Proteomics to display lovastatin-induced protein and pathway regulation in rat liver

Lovastatin is a lipid lowering agent that acts by inhibiting 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase, a key regulatory enzyme in cholesterol biosynthesis. In this study the pattern of gene network regulation induced in hepatic proteins as a response to lovastatin treatment was analyzed by proteomics. In livers of male F344 rats treated with 1.6 mg/kg/day lovastatin or 150 mg/kg/day lovastatin for seven days, 36 proteins were found to be significantly altered (p<0.001) in relation to treatment. The changed proteins were classified according to their cellular function and participation in biochemical pathways. The following observations were made: (i) inhibition of HMG-CoA reductase provoked a regulatory response in the cholesterol synthesis pathway including the induction of cytosolic HMG-CoA synthase and of isopentenyl-diphosphate delta-isomerase, (ii) manipulation of the lipid metabolism triggered alterations in key enzymes of the carbohydrate metabolism, and (iii) lovastatin treatment was associated with signs of toxicity as reflected by changes in a heterogeneous set of cellular stress proteins involved in functions such as cytoskeletal structure, calcium homeostasis, protease inhibition, cell signaling or apoptosis. These results present new insights into liver gene network regulations induced by lovastatin and illustrate a yet unexplored application of proteomics to discover new targets by analysis of existing drugs and the pathways that they regulate.     

A network-based pharmacology study of active compounds and targets of Fritillaria thunbergii against influenza

Seasonal and pandemic influenza infections are serious threats to public health and the global economy. Since antigenic drift reduces the effectiveness of conventional therapies against the virus, herbal medicine has been proposed as an alternative. Fritillaria thunbergii (FT) have been traditionally used to treat airway inflammatory diseases such as coughs, bronchitis, pneumonia, and fever-based illnesses. Herein, we used a network pharmacology-based strategy to predict potential compounds from Fritillaria thunbergii (FT), target genes, and cellular pathways to better combat influenza and influenza-associated diseases. We identified five compounds, and 47 target genes using a compound-target network (C-T). Two compounds (beta-sitosterol and pelargonidin) and nine target genes (BCL2, CASP3, HSP90AA1, ICAM1, JUN, NOS2, PPARG, PTGS1, PTGS2) were identified using a compound-influenza disease target network (C-D). Protein-protein interaction (PPI) network was constructed and we identified eight proteins from nine target genes formed a network. The compound-disease-pathway network (C-D-P) revealed three classes of pathways linked to influenza: cancer, viral diseases, and inflammation. Taken together, our systems biology data from C-T, C-D, PPI and C-D-P networks predicted potent compounds from FT and new therapeutic targets and pathways involved in influenza.     

Globally Approved EGFR Inhibitors: Insights into Their Syntheses,Target Kinases,Biological Activities,Receptor Interactions,and Metabolism

Targeting the EGFR with small-molecule inhibitors is a confirmed valid strategy in cancer therapy. Since the FDA approval of the first EGFR-TKI, erlotinib, great efforts have been devoted to the discovery of new potent inhibitors. Until now, fourteen EGFR small-molecule inhibitors have been globally approved for the treatment of different types of cancers. Although these drugs showed high efficacy in cancer therapy, EGFR mutations have emerged as a big challenge for these drugs. In this review, we focus on the EGFR small-molecule inhibitors that have been approved for clinical uses in cancer therapy. These drugs are classified based on their chemical structures, target kinases, and pharmacological uses. The synthetic routes of these drugs are also discussed. The crystal structures of these drugs with their target kinases are also summarized and their bonding modes and interactions are visualized. Based on their binding interactions with the EGFR, these drugs are also classified into reversible and irreversible inhibitors. The cytotoxicity of these drugs against different types of cancer cell lines is also summarized. In addition, the proposed metabolic pathways and metabolites of the fourteen drugs are discussed, with a primary focus on the active and reactive metabolites. Taken together, this review highlights the syntheses, target kinases, crystal structures, binding interactions, cytotoxicity, and metabolism of the fourteen globally approved EGFR inhibitors. These data should greatly help in the design of new EGFR inhibitors.     

