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Authors: Zafer Aydin 1 ; David Baker 2 and William Stafford Noble 2

Affiliations: 1 Abdullah Gul University, Turkey ; 2 University of Washington, United States

Keyword(s): Protein Torsion Angle Prediction, Structural Frequency Profiles, Template Scoring, Profile-Profile Alignment.

Related Ontology Subjects/Areas/Topics: Algorithms and Software Tools ; Bioinformatics ; Biomedical Engineering ; Model Design and Evaluation ; Sequence Analysis ; Structural Bioinformatics ; Structure Prediction

Abstract: Structural frequency profiles provide important constraints on structural aspects of a protein and is receiving a growing interest in the structure prediction community. In this paper, we introduce new techniques for scoring templates that are later combined to form structural profiles of 7-state torsion angles. By employing various parameters of target-template alignments we improve the quality and accuracy of structural profiles considerably. The most effective technique is the scaling of templates by integer powers of sequence identity score in which the power parameter is adjusted with respect to the similarity interval of the target. Incorporating other alignment scores as multiplicative factors further improves the accuracy of profiles. After analyzing the individual strengths of various structural profile methods, we combine them with ab-initio predictions of 7-state torsion angles by a linear committee approach. We show that incorporating template information improves the ac curacy of ab-initio predictions significantly at all levels of target-template similarity even when templates are distant from the target. Template scaling methods developed in this work can be applied in many other prediction tasks and in more advanced methods designed for computing structural profiles. (More)

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Paper citation in several formats:
Aydin, Z.; Baker, D. and Noble, W. (2015). Constructing Structural Profiles for Protein Torsion Angle Prediction. In Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms (BIOSTEC 2015) - BIOINFORMATICS; ISBN 978-989-758-070-3; ISSN 2184-4305, SciTePress, pages 26-35. DOI: 10.5220/0005208500260035

@conference{bioinformatics15,
author={Zafer Aydin. and David Baker. and William Stafford Noble.},
title={Constructing Structural Profiles for Protein Torsion Angle Prediction},
booktitle={Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms (BIOSTEC 2015) - BIOINFORMATICS},
year={2015},
pages={26-35},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005208500260035},
isbn={978-989-758-070-3},
issn={2184-4305},
}

TY - CONF

JO - Proceedings of the International Conference on Bioinformatics Models, Methods and Algorithms (BIOSTEC 2015) - BIOINFORMATICS
TI - Constructing Structural Profiles for Protein Torsion Angle Prediction
SN - 978-989-758-070-3
IS - 2184-4305
AU - Aydin, Z.
AU - Baker, D.
AU - Noble, W.
PY - 2015
SP - 26
EP - 35
DO - 10.5220/0005208500260035
PB - SciTePress

- Science and Technology Publications, Lda.
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