Machine learning overcomes human bias in the discovery of self-assembling peptides.
Machine learning overcomes human bias in the discovery of self-assembling peptides.
复制标题
DOI：
10.1038/s41557-022-01055-3
复制
发表时间：
2022-12
期刊：
影响因子：
21.8
通讯作者：
中科院分区：
文献类型：
--
作者：
Peptide materials have a wide array of functions, from tissue engineering and surface coatings to catalysis and sensing. Tuning the sequence of amino acids that comprise the peptide modulates peptide functionality, but a small increase in sequence length leads to a dramatic increase in the number of peptide candidates. Traditionally, peptide design is guided by human expertise and intuition and typically yields fewer than ten peptides per study, but these approaches are not easily scalable and are susceptible to human bias. Here we introduce a machine learning workflow–AI-expert–that combines Monte Carlo tree search and random forest with molecular dynamics simulations to develop a fully autonomous computational search engine to discover peptide sequences with high potential for self-assembly. We demonstrate the efficacy of the AI-expert to efficiently search large spaces of tripeptides and pentapeptides. The predictability of AI-expert performs on par or better than our human experts and suggests several non-intuitive sequences with high self-assembly propensity, outlining its potential to overcome human bias and accelerate peptide discovery.
登录
查看更多内容
影响因子：
21.8
作者：
Frederix, Pim W. J. M.;Scott, Gary G.;Tuttle, Tell
通讯作者：
Tuttle, Tell
影响因子：
5.5
作者：
Hess, Berk
通讯作者：
Hess, Berk
影响因子：
17.1
作者：
Kholkin, Andrei;Amdursky, Nadav;Rosenman, Gil
通讯作者：
Rosenman, Gil
影响因子：
17.1
作者：
Brahmachari, Sayanti;Arnon, Zohar A.;Adler-Abramoyich, Lihi
通讯作者：
Adler-Abramoyich, Lihi
影响因子：
5.5
作者：
de Jong, Djurre H.;Periole, Xavier;Marrink, Siewert J.
通讯作者：
Marrink, Siewert J.