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| title | chunk | source | category | tags | date_saved | instance |
|---|---|---|---|---|---|---|
| 3D-Jury | 1/1 | https://en.wikipedia.org/wiki/3D-Jury | reference | science, encyclopedia | 2026-05-05T14:00:40.841013+00:00 | 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 As of January 2024, the links to 3D-Jury originally hosted by the BioInfoBank Institute are no longer valid.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,
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{\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 The authors admittedly chose this threshold based on unpublished work.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 (
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{\displaystyle 3D-Jury-single(M_{a,b})}
) and the all-model-mode score that considers all models from each server (
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{\displaystyle 3D-Jury-all(M_{a,b})}
). The best-model-mode score using one model per server,
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{\displaystyle 3D-Jury-single(M_{a,b})}
, is calculated as,
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{\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
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{\displaystyle N}
is the number of servers and
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{\displaystyle N_{i}}
is the number of top ranking models (with a maximum of 10) from the server
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{\displaystyle i}
, while a pairwise similarity score is calculated between models
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{\displaystyle M_{a,b}}
(model
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from server
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{\displaystyle a}
) and
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{\displaystyle M_{i,j}}
(model
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from server
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). While the all-model-mode score considering all models from the servers,
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{\displaystyle 3D-Jury-all(M_{a,b})}
, is calculated as,
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{\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