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Lichtarge Computational Biology Lab

Houston, Texas

Lichtarge Computational Biology Lab
Lichtarge Computational Biology Lab
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    To view traces, input a PDB identifier, for example 1f88.


    Evolutionary Trace

    The Evolutionary Trace ranks amino acid residues in a protein sequence by their relative evolutionary importance, and when a structure is available for that protein, it also can display a structural map of where top-ranked residues fall. This can be useful for rational function re-design and protein engineering because biologist can then efficiently target mutations to the most relevant parts of a protein. For example, one may 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. We provide two means of generating and visualizing the ET ranks of importance: the ET Viewer and the ET report_maker.

    PyETV is a plugin for the PyMOL molecular graphics system (Schrödinger, LLC.) that enables viewing, analyzing and manipulating predictions of evolutionarily important residues and sites in protein structures and their complexes. PyETV integrates data from several sources (rank data from ET, structures from PDB, predicted biological units from PISA (Krissinel and Henrick, 2007)) and extends the trace-to-structure mapping originally implemented in the Java-based ET Viewer described below to any number of structures and traces.

    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.

    (06/19/2009)A special note for Mac users:

    The latest Java update for Mac, "Java for Mac OS X 10.5 Update 4", moves the Java Web Start application to a new location, causing problems launching ET viewer and other Java Web Start programs. In order to fix this, you need to show your computer where the new location is for Java Web Start.

    1. In Finder, select the ET_Viewer_2_pub.jnlp file (which is probably in your downloads folder).
    2. Under the "File" menu, select "Get Info".
    3. In the resulting window, there's a section called "Open With:"
    4. Click the drop-down menu and select "Other...". A new window will open.
    5. Navigate to your hard drive, select "System", then "Library", then "CoreServices", and then select Java Web
    6. Then click the "Change All..." button in the "Open With:" section to make this change permanent.

    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.


  • 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.
  • Lua RC and Lichtarge O. PyETV: A PyMOL Evolutionary Trace viewer to analyze functional site predictions in protein complexes. Bioinformatics 2010; doi: 10.1093/bioinformatics/btq566
  • Morgan, D.H., D.M. Kristensen, D. Mittelman, 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.