DeepMind, a company owned by Google, announced this week that it had predicted the three-dimensional structures of more than 200 million proteins using AlphaFold.
- AlphaFold is an AI-based protein structure prediction tool.
- It used processes based on “training, learning, retraining and relearning” to predict the structures of the entire 214 million unique protein sequences deposited in the Universal Protein Resource (UniProt) database.
- The Indian community of structural biology needs to take advantage of the AlphaFold database and learn how to use the structures to design better vaccines and drugs.
- The first step uses the available structures of 1,70,000 proteins in the Protein Data Bank (PDB) to train the computer model.
- Then, it uses the results of that training to learn the structural predictions of proteins not in the PDB.
- Then, it uses the high-accuracy predictions from the first step to retrain and relearn to gain higher accuracy of the earlier predictions.
- By using this method, AlphaFold has now predicted the structures of the entire 214 million unique protein sequences deposited in the Universal Protein Resource (UniProt) database.