Current Bioinformatics

Yi-Ping Phoebe Chen
Department of Computer Science and Information Technology
La Trobe University
Melbourne
Australia

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Improved Prediction of Protein Crystallization, Purification and Production Propensity Using Hybrid Sequence Representation

Author(s): Jianzhao Gao, Gang Hu, Zhonghua Wu, Jishou Ruan, Shiyi Shen, Michelle Hanlon, Kui Wang.

Abstract:

Production of high-quality crystals is one of the main bottlenecks in X-ray crystallography-based protein structure determination. In this paper we introduce PPCinter, a novel method to predict the propensity for production of diffraction-quality crystals, production of crystals, purification and production of protein material.

PPCinter utilizes not only intra-molecular factors, but considers inter-molecular factors as well. Our method outperforms several current crystallization predictors, obtaining an overall accuracy of 57.5% and an average MCC of 0.39. Our method also reveals several factors that influence the success of the crystallization process, including the unfold-based index, energy-based, solvent accessibility, and hydrophobicity-based indices, amino acid composition, the isoelectric point and disorder-based features.

The proposed method, PPCinter, could provide useful input for the target selection procedures utilized by structural genomics centers.

Keywords: Protein crystallization, protein purification, X-ray crystallography.

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Article Details

VOLUME: 9
ISSUE: 1
Year: 2014
Page: [57 - 64]
Pages: 8
DOI: 10.2174/15748936113080990006