Jie Dong

Central South University | CSU · Xiangya School of Pharmaceutical Sciences

The emergence of antibiotic-resistant "superbugs" poses a serious threat to human health. Nanomaterials and cationic polymers have shown unprecedented advantages as effective antimicrobial therapies due to their flexibility and ability to interact with biological macromolecules. They can incorporate a variety of antimicrobial substances, achieving...

As a significant signaling gas molecule, carbon monoxide (CO) has a crucial impact on various physiological and pathological processes in organisms, particularly in oxidative stress processes. Hence, designing and synthesizing a fluorescent probe that can effectively image CO in vivo holds immense significance. In this work, under the guidance of d...

Monitoring the physiological changes of organelles is essential for understanding the local biological information of cells and for improving the diagnosis and therapy of diseases. Currently, fluorescent probes are considered as the most powerful tools for imaging and have been widely applied in biomedical fields. However, the expected targeting ef...

Traditional Chinese Medicine (TCM) has been widely used in the treatment of various diseases for millennia. In the modernization process of TCM, TCM ingredient databases are playing more and more important roles. However, most of the existing TCM ingredient databases do not provide simplification function for extracting key ingredients in each herb...

Bioactive ingredients from natural products have always been an important resource for the discovery of drugs for Alzheimer's disease (AD). Senile plaques, which are formed with amyloid-beta (Aβ) peptides and excess metal ions, are found in AD brains and have been suggested to play an important role in AD pathogenesis. Here, we attempted to design...

Background β-Secretase (BACE1) is the vital enzyme in the pathogenic processes of Alzheimer's disease (AD). However, the development of a powerful tool with sensitivity for BACE1 determination in vivo is a challenge. Methods A novel NIR fluorescent probe HBAE was synthetized from 2-hydroxy-3-methylbenzaldehyde and 2-amino-benzenethiol by 5 steps....

Antimicrobial resistance could threaten millions of lives in the immediate future. Antimicrobial peptides (AMPs) are an alternative to conventional antibiotics practice against infectious diseases. Despite the potential contribution of AMPs to the antibiotic’s world, their development and optimization have encountered serious challenges. Cutting-ed...

Ligand-based drug design methods are thought to require large experimental datasets to become useful for virtual screening. In this work, we propose a computational strategy to design novel inhibitors of coronavirus main protease, Mpro. The pipeline integrates publicly available screening and binding affinity data in a two-stage machine-learning mo...

No observed adverse effect level (NOAEL) is an identified dose level which used as a point of departure to infer a safe exposure limit of chemicals, especially in food additives and cosmetics. Recently, in silico approaches have been employed as effective alternatives to determine the toxicity endpoints of chemicals instead of animal experiments. S...

Background β-Secretase (BACE1) is the vital enzyme in the pathogenic processes of Alzheimer's disease (AD). However, the development of a powerful tool with sensitivity for BACE1 determination in vivo is a challenge. Methods A novel NIR fluorescent probe HBAE was synthetized starting from 2-hydroxy-3-methylbenzaldehyde and 2-amino-benzenethiol via...

Background β-Secretase (BACE1) is the vital enzyme in the pathogenic processes of Alzheimer's disease (AD). However, the development of a powerful tool with sensitivity for BACE1 determination in vivo is a challenge. Methods A novel NIR fluorescent probe HBAE was synthetized from 2-hydroxy-3-methylbenzaldehyde and 2-amino-benzenethiol by 5 steps....

From ZINC database with a total of 1.8 million small molecules, four compounds are identified as prolyl hydroxylase 2 inhibitors through a virtual screening workflow that sequentially incorporates machine learning, molecular docking, and molecular dynamics. Among them, compound 103, (E)-5-(5-((2-(1H-tetrazol-5-yl)hydrazineylidene)methyl)furan-2-yl)...

The cross-reactivity (CR) of monoclonal antibody (mAb) is mainly determined by chemical structure of hapten which is used to synthesize immunogen. Hapten structures are commonly designed based on experience and then verified via experiments. To save cost, a theoretical model is extremely necessary to guide hapten structure design. In this study, th...

Caspase-3 plays irreplaceable roles in apoptosis and related diseases. An imbalance in the measured levels of Caspase-3 is implicated in irreversible apoptosis. Therefore, the detection of Caspase-3 is of great significance for apoptosis imaging and the evaluation effect of early tumor treatment and other diseases. Herein, advances in the recent in...

Nowadays, computational approaches have drawn more and more attention when exploring the relationship between sweetness and chemical structure instead of traditional experimental tests. In this work, we proposed a novel multi-layer sweetness evaluation system based on machine learning methods. It can be used to evaluate sweet properties of compound...

The price of chemicals is a very complex variable. It can be impacted by production costs but also by market and managerial factors, which may have complex relationships with molecular characteristics and the state of technology and society. In this work, we explore the extent to which molecular characteristics can help explain natural product pric...

