AlphaFold3, unlike its predecessors, is capable of modelling proteins in concert with other molecules. But instead of releasing its underlying code as was done with AlphaFold2 DeepMind provided access via a web server that restricted the number and types of predictions scientists could make.The AlphaFold3 server prevented scientists from predicting how proteins behave in the presence of potential drugs. But now, DeepMind’s decision to release the code means academic scientists can predict such interactions by running the model themselves. DeepMind has got competition: over the past few months, several companies have unveiled open-source protein structure prediction tools based on AlphaFold3, relying on specifications described in the original paper known as pseudocode e.g. Two Chinese companies technology giant Baidu and TikTok developer ByteDance have rolled out their own AlphaFold3 inspired models, as has a start-up in San Francisco, California, called Chai Discovery. Is Protein prediction an area that requires huge investing to maximize on research ?
