Improving Strand Pairing Prediction through Exploring Folding Cooperativity

  • Authors:
  • Jieun Jeong;Piotr Berman;Teresa M. Przytycka

  • Affiliations:
  • Penn State University, University Park;Penn State University, University Park;NIH, Bethesda

  • Venue:
  • IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

The topology of $\beta$-sheets is defined by the pattern of hydrogen-bonded strand pairing. Therefore, predicting hydrogen bonded strand partners is a fundamental step towards predicting $\beta$-sheet topology. At the same time, finding the correct partners is very difficult due to long range interactions involved in strand pairing. Additionally, patterns of aminoacids involved, in $\beta$-sheet formations are very general and therefore difficult to use for computational recognition of specific contacts between strands. In this work, we report a new strand pairing algorithm. To address above mentioned difficulties, our algorithm attempts to mimic elements of the folding process. Namely, in addition to ensuring that the predicted hydrogen bonded strand pairs satisfy basic global consistency constraints, it takes into account hypothetical folding pathways. Consistently with this view, introducing hydrogen bonds between a pair of strands changes the probabilities of forming hydrogen bonds between other pairs of strand. We demonstrate that this approach provides an improvement over previously proposed algorithms. We also compare the performance of this method to that of a global optimization algorithm that poses the problem as integer linear programming optimization problem and solves it using ILOG CPLEX\texttrademark\ package.