Drug-excipient compatibility study is the essential basis for excipient selection at the pre-formulation stage. According to the pharmaceutical Quality by Design (QbD) principles, a comprehensive understanding of the ingredients' physicochemical properties and a theoretical evaluation of the interaction risk between the drugs and excipients are req...

The drug formulation design of self-emulsifying drug delivery systems (SEDDS) often requires numerous experiments, which are time- and money-consuming. This research aimed to rationally design the SEDDS formulation by the integrated computational and experimental approaches. 4495 SEDDS formulation datasets were collected to predict the pseudo-terna...

Solid dispersion is an effective way to improve the dissolution and oral bioavailability of water-insoluble drugs. To obtain an effective solid dispersion formulation, researchers need to evaluate a series of important properties of the designed formulation, including in vitro dissolution and physical stability of solid dispersion. It is usually ti...

Drugs in solid dispersion (SD) take advantage of fast and extended dissolution, thus attains a higher bioavailability than the crystal form. However, current development of SD relies on a random large-scale formulation screening method with low efficiency. Current research aims to integrate various computational tools, including machine learning (M...

Background Fluorescent detection methods are indispensable tools for chemical biology. However, the frequent appearance of potential fluorescent compound has greatly interfered with the recognition of compounds with genuine activity. Such fluorescence interference is especially difficult to identify as it is reproducible and possesses concentration...

Food Bioactive Small Molecule Databases (FBSMDs) provide valuable data resources for the study of molecular behavior, molecular nutrition, as well as the R&D of drugs and health products. In this review, 89 food databases were collected and 32 of them were classified as FBSMDs. Furthermore, we summarized their research contents and features in deta...

Luciferase-based bioluminescence detection techniques are highly favored in high-throughput screening (HTS), in which the firefly luciferase (FLuc) is the most commonly used variant. However, FLuc inhibitors can interfere with the activity of luciferase, which may result in false positive signals in HTS assays. In order to reduce the unnecessary co...

This research aims to predict the complexation performance of phospholipid complex by machine learning methods. 341 drugs/ phospholipid complex formulations were collected from the literature. The datasets were trained by the lightGBM method. To validate the prediction modeling, berberine (BBR) was used as the model drug to form the complex with ph...

Background: With the increasing development of biotechnology and information technology, publicly available data in chemistry and biology are undergoing explosive growth. Such wealthy information in these resources needs to be extracted and then transformed to useful knowledge by various data mining methods. However, a main computational challenge...

Aggregation has been posing a great challenge in drug discovery. Current computational approaches aiming to filter out aggregated molecules based on their similarity to known aggregators, such as Aggregators Advisor, have low prediction accuracy, and therefore development of reliable in silico models to detect aggregators is highly desirable. In th...

Cyclooxygenase-2 (COX-2), an isozyme of the cyclooxygenase enzyme family, is not only high-expressed in various types of tumors, but also over-expressed in all stages of cancers. Herein, we report the design and preparation of an aggregation-induced emission (AIE) based fluorescent probe TPI-IMC for the imaging of COX-2 by the conjugation of 4-(1,4...

In this work, interaction of soybean Bowman-Birk inhibitor (BBI) with stevioside (STE) was studied by stopped-flow/fluorescence and molecular docking. STE inactivating protease inhibitor activities in soymilk and the influence of STE addition on the sensory character of soymilk were also evaluated. The results indicate that STE binds BBI with a bin...

In this work, a novel water soluble fluorescent probe 2,2'-(((4-(4,5-bis(4-methoxyphenyl)-1-phenyl-1H-imidazol-2-yl)phenyl)methylene)bis(sulfanediyl))diethanol (MPIPBS) for Hg2+ was rationally developed based on Hg2+-induced umpolung reaction and aggregation induced emission (AIE). MPIPBS exhibits high selectivity and sensitivity toward Hg2+ over o...

Autophagy is an important homeostatic cellular recycling mechanism responsible for degrading unnecessary or dysfunctional cellular organelles and proteins in all living cells. In addition to its vital homeostatic role, this degradation pathway also involves in various human disorders, including metabolic conditions, neurodegenerative diseases, canc...

Formaldehyde (FA) is a product of an endogenous production that is formed through demethylase and oxidase enzymes, which regulate epigenetics and metabolism. However, the presence of abnormally high levels of FA are often associated with a variety of disease pathologies, including chronic liver, heart and neurodegenerative diseases, in addition to...

Current pharmaceutical research and development (R&D) is a high-risk investment which is usually faced with some unexpected even disastrous failures in different stages of drug discovery. One main reason for R&D failures is the efficacy and safety deficiencies which are related largely to absorption, distribution, metabolism and excretion (ADME) pr...

Background: With the increasing development of biotechnology and informatics technology, publicly available data in chemistry and biology are undergoing explosive growth. Such wealthy information in these data needs to be extracted and transformed to useful knowledge by various data mining methods. Considering the amazing rate at which data are ac...

Herein, a novel self-assembled nanoprobe for long-term tracking nucleolus of cancer cells and differentiating clinical breast cancer tissues and para-carcinoma tissues has been developed.

