title: Prediction of non-classical secreted proteins using informative physicochemical properties.
abstract: The prediction of non-classical secreted proteins is a significant problem for drug discovery and development of disease diagnosis. The characteristic of non-classical secreted proteins is they are leaderless proteins without signal peptides in N-terminal. This characteristic makes the prediction of non-classical proteins more difficult and complicated than the classical secreted proteins. We identify a set of informative physicochemical properties of amino acid indices cooperated with support vector machine (SVM) to find discrimination between secreted and non-secreted proteins and to predict non-classical secreted proteins. When the sequence identity of dataset was reduced to 25%, the prediction accuracy on training dataset is 85% which is much better than the traditional sequence similarity-based BLAST or PSI-BLAST tool. The accuracy of independent test is 82%. The most effective features of prediction revealed the fundamental differences of physicochemical properties between secreted and non-secreted proteins. The interpretable and valuable information could be beneficial for drug discovery or the development of new blood biochemical examinations.
authors.affiliation: Institute of Bioinformatics and Systems Biology, National Chiao Tung University, Hsinchu, 300, Taiwan.
authors.forename: Chiung-Hui
authors.initials: CH
authors.lastname: Hung
authors.forename: Hui-Ling
authors.initials: HL
authors.lastname: Huang
authors.forename: Kai-Ti
authors.initials: KT
authors.lastname: Hsu
authors.forename: Shinn-Jang
authors.initials: SJ
authors.lastname: Ho
authors.forename: Shinn-Ying
authors.initials: SY
authors.lastname: Ho
mesh_terms: D000595:Amino Acid Sequence; D000596:Amino Acids / Q000032:analysis*; D055808:Drug Discovery; D006403:Hematologic Tests / Q000379:methods; D011506:Proteins / Q000737:chemistry*; D015203:Reproducibility of Results; D020539:Sequence Analysis, Protein / Q000379:methods*; D060388:Support Vector Machine
chemical_list: D000596:Amino Acids; D011506:Proteins