Fluorine in medicinal chemistry: Recent therapeutic applications of fluorinated small molecules

Advances in the development of newly developed fluorinated drugs, approved or in clinical trials, as organized by biological targets/disease states, are reviewed. In a few cases, compounds in early stages of development will be discussed, particularly where new promising targets are involved. Important topics such as anticancer and antiviral drugs were covered in the two previous reviews in this series. Included herein will be fluorinated drugs for treatment of diseases of the central nervous system, various cardiovascular diseases and obesity, antibacterial agents, and antifungal therapy.     

Antitumor effect of guava leaves on lung cancer: A network pharmacology study

Guava is known for its hypoglycemic, antivirus, antibacterial, anti-inflammatory, antioxidant, and antitumor properties. In this study, triterpenoids, sesquiterpenes, and flavonoids were examined as potential targets of constituents of guava leaves. Our study was aimed to reveal the antitumor mechanism and construct the network pharmacology network of guava leaf constituents and lung cancer. The potential targets of guava leaf constituents were searched in target databases, while the disease genes were searched in the GeneCards database. The common targets of drugs and diseases were screened out. A network map was constructed by the Cytoscape software, and the GO and KEGG pathways were analyzed. The existing cases were studied by SystemsDock molecular docking and cBioPortal tumor database study. Among the 66 chemical constituents of guava leaves, 153 of their targets were the lung cancer genes involved in many signaling pathways, such as the PI3K-Akt signaling pathway, in small cell lung cancer and non-small cell lung cancer. There was a binding activity between ligand compounds and receptor proteins. Guava leaves inhibited tumor through a gene regulatory network, and may play an important role in gene-targeting therapy. Through network pharmacology, we found that guava leaves had potential targets that interacted with various tumors, regulating the signaling pathways of cancers. This study preliminarily verified the pharmacological basis and the mechanism of the antitumor effect of guava leaves, providing a foundation for further research.     

Design of a tripartite network for the prediction of drug targets

Drug-target networks have aided in many target prediction studies aiming at drug repurposing or the analysis of side effects. Conventional drug-target networks are bipartite. They contain two different types of nodes representing drugs and targets, respectively, and edges indicating pairwise drug-target interactions. In this work, we introduce a tripartite network consisting of drugs, other bioactive compounds, and targets from different sources. On the basis of analog relationships captured in the network and so-called neighbor targets of drugs, new drug targets can be inferred. The tripartite network was found to have a stable structure and simulated network growth was accompanied by a steady increase in assortativity, reflecting increasing correlation between degrees of connected nodes leading to even network connectivity. Local drug environments in the tripartite network typically contained neighbor targets and revealed interesting drug-compound-target relationships for further analysis. Candidate targets were prioritized. The tripartite network design extends standard drug-target networks and provides additional opportunities for drug target prediction.     

Recent research progress on small molecule compounds and its derivatives of antiparasitic drugs

Neglected tropical diseases (NTDs) refer to infectious diseases caused by multiple pathogens that are prevalent in hot, humid climates in tropical areas. With the global economic growth and the improvement of public health status, eliminating neglected tropical diseases will be of great significance to the healthy development of human beings. However, the number of drugs and vaccines for NTDs treatment is extremely limited, so it is urgent to develop new drugs. Since most NTDs are caused by parasites, this paper selected parasitic diseases with high morbidity and mortality, and focused on new effective therapeutic targets and excellent lead compounds for these diseases. Schistosomiasis, human African trypanosomiasis (HAT), Chagas disease, leishmaniasis, filariasis and toxoplasmosis correspond to a series targets such as smHDAC8, thioredoxin glutathione reductase (TGR), T. cruzi glucokinase (TcGlcK), phosphofructokinase (PFK), type IB topoisomerase, cell division cycle-2-related Kinase, sterolmethyl transferase, calumenin, dihydrofolate reductase (DHFR) and Toxoplasma gondii farnesyl-diphosphate synthase (TgFPPs). In this paper, the pharmacological effects of typical lead compounds corresponding to each disease, the structural characteristics of the mother nucleus and the pharmacological activities of the substituent. In addition, the binding patterns of some involved targets (such as smHDAC8) with corresponding lead compounds (such as compound 13) and the signaling pathways associated with gluconeogenesis, glycolysis, and pentose phosphate pathways are analyzed in detail. In this paper, the interaction mechanism between the lead compounds and the target were thoroughly discussed, in order to provide the research ideas of potential anti-parasite compounds, and further improve the understanding and prevention ability of such diseases of NTDs.     

