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Computational Drug Discovery and Design

Volume 819 of the series Methods in Molecular Biology pp 29-42

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Evolutionary Trace for Prediction and Redesign of Protein Functional Sites

  • Angela WilkinsAffiliated withDepartment of Molecular and Human Genetics, Baylor College of MedicineW. M. Keck Center for Interdisciplinary Bioscience Training
  • , Serkan ErdinAffiliated withDepartment of Molecular and Human Genetics, Baylor College of MedicineW. M. Keck Center for Interdisciplinary Bioscience Training
  • , Rhonald LuaAffiliated withDepartment of Molecular and Human Genetics, Baylor College of Medicine
  • , Olivier LichtargeAffiliated withW. M. Keck Center for Interdisciplinary Bioscience TrainingDepartment of Molecular and Human Genetics, Verna and Marrs Mclean Department of Biochemistry and Molecular Biology, Baylor College of Medicine Email author 

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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/​.

Key words

Evolutionary trace Protein design Protein engineering Function annotation Phylogenomics Protein–protein interaction