Anti-inflammatory or anti-SARS-CoV-2 ingredients in Huashi Baidu Decoction and their corresponding targets: Target screening and molecular docking study

Coronavirus disease 2019 (COVID-19) is a rapidly emerging infectious disease caused by SARS-CoV-2. Inflammatory factors may play essential roles in COVID-19 progression. Huashi Baidu Decoction (HSBD) is a traditional Chinese medicine (TCM) formula that can expel cold, dispel dampness, and reduce inflammation. HSBD has been widely used for the treatment of COVID-19. However, the active ingredients and potential targets for HSBD to exert anti-inflammatory or anti-SARS-CoV-2 effects remain unclear. In this paper, the active ingredients with anti-inflammatory or anti-viral effects in HSBD and their potential targets were screened using the Discovery Studio 2020 software. By overlapping the targets of HSBD and COVID-19, 8 common targets (FYN, SFTPD, P53, RBP4, IL1RN, TTR, SRPK1, and AKT1) were identified. We determined 2 key targets (P53 and AKT1) by network pharmacology. The main active ingredients in HSBD were evaluated using the key targets as receptor proteins for molecular docking. The results suggested that the best active ingredients Kaempferol2 and Kaempferol3 have the potential as supplements for the treatment of COVID-19.     

中草药活性成分的高通量筛选技术研究进展

随着高通量筛选技术的不断发展,该技术已经成为发现新药物的重要途径之一。高通量筛选技术已大量应用于筛选药物活性成分的领域中,但是其中大部分为从化合物库中筛选活性成分,仅有十几篇文献应用于中药活性成分的筛选,而中国传统中草药却是探索和发展新药物的丰富来源。本文通过综述国内外2008年到2017年的相关文献,阐述了分子和细胞水平上的高通量筛选技术在中草药活性成分的筛选及其应用进展,为今后中草药新药研发提供参考。     

介孔硅纳米储存器在智能药物释放系统的应用

开发新型细胞微环境刺激响应性智能药物控释系统是目前材料学、药理学与临床医学研究的共同热点之一,其目的在于寻求合适的药物载体,提高药物的安全性、有效性及降低药物毒副作用。本文综述了介孔硅功能复合纳米材料在生物医药领域的应用研究进展;通过对其进行特定的化学修饰、生物修饰、物理修饰,不仅能特异性细胞识别靶向,还能针对病变细胞实现药物定点、定时、定量的“生物爆破”释放;这在药物可控释放、靶向癌症治疗、靶向基因递送等领域展示了其广阔的应用前景。同时,本文还系统地分析和总结了各种智能响应性介孔硅纳米储存器的制备方法和响应机制,包括“无机纳米塞-介孔硅”纳米智能控释系统、“有机大分子控制器-介孔硅”智能功能复合型控释系统、“分子开关控制器-介孔硅”自响应性纳米控释系统等,这为设计新型响应性介孔硅纳米储存器系统提供了借鉴与思路。     

Pharmaceutical Applications of Ionic Liquids: A Personal Account

Ionic liquids (ILs) have been extensively used in drug formulation and delivery as designer solvents and other components because of their inherent tunability and useful physicochemical and biopharmaceutical properties. ILs can be used to manage some of the operational and functional challenges of drug delivery, including drug solubility, permeability, formulation instability, and in vivo systemic toxicity, that are associated with conventional organic solvents/agents. Furthermore, ILs have been recognized as potential solvents to address the polymorphism, limited solubility, poor permeability, instability, and low bioavailability of crystalline drugs. In this account, we discuss the technological progress and strategies toward designing biocompatible ILs and explore potential biomedical applications, namely the solubilization of small and macromolecular drugs, the creation of active pharmaceutical ingredients, and the delivery of pharmaceuticals.     

An integrated approach of high-performance liquid chromatography–mass spectrometry-based chemical profiling,network pharmacology,and molecular docking to reveal the potential mechanisms of Qishen Gubiao granules for treating coronavirus disease 2019

Qishen Gubiao granules, a traditional Chinese medicine preparation composed of nine herbs, have been widely used to prevent and treat coronavirus disease 2019 with good clinical efficacy. In the present study, an integrated strategy based on chemical profiling followed by network pharmacology and molecular docking was employed, to explore the active components and potential molecular mechanisms of Qishen Gubiao granules in the therapy of coronavirus disease 2019. Using the ultra-high performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry technique, a total of 186 ingredients corresponding to eight structure types in Qishen Gubiao preparation were identified or structurally annotated with the elucidation of the fragmentation pathways in the typical compounds. The network pharmacology analysis screened 28 key compounds including quercetin, apigenin, scutellarein, luteolin and naringenin acting on 31 key targets, which possibly modulated signal pathways associated with immune and inflammatory responses in the treatment of coronavirus disease 2019. The molecular docking results observed that the top 5 core compounds had a high affinity for angiotensin-converting enzyme 2 and 3-chymotrypsin-like protease. This study proposed a reliable and feasible approach for elucidating the multi-components, multi-targets, and multi-pathways intervention mechanism of Qishen Gubiao granules against coronavirus disease 2019, providing a scientific basis for its further quality evaluation and clinical application.     

