The first public available pytorch version alphafold2 is reproduced, and Columbia University is open source openfold, with more than 1000 stars

just , Assistant professor of systems biology, Columbia University Mohammed AlQuraishi Announce on twitter , They trained a new one called OpenFold Model of , The model is AlphaFold2 Trainable PyTorch Duplicate version .Mohammed AlQuraishi Also said , This is the first one available to the public AlphaFold2 Reappear .

AlphaFold2 Protein structure can be predicted periodically with atomic accuracy , Technically, multi sequence alignment and deep learning algorithm are used to design , Combined with the physical and biological knowledge of protein structure, the prediction effect is improved . It has achieved 2/3 The outstanding achievement of protein structure prediction was listed on the 《 natural 》 The magazine . What's more surprising is ,DeepMind The team not only opened the model , Will also AlphaFold2 The forecast data is made into a free and open data set .

However , Open source doesn't mean you can use 、 To use . Actually ,AlphaFold2 The deployment of software system is very difficult , And high requirements for hardware 、 The data set download cycle is long 、 Large space , Every one of them makes ordinary developers flinch . therefore , The open source community has been working hard to achieve AlphaFold2 The available version of .

This time Columbia University Mohammed AlQuraishi Realized by professors and others OpenFold The total training time is about 100000 A100 Hours , But around 3000 It will be reached within hours 90% The accuracy of .

OpenFold With the original AlphaFold2 The accuracy of this method is quite , Even slightly better , May be because OpenFold Your training set is a little bigger ：

OpenFold The main advantage of is that the reasoning speed is significantly improved , For shorter protein sequences ,OpenFold The speed of reasoning can reach AlphaFold2 Twice as many . in addition , Due to the use of custom CUDA kernel ,OpenFold With less memory, you can infer longer protein sequences .

For more details, see GitHub： https://github.com/aqlaboratory/openfold