Abstract
We give an algorithm that locally improves the fit between two proteins modeled as space-filling diagrams. The algorithm defines the fit in purely geometric terms and improves by applying a rigid motion to one of the two proteins. Our implementation of the algorithm takes between three and ten seconds and converges with high likelihood to the correct docked configuration, provided it starts at a position away from the correct one by at most 18 degrees of rotation and at most 3.0Å of translation. The speed and convergence radius make this an attractive algorithm to use in combination with a coarse sampling of the six-dimensional space of rigid motions.
Keywords
- Rigid Motion
- Local Search Heuristic
- Docking Algorithm
- Bovine Pancreatic Trypsin Inhibitor
- Convergence Radius
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
All authors are supported by NSF under grant CCR-00-86013. VC, JR, and HE are also supported by a BGT Postdoc Program from Duke University. JR and HE are also supported by NIH under grant R01 GM61822-01. PA is also supported by NSF under grants EIA-01-31905 and CCR-02-04118 and by the U.S.-Israel Binational Science Foundation.
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Choi, V., Agarwal, P.K., Edelsbrunner, H., Rudolph, J. (2004). Local Search Heuristic for Rigid Protein Docking. In: Jonassen, I., Kim, J. (eds) Algorithms in Bioinformatics. WABI 2004. Lecture Notes in Computer Science(), vol 3240. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30219-3_19
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DOI: https://doi.org/10.1007/978-3-540-30219-3_19
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