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16:41
A Protocol for Computer-Based Protein Structure and Function Prediction
Published on: November 3, 2011
Protein structure-structure alignment with discrete Fréchet distance.
Minghui Jiang1, Ying Xu, Binhai Zhu
1Department of Computer Science, Utah State University, Logan, UT 84322-4205, USA. mjiang@cc.usu.edu
Journal of Bioinformatics and Computational Biology
|March 8, 2008
Summary
This study introduces new algorithms for matching polygonal chains in 2D and 3D spaces using the discrete Fréchet distance, improving geometric similarity assessments for applications like protein structure alignment.
Area of Science:
- Computer Vision
- Computational Biology
- Geometric Algorithms
Background:
- Matching geometric objects is crucial for fields like computer vision and protein structure prediction.
- The Fréchet distance is a superior measure for comparing polygonal chains compared to Hausdorff distance.
- Discrete Fréchet distance approximates continuous Fréchet distance and is suitable for biomolecular structures.
Purpose of the Study:
- Develop algorithms for matching 2D polygonal chains to minimize discrete Fréchet distance under translation and rotation.
- Create an effective heuristic for matching 3D polygonal chains.
- Apply discrete Fréchet distance to protein structure-structure alignment.
Main Methods:
- Novel algorithms for 2D polygonal chain matching under translation and rotation.
- Development of a heuristic approach for 3D polygonal chain matching.
- Empirical evaluation of discrete Fréchet distance in protein structure alignment.
Main Results:
- New algorithms presented for 2D discrete Fréchet distance minimization.
- An effective heuristic for 3D polygonal chain matching is described.
- Demonstrated applicability of discrete Fréchet distance to protein structure comparison.
Conclusions:
- The presented algorithms and heuristics offer improved methods for geometric object matching.
- Discrete Fréchet distance is a valuable tool for assessing similarity in biomolecular structures.
- This work advances the field of computational geometry and its applications in structural biology.
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