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1,505 claims from 935 papers are on the record. 46 have been checked so far; the other 1,459 have no check with a result yet.

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Status: Unchecked ×Keyword: protein 3D structure ×Clear all

5 claims from 2 papers

1. Materials Science › Enzyme Structure and Function

   RCSB Protein Data Bank (RCSB.org): delivery of experimentally-determined PDB structures alongside one million computed structure models of proteins from artificial intelligence/machine learning

   Burley, Bhikadiya, Bi et al. · Nucleic Acids Research · 2022

   Unchecked3 claims
   Show 3 claims

   1. Unchecked“Every PDB structure and CSM is integrated weekly with related functional annotations from external biodata resources, providing up-to-date information for the entire corpus of 3D biostructure data freely available from RCSB.org with no usage limitations.”
   2. Unchecked“Within RCSB.org, PDB structures and the CSMs are clearly identified as to their provenance and reliability.”
   3. Unchecked“Both are fully searchable, and can be analyzed and visualized using the full complement of RCSB.org web portal capabilities.”

2. Biochemistry, Genetics and Molecular Biology › Protein Structure and Dynamics

   State-of-the-Art Estimation of Protein Model Accuracy Using AlphaFold

   Roney and Ovchinnikov · Physical Review Letters · 2022

   The paper argues AlphaFold has learned an approximate energy function, which can rank candidate protein structures with state-of-the-art accuracy without coevolution data.

   Unchecked2 claims
   Show 2 claims

   1. UncheckedThe authors present evidence that AlphaFold has learned an energy function for protein folding and uses coevolution data to search for low-energy shapes.“We provide evidence that alphafold has learned such an energy function, and uses coevolution data to solve the global search problem of finding a low-energy conformation.”
   2. UncheckedAlphaFold's learned energy function can rank candidate protein structures by quality with state-of-the-art accuracy, without any coevolution data.“We demonstrate that alphafold'slearned energy function can be used to rank the quality of candidate protein structures with state-of-the-art accuracy, without using any coevolution data.”