Applying and improving AlphaFold at CASP14.
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ABSTRACT:
SUBMITTER: Jumper J
PROVIDER: S-EPMC9299164 | biostudies-literature | 2021 Dec
REPOSITORIES: biostudies-literature
Publications
Applying and improving AlphaFold at CASP14.
Jumper John J Evans Richard R Pritzel Alexander A Green Tim T Figurnov Michael M Ronneberger Olaf O Tunyasuvunakool Kathryn K Bates Russ R Žídek Augustin A Potapenko Anna A Bridgland Alex A Meyer Clemens C Kohl Simon A A SAA Ballard Andrew J AJ Cowie Andrew A Romera-Paredes Bernardino B Nikolov Stanislav S Jain Rishub R Adler Jonas J Back Trevor T Petersen Stig S Reiman David D Clancy Ellen E Zielinski Michal M Steinegger Martin M Pacholska Michalina M Berghammer Tamas T Silver David D Vinyals Oriol O Senior Andrew W AW Kavukcuoglu Koray K Kohli Pushmeet P Hassabis Demis D
Proteins 20211201 12
We describe the operation and improvement of AlphaFold, the system that was entered by the team AlphaFold2 to the "human" category in the 14th Critical Assessment of Protein Structure Prediction (CASP14). The AlphaFold system entered in CASP14 is entirely different to the one entered in CASP13. It used a novel end-to-end deep neural network trained to produce protein structures from amino acid sequence, multiple sequence alignments, and homologous proteins. In the assessors' ranking by summed z ...[more]
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Project description:SummaryThe AlphaFold2 neural network model has revolutionized structural biology with unprecedented performance. We demonstrate that by stochastically perturbing the neural network by enabling dropout at inference combined with massive sampling, it is possible to improve the quality of the generated models. We generated ∼6000 models per target compared with 25 default for AlphaFold-Multimer, with v1 and v2 multimer network models, with and without templates, and increased the number of recycles within the network. The method was benchmarked in CASP15, and compared with AlphaFold-Multimer v2 it improved the average DockQ from 0.41 to 0.55 using identical input and was ranked at the very top in the protein assembly category when compared with all other groups participating in CASP15. The simplicity of the method should facilitate the adaptation by the field, and the method should be useful for anyone interested in modeling multimeric structures, alternate conformations, or flexible structures.Availability and implementationAFsample is available online at http://wallnerlab.org/AFsample.
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