5 Cool AI-Powered Drug Discovery Tools



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AlphaFold

Biotech News in the latest 2 years has been focused on this tool from Deepmind. Indeed the two software versions from DeepMind’s program outperformed the other 97 teams in a biennial protein-structure prediction challenge Critical Assessment of Structure Prediction (CASP) in the 13th and 14th editions. AlphaFold is practically a neural network that predicts the structure of a protein’s spatial graph given its DNA. It is used as input genetic sequences and with the combination of multiple sequence alignment, geometric representations, and deep learning to obtain the protein’s structural graph. The 14th CASP edition was focused on the ORF3a protein of the SARS-COV2 protein but tested also in other related COVID19 proteins.

As tons of reviews about this tool have been already all over the media, I limit to share the repository for the first version here which won the CASP13 in 2018 which is based on Tensorflow 1.14. The original paper was published in Nature 2020.

Alphafold 2 has been preseted but a “proper article” and the official repository has not been published. Until there will be, the official publication is the abstract of Jumper et al. at CASP14 and the unofficial implementations based on Pytorch available at https://github.com/lucidrains/alphafold2

The major difference between the tools is that AlphaFold 1 and AlphaFold 2 are in the used neural network architecture. Version 1 used concurrent neural networks (CNNs) and version 2 uses Transformers.

Alpha Fold 2 architecture summary. Credits: Deepmind (under creative commons).

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