Homotherapy for heteropathy active components and mechanisms of Qiang-Huo-Sheng-Shi decoction for treatment of rheumatoid arthritis and osteoarthritis

Qiang-Huo-Sheng-Shi decoction (QHSSD), a classic traditional Chinese herbal formula, which has been reported to be effective in rheumatoid arthritis (RA) and osteoarthritis (OA). However, the concurrent targeting mechanism of how the aforementioned formula is valid in the two distinct diseases OA and RA, which represents the homotherapy-for-heteropathy principle in traditional Chinese medicine (TCM), have not yet been clarified. In the present study, network pharmacology was adopted to analyze the potential molecular mechanism, and therapeutic effective components of QHSSD on both OA and RA. A total of 153 active ingredients in QHSSD were identified, 142 of which associated with 59 potential targets for the two diseases were identified. By constructing the protein-protein interaction network and the compound-target-disease network, 72 compounds and 10 proteins were obtained as the hub targets of QHSSD against OA and RA. The hub genes of ESR1, PTGS2, PPARG, IL1B, TNF, MMP2, IL6, CYP3A4, MAPK8, and ALB were mainly involved in osteoclast differentiation, the NF-κB and TNF signaling pathways. Moreover, molecular docking results showed that the screened active compounds had a high affinity for the hub genes. This study provides new insight into the molecular mechanisms behind how QHSSD presents homotherapy-for-heteropathy therapeutic efficacy in both OA and RA. For the first time, a two-disease model was linked with a TCM formula using network pharmacology to identify the key active components and understand the common mechanisms of its multi-pathway regulation. This study will inspire more innovative and important studies on the modern research of TCM formulas.     

Exploring the mechanism of action Xianlingubao Prescription in the treatment of osteoporosis by network pharmacology

In this study, the network pharmacology analysis method was used to explore the bioactive components and targets of Xianlinggubao (XLGB) and further elucidate its potential biological mechanisms of action in the treatment of osteoporosis (OP). The bioactive compounds and predictive targets of XLGB were collected from the traditional Chinese medicine systems pharmacology databases and analysis platform(TCMSP), the Encyclopeida of traditional Chinese medicine (ETCM), traditional Chinese medicine Databse@Taiwan, ChEMBL, STITCH, and SymMap database. The targets corresponding to OP were obtained by using Online Mendelian Inheritance in Man® (OMIM), GeneCards, the National Center for Biotechnology Information-Gene database. The XLGB-OP targets were obtained by intersecting with the targets of XLGB and OP. Protien-Protien interaciton (PPI) network was constructed using STRING online database and analyzed using Cytoscape 3.7.0 software to screen out hub genes. Gene ontology (GO) and KEGG enrichment analysis of the target in the PPI network was conducted using the ClusterProfiler package in R with adjusted p-value<0.05. A total of 65 XLGB bioactive compounds were screened corresponding to 776 XLGB targets and 2556 OP targets. The GO analysis and KEGG enrichment analyses suggested XLGB played a therapeutic roles in OP treatment via the interleukin-17 signaling pathway, hypoxia-inducible factor-1 signaling pathway, insulin resistance, Th-17 signaling pathway, etc. Five hub genes (AKT1, MAPK1, MAPK8, TP53, and STAT3) were screened using the degree algorithm, and molecular docking stimulation results showed that most bioactive compounds of XLGB had strong binding efficiency with hub genes. Overall, this study laid the foundation for further in vivo and in vitro experimental research and expanded the clinical applications of XLGB.     

