Detection of lipase activity in human serum based on a ratiometric fluorescent probe

Luo, Jiajie; Zhang, Hongyi; Guan, Jialiang; An, Baoshuai; Peng, Junli; Zhu, Wei; Wang, Ningning; Zhang, Yanru

doi:10.1039/d1nj01155c

Cited by 8 publications

(4 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Our dual-resolution implementation mitigates this issue significantly by lowering the memory requirements, but grids much larger than 48 Å would still require expensive multi-GPU training. Although we think that the space-filling property of the grid-based representation has significant advantages, other generative methods, such as graph and point-cloud based models, are being developed to avoid these limitations. − , …”

Section: Discussionmentioning

confidence: 99%

“…Rather than further optimizing the exhaustive search of chemical space, deep generative models are capable of learning distributions over molecular data. These models have already been successfully applied to large drug-like chemical data sets for de novo molecular generation of drug-like molecules − and discovery of new potent hit molecules. − Lately, efforts have turned toward modeling drug-target interactions by training models on data sets of ligand-bound receptor crystal structures. − By learning a joint probability distribution of ligands bound to their receptors, these models can generate new molecules conditioned on the receptor, effectively narrowing the regions of chemical space in which to search for new drugs. Because generative models are generally trained in an unsupervised fashion to accurately reproduce features of the training data set, their applicability will both be defined by and improve with the size, scope, and quality of available data.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Structure-Based Drug Design with a Deep Hierarchical Generative Model

Weller,

Rohs

2024

J. Chem. Inf. Model.

View full text Add to dashboard Cite

Recently, the remarkable growth of available crystal structure data and libraries of commercially available or readily synthesizable molecules have unlocked previously inaccessible regions of chemical space for drug development. Paired with improvements in virtual ligand screening methods, these expanded libraries are having a notable impact on early drug design efforts. Yet screening-based methods still face scalability limits, due to computational constraints and the sheer scale of drug-like space. Machine learning approaches are overcoming these limitations by learning the fundamental intra-and intermolecular relationships in drug-target systems from existing data. Here, we introduce DrugHIVE, a deep hierarchical variational autoencoder that outperforms state-of-the-art autoregressive and diffusion-based methods in both speed and performance on common generative benchmarks. DrugHIVE's hierarchical design enables improved control over molecular generation. Its capabilities include dramatically increasing virtual screening efficiency and accelerating a wide range of common drug design tasks, including de novo generation, molecular optimization, scaffold hopping, linker design, and high-throughput pattern replacement. Our highly scalable method can even be applied to receptors with highconfidence AlphaFold-predicted structures, extending the ability to generate high-quality drug-like molecules to a majority of the unsolved human proteome.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Structure-Based Drug Design with a Deep Hierarchical Generative Model

Weller,

Rohs

2024

J. Chem. Inf. Model.

View full text Add to dashboard Cite

show abstract

“…Compared with other methods, Fluorescence probe technology used for detection of intracellular H 2 O 2 has the advantages of non-invasiveness and good biocompatibility (An et al, 2020;Zhang et al, 2020;Luo et al, 2021;Xu et al, 2021;Zheng et al, 2021) over the traditional detection assays including chromatography (Tarvin et al, 2011), mass spectrometry (Cocheme et al, 2011), colorimetry (Zou et al, 2019) and electrochemistry (Liu et al, 2014). Many fluorescent probes for H 2 O 2 are developed based on small molecular fluorophores such as rhodamine (Gu et al, 2020), coumarin (Du et al, 2010), naphthalimide (Sun et al, 2013), and BODIPY (Purdey et al, 2018;Wei et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

A novel near-infrared fluorescent probe for visualization of intracellular hydrogen peroxide

Pang

Zhang

et al. 2022

Front. Chem.

View full text Add to dashboard Cite

Hydrogen peroxide (H2O2) as a crucial reactive oxygen species (ROS) plays a crucial role in redox signaling in physiological and pathological processes of living cells. Its normal production is closely related to signal transduction of living cells. Overproduction of H2O2in vivo has been proved to be related to many diseases. Some were developed to reveal the roles of H2O2. However, current fluorescent probes for the detection of H2O2 are restricted in their short emission wavelengths and small Stokes shifts that significantly decrease the sensitivity of detection and cellular visualization. In this work, a novel fluorescent probe BC-B was designed and synthesized with pinacol phenylboronic acid ester as a recognition group and near-infrared fluorophore BC-OH as a reporter group. BC-B probe exhibits a large Stokes shift (122 nm) and near-infrared emission (672 nm), showing an excellent selectivity and sensitivity in detection of H2O2 with the limit of 0.003 μmol/L. Confocal fluorescence imaging further demonstrates that BC-B can be used for detecting endogenous H2O2 in living cells.

show abstract

“…Therefore, the detection of lipase activity in vivo is important and highly valuable for the clinical diagnosis of AP. The existing approaches for the detection of lipase mainly include the colorimetric assay, − fluorescence detection, − and the zymography assay . Although these methods are of great significance for the detection of lipase, they commonly require multistep preparation and professional equipment.…”

mentioning

confidence: 99%

Paper-Based Distance Sensor for the Detection of Lipase via a Phase Separation-Induced Viscosity Change

Xia

Yin

et al. 2022

Anal. Chem.

View full text Add to dashboard Cite

Human pancreatic lipase is a symbolic biomarker for the diagnosis of acute pancreatitis, which has profound significance for clinical detection and disease treatment. Herein, we first demonstrate a paper-based lipase sensor via a phase separation-induced viscosity change. Lipase catalyzes triolein to produce oleic acid and glycerol. Adding an excess of Ca2+ produces calcium oleate. The remaining Ca2+ binds with sodium alginate, triggering hydrogelation with an “egg-box” structure. The viscosity change of the aqueous solution induced by the phase separation process can be quantified by measuring the solution flow distance on a pH test paper. The paper-based lipase sensor has high sensitivity with a detection limit of 0.052 U/mL and also shows excellent specificity. Additionally, it is also utilized for quantitative lipase analysis in human serum samples to exhibit its potency in acute pancreatitis detection. This method overcomes the drawbacks of low sensitivity, slow response, and poor reproducibility caused by the nonuniform distribution of the highly viscous hydrogel on the sensing interface in existing approaches. In conclusion, thanks to the prominent characteristics of high portability, low cost, and easy operation, it is prospective for simple quantitative detection of lipase and has great potential for commercialization.

show abstract

Detection of lipase activity in human serum based on a ratiometric fluorescent probe

Abstract: CARA can monitor lipase activity through hydrolyzing the ester bond to interrupt the FRET process.

Cited by 8 publications

References 36 publications

Structure-Based Drug Design with a Deep Hierarchical Generative Model

Structure-Based Drug Design with a Deep Hierarchical Generative Model

A novel near-infrared fluorescent probe for visualization of intracellular hydrogen peroxide

Paper-Based Distance Sensor for the Detection of Lipase via a Phase Separation-Induced Viscosity Change

Contact Info

Product

Resources

About