PED in 2024: improving the community deposition of structural ensembles for intrinsically disordered proteins

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.

Graphical Abstract

Figure 1.

Experimental techniques and ensemble generation methods. (A) Matrix layout quantifies the combinations of experimental techniques for PED entries, sorted by size. Filled circles in the matrix indicate which experimental measurement is part of the intersection. (B) Distribution of ensemble generation methods and auxiliary software applied in PED. The X axis represents the number of PED entries.

Figure 2.

PEDdeposition service workflow. The workflow begins with the submission of an ensemble, which includes the description of both experimental and computational components, the deposition of conformers and the specification of the protein construct via UniProt accessions and/or protein sequence. The next step involves running the validation pipeline to evaluate the uploaded structures and generating insightful statistics through tools such as MolProbity, DSSP and calculating the radius of gyration. At the final stage, the submitted ensemble entry undergoes a final review by biocurators who determine whether to accept or reject it. Ultimately, approved ensembles are subsequently published on PED for public access.