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Transmembrane helix predictions revisited

Protein science, 2002-12, Vol.11 (12), p.2774-2791 [Peer Reviewed Journal]

Copyright © 2002 The Protein Society ;Copyright © Copyright 2002 The Protein Society ;ISSN: 0961-8368 ;EISSN: 1469-896X ;DOI: 10.1110/ps.0214502 ;PMID: 12441377

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Title:
Transmembrane helix predictions revisited
Author: Chen, Chien Peter ; Kernytsky, Andrew ; Rost, Burkhard
Subjects: Algorithms ; Animals ; Av‐Cid, normalized average hydrophobicity scale (Cid 1992) ; A‐Cid, normalized hydrophobicity scale for α‐proteins (Cid 1992) ; Ben‐Tal, hydrophobicity scale representing the free energy of transferring an amino acid from water into the center of the hydrocarbon region of a lipid bilayer (Kessel and Ben‐Tal 2002) ; BIG, nonidentical merger of SWISS‐PROT (Bairoch and Apweiler 2000) and TrEMBL (Bairoch and Apweiler 2000) and PDB (Berman et al. 2000) ; bioinformatics ; BLAST, fast sequence alignment method (Altschul and Gish 1996) ; Bull‐Breese, Bull‐Breese hydrophobicity scale (Bull 1974) ; comparing genomes ; computational biology ; Computational Biology - methods ; DSSP, program assigning secondary structure (Kabsch and Sander 1983) ; Eisenberg, normalized consensus hydrophobicity scale (Eisenberg et al. 1984) ; EM, Solvation free energy (Eisenberg and McLachlan 1986) ; EVA, server automatically evaluating structure prediction methods (Eyrich et al. 2001a,b) ; Fauchere, hydrophobic parameter π from the partitioning of N‐acetyl‐amino‐acid amides (Fauchere and Pliska 1983) ; GES, hydrophobicity property (Engelman et al. 1986; Prabhakaran 1990) ; Heijne, transfer free energy to lipophilic phase (von Heijne and Blomberg 1979) ; HMM, hidden Markov model ; HMMTOP, hidden Markov model predicting transmembrane helices (Tusnady and Simon 1998) ; Hopp‐Woods, Hopp‐Woods hydrophilicity value (Hopp and Woods 1981) ; KD, Kyte–Doolittle hydropathy index (Kyte and Doolittle 1982) ; Lawson, transfer free energy (Lawson et al. 1984) ; Levitt, hydrophobic parameter (Levitt 1976) ; MaxHom, dynamic programming algorithm for conservation weight‐based multiple sequence alignment (Sander and Schneider 1991) ; Membrane Proteins - chemistry ; MEMSAT, dynamic‐programming based prediction of transmembrane helices (Jones et al. 1994) ; META‐PP, internet service allowing access to a variety of bioinformatics tools through one single interface (Eyrich and Rost 2000) ; Models, Molecular ; multiple alignments, predicting transmembrane helices ; Nakashima, normalized composition of membrane proteins (Nakashima et al. 1990) ; PDB, Protein Data Bank of experimentally determined 3D structures of proteins (Bernstein et al. 1977; Berman et al. 2000) ; PHDhtm, profile‐based neural network prediction of transmembrane helices (Rost 1996; Rost et al. 1996b) ; PHDpsihtm, divergent profile (PSI‐BLAST)‐based neural network prediction 2002 ; Protein Folding ; protein structure prediction ; Protein Structure, Secondary ; proteomes ; PSI‐BLAST, position‐specific iterated database search (Altschul et al. 1997) ; Radzicka, transfer free energy from 1‐octanol to water (Radzicka and Wolfenden 1988) ; Roseman, solvation‐corrected side‐chain hydropathy (Roseman 1988) ; Sensitivity and Specificity ; Sequence analysis ; SignalP, signal peptide prediction (Nielsen et al. 1997a) ; Software ; SOSUI, hydrophobicity‐ and amphiphilicity‐based transmembrane helix prediction (Hirokawa et al. 1998) ; SPLIT, transmembrane helix prediction (Juretic et al. 1998) ; Sweet, optimal matching hydrophobicity (Sweet and Eisenberg 1983) ; SWISS‐PROT, database of protein sequences (Bairoch and Apweiler 2000) ; TM, transmembrane ; TMAP, alignment‐based prediction of transmembrane helices (Persson and Argos 1996) ; TMH, transmembrane helix ; TMHMM, transmembrane prediction using cyclic hidden Markov models (Sonnhammer et al. 1998; Krogh et al. 2001) ; TMpred, prediction of transmembrane helices (Hofmann and Stoffel 1993) ; TopPred2, hydrophobicity‐based membrane helix prediction (von Heijne 1992; Cserzö et al. 1997) ; TrEMBL, translation of the EMBL‐nucleotide database coding DNA to protein sequences (Bairoch and Apweiler 2000) ; Wolfenden, hydration potential (Wolfenden et al. 1981) ; WW, Wimley–White hydrophobicity scale‐based method (Wimley et al. 1996a,b; White and Wimley 1999; White 2001)
Is Part Of: Protein science, 2002-12, Vol.11 (12), p.2774-2791
Description: Methods that predict membrane helices have become increasingly useful in the context of analyzing entire proteomes, as well as in everyday sequence analysis. Here, we analyzed 27 advanced and simple methods in detail. To resolve contradictions in previous works and to reevaluate transmembrane helix prediction algorithms, we introduced an analysis that distinguished between performance on redundancy‐reduced high‐ and low‐resolution data sets, established thresholds for significant differences in performance, and implemented both per‐segment and per‐residue analysis of membrane helix predictions. Although some of the advanced methods performed better than others, we showed in a thorough bootstrapping experiment based on various measures of accuracy that no method performed consistently best. In contrast, most simple hydrophobicity scale‐based methods were significantly less accurate than any advanced method as they overpredicted membrane helices and confused membrane helices with hydrophobic regions outside of membranes. In contrast, the advanced methods usually distinguished correctly between membrane‐helical and other proteins. Nonetheless, few methods reliably distinguished between signal peptides and membrane helices. We could not verify a significant difference in performance between eukaryotic and prokaryotic proteins. Surprisingly, we found that proteins with more than five helices were predicted at a significantly lower accuracy than proteins with five or fewer. The important implication is that structurally unsolved multispanning membrane proteins, which are often important drug targets, will remain problematic for transmembrane helix prediction algorithms. Overall, by establishing a standardized methodology for transmembrane helix prediction evaluation, we have resolved differences among previous works and presented novel trends that may impact the analysis of entire proteomes.
Publisher: Bristol: Cold Spring Harbor Laboratory Press
Language: English
Identifier: ISSN: 0961-8368
EISSN: 1469-896X
DOI: 10.1110/ps.0214502
PMID: 12441377
Source: Geneva Foundation Free Medical Journals at publisher websites
MEDLINE
PubMed Central

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Transmembrane helix predictions revisited

Copyright © 2002 The Protein Society ;Copyright © Copyright 2002 The Protein Society ;ISSN: 0961-8368 ;EISSN: 1469-896X ;DOI: 10.1110/ps.0214502 ;PMID: 12441377

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