核酸适配体在肿瘤靶向治疗方面的研究进展

传统的抗肿瘤药物大多不具有选择性,在临床治疗中产生了严重的毒副作用。核酸适配体是一种小分子核酸,能够与靶标高亲和性、高特异性地结合。选择与癌症发生发展过程密切相关的生物标记物为靶标进行SELEX过程筛选出的核酸适配体自身可作为药物,也可与药物、siRNA、纳米粒等结合构成靶向给药体系,该体系能靶向作用于特定的肿瘤细胞,降低对正常细胞的毒性,用药量显著降低,药效提高。本文综述了近年来核酸适配体直接作为抗肿瘤药物、药物载体、siRNA载体以及作为纳米材料靶向剂构成多元复合靶向给药体系在肿瘤靶向治疗领域的研究进展。     

Molecular Simulation and Statistical Learning Methods toward Predicting Drug–Polymer Amorphous Solid Dispersion Miscibility,Stability, and Formulation Design

Amorphous solid dispersions (ASDs) have emerged as widespread formulations for drug delivery of poorly soluble active pharmaceutical ingredients (APIs). Predicting the API solubility with various carriers in the API–carrier mixture and the principal API–carrier non-bonding interactions are critical factors for rational drug development and formulation decisions. Experimental determination of these interactions, solubility, and dissolution mechanisms is time-consuming, costly, and reliant on trial and error. To that end, molecular modeling has been applied to simulate ASD properties and mechanisms. Quantum mechanical methods elucidate the strength of API–carrier non-bonding interactions, while molecular dynamics simulations model and predict ASD physical stability, solubility, and dissolution mechanisms. Statistical learning models have been recently applied to the prediction of a variety of drug formulation properties and show immense potential for continued application in the understanding and prediction of ASD solubility. Continued theoretical progress and computational applications will accelerate lead compound development before clinical trials. This article reviews in silico research for the rational formulation design of low-solubility drugs. Pertinent theoretical groundwork is presented, modeling applications and limitations are discussed, and the prospective clinical benefits of accelerated ASD formulation are envisioned.     

Chemistry and Biology of the Caged Garcinia Xanthones

Natural products have been a great source of many small molecule drugs for various diseases. In spite of recent advances in biochemical engineering and fermentation technologies that allow us to explore microorganisms and the marine environment as alternative sources of drugs, more than 70 % of the current small molecule therapeutics derive their structures from plants used in traditional medicine. Natural‐product‐based drug discovery relies heavily on advances made in the sciences of biology and chemistry. Whereas biology aims to investigate the mode of action of a natural product, chemistry aims to overcome challenges related to its supply, bioactivity, and target selectivity. This review summarizes the explorations of the caged Garcinia xanthones, a family of plant metabolites that possess a unique chemical structure, potent bioactivities, and a promising pharmacology for drug design and development.     

Can an in silico drug-target search method be used to probe potential mechanisms of medicinal plant ingredients?

Medicinal plants have been explored therapeutically in traditional medicines and are a valuable source for drug discovery. Insufficient knowledge about the molecular mechanism of these medicinal plants limits the scope of their application and hinders the effort to design new drugs using the therapeutic principles of herbal medicines. This problem can be partially alleviated if efficient methods for rapid identification of protein targets of herbal ingredients can be introduced. Efforts have been directed at developing efficient computer methods for facilitating target identification. Various methods being explored or under investigation are reviewed here. So far, one computer method, INVDOCK, has been specifically used for automated drug target identification. Its usefulness in the identification of therapeutic targets of medicinal herbal ingredients as well as synthetic chemicals is reviewed. The majority of INVDOCK identified therapeutic targets of several well-known medicinal herbal ingredients have been found to be confirmed or implicated by experiments, which suggests the potential of in silico methods in facilitating the study of molecular mechanism of medicinal plants.     

Review: Separation and Pharmacology of Chiral Compounds in Traditional Chinese Medicine

More than 60% commonly used pharmaceutical active ingredients are chiral compounds. Developing more effective and safe chiral compounds has become a focus in the pharmaceutical industry. Chiral compounds widely exist in traditional Chinese medicine and include alkaloids, flavonoids, volatile oils, and amino acids. The characterization of chiral compounds used in traditional Chinese medicine remains limited. Here, the characterization of chiral compounds commonly used in traditional Chinese medicine is reviewed focusing upon their separation and pharmacology.     

Prodrugs in cardiovascular therapy

Prodrugs are biologically inactive derivatives of an active drug intended to solve certain problems of the parent drug such as toxicity, instability, minimal solubility and non-targeting capabilities. The majority of drugs for cardiovascular diseases undergo first-pass metabolism, resulting in drug inactivation and generation of toxic metabolites, which makes them appealing targets for prodrug design. Since prodrugs undergo a chemical reaction to form the parent drug once inside the body, this makes them very effective in controlling the release of a variety of compounds to the targeted site. This review will provide the reader with an insight on the latest developments of prodrugs that are available for treating a variety of cardiovascular diseases. In addition, we will focus on several drug delivery methodologies that have merged with the prodrug approach to provide enhanced target specificity and controlled drug release with minimal side effects.     

