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Unfolding the Protein Surface for Pattern Matching
Book chapter   Peer reviewed

Unfolding the Protein Surface for Pattern Matching

Heng Yang, Chunyu Zhao and Ahmet Sacan
Bioinformatics Research and Applications, pp 84-95
31 May 2017
DOI: https://doi.org/10.1007/978-3-319-59575-7_8
Featured in Collection :   UN Sustainable Development Goals @ Drexel

Abstract

Dimension reduction Image processing Ligand binding sites Protein structure Template matching
Protein 3-D structural data is a valuable resource in computational biology, and the comparison and interpretation of protein structural patterns have remained scientific and computational challenges. We introduce a novel representation of 3-D protein surface patches as 2-D images, obtained using dimension reduction. We utilize image registration to compare these surface patches and infer protein function and binding based on surface similarity. Our surface representation can capture various structural and physicochemical properties, including curvature, electrostatic potential, hydrophobicity, and evolutionary conservation. The results we present support the use of surface images as a new type of family-specific signatures in functional annotation and drug-binding tasks. We demonstrate the ability of our method to detect local surface similarities between proteins and to correctly identify functional classification of proteins.

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Collaboration types
Industry collaboration
Domestic collaboration
Web of Science research areas
Biochemical Research Methods
Computer Science, Information Systems
Mathematical & Computational Biology
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