--- title: "3D-Jury" chunk: 1/1 source: "https://en.wikipedia.org/wiki/3D-Jury" category: "reference" tags: "science, encyclopedia" date_saved: "2026-05-05T14:00:40.841013+00:00" instance: "kb-cron" --- 3D-Jury is a metaserver that aggregates and compares models from various protein structure prediction servers. 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. 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. The Robetta automatic protein structure prediction server incorporates 3D-Jury into its prediction pipeline. As of January 2024, the links to 3D-Jury originally hosted by the BioInfoBank Institute are no longer valid. == Algorithm == 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. The score, s i m ( M a , b , M i , j ) {\displaystyle sim(M_{a,b},M_{i,j})} , 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". The authors admittedly chose this threshold based on unpublished work.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 ( 3 D − J u r y − s i n g l e ( M a , b ) {\displaystyle 3D-Jury-single(M_{a,b})} ) and the all-model-mode score that considers all models from each server ( 3 D − J u r y − a l l ( M a , b ) {\displaystyle 3D-Jury-all(M_{a,b})} ). The best-model-mode score using one model per server, 3 D − J u r y − s i n g l e ( M a , b ) {\displaystyle 3D-Jury-single(M_{a,b})} , is calculated as, 3 D − J u r y − s i n g l e ( M a , b ) = ∑ i N max j , a ≠ i OR b ≠ j N i ( s i m ( M a , b , M i , j ) ) 1 + N {\displaystyle 3D-Jury-single(M_{a,b})={\frac {\sum _{i}^{N}\max _{j,a\neq i{\mbox{ OR }}b\neq j}^{N_{i}}(sim(M_{a,b},M_{i,j}))}{1+N}}} where N {\displaystyle N} is the number of servers and N i {\displaystyle N_{i}} is the number of top ranking models (with a maximum of 10) from the server i {\displaystyle i} , while a pairwise similarity score is calculated between models M a , b {\displaystyle M_{a,b}} (model b {\displaystyle b} from server a {\displaystyle a} ) and M i , j {\displaystyle M_{i,j}} (model j {\displaystyle j} from server i {\displaystyle i} ). While the all-model-mode score considering all models from the servers, 3 D − J u r y − a l l ( M a , b ) {\displaystyle 3D-Jury-all(M_{a,b})} , is calculated as, 3 D − J u r y − a l l ( M a , b ) = ∑ i N ∑ j , a ≠ i OR b ≠ j N i s i m ( M a , b , M i , j ) 1 + ∑ i N N i {\displaystyle 3D-Jury-all(M_{a,b})={\frac {\sum _{i}^{N}\sum _{j,a\neq i{\mbox{ OR }}b\neq j}^{N_{i}}sim(M_{a,b},M_{i,j})}{1+\sum _{i}^{N}N_{i}}}} 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. == See also == Protein structure prediction Comparison of software for molecular mechanics modeling List of protein structure prediction software == References == == External links == BioInfoBank Meta Server 3D-Jury web interface