Meta AI Unlocks Hundreds of Millions of Proteins To Aid Drug Discovery

Facebook parent company Meta Platforms has created a tool to predict the structure of hundreds of millions of proteins using artificial intelligence. Researchers say it promises to deepen scientists’ understanding of biology, and perhaps speed the discovery of new drugs.

Meta’s research arm, Meta AI, used the new AI-based computer program known as ESMFold to create a public database of 617 million predicted proteins. Proteins are the building blocks of life and of many medicines, required for the function of tissues, organs and cells. Drugs based on proteins are used to treat heart disease, certain cancers and HIV, among other illnesses, and many pharmaceutical companies have begun to pursue new drugs with artificial intelligence. Using AI to predict protein structures is expected to not only boost the effectiveness of existing drugs and drug candidates but also help discover molecules that could treat diseases whose cures have remained elusive.

With ESMFold, Meta is squaring off against another protein-prediction computer model known as AlphaFold from DeepMind Technologies, a subsidiary of Google parent Alphabet. AlphaFold said last year that its database has 214 million predicted proteins that could help accelerate drug discovery. Meta says ESMFold is 60 times faster than AlphaFold, but less accurate. The ESMFold database is larger because it made predictions from genetic sequences that hadn’t been studied previously. Predicting a protein’s structure can help scientists understand its biological function, according to Alexander Rives, co-author of a study published Thursday in the journal Science and a research scientist at Meta AI. Meta had previously released the paper describing ESMFold in November 2022 on a preprint server. Further reading: What metaverse? Meta says its single largest investment is now in ‘advancing AI.’