

Proteins of a particular molecular function with predicted reentrant region

● Each sequence was mapped to HMM-based domain library PFAM.

● Earlier literature suggests reentrant loops were primarily found in passive transporter

proteins.

● This data suggests their occurrence in active transporters is higher than previously thought.

Page 19: Structural Classification and Prediction of Reentrant Regions in Alpha-Helical Transmembrane Proteins: Application to Complete Genomes Håkan Viklunda,

Conclusions

● For at least the last 10 years, the dominating non-experimental way of attaining structural

information of alpha-helical TM proteins has been by predicting topology.

● As more 3D structures have been resolved, it has become apparent that TM proteins are

often too complex to fit in to the helix, inside loop, outside loop constraints where loops are

always on opposite sides of the membrane.

● This suggests that a finer grained nomenclature, as well as finer grained methods, is needed

to study these proteins.

● Define more detailed substructures.

● Predict the structure directly using ab initio methods.

● Solve more 3D structures.