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

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.