title: Protein topology classification using two-stage support vector machines.
abstract: The determination of the first 3-D model of a protein from its sequence alone is a non-trivial problem. The first 3-D model is the key to the molecular replacement method of solving phase problem in x-ray crystallography. If the sequence identity is more than 30%, homology modelling can be used to determine the correct topology (as defined by CATH) or fold (as defined by SCOP). If the sequence identity is less than 25%, however, the task is very challenging. In this paper we address the topology classification of proteins with sequence identity of less than 25%. The input information to the system is amino acid sequence, the predicted secondary structure and the predicted real value relative solvent accessibility. A two stage support vector machine (SVM) approach is proposed for classifying the sequences to three different structural classes (alpha, beta, alpha+beta) in the first stage and 39 topologies in the second stage. The method is evaluated using a newly curated dataset from CATH with maximum pairwise sequence identity less than 25%. An impressive overall accuracy of 87.44% and 83.15% is reported for class and topology prediction, respectively. In the class prediction stage, a sensitivity of 0.77 and a specificity of 0.91 is obtained. Data file, SVM implementation (SVMHEAVY) and result files can be downloaded from http://www.ee.unimelb.edu.au/ISSNIP/downloads/.
authors.affiliation: Department of Electrical and Electronics Engineering, The University of Melbourne, Parkville, Victoria 3010, Australia. jrgl@ee.unimelb.edu.au
authors.forename: Jayavardhana
authors.initials: J
authors.lastname: Gubbi
authors.forename: Alistair
authors.initials: A
authors.lastname: Shilton
authors.forename: Michael
authors.initials: M
authors.lastname: Parker
authors.forename: Marimuthu
authors.initials: M
authors.lastname: Palaniswami
mesh_terms: D000595:Amino Acid Sequence; D018360:Crystallography, X-Ray; D016208:Databases, Factual; D019143:Evolution, Molecular; D008969:Molecular Sequence Data; D011237:Predictive Value of Tests; D011487:Protein Conformation; D017510:Protein Folding; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry* / Q000145:classification*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016415:Sequence Alignment / Q000379:methods; D020539:Sequence Analysis, Protein; D012984:Software; D012997:Solvents / Q000737:chemistry; D013816:Thermodynamics
chemical_list: D011506:Proteins; D012997:Solvents