PSI Structural Biology Knowledgebase

PSI | Structural Biology Knowledgebase
Header Icons
E-Collection

Related Articles
Drug Discovery: Solving the Structure of an Anti-hypertension Drug Target
July 2015
Retrospective: 7,000 Structures Closer to Understanding Biology
July 2015
Design and Evolution: Bespoke Design of Repeat Proteins
June 2015
Design and Evolution: Molecular Sleuthing Reveals Drug Selectivity
June 2015
Design and Evolution: Tunable Antibody Binders
June 2015
Design and Evolution: Unveiling Translocator Proteins
June 2015
Evolution of Photoconversion
June 2015
Families in Gene Neighborhoods
June 2015
Protein Folding and Misfolding: A TRiC-ster that Follows the Rules
March 2015
Protein Folding and Misfolding: Beneficial Aggregation
March 2015
Peptidyl-carrier Proteins
October 2014
Predicting Protein Crystal Candidates
October 2014
Protein and Peptide Synthesis: Coming Full Circle
October 2014
Protein and Peptide Synthesis: Sensing Energy Balance
October 2014
Mining Protein Dynamics
May 2014
Novel Proteins and Networks: Assigning Function
May 2014
Novel Proteins and Networks: Polysaccharide Metabolism in the Human Gut
May 2014
Design and Discovery: Evolutionary Dynamics
January 2014
Design and Discovery: Identifying New Enzymes and Metabolic Pathways
January 2014
Design and Discovery: Virtual Drug Screening
January 2014
Caught in the Act
December 2013
Microbiome: Insights into Secondary Bile Acid Synthesis
September 2013
Microbiome: Structures from Lactic Acid Bacteria
September 2013
The Immune System: A Brotherhood of Immunoglobulins
June 2013
The Immune System: Super Cytokines
June 2013
Design and Discovery: A Cocktail for Proteins Without ID
February 2013
Design and Discovery: Enzyme Reprogramming
February 2013
Design and Discovery: Extreme Red Shift
February 2013
Design and Discovery: Flexible Backbone Protein Redesign
February 2013
Designer Proteins
February 2013
Membrane Proteome: Sphingolipid Synthesis Selectivity
December 2012
Symmetry from Asymmetry
October 2012
Serum albumin diversity
August 2012
Pocket changes
July 2012
Predictive protein origami
July 2012
Targeting Enzyme Function with Structural Genomics
July 2012
Finding function for enolases
June 2012
Substrate specificity sleuths
April 2012
Disordered Proteins
February 2012
Metal mates
February 2012
Making invisible proteins visible
October 2011
Alpha/Beta Barrels
October 2010
Deducing function from small structural clues
February 2010
Extremely salty
February 2010
Membrane proteins spotted in their native habitat
January 2010
How does Dali work?
December 2009
Secretagogin
December 2009
Designing activity
September 2008

Research Themes Protein design

How does Dali work?

PSI-SGKB [doi:10.1038/th_psisgkb.2009.55]
Technical Highlight - December 2009
Short description: Comparing three-dimensional protein structures can reveal functional clues. The Dali server is one of the most popular ways to achieve this.

DaliLite results page.

New structures are routinely scanned against those already in the Protein Data Bank (PDB) using one of a multitude of structural comparison servers in the hope that they will reveal similarities that will help to indicate a protein's function.

The traditional way to compare structures, and the method that many structural alignment programs use, is to treat each one as a rigid three-dimensional object and superimpose one on the other. Differences are calculated using a least-squares method.

The Dali server works differently, in that it uses a sum-of-pairs method, which produces a measure of similarity by comparing intramolecular distances. Similarity is measured by Dali-Z scores. Structures that have significant similarities have a Z-score above 2, and usually have similar folds.

DaliLite is a standalone software package, which users can download and run locally on their own computers, and it can also be used via the web to compare two structures.

With over 61,000 structures in the PDB, any search requires huge computing power. And so to speed up the process, the Dali server works by organizing structures ahead of time according to their fold. Originally, an internal database of processed PDB entries and their alignments was updated each week, until the sheer number of new structures began to overwhelm the system, leading to the PDB weekly update taking longer than a week to process.

To solve this problem, the update procedure was re-engineered so that similar structures are placed in a graph rather than recorded against every other structure, to speed up both the searching and the cataloguing of new structures.

The nodes of the graph represent protein structures and edges represent alignments. So instead of each structure being linked to all its nearest neighbors, it is now presented as a path of continuous structural similarity. This new mode is 30 times faster than the previous search mode.

But is DaliLite any good? In a recent example, six out of 32 programs or web servers that use a pairwise method of alignment correctly aligned the functional residues in urease and adenosine deaminase 1 . DaliLite was one of them. The others were SSAP, LGA/GDT, TOPOFIT, GASH and PPM.

Related articles

GPCR modeling: any good?

Protein modeling made easy

Model proteins in your lunch break

Maria Hodges

References

  1. H. Hasegawa and L. Holm. Advances and pitfalls of protein structural alignment.
    Curr. Opin. Cell Biol. 19, 341-348 (2009). doi:10.1016/j.sbi.2009.04.003

  2. L. Holm, S. Kääriäinen, P. Rosenström and A. Schenkel. Searching protein structure databases with DaliLite v.3. Bioinformatics.
    24, 2780-2781 (2008). doi:10.1093/bioinformatics/btn507

Structural Biology Knowledgebase ISSN: 1758-1338
Funded by a grant from the National Institute of General Medical Sciences of the National Institutes of Health