AlphaFill: enriching AlphaFold models with ligands and cofactors
By Maarten L. Hekkelman, I. de Vries, Robbie P. Joosten, Anastassis Perrakis. 2022
396 citations recorded by the source corpus.
Artificial intelligence-based protein structure prediction approaches have had a transformative effect on biomolecular sciences. The predicted protein models in the AlphaFold protein structure database, however, all lack coordinates for small molecules, essential for molecular structure or function: hemoglobin lacks bound heme; zinc-finger motifs lack zinc ions essential for structural integrity and metalloproteases lack metal ions needed for catalysis. Ligands important for biological function are absent too; no ADP or ATP is bound to any of the ATPases or kinases. Here we present AlphaFill, an algorithm that uses sequence and structure similarity to ‘transplant’ such ‘missing’ small molecules and ions from experimentally determined structures to predicted protein models. The algorithm was successfully validated against experimental structures. A total of 12,029,789 transplants were performed on 995,411 AlphaFold models and are available together with associated validation metrics in the alphafill.eu databank, a resource to help scientists make new hypotheses and design targeted experiments. The AlphaFill algorithm transplants missing small molecules and ions from experimentally determined structures to predicted protein models in the AlphaFold protein structure database. All AlphaFill entries are available for visual inspection and download through the AlphaFill website.
Subfields: Materials Chemistry, Molecular Biology
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Materials Chemistry
- Anastasiia V. Sadybekov
- Jingi Yeo
- Vsevolod Katritch
- S. Velankar
- Martin Steinegger
- Milot Mirdita
- Mihaly Varadi
In Molecular Biology
- Milot Mirdita
- Martin Steinegger
- S. Velankar
- Mihaly Varadi
- Jingi Yeo
- Anastasiia V. Sadybekov
- Ewan Birney
- Vsevolod Katritch
Citations in the corpus
- Computational approaches streamlining drug discovery (2023, background): “The recently developed AphaFill approach 109 for ‘transplanting’ small-molecule cofactors and ligands form PDB structures to homologous AlphaFold2 models can potentially help to validate and optimize these models, although further assessment of their utility for docking and virtual screening is…”
- AlphaFold Protein Structure Database in 2024: providing structure coverage for over 214 million protein sequences (2023, positive): “In parallel with these anticipated data updates, we are also working towards enriching the predicted structures with domain annotations ( 26 ), integrating small molecules through AlphaFill ( 27 ), referencing cross-linking data, and devising dedicated pages tailored for fragments.”