Differential sensing with arrays of de novo designed peptide assemblies.
Differential sensing with arrays of de novo designed peptide assemblies.
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具有从头设计的肽组件阵列的差异传感。
DOI:
10.1038/s41467-023-36024-y
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发表时间:
2023-01-24
影响因子:
16.6
通讯作者:
Woolfson, Derek N.
中科院分区:
文献类型:
--
作者:
Dawson, William M.;Shelley, Kathryn L.;Fletcher, Jordan M.;Scott, D. Arne;Lombardi, Lucia;Rhys, Guto G.;LaGambina, Tania J.;Obst, Ulrike;Burton, Antony J.;Cross, Jessica A.;Davies, George;Martin, Freddie J. O.;Wiseman, Francis J.;Brady, R. Leo;Tew, David;Wood, Christopher W.;Woolfson, Derek N.
Differential sensing attempts to mimic the mammalian senses of smell and taste to identify analytes and complex mixtures. In place of hundreds of complex, membrane-bound G-protein coupled receptors, differential sensors employ arrays of small molecules. Here we show that arrays of computationally designed de novo peptides provide alternative synthetic receptors for differential sensing. We use self-assembling α-helical barrels (αHBs) with central channels that can be altered predictably to vary their sizes, shapes and chemistries. The channels accommodate environment-sensitive dyes that fluoresce upon binding. Challenging arrays of dye-loaded barrels with analytes causes differential fluorophore displacement. The resulting fluorimetric fingerprints are used to train machine-learning models that relate the patterns to the analytes. We show that this system discriminates between a range of biomolecules, drink, and diagnostically relevant biological samples. As αHBs are robust and chemically diverse, the system has potential to sense many analytes in various settings. Differential sensing aims to mimic senses such as taste and smell through the use of synthetic receptors. Here, the authors show that arrays of de novo designed peptide assemblies can be used as sensor components to distinguish various analytes and complex mixtures.
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影响因子:
12.8
作者:
Bourgeois, W;Stuetz, RM
通讯作者:
Stuetz, RM
影响因子:
64.8
作者:
Herud-Sikimić O;Stiel AC;Kolb M;Shanmugaratnam S;Berendzen KW;Feldhaus C;Höcker B;Jürgens G
通讯作者:
Jürgens G
影响因子:
8.6
作者:
Huynh, Kevin;Barlow, Christopher K.;Meikle, Peter J.
通讯作者:
Meikle, Peter J.
影响因子:
2.9
作者:
Alpaydin, E
通讯作者:
Alpaydin, E
影响因子:
8.4
作者:
Dawson WM;Martin FJO;Rhys GG;Shelley KL;Brady RL;Woolfson DN
通讯作者:
Woolfson DN