Identifying disordered regions in proteins from amino acid sequence

P. Romero, Z. Obradovi, C. Kissinger, J. E. Villafranca, A. Dunker

Research output: Chapter in Book/Report/Conference proceedingConference contribution

199 Citations (Scopus)

Abstract

A rule-based and several neural network predictors are developed for identifying disordered regions in proteins. The rule-based predictor, which relied on the observation that disordered regions contain few aromatic amino acids, was suitable only for very long disordered regions, whereas the neural network predictors were developed separately for short-, medium-, and long-disordered regions (S-, M-, and LDRs, respectively). The out-of-sample prediction accuracies on a residue-by-residue basis ranged from 69 to 74% for the neural network predictors when applied to the same length class, but fell to 50 to 67% when applied to different length classes. Testing the rule-based predictor on a residue-by-residue basis using out-of-sample LDRs gave a success rate of 70%. Application of both the rule-based and LDR neural network predictors to large databases of protein sequences provide strong evidence that disordered regions are very common in nature. These results are consistent with our recent proposal that disordered regions are crucial for the evolution of molecular recognition.

Original languageEnglish (US)
Title of host publicationIEEE International Conference on Neural Networks - Conference Proceedings
PublisherIEEE
Pages90-95
Number of pages6
Volume1
StatePublished - 1997
Externally publishedYes
EventProceedings of the 1997 IEEE International Conference on Neural Networks. Part 4 (of 4) - Houston, TX, USA
Duration: Jun 9 1997Jun 12 1997

Other

OtherProceedings of the 1997 IEEE International Conference on Neural Networks. Part 4 (of 4)
CityHouston, TX, USA
Period6/9/976/12/97

Fingerprint

Amino acids
Neural networks
Proteins
Molecular recognition
Carboxylic acids
Testing

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Artificial Intelligence

Cite this

Romero, P., Obradovi, Z., Kissinger, C., Villafranca, J. E., & Dunker, A. (1997). Identifying disordered regions in proteins from amino acid sequence. In IEEE International Conference on Neural Networks - Conference Proceedings (Vol. 1, pp. 90-95). IEEE.

Identifying disordered regions in proteins from amino acid sequence. / Romero, P.; Obradovi, Z.; Kissinger, C.; Villafranca, J. E.; Dunker, A.

IEEE International Conference on Neural Networks - Conference Proceedings. Vol. 1 IEEE, 1997. p. 90-95.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Romero, P, Obradovi, Z, Kissinger, C, Villafranca, JE & Dunker, A 1997, Identifying disordered regions in proteins from amino acid sequence. in IEEE International Conference on Neural Networks - Conference Proceedings. vol. 1, IEEE, pp. 90-95, Proceedings of the 1997 IEEE International Conference on Neural Networks. Part 4 (of 4), Houston, TX, USA, 6/9/97.
Romero P, Obradovi Z, Kissinger C, Villafranca JE, Dunker A. Identifying disordered regions in proteins from amino acid sequence. In IEEE International Conference on Neural Networks - Conference Proceedings. Vol. 1. IEEE. 1997. p. 90-95
Romero, P. ; Obradovi, Z. ; Kissinger, C. ; Villafranca, J. E. ; Dunker, A. / Identifying disordered regions in proteins from amino acid sequence. IEEE International Conference on Neural Networks - Conference Proceedings. Vol. 1 IEEE, 1997. pp. 90-95
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