Graphical models of residue coupling in protein families
Proceedings of the 5th international workshop on Bioinformatics
Graphical Models of Residue Coupling in Protein Families
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Protein Fragment Swapping: A Method for Asymmetric, Selective Site-Directed Recombination
RECOMB 2'09 Proceedings of the 13th Annual International Conference on Research in Computational Molecular Biology
RECOMB'08 Proceedings of the 12th annual international conference on Research in computational molecular biology
Optimization of combinatorial mutagenesis
RECOMB'11 Proceedings of the 15th Annual international conference on Research in computational molecular biology
Algorithms for optimizing cross-overs in DNA shuffling
Proceedings of the 2nd ACM Conference on Bioinformatics, Computational Biology and Biomedicine
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Relationships among amino acids determine stability and function and are also constrained by evolutionary history. We develop a probabilistic hypergraph model of residue relationships that generalizes traditional pairwise contact potentials to account for the statistics of multi-residue interactions. Using this model, we detected non-random associations in protein families and in the protein database. We also use this model in optimizing site-directed recombination experiments to preserve significant interactions and thereby increase the frequency of generating useful recombinants. We formulate the optimization as a sequentially-constrained hypergraph partitioning problem; the quality of recombinant libraries wrt a set of breakpoints is characterized by the total perturbation to edge weights. We prove this problem to be NP-hard in general, but develop exact and heuristic polynomial-time algorithms for a number of important cases. Application to the beta-lactamase family demonstrates the utility of our algorithms in planning site-directed recombination.