期刊
BIOCHEMICAL AND BIOPHYSICAL RESEARCH COMMUNICATIONS
卷 355, 期 3, 页码 764-769出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.bbrc.2007.02.040
关键词
protein crystallization; X-ray crystallography; collocated amino acid pairs; classification; CRYSTALP; Naive Bayes
While above 80% of protein structures in PDB were determined using X-ray crystallography, in some cases only 42% of soluble purified proteins yield crystals. Since experimental verification of protein's ability to crystallize is relatively expensive and time-consuming, we propose a new in silico prediction system, called CRYSTALP, which is based on the protein's sequence. CRYSTALP uses a novel feature-based sequence representation and applies a Naive Bayes classifier. It was compared with recent, competing in silico method, SECRET [P. Smialowski, T. Schmidt, J. Cox, A. Kirschner, D. Frishman, Will my protein crystallize'? A sequence-based predictor, Proteins 62 (2) (2006) 343-355], and other state-of-the-art classifiers. Based on experimental tests, CRYSTALP is shown to predict crystallization with 77.5% accuracy, which is better by over 10% than the SECRET's accuracy, and better than accuracy of the other considered classifiers. CRYSTALP uses different and over 50% less features to represent sequences than SECRET. Additionally, features used by CRYSTALP may help to discover intra-molecular markers that influence protein crystallization. (c) 2007 Elsevier Inc. All rights reserved.
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