CAMEO - Perspectives on the future of fully automated evaluation of structure prediction methods
By X. Robin, J. Haas, Rafal Gumienny, Anna Smolinski, Gerardo Tauriello, Torsten Schwede. 2021
68 citations recorded by the source corpus.
The Continuous Automated Model EvaluatiOn (CAMEO) platform complements the biennial CASP experiment by conducting fully automated blind evaluations of three‐dimensional protein prediction servers based on the weekly prerelease of sequences of those structures, which are going to be published in the upcoming release of the Protein Data Bank. While in CASP14, significant success was observed in predicting the structures of individual protein chains with high accuracy, significant challenges remain in correctly predicting the structures of complexes. By implementing fully automated evaluation of predictions for protein–protein complexes, as well as for proteins in complex with ligands, peptides, nucleic acids, or proteins containing noncanonical amino acid residues, CAMEO will assist new developments in those challenging areas of active research.
Subfields: Computational Theory and Mathematics, Materials Chemistry, Molecular Biology
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Citations in the corpus
- Assessment of three-dimensional RNA structure prediction in CASP15 (2023, neutral): “59,60 Across all targets, lDDT values for best predictions ranged from 0.5 to between each pair of scores labeled on each row and column, colored by high correlation (dark blue), no correlation (white).”
- Dynamic-Backbone Protein-Ligand Structure Prediction with Multiscale Generative Diffusion Models (2022, methodology): “Protein binding site accuracy is measured by the lDDT-BS metric [47] with cutoff parameters consistent with CAMEO [48].”