# The impact of AlphaFold Protein Structure Database on the fields of life sciences

Review · Mihály Váradi, Sameer S Velankar

- Archive id: doi:10.1002/pmic.202200128
- Published: 2022-11-16
- Venue: PROTEOMICS
- DOI: https://doi.org/10.1002/pmic.202200128
- PMID: 36382391
- Citations: 125
- Source URL: https://doi.org/10.1002/pmic.202200128
- PDF: https://onlinelibrary.wiley.com/doi/pdfdirect/10.1002/pmic.202200128
- Provenance: openalex

## Abstract

Arguably, 2020 was the year of high-accuracy protein structure predictions, with AlphaFold 2.0 achieving previously unseen accuracy in the Critical Assessment of Protein Structure Prediction (CASP). In 2021, DeepMind and EMBL-EBI developed the AlphaFold Protein Structure Database to make an unprecedented number of reliable protein structure predictions easily accessible to the broad scientific community. We provide a brief overview and describe the latest developments in the AlphaFold database. We highlight how the fields of data services, bioinformatics, structural biology, and drug discovery are directly affected by the influx of protein structure data. We also show examples of cutting-edge research that took advantage of the AlphaFold database. It is apparent that connections between various fields through protein structures are now possible, but the amount of data poses new challenges. Finally, we give an outlook regarding the future direction of the database, both in terms of data sets and new functionalities.

_Abstract reproduced under CC-BY (publisher license, via OpenAlex)._

Topics: [AI Protein Design & Structure Prediction](https://space-kitty.com/topics/protein-design)

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