: The Protein Ensemble Database (PED) (URL: https://proteinensemble.org) is the primary resource for depositing structural ensembles of intrinsically disordered proteins. This updated version of PED reflects advancements in the field, denoting a continual expansion with a total of 461 entries and 538 ensembles, including those generated without explicit experimental data through novel machine learning (ML) techniques. With this significant increment in the number of ensembles, a few yet-unprecedented new entries entered the database, including those also determined or refined by electron paramagnetic resonance or circular dichroism data. In addition, PED was enriched with several new features, including a novel deposition service, improved user interface, new database cross-referencing options and integration with the 3D-Beacons network-all representing efforts to improve the FAIRness of the database. Foreseeably, PED will keep growing in size and expanding with new types of ensembles generated by accurate and fast ML-based generative models and coarse-grained simulations. Therefore, among future efforts, priority will be given to further develop the database to be compatible with ensembles modeled at a coarse-grained level.
PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins / Ghafouri, H., Lazar, T., Del Conte, A., Tenorio Ku, L.G., Tompa, P., Tosatto, S.C.E., Monzon, A.M., Aspromonte, M.C., Bernado, P., Chaves-Arquero, B., Chemes, L.B., Clementel, D., Cordeiro, T.N., Elena-Real, C.A., Feig, M., Felli, I.C., Ferrari, C., Forman-Kay, J.D., Gomes, T., Gondelaud, F., et al.. - In: NUCLEIC ACIDS RESEARCH. - ISSN 1362-4962. - 52:D1(2024), pp. 536-544. [10.1093/nar/gkad947]
PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins
Mercadante D.;
2024
Abstract
: The Protein Ensemble Database (PED) (URL: https://proteinensemble.org) is the primary resource for depositing structural ensembles of intrinsically disordered proteins. This updated version of PED reflects advancements in the field, denoting a continual expansion with a total of 461 entries and 538 ensembles, including those generated without explicit experimental data through novel machine learning (ML) techniques. With this significant increment in the number of ensembles, a few yet-unprecedented new entries entered the database, including those also determined or refined by electron paramagnetic resonance or circular dichroism data. In addition, PED was enriched with several new features, including a novel deposition service, improved user interface, new database cross-referencing options and integration with the 3D-Beacons network-all representing efforts to improve the FAIRness of the database. Foreseeably, PED will keep growing in size and expanding with new types of ensembles generated by accurate and fast ML-based generative models and coarse-grained simulations. Therefore, among future efforts, priority will be given to further develop the database to be compatible with ensembles modeled at a coarse-grained level.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
