Increasing the Assembly Efficacy of Peptidic β-Sheets for a Highly-Sensitive HIV Detection
- 30 June 2020
- journal article
- research article
- Published by American Chemical Society (ACS) in Analytical Chemistry
- Vol. 92 (16), 11089-11094
- https://doi.org/10.1021/acs.analchem.0c00951
Abstract
Our recent publication illustrates the critical role of phenylalanine-mediated aromatic-aromatic interactions in determining the assembly of peptidic β-sheets. However, the effect of phenylalanine number on regulating the assembly efficacy of peptidic β-sheets remains poorly understood. We herein evaluate the assembly efficacy of β-sheets of a series of oligo-peptides which contain 0, 1, 2 or 3 phenylalanine in their molecular backbones. In our assembly system, two phenylalanine (2F) is the minimum number for driving the assembly of β-sheets of oligo-peptides. Oligo-peptides with three phenylalanine (3F) show significantly increased assembly efficacy of β-sheets than that with 2F. These results suggest a positive correlation between phenylalanine number and assembly efficacy of β-sheets. By improving the assembly efficacy of β-sheets, we further develop a highly-sensitive HIV analytical system in which the specific-binding of β-sheets with Congo Red induces enhanced fluorescence. For HIV p24 detection, 3F-based analytical system (0.61 pg/ml) shows a significantly lower limit of detection (LOD) than 2F-based analytical system (2.44 pg/ml), both of which are more sensitive than commercial ELISA (5 pg/ml) used in the clinic. This work not only illustrates the effect of phenylalanine number on regulating the assembly efficacy of β-sheets, but also provides a guideline for the construction of a highly-sensitive analytical system of disease diagnosis.Keywords
Funding Information
- Ministry of Science and Technology of the People's Republic of China (2017YFA0205901, 2018YFA0902600, 2018ZX10731101-001-011)
- Chinese Academy of Medical Sciences (2018RC310021)
- National Natural Science Foundation of China (21535001, 21761142006, 21874033, 81730051)
- Chinese Academy of Sciences (121D11KYSB20170026, QYZDJ-SSW-SLH039, XDA16020902)
- Leading Medical Talents Program of Health Commission of Yunnan Province (L-2018013)
- Yunnan Province
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