Nano Carrier Drug Delivery Systems for the Treatment of Neuropsychiatric Disorders: Advantages and Limitations

Neuropsychiatric diseases are one of the main causes of disability, affecting millions of people. Various drugs are used for its treatment, although no effective therapy has been found yet. The blood brain barrier (BBB) significantly complicates drugs delivery to the target cells in the brain tissues. One of the problem-solving methods is the usage of nanocontainer systems. In this review we summarized the data about nanoparticles drug delivery systems and their application for the treatment of neuropsychiatric disorders. Firstly, we described and characterized types of nanocarriers: inorganic nanoparticles, polymeric and lipid nanocarriers, their advantages and disadvantages. We discussed ways to interact with nerve tissue and methods of BBB penetration. We provided a summary of nanotechnology-based pharmacotherapy of schizophrenia, bipolar disorder, depression, anxiety disorder and Alzheimer’s disease, where development of nanocontainer drugs derives the most active. We described various experimental drugs for the treatment of Alzheimer’s disease that include vector nanocontainers targeted on β-amyloid or tau-protein. Integrally, nanoparticles can substantially improve the drug delivery as its implication can increase BBB permeability, the pharmacodynamics and bioavailability of applied drugs. Thus, nanotechnology is anticipated to overcome the limitations of existing pharmacotherapy of psychiatric disorders and to effectively combine various treatment modalities in that direction.     

Prodrugs for the treatment of neglected diseases

Recently, World Health Organization (WHO) and Medicins San Frontieres (MSF) proposed a classification of diseases as global, neglected and extremely neglected. Global diseases, such as cancer, cardiovascular and mental (CNS) diseases represent the targets of the majority of the R&D efforts of pharmaceutical companies. Neglected diseases affect millions of people in the world yet existing drug therapy is limited and often inappropriate. Furthermore, extremely neglected diseases affect people living under miserable conditions who barely have access to the bare necessities for survival. Most of these diseases are excluded from the goals of the R&D programs in the pharmaceutical industry and therefore fall outside the pharmaceutical market. About 14 million people,mainly in developing countries, die each year from infectious diseases. From 1975 to 1999,1393 new drugs were approved yet only 1% were for the treatment of neglected diseases[3]. These numbers have not changed until now, so in those countries there is an urgent need for the design and synthesis of new drugs and in this area the prodrug approach is a very interesting field. It provides, among other effects, activity improvements and toxicity decreases for current and new drugs, improving market availability. It is worth noting that it is essential in drug design to save time and money, and prodrug approaches can be considered of high interest in this respect. The present review covers 20 years of research on the design of prodrugs for the treatment of neglected and extremely neglected diseases such as Chagas' disease (American trypanosomiasis), sleeping sickness (African trypanosomiasis), malaria, sickle cell disease, tuberculosis, leishmaniasis and schistosomiasis.     

丹荷颗粒治疗高脂血症质量标志物发现研究

为寻找丹荷颗粒治疗高脂血症的质量标志物,该研究基于丹荷颗粒体内成分分析结果,采用Cytoscape软件构建高脂血症-共有靶点-丹荷