4.6 Article

A New Strategy Involving the Use of Peptides and Graphene Oxide for Fluorescence Turn-on Detection of Proteins

期刊

SENSORS
卷 18, 期 2, 页码 -

出版社

MDPI
DOI: 10.3390/s18020385

关键词

peptide; GO; ariginines; sensitivity; selectivity

资金

  1. Natural Science Foundation of China [21302108]
  2. Shenzhen Municipal Government [JCYJ20160301153959476, JCYJ20160324163734374]
  3. Shenzhen Reform Commission (Disciplinary Development Program for Chemical Biology)
  4. China Scholarship Council

向作者/读者索取更多资源

The detection of proteins is of great biological significance as disease biomarkers in early diagnosis, prognosis tracking and therapeutic evaluation. Thus, we developed a simple, sensitive and universal protein-sensing platform based on peptide and graphene oxide (GO). The design consists of a fluorophore (TAMRA, TAM), a peptide containing eight arginines and peptide ligand that could recognize the target protein, and GO used as a quencher. To demonstrate the feasible use of the sensor for target detection, Bcl-xL was evaluated as the model target. The sensor was proved to be sensitive and applied for the detection of the target proteins in buffer, 2% serum and living cells.

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。

评论

主要评分

4.6
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

Article Chemistry, Analytical

Near-Infrared Thienoisoindigos with Aggregation-Induced Emission: Molecular Design, Optical Performance, and Bioimaging Application

Weijie Chen, Chen Zhang, Huijuan Chen, Kun Zang, Sheng Hua Liu, Yuan Xie, Ying Tan, Jun Yin

Summary: In this study, a thienoisoindigo fluorophore was utilized to construct near-infrared fluorescent materials with aggregation-induced emission, showing excellent photostability and lysosomal targeting capability for in vivo fluorescence imaging.

ANALYTICAL CHEMISTRY (2021)

Article Chemistry, Medicinal

Design, synthesis and evaluation of novel ErbB/HDAC multitargeted inhibitors with selectivity in EGFRT790M mutant cell lines

Lei Zhao, Tingting Fan, Zhichao Shi, Chao Ding, Cunlong Zhang, Zigao Yuan, Qinsheng Sun, Chunyan Tan, Bizhu Chu, Yuyang Jiang

Summary: The novel series of multitargeted inhibitors showed moderate activity in EGFR-resistant lung cancer cells, providing insights into the molecular mechanisms of both EGFR wild-type and EGFR(T790M) resistance mutation, with low toxicity towards normal cells.

EUROPEAN JOURNAL OF MEDICINAL CHEMISTRY (2021)

Article Chemistry, Analytical

Unveiling the Molecular Dynamics in a Living Cell to the Subcellular Organelle Level Using Second-Harmonic Generation Spectroscopy and Microscopy

Bifei Li, Jianhui Li, Wei Gan, Ying Tan, Qunhui Yuan

Summary: This study utilized SHG and TPF spectra to investigate the dynamics of an amphiphilic ion D289 on K562 cells, revealing its adsorption and cross-membrane transport within the cells and organelles. SHG images demonstrated the capability of probing molecular dynamics in organelles in K562 cells, showing the first investigation of cross-membrane transport dynamics on subcellular organelles' surfaces.

ANALYTICAL CHEMISTRY (2021)

Article Chemistry, Multidisciplinary

Fluorescence Analysis of Circulating Exosomes for Breast Cancer Diagnosis Using a Sensor Array and Deep Learning

Yuyao Jin, Nan Du, Yuanfang Huang, Wanxiang Shen, Ying Tan, Yu Zong Chen, Wei-Tao Dou, Xiao-Peng He, Zijian Yang, Naihan Xu, Chunyan Tan

Summary: Emerging liquid biopsy methods, such as the breast cancer liquid biopsy system developed in this study, provide a promising noninvasive approach for detecting and classifying cancer cells based on fluorescence signals collected from cells and exosomes. The integration of a fluorescence sensor array and deep learning tool AggMapNet allows for accurate differentiation between normal and cancerous cells, as well as accurate prediction of breast cancer in plasma-derived exosomes.

ACS SENSORS (2022)

Article Chemistry, Multidisciplinary

De Novo Construction of Chiral Aminoindolines by Cu-Catalyzed Asymmetric Cyclization and Subsequent Discovery of an Unexpected Sulfonyl Migration

Bao-Cheng Wang, Tingting Fan, Fen-Ya Xiong, Peng Chen, Kai-Xin Fang, Ying Tan, Liang-Qiu Lu, Wen-Jing Xiao

Summary: This study reports a Cu-catalyzed asymmetric cyclization reaction for the efficient synthesis of chiral 3-aminoindolines with high yield and enantioselectivity. The resulting products can undergo a radical-mediated sulfonyl migration to generate chiral 3-aminoindolines with alkenyl sulfonyl groups. Bioactivity evaluations demonstrate that these chiral 3-aminoindolines show notable antitumor activities and the chirality of the compounds plays a significant role in their antitumor activity.

JOURNAL OF THE AMERICAN CHEMICAL SOCIETY (2022)

Article Chemistry, Analytical

A universal platform for one-pot detection of circulating non-coding RNA combining CRISPR-Cas12a and branched rolling circle amplification

Hui Chen, Zhiyuan Zhuang, Yan Chen, Cheng Qiu, Ying Qin, Chunyan Tan, Ying Tan, Yuyang Jiang

Summary: A new platform based on branched rolling circle amplification and CRISPR-Cas12a was developed for the detection of multiple circulating non-coding RNAs as biomarkers for early-stage colorectal cancer diagnosis. The method showed high detection sensitivity and consistent results with the conventional RT-qPCR method. This one-pot, isothermal, and specific BRCACas platform holds promise as a rapid, adaptable, and practical diagnostic/prognostic cancer screening method.

