Abstract
More than sequence or structure, function imposes very tight constraints on the evolutionary variability within a protein family. As such, numerous functional site prediction methods are based on algorithms to uncover conserved regions that lead to conserved function. Nevertheless, evolution does allow for some systematic variability within functional regions. Based on this tenet, we have introduced the MINER algorithm to predict functional regions from phylogenetic motifs. Specifically, our approach identifies alignment fragments that parallel the overall phylogeny of the family, which are more likely to be functional due to increased evolutionary signature. In this chapter, we provide an overview of the method, summarize recent developments, and comment on future work.
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Acknowledgements
The development and application of MINER is based on the dedicated work of a number of people. Specifically, we wish to thank Dr. Usman Roshan, Ehsan Tabari, Brian Sutch, Patrick Kidd, and Dr. Sepehr Eskandari for contributions to the results discussed herein.
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Livesay, D.R., KC, D.B., La, D. (2011). Predicting Protein Functional Sites with Phylogenetic Motifs: Past, Present and Beyond. In: Kihara, D. (eds) Protein Function Prediction for Omics Era. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-0881-5_5
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DOI: https://doi.org/10.1007/978-94-007-0881-5_5
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