The behavior of a chemical in human or environment mostly depends on its several key physicochemical properties, such as aqueous solubility, octanol-water partition coefficient (logP), boiling point (BP), density, flash point (FP), viscosity, surface tension (ST), vapor pressure (VP) and melting point (MP). Commonly, these properties are important...

Plasma protein binding affinity of a drug compound has a strong influence on its pharmacodynamic behavior because it can affect the drug uptake and distribution. In this study, we collected a sizeable dataset consisting of 1830 drug compounds from several accessible sources. A descriptor pool composed of four different types of descriptors (2-D, 3-...

Formaldehyde (FA), a carcinogenic potential toxic aldehyde, has attracted more and more attention in the domain of science. Less dose of FA can cause pain, emesia, somnolence and stupor, and uptake of large amounts of FA can cause death. To make sure that remains FA has no detrimental on human health, it is pivotal to control the FA level via early...

Specific detection or imaging protein has high potential to contribute greatly to medical diagnosis, biological research and therapeutic applications. The level of Human Serum Albumin (HSA) in blood is related to a variety of diseases and thus serves as an important biomarker for fast clinical diagnosis. Here we report the use of aggregation-induce...

Heparin is widely used to anticoagulation treatment in clinic, while the overdoses of heparin can cause potentially catastrophic complications. Thus, the selective and sensitive detection of heparin is of great importance. Herein, a novel water-soluble AIE-based fluorescent probe (TIBI) with red emission (650 nm) has been rationally developed to de...

In QSAR/QSPR modeling, building an accurate partial least squares (PLS) model usually involves descriptor selection, outlier detection, applicability domain assessment, nonlinear relationship, and model stability problems. In the present study, we presented an ensemble PLS (EnPLS) method for solving these modeling tasks under a unified methodology...

Sulfur dioxide (SO2) is a widely distributed air pollutant, and human exposure and inhalation of SO2 is easily transformed into sulfite thus to induce respiratory responses and diseases. Hence, to develop a rapid, sensitive and selective method for detection of sulfites is of great importance. Herein, we designed and synthesized a novel tetraphenyl...

Background: In recent years, predictive models based on machine learning techniques have proven to be feasible and effective in drug discovery. However, to develop such a model, researchers usually have to combine multiple tools and undergo several different steps (e.g., RDKit or ChemoPy package for molecular descriptor calculation, ChemAxon Stand...

Anionic surfactants are widely used in detergents, cosmetics, medicine and other industries, but the residue in the water can pollute the water quality and destruct aquatic ecosystems. Thus, to develop a rapid, sensitive and selective strategy for detection of anionic surfactants is of great importance. Herein, we rationally designed and synthesize...

With the increase of complexity and risk in drug discovery processes, human intestinal absorption (HIA) prediction has become more and more important. Up to now, some predictive models have been constructed to estimate HIA of new drug-like compounds with acceptable accuracies, but there are still some issues to be explored including the limited and...

Background: More and more evidences from network biology indicate that most cellular components exert their functions through interactions with other cellular components, such as proteins, DNAs, RNAs and small molecules. The rapidly increasing amount of publicly available data in biology and chemistry enables researchers to revisit interaction pro...

Drug–target interactions (DTIs) are central to current drug discovery processes and public health fields. Analyzing the DTI profiling of the drugs helps to infer drug indications, adverse drug reactions, drug–drug interactions, and drug mode of actions. Therefore, it is of high importance to reliably and fast predict DTI profiling of the drugs on a...

Caco-2 cell monolayer model is a popular surrogate in predicting the in vitro human intestinal permeability of a drug due to its morphological and functional similarity with human enterocytes. A quantitative structure-property relationship (QSPR) study was carried out to predict Caco-2 cell permeability of a large data set consisting of 1272 compou...

Background: Molecular descriptors and fingerprints have been routinely used in QSAR/SAR analysis, virtual drug screening, compound search/ranking, drug ADME/T prediction and other drug discovery processes. Since the calculation of such quantitative representations of molecules may require substantial computational skills and efforts, several tools...

As a representative paradigm of evolutionary algorithms, particle swarm optimization (PSO) has been combined with partial least square (PLS) (called PSO-PLS) to select informative descriptors in quantitative structure-activity/property relationship (QSAR/QSPR). However, one of the main limitations of PSO-PLS is that it ignores PLS model information...

There is a great need to assess the harmful effects or toxicities of chemicals to which man is exposed. In the present paper, the kernel fusion technique, together with the state-of-the-art support vector machine (SVM) algorithm, was developed to classify the toxicity of chemicals from Distributed Structure-Searchable Toxicity (DSSTox) database net...

To preliminarily evaluate the refining effect on Chinese medicinal materials extract using the microfiltration membrane of Ti-A1 intermetallic compound. Conduct a series of microfiltration experiments on the extract of several commonly used Chinese medicinal materials (Nelumubinis Plumula and Eucommiae Folium)and compound preparation of Baihuasandi...