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The prospects and opportunities of protein structure prediction with AI
Nature Reviews Molecular Cell Biology ( IF 81.3 ) Pub Date : 2022-04-27 , DOI: 10.1038/s41580-022-00488-5
Kathryn Tunyasuvunakool 1
Affiliation  

A Comment on the impact of improved protein structure prediction by Kathryn Tunyasuvunakool from DeepMind — the company behind AlphaFold. The 2020 Critical Assessment of protein Structure Prediction (CASP) marked a significant advance. The machine learning method AlphaFold predicted the structure of most target proteins to an accuracy assessors called “competitive with experiment”. Here, I discuss the impact of improved protein structure prediction, highlighting exciting research areas and remaining challenges.

中文翻译:

人工智能蛋白质结构预测的前景和机遇

来自 DeepMind(AlphaFold 背后的公司)的 Kathryn Tunyasuvunakool 对改进的蛋白质结构预测的影响的评论。2020 年蛋白质结构预测关键评估 (CASP) 标志着一项重大进展。机器学习方法 AlphaFold 向称为“与实验竞争”的准确性评估人员预测了大多数目标蛋白质的结构。在这里,我讨论了改进的蛋白质结构预测的影响,强调了令人兴奋的研究领域和仍然存在的挑战。
更新日期:2022-04-29
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