DeepMind Technologies’ achievement of applying machine learning to predict 3D protein structures has certainly got the scientific world excited, with some experts hailing a massive step forward for medical research.
AlphaFold2 was triumphant in a biennial contest, the Critical Assessment of Protein Structure Prediction (CASP). It beat more than 100 other computational protein prediction teams in two categories – regular targets and interdomain predictions analysis. DeepMind’s software tested in illustrating 3D protein structures was already known by biologists, to some degree, without having been made public. The results of the contest were unveiled in November 2020.
DeepMind has published peer-review papers in two academic journals, Nature and Proteins: Structure, Function and Bioinformatics, arguing its algorithms can help figure out how amino acids fold into 3D protein structures.
Its model started with massive genomic and structural data sets to establish distances between individual pairs of amino acids, according to Nature. More development then added information on physical and geometric boundaries that influence protein folding and its target was expanded to establishing the final structures of target protein sequences.
DeepMind is a…
