BETTY: Prediction of beta;-Strand Type from Sequence

Article type: Research Article

Authors: Zimmermann, Olav | Wang, Longhui | Hansmann, Ulrich H.E.^;

Affiliations: John v. Neumann Institute for Computing, FZ Jülich, 52425 Jülich, Germany | Department of Physics, Michigan Technological University, Houghton, MI 49931-1295, USA

Note: [] Corresponding author. E-mail: [email protected]

Abstract: Most secondary structure prediction programs do not distinguish between parallel and antiparallel β-sheets. However, such knowledge would constrain the available topologies of a protein significantly, and therefore aid existing fold recognition algorithms. For this reason, we propose a technique which, in combination with existing secondary structure programs such as PSIPRED, allows one to distinguish between parallel and antiparallel β-sheets. We propose the use of a support vector machine (SVM) procedure, BETTY, to predict parallel and antiparallel sheets from sequence. We found that there is a strong signal difference in the sequence profiles which SVMs can efficiently extract. With strand type assignment accuracies of 90.7% and 83.3% for antiparallel and parallel strands, respectively, our method adds considerably to existing information on current 3-class secondary structure predictions. BETTY has been implemented as an online service which academic researchers can access from our website http://www.fz-juelich.de/nic/cbb/service/service.php.

Keywords: SVM, support vector machine, structure prediction, secondary structure prediction, tertiary structure prediction, beta-sheets, beta-strands, parallel beta-sheets, antiparallel beta-sheets, long range constraints

Journal: In Silico Biology, vol. 7, no. 4-5, pp. 535-542, 2007