Tools predicting protein level changes
An extensive overview of tools predicting protein level changes can be found from the recent review article by Thusberg and Vihinen. The program categorisation used here follows the one in the review article. Because of the large amount of programs available the information concerning the each subgroup is divided to its own page. Below are listed the subcategories of the protein prediction tools. Click each title to see detailed information about tools belonging to each subgroup.
This subgroup of methods mainly predicts whether the mutation has an effect on disease susceptibility or not. Methods does not take into account the protein level change which causes the difference in disease susceptibility.
Methods of this group are based on the fact that the changes in more conserved amino acids are more likely to cause effects to proteins function than changes in less conserved amino acids. Therefore the important step in these analysis is the protein multiple sequence alignment. This subgorup collects together programs constructing these multiple sequence alignments (MSAs).
Good way to detect information about positional sequence conservation is to visualize MSAs. This subgroup of tools consist of programs visualizing the MSAs, calculating conservation indices for each position in the alignment and color-coding the aligment for different level of sequence conservation (Thusberg et al). Group also contains tools which do the color-coding for protein-structures or based on physicochemical properties.
Changes in the stability of the protein as a result of the mutation is one important factors considered to predict the mutations ability to increase disease susceptibility. This subgroup of programs contains tools predicting whether the mutation has an effect on proteins stability.
Disorder prediction is associated with disordered proteins. These kinds of proteins exists and they are important in tasks like molecular recognition, molecular assembly, protein assembly and entropy chain and several other important tasks. In addition to these proteins mutations may introduce disorder into usually ordered parts of protein and therefore possible change the protein function (Thusberg and Vihinen 2009).
Chemical bonds and interactions between amino acid side chains determine the two- and three dimensional fold and detailed shape of the protein. Changes in these bond and interactions as a result of mutation effect the stability of the proteins and can therefore have an affect on disease susceptibility. Tools gathered into this subgroup evaluate these interatomic contacts.
Aggregation of proteins have been linked with diseases like neurogenerative diseases. Missense mutations can change the properties of proteins so that its tendency to aggregate increase. For this reason the predisposition of mutated proteins is evalutated by using the tools described in this group.
This subgroup contains methods belonging to group of proteomics tools (like SABLE and SNPeffect) and other tools like ExPASy.
- PDB (database of protein structures containing currently around 60 000 protein structures)
- HGMD (Human Genome Mutation Database)
- OMIM (Online Mendelian Heritance in Man)
- KMDB/Mutation View
- LSDBs (Locus specific databases) and CMDBs ( Central Mutation databases) (see list of these)
- Genome browsers: UCSC Genome Browser, NCBI Map Viewer and Ensemble Genome Browser
- Janita Thusberg and Mauno Vihinen. Pathogenic or Not? And If So, Then How? Studying the Effects of Missense Mutations Using Bioinformatics Methods. Hum Mutat. 2009 May;30(5):703-14: doi:10.1002/humu.20938