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Lichtarge Computational Biology Lab

Houston, Texas

Lichtarge Computational Biology Lab
Lichtarge Computational Biology Lab
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Evolutionary Trace


Evolutionary Trace results for 1a5i are available in two ways:

Uniprot P98119.

1a5i colored by chain (from RCSB PDB Image Library).

View Trace of

All Data Files


All results with PyMol:


The ET Viewer runs real-value ET or integer ET and displays results. Its ET Wizard takes a PDB identifier, or file, for input, and it outputs ranks of evolutionary importance for every sequence position in the protein. All trace parameters may be adjusted: custom alignments and phylogenetic trees may be used. The ET Viewer then displays a color map of the structure showing which residues are ranked among the top nth percentile, where n is adjustable, and whether they cluster (a z-score indicates whether these top-ranked residues cluster in a statistically significant manner). A multiple sequence alignment viewer and phylogenetic tree viewer display the underlying data.

Report Only

All Files


The ET report_maker runs real-value ET with hard-wired parameters. The input is either a PDB identifier or a UniProt accession number and it returns a PDF report, plus all data files, including the .etvx file read by the ET Viewer . A feature of the ET_report_maker is that it tries to pool information about protein sequence, structure, and elementary annotations to better interpret the ET ranks of importance of individual residues. It also suggests where one might target mutations, and which subsitutions to make in order to selectively knock out individual functional sites.


Both analyses are based on slightly different alignments, and can be viewed as complementary. These predictions can be useful for rational protein re-design and engineering since they enable researchers to efficiently target mutations to the most relevant parts of a protein. In turn this can selectively block, separate, rewire, or mimic functions. ET-based functional annotations may also be useful to suggest protein function (see the ET Annotation Server). ET rank essentially captures the extent of evolutionary pressure at a given sequence position. It is obtained by correlating the sequence variations in an alignment of a protein family with its evolutionary divergences. Top-ranked residues are associated with variations that correlate with large divergences near the root of the evolutionary tree, and presumably linked to significant functional changes. Poorly-ranked residues in contrast are associated with variations near the leaves of the tree, presumably linked to modest functional differences, if any at all.

This web page gives access to additional pre-computed traces.

E-mail suggestions, bugs and inquiries to:

Selected citations:

  • Lichtarge, O., H.R. Bourne and F.E. Cohen (1996). "An evolutionary trace method defines binding surfaces common to protein families." J. Mol. Biol. 257(2): 342-58.
  • Morgan, D.H., D.M. Kristensen, D. Mittleman, and O. Lichtarge. "ET Viewer: An Application for Predicting and Visualizing Functional Sites in Protein Structures." Bioinformatics. 2006 Aug 15;22(16):2049-50. Epub 2006 Jun 29.
  • Mihalek I., I. Res and O. Lichtarge. "Evolutionary Trace Report Maker: a new type of service for comparative analysis of proteins." Bioinformatics. 2006 Jul 1;22(13):1656-7. Epub 2006 Apr 27.
  • Mihalek, I., I. Res, O. Lichtarge. (2004). "A Family of Evolution-Entropy Hybrid Methods for Ranking of Protein Residues by Importance" J. Mol. Bio. 336(5): 1265-82.
  • Warren L. DeLano "The PyMOL Molecular Graphics System. DeLano Scientific LLC, San Carlos, CA, USA.

  • The Evolutionary Trace is freely available for non-profit use.
    Contact Lisa Beveridge (, 713-798-6821 )
    to request a commercial license from Baylor College of Medicine.