Abstract
The evolutionary trace (ET) is the single most validated approach to identify protein functional determinants and to target mutational analysis, protein engineering and drug design to the most relevant sites of a protein. It applies to the entire proteome; its predictions come with a reliability score; and its results typically reach significance in most protein families with 20 or more sequence homologs. In order to identify functional hot spots, ET scans a multiple sequence alignment for residue variations that correlate with major evolutionary divergences. In case studies this enables the selective separation, recoding, or mimicry of functional sites and, on a large scale, this enables specific function predictions based on motifs built from select ET-identified residues. ET is therefore an accurate, scalable and efficient method to identify the molecular determinants of protein function and to direct their rational perturbation for therapeutic purposes. Public ET servers are located at: http://mammoth.bcm.tmc.edu/.
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Acknowledgments
The authors gratefully acknowledge grant support from the National Institute of Health through NIH-GM079656, NIH-GM066099, T90 DA022885, R90 DA023418, NLM 5T15LM07093, and of the National Science Foundation through NSF CCF-0905536.
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Wilkins, A., Erdin, S., Lua, R., Lichtarge, O. (2012). Evolutionary Trace for Prediction and Redesign of Protein Functional Sites. In: Baron, R. (eds) Computational Drug Discovery and Design. Methods in Molecular Biology, vol 819. Springer, New York, NY. https://doi.org/10.1007/978-1-61779-465-0_3
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DOI: https://doi.org/10.1007/978-1-61779-465-0_3
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