3D-Jury
3D-Jury is a metaserver that aggregates and compares models from various protein structure prediction servers.[1]
The 3D-Jury algorithm takes in groups of predictions made by a collection of servers and assigns each pair a 3D-Jury score, based on structural similarity. To improve accuracy of the final model, users can select the prediction servers from which to aggregate results.[1] The authors of 3D-Jury designed the system as a meta-predictor because earlier results concluded that the average low-energy protein conformation (by way of aggregation) fit the true conformation better than simply the lowest-energy protein conformation.[2]
The Robetta automatic protein structure prediction server incorporates 3D-Jury into its prediction pipeline.[3]
As of January 2024, the links to 3D-Jury originally hosted by the BioInfoBank Institute are no longer valid.[4]
Algorithm
[edit]First, pairwise comparisons are made between every combination of models generated from chosen protein prediction servers. Each comparison is then scored using the MaxSub tool.[5] The score, , is generated by counting the number of Cα atoms in the two predictions within 3.5 Å of each other after being superpositioned.
To get a roughly 90% chance two models are of a similar fold class, the authors set a threshold of 40 as the lowest score possible for a pair of models to be annotated as "similar".[1] The authors admittedly chose this threshold based on unpublished work.
There are two scores 3D-Jury gives: the best-model-mode score using one model from each server () and the all-model-mode score that considers all models from each server ().[1]
The best-model-mode score using one model per server, , is calculated as,
where is the number of servers and is the number of top ranking models (with a maximum of 10) from the server , while a pairwise similarity score is calculated between models (model from server ) and (model from server ).[1]
While the all-model-mode score considering all models from the servers, , is calculated as,
using similar variables as noted with the best-model-mode score.
Note, these meta-predictor scores do not take into account the confidence scores from each of the models from other servers.[1]
References
[edit]- ^ a b c d e f Ginalski K; et al. (2003). "3D-Jury: a simple approach to improve protein structure predictions". Bioinformatics. 19 (8): 1015–1018. doi:10.1093/bioinformatics/btg124. ISSN 1367-4803. OCLC 110817016. PMID 12761065.
- ^ Bonneau, Richard; Ruczinski, Ingo; Tsai, Jerry; Baker, David (2002). "Contact order and ab initio protein structure prediction". Protein Science. 11 (8): 1937–1944. doi:10.1110/ps.3790102. ISSN 0961-8368. OCLC 112117834. PMC 2373674. PMID 12142448.
- ^ Chivian D; et al. (2005). "Prediction of CASP6 structures using automated Robetta protocols". Proteins. 61 (S7): 157–166. doi:10.1002/prot.20733. PMID 16187358. S2CID 8122486. Archived from the original on 2012-12-10.
- ^ "BioInfoBank Meta Server". BioInfoBank Meta Server. Archived from the original on 2007-01-13. Retrieved 2024-01-17.
- ^ Siew, Naomi; Elofsson, Arne; Rychlewski, Leszek; Fischer, Daniel (2000-09-01). "MaxSub: an automated measure for the assessment of protein structure prediction quality". Bioinformatics. 16 (9): 776–785. doi:10.1093/bioinformatics/16.9.776. ISSN 1367-4803. OCLC 121793099. PMID 11108700.
External links
[edit]- BioInfoBank Meta Server 3D-Jury web interface