Accurate structure prediction of biomolecular interactions with AlphaFold 3 | Nature

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Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript. Advertisement Nature volume 630, pages 493–500 (2024)Cite this article 445k Accesses 147 Citations 1634 Altmetric Metrics details The introduction of AlphaFold 21 has spurred a revolution in modelling the structure of proteins and their interactions, enabling a huge range of applications in protein modelling and design2,3,4,5,6. Here we describe our AlphaFold 3 model with a substantially updated diffusion-based architecture that is capable of predicting the joint structure of complexes including proteins, nucleic acids, small molecules, ions and modified residues. The new AlphaFold model demonstrates substantially impro

Download PDF Subjects Drug discovery Machine learning Protein structure predictions Structural biology An Addendum to this article was published on 27 November 2024 Abstract The introduction of AlphaFold 2 1 has spurred a revolution in modelling the structure of proteins and their interactions, enabling a huge range of applications in protein modelling and design 2 , 3 , 4 , 5 , 6 . Here we describe our AlphaFold 3 model with a substantially updated diffusion-based architecture that is capable of predicting the joint structure of complexes including proteins, nucleic acids, small molecules, io

Accurate structure prediction of biomolecular interactions with AlphaFold 3 | Nature

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