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AI 도감

AlphaFold

아미노산 서열로 단백질의 3차원 구조를 예측한다

Google DeepMind 모델 오픈 소스

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무엇인가

AlphaFold is Google DeepMind’s protein-structure prediction system; the second version (AlphaFold2) was announced at the CASP14 assessment in November 2020 with accuracy close to experimental methods. It takes a protein’s amino-acid sequence and a multiple sequence alignment as input, uses an attention-based Evoformer module to model relationships between residues, and outputs three-dimensional coordinates. DeepMind later open-sourced the code and model weights and, with EMBL-EBI, built the AlphaFold Protein Structure Database, which holds hundreds of millions of predicted structures.

기억할 만한 이유

It pushed protein-structure prediction to near-experimental accuracy, released the code and weights, and built a large structure database, becoming one of the most cited cases of AI applied to scientific research.

주요 사양

Open source
Yes (code and model weights released)
Database scale
AlphaFold DB holds hundreds of millions of predicted structures
Input
Amino-acid sequence and multiple sequence alignment
Released
2020-11 (CASP14)

관련 개념