ANALYTICA CHIMICA ACTA (2023)

Article Chemistry, Medicinal

Infrared Spectral Analysis for Prediction of Functional Groups Based on Feature-Aggregated Deep Learning

Tianyi Wang, Ying Tan, Yu Zong Chen, Chunyan Tan

Summary: Infrared (IR) spectroscopy is a powerful tool for analyzing functional groups in organic compounds. This paper presents a new deep learning method for transforming IR spectral features into intuitive image-like feature maps and predicting major functional groups. The method successfully identifies 21 major functional groups for each molecule without expert guidance and feature selection, and it also shows potential for automated analysis in various fields.

JOURNAL OF CHEMICAL INFORMATION AND MODELING (2023)

Article Nanoscience & Nanotechnology

Molecular Design and Photothermal Application of Thienoisoindigo Dyes with Aggregation-Induced Emission

Weijie Chen, Huijuan Chen, Yurou Huang, Ying Tan, Chunyan Tan, Yuan Xie, Jun Yin

Summary: Organic fluorescent dyes with aggregation-induced emission (AIE) property have extensive applications in imaging, labeling, and adjusting microprocesses in aggregated environments. Thienoisoindigo derivatives with AIE characteristics, such as TII-TPE, have been developed and demonstrated high photostability and efficient photothermal conversion efficiency. These derivatives can be used as functional AIE structures by installing AIE blocks or other rotatable groups. The nanoparticles prepared from thienoisoindigo and tetraphenylethene (TII-TPE) and thienoisoindigo and triphenylamine (TII-TPA) showed significant inhibitory effects on tumor growth in a tumor mouse model after four treatment cycles.

ACS APPLIED BIO MATERIALS (2022)

Article Nanoscience & Nanotechnology

Molecular Design and Photothermal Application of Thienoisoindigo Dyes with Aggregation-Induced Emission

Weijie Chen, Huijuan Chen, Yurou Huang, Ying Tan, Chunyan Tan, Yuan Xie, Jun Yin

Summary: Organic fluorescent dyes with aggregation-induced emission (AIE) property have a wide range of applications in imaging, labeling, and microprocesses in aggregated environments. In this study, a thienoisoindigo derivative with AIE characteristics was developed and nanoparticles were prepared, showing significant inhibition of tumor growth.

ACS APPLIED BIO MATERIALS (2022)

Article Food Science & Technology

Discrimination of Powdered Infant Formula According to Species, Country of Origin, and Brand Using a Fluorescent Sensor Array

Xin Yu Zhao, Nan Du, Yuanfang Huang, Yishun Shen, Ying Tan, Chunyan Tan

Summary: An array of three fluorescent sensors has been developed for the discrimination of powdered infant formulas by species, country of origin, and brand, showing comparable or superior speed and efficacy to existing methods without the need for sample pre/post-treatment.

ACS FOOD SCIENCE & TECHNOLOGY (2021)

Article Nanoscience & Nanotechnology

One-Pot Simultaneous Detection of Multiple DNA and MicroRNA by Integrating the Cationic-Conjugated Polymer and Nuclease-Assisted Cyclic Amplification

Junyue Chen, Tian Jin, Jingfeng Li, Xinyan Zhang, Feng Liu, Chunyan Tan, Ying Tan

Summary: A biosensor based on cationic polymers and nuclease-assisted cyclic amplification has been developed for the high sensitivity and specificity detection of multiple DNA and microRNA in a one-pot reaction. The biosensor utilizes a novel polymer quencher and DNA probes modified with multiple fluorophores to achieve specific and accurate detection even for single-base mismatches. This system shows promising potential for clinical diagnostics by distinguishing miRNA expression in various cell lines with reliable performance in real biological samples.

ACS APPLIED BIO MATERIALS (2021)

Article Nanoscience & Nanotechnology

Conjugated Polymer Nanoparticles Based on Copper Coordination for Real-Time Monitoring of pH-Responsive Drug Delivery

Jiatong Li, Nan Du, Ying Tan, Hsien-Yi Hsu, Chunyan Tan, Yuyang Jiang

Summary: Metal coordination-driven composite systems with excellent stability and pH-responsive ability show potential for specific drug delivery in physiological conditions. pH-responsive nanoparticles, PPEIDA-Cu-DOX CPNs, constructed in this study exhibit high drug loading, efficient drug release monitoring, and lower toxicity to normal cells, demonstrating feasibility for cancer treatment.

ACS APPLIED BIO MATERIALS (2021)

Article Computer Science, Artificial Intelligence

Out-of-the-box deep learning prediction of pharmaceutical properties by broadly learned knowledge-based molecular representations

Wan Xiang Shen, Xian Zeng, Feng Zhu, Ya Li Wang, Chu Qin, Ying Tan, Yu Yang Jiang, Yu Zong Chen

Summary: The study demonstrates that combining human knowledge-based molecular representations with convolutional neural networks can enhance deep learning of pharmaceutical properties. By extensively learning molecular descriptors and fingerprint features, the MolMap method was developed and MolMapNet models were constructed, which outperformed other models on various benchmark datasets and a novel dataset.

NATURE MACHINE INTELLIGENCE (2021)

暂无数据