Multiple-Molecule Drug Design Based on Systems Biology Approaches and Deep Neural Network to Mitigate Human Skin Aging

Human skin aging is affected by various biological signaling pathways, microenvironment factors and epigenetic regulations. With the increasing demand for cosmetics and pharmaceuticals to prevent or reverse skin aging year by year, designing multiple-molecule drugs for mitigating skin aging is indispensable. In this study, we developed strategies for systems medicine design based on systems biology methods and deep neural networks. We constructed the candidate genomewide genetic and epigenetic network (GWGEN) via big database mining. After doing systems modeling and applying system identification, system order detection and principle network projection methods with real time-profile microarray data, we could obtain core signaling pathways and identify essential biomarkers based on the skin aging molecular progression mechanisms. Afterwards, we trained a deep neural network of drug–target interaction in advance and applied it to predict the potential candidate drugs based on our identified biomarkers. To narrow down the candidate drugs, we designed two filters considering drug regulation ability and drug sensitivity. With the proposed systems medicine design procedure, we not only shed the light on the skin aging molecular progression mechanisms but also suggested two multiple-molecule drugs for mitigating human skin aging from young adulthood to middle age and middle age to old age, respectively.     

Exploring polypharmacology using a ROCS-based target fishing approach

Polypharmacology has emerged as a new theme in drug discovery. In this paper, we studied polypharmacology using a ligand-based target fishing (LBTF) protocol. To implement the protocol, we first generated a chemogenomic database that links individual protein targets with a specified set of drugs or target representatives. Target profiles were then generated for a given query molecule by computing maximal shape/chemistry overlap between the query molecule and the drug sets assigned to each protein target. The overlap was computed using the program ROCS (Rapid Overlay of Chemical Structures). We validated this approach using the Directory of Useful Decoys (DUD). DUD contains 2950 active compounds, each with 36 property-matched decoys, against 40 protein targets. We chose a set of known drugs to represent each DUD target, and we carried out ligand-based virtual screens using data sets of DUD actives seeded into DUD decoys for each target. We computed Receiver Operator Characteristic (ROC) curves and associated area under the curve (AUC) values. For the majority of targets studied, the AUC values were significantly better than for the case of a random selection of compounds. In a second test, the method successfully identified off-targets for drugs such as rimantadine, propranolol, and domperidone that were consistent with those identified by recent experiments. The results from our ROCS-based target fishing approach are promising and have potential application in drug repurposing for single and multiple targets, identifying targets for orphan compounds, and adverse effect prediction.     

中药活性成分研究是中药现代化的重要组成部分

中药现代化是一个逐步发展、不断完善和充实的长期的系统工程。中医药在我国民族生存和繁衍的几千年历程中起着至关重要的作用,具有自己的特色和优势,是中华民族的宝贵财富,既要继承,又要创新和发展。中药现代化可以有多种模式,只要有利于人民健康,有利于传承和发展中医药,不管采取何种模式均应得到鼓励和欢迎。中药的活性成分研究是中药现代化的重要组成部分：一方面,一些活性成分能直接或作为先导化合物间接发展成药物;另一方面,活性成分又为中药复方现代化提供物质基础。这体现在活性成分既在现代化中药的制造和生产中起到标准化作用,同时活性成分也是中药复方专利最重要的核心组成部分。     

Analysis of five active ingredients of Er-Zhi-Wan,a traditional Chinese medicine water-honeyed pill,using the biopharmaceutics classification system

Er-Zhi-Wan (EZW) is a traditional Chinese medicine with many clinical applications and used as a health product in East Asia. Five active ingredients (salidroside, specnuezhenide, nuezhenoside, luteolin, and oleanolic acid) were screened out from EZW to develop an in vitro rapid evaluation method for the classification of in vivo drug absorption behavior by biopharmaceutics classification system (BCS). Ultra-performance liquid chromatography was used for quantitative analysis. Solubility and permeability were assayed by equilibrium solubility and multiple models: everted rat intestinal sac model, cultured Caco-2 cells, octanol–water partition coefficient (LogP) method. The BCS properties of drugs were predicted using software applications, and the correlations of measured and predicted values of factors affecting oral drug absorption were calculated. The results were verified by measuring the absolute bioavailability of the active ingredients. Salidroside, specnuezhenide, and nuezhenoside were classified as BCS class III drugs, and luteolin was classified as a BCS class III/I drug because of the difference in LogP and intestinal permeability. Oleanolic acid was classified as a BCS class II/IV drug in acidic media and BCS class I/III drug in other media. Overall, EZW may be classified as a BCS class III drug, and permeability was identified as the primary factor limiting absorption. The results provide a novel method for the evaluation of the in vivo absorption of oral traditional Chinese medicines.