Protein fold recognition using sequence-derived predictions - PubMed
Protein fold recognition using sequence-derived predictions
D Fischer et al. Protein Sci. 1996 May.
Abstract
In protein fold recognition, one assigns a probe amino acid sequence of unknown structure to one of a library of target 3D structures. Correct assignment depends on effective scoring of the probe sequence for its compatibility with each of the target structures. Here we show that, in addition to the amino acid sequence of the probe, sequence-derived properties of the probe sequence (such as the predicted secondary structure) are useful in fold assignment. The additional measure of compatibility between probe and target is the level of agreement between the predicted secondary structure of the probe and the known secondary structure of the target fold. That is, we recommend a sequence-structure compatibility function that combines previously developed compatibility functions (such as the 3D-1D scores of Bowie et al. [1991] or sequence-sequence replacement tables) with the predicted secondary structure of the probe sequence. The effect on fold assignment of adding predicted secondary structure is evaluated here by using a benchmark set of proteins (Fischer et al., 1996a). The 3D structures of the probe sequences of the benchmark are actually known, but are ignored by our method. The results show that the inclusion of the predicted secondary structure improves fold assignment by about 25%. The results also show that, if the true secondary structure of the probe were known, correct fold assignment would increase by an additional 8-32%. We conclude that incorporating sequence-derived predictions significantly improves assignment of sequences to known 3D folds. Finally, we apply the new method to assign folds to sequences in the SWISSPROT database; six fold assignments are given that are not detectable by standard sequence-sequence comparison methods; for two of these, the fold is known from X-ray crystallography and the fold assignment is correct.
Similar articles
-
Rice DW, Eisenberg D. Rice DW, et al. J Mol Biol. 1997 Apr 11;267(4):1026-38. doi: 10.1006/jmbi.1997.0924. J Mol Biol. 1997. PMID: 9135128
-
Protein structure prediction by threading methods: evaluation of current techniques.
Lemer CM, Rooman MJ, Wodak SJ. Lemer CM, et al. Proteins. 1995 Nov;23(3):337-55. doi: 10.1002/prot.340230308. Proteins. 1995. PMID: 8710827
-
Hidden Markov models that use predicted secondary structures for fold recognition.
Hargbo J, Elofsson A. Hargbo J, et al. Proteins. 1999 Jul 1;36(1):68-76. Proteins. 1999. PMID: 10373007
-
[A turning point in the knowledge of the structure-function-activity relations of elastin].
Alix AJ. Alix AJ. J Soc Biol. 2001;195(2):181-93. J Soc Biol. 2001. PMID: 11727705 Review. French.
-
Assigning amino acid sequences to 3-dimensional protein folds.
Fischer D, Rice D, Bowie JU, Eisenberg D. Fischer D, et al. FASEB J. 1996 Jan;10(1):126-36. doi: 10.1096/fasebj.10.1.8566533. FASEB J. 1996. PMID: 8566533 Review.
Cited by
-
Kumar AV, Ali RF, Cao Y, Krishnan VV. Kumar AV, et al. Biochim Biophys Acta. 2015 Oct;1854(10 Pt A):1545-52. doi: 10.1016/j.bbapap.2015.02.016. Epub 2015 Mar 7. Biochim Biophys Acta. 2015. PMID: 25758094 Free PMC article.
-
GDAP: a web tool for genome-wide protein disulfide bond prediction.
O'Connor BD, Yeates TO. O'Connor BD, et al. Nucleic Acids Res. 2004 Jul 1;32(Web Server issue):W360-4. doi: 10.1093/nar/gkh376. Nucleic Acids Res. 2004. PMID: 15215411 Free PMC article.
-
Malkov SN, Zivković MV, Beljanski MV, Hall MB, Zarić SD. Malkov SN, et al. J Mol Model. 2008 Aug;14(8):769-75. doi: 10.1007/s00894-008-0313-0. Epub 2008 May 27. J Mol Model. 2008. PMID: 18504624
-
The restriction enzyme SgrAI: structure solution via combination of poor MIRAS and MR phases.
Dunten PW, Little EJ, Horton NC. Dunten PW, et al. Acta Crystallogr D Biol Crystallogr. 2009 Apr;65(Pt 4):393-8. doi: 10.1107/S0907444909003266. Epub 2009 Mar 19. Acta Crystallogr D Biol Crystallogr. 2009. PMID: 19307723 Free PMC article.
-
Genomic evidence that the intracellular proteins of archaeal microbes contain disulfide bonds.
Mallick P, Boutz DR, Eisenberg D, Yeates TO. Mallick P, et al. Proc Natl Acad Sci U S A. 2002 Jul 23;99(15):9679-84. doi: 10.1073/pnas.142310499. Epub 2002 Jul 9. Proc Natl Acad Sci U S A. 2002. PMID: 12107280 Free PMC article.
References
Publication types
MeSH terms
Substances
LinkOut - more resources
Full Text Sources
Other Literature Sources