Transmembrane structure predictions with hydropathy index/charge two-dimensional trajectories of stochastic dynamical systems.
A novel algorithm is proposed for predicting transmembrane protein secondary structure from two-dimensional vector trajectories consisting of a hydropathy index and formal charge of a test amino acid sequence using stochastic dynamical system models. Two prediction problems are discussed. One is the prediction of transmembrane region counts; another is that of transmembrane regions, i.e. predicting whether or not each amino acid belongs to a transmembrane region. The prediction accuracies, using a collection of well-characterized transmembrane protein sequences and benchmarking sequences, suggest that the proposed algorithm performs reasonably well. An experiment was performed with a glutamate transporter homologue from Pyrococcus horikoshii. The predicted transmembrane regions of the five human glutamate transporter sequences and observations based on the computed likelihood are reported.
Kaburagi
Takashi
T
Department of Electrical Engineering and Bioscience, Waseda University, 3-4-1 Ohkubo, Shinjuku-ku, Tokyo 169-8555, Japan. kaburagi@matsumoto.elec.waseda.ac.jp
Muramatsu
Daigo
D
Matsumoto
Takashi
T
D000465:Algorithms; D000595:Amino Acid Sequence; D027322:Amino Acid Transport System X-AG / Q000737:chemistry / Q000235:genetics; D019843:Archaeal Proteins / Q000737:chemistry / Q000235:genetics; D019295:Computational Biology; D030562:Databases, Protein; D006801:Humans; D016013:Likelihood Functions; D008565:Membrane Proteins / Q000737:chemistry*; D008958:Models, Molecular; D008969:Molecular Sequence Data; D016571:Neural Networks, Computer; D017433:Protein Structure, Secondary; D043902:Pyrococcus horikoshii / Q000737:chemistry / Q000235:genetics; D013269:Stochastic Processes
D027322:Amino Acid Transport System X-AG; D019843:Archaeal Proteins; D008565:Membrane Proteins