Pfam 22.0 :: Help Page : Graphic domain view
How to interpret and configure graphical view of sequences

Configuring and interpreting Pfam graphic domain views

Aside from Pfam domains, the graphic view of sequences includes the locations of SMART domains and four types of automated annotation that is computed for all sequences with each major Pfam release. Each Pfam-A and Pfam-B domain and each type of other annotation has a distinct graphic associated with it.

The graphic objects

A key is printed at the top and bottom of the graphic domain view to help you interpret the graphics.

Clicking on a sequence name links to the SwissProt entry for that sequence.

Mousing over any graphic object will display additional information in the status bar, located at the bottom of the browser windows. The type of object and start and end points in the sequence will be shown. In addition, Pfam-A objects will display a short description. Mouse clicks have different effects depending on the object.

Configuring the view

Annotation will often overlap, and one type of annotation will obscure others. You can configure the display priority with the series of drop-down menus near the top of the page. The priority is from left to right. You can select the blank menu entry to remove a type of annotation.

More on non-domain annotation

The following types of annotation are all generated automatically for each major Pfam release by running programs on the entire set of Pfam sequences. The program used follows the description below.

Transmembrane regions

Transmembrane helices indicate a protein has a membrane bound location. Prediction of individual transmembrane spans is quite accurate however care must be exercised and these regions should be verified by other means.

TMHMM (v2.0)

  1. A. Krogh, B. Larsson, G. von Heijne, and E. L. L. Sonnhammer.
    Predicting transmembrane protein topology with a hidden Markov model: Application to complete genomes.
    Journal of Molecular Biology, 305(3):567-580, January 2001.

  2. E.L.L. Sonnhammer, G. von Heijne, and A. Krogh.
    A hidden Markov model for predicting transmembrane helices in protein sequences.
    In J. Glasgow, T. Littlejohn, F. Major, R. Lathrop, D. Sankoff, and C. Sensen, editors, Proceedings of the Sixth International Conference on Intelligent Systems for Molecular Biology, pages 175-182, Menlo Park, CA, 1998. AAAI Press.

Signal peptide

Signal peptides indicate a protein that will be secreted. Prediction of signal peptides is quite accurate however care must be exercised and these regions should be verified by other means.

SignalP (v1.1)

  1. Henrik Nielsen, Jacob Engelbrecht, Søren Brunak and Gunnar von Heijne.
    Identification of prokaryotic and eukaryotic signal peptides and prediction of their cleavage sites.
    Protein Engineering 10, 1-6 (1997)

Coiled coils

Coiled coils are found in a wide variety of proteins. Structurally they are composed of two or three alpha helices that wind around each other.

ncoils

  1. R.B. Russell, A.N. Lupas, 1999 based on Lupas, Van Dyck & Stock (1991) Science 252,1162-1164

Low complexity regions

Low complexity regions are regions of biased composition. These regions are often mosiacs of a small number of amino acids. These regions have been shown to be functionally important in some proteins, but they are generally not very well understood.

seg

  1. Wan H, Wootton JC. Related Articles
    A global compositional complexity measure for biological sequences: AT-rich and GC-rich genomes encode less complex proteins.
    Comput Chem. 2000 Jan;24(1):71-94.
    PMID: 10642881

  2. Wootton JC. Related Articles
    Non-globular domains in protein sequences: automated segmentation using complexity measures.
    Comput Chem. 1994 Sep;18(3):269-85.
    PMID: 7952898