AI system AlphaFold added WHO priority pathogens to its library
By using its AI-based system AlphaFold British company DeepMind has added the predicted proteome of almost the complete list of WHO priority pathogens to their library. The database will be expanded during 2022 to cover a large proportion of all catalogued proteins (the over 100 million in UniRef90). This holds exciting promises for the fight against AMR and novel antibiotics research.
Determining the 3D structure of proteins is one of the biggest challenges in modern biology and has the potential to dramatically deepen the understanding of nature, with implications for all areas, including drug design. AlphaFold, a state-of-the-art AI system developed by London-based company DeepMind which was bought by internet giant Google, is able to computationally predict protein structures with unprecedented accuracy and speed. As reported in Nature in 2021, AlphaFold has been shown to yield results in a high number of cases that are as accurate as real experiments. With AlphaFold researchers can obtain a prediction with a 58% reliability and save an enormous amount of time. These predictions are being made freely and openly available to the global scientific community in partnership with EMBL’s European Bioinformatics Institute (EMBL-EBI), giving way to new and exciting research opportunities. DeepMind and EMBLpublished more than 350,000 structures on July in 2021, including some 20,000 human proteins and those of 20 other organisms, such as a lab mouse and the tuberculosis bacteria. Venki Ramakrishnan of the Medical Research Council Laboratory of Molecular Biology in Cambridge and winner of the 2009 Nobel Prize in Chemistry, says at the time that it is “an astonishing advancement” with unpredictable consequences. “It has taken place long before many experts had predicted. It is going to be exciting to see the many ways in which it is going to radically change biological investigation.”
Learn more about Alphafold here: https://alphafold.ebi.ac.uk/
Directly go to the pathogen proteome database: https://alphafold.ebi.ac.uk/download