期刊
SCIENCE
卷 357, 期 6347, 页码 168-174出版社
AMER ASSOC ADVANCEMENT SCIENCE
DOI: 10.1126/science.aan0693
关键词
-
资金
- Howard Hughes Medical Institute
- Natural Sciences and Engineering Research Council of Canada
- AbbVie
- Bayer Pharma AG
- Boehringer Ingelheim
- Canada Foundation for Innovation
- Eshelman Institute for Innovation
- Genome Canada through Ontario Genomics Institute [OGI-055]
- Innovative Medicines Initiative (EU/EFPIA) through ULTRA-DD [115766]
- Janssen Pharmaceuticals
- Merck Co.
- Novartis Pharma AG
- Ontario Ministry of Research, Innovation and Science (MRIS)
- Pfizer
- Sao Paulo Research Foundation-FAPESP
- Takeda
- Wellcome Trust
Proteins fold into unique native structures stabilized by thousands of weak interactions that collectively overcome the entropic cost of folding. Although these forces are encoded in the thousands of known protein structures, decoding them is challenging because of the complexity of natural proteins that have evolved for function, not stability. We combined computational protein design, next-generation gene synthesis, and a high-throughput protease susceptibility assay to measure folding and stability for more than 15,000 de novo designed miniproteins, 1000 natural proteins, 10,000 point mutants, and 30,000 negative control sequences. This analysis identified more than 2500 stable designed proteins in four basic folds-a number sufficient to enable us to systematically examine how sequence determines folding and stability in uncharted protein space. Iteration between design and experiment increased the design success rate from 6% to 47%, produced stable proteins unlike those found in nature for topologies where design was initially unsuccessful, and revealed subtle contributions to stability as designs became increasingly optimized. Our approach achieves the long-standing goal of a tight feedback cycle between computation and experiment and has the potential to transform computational protein design into a data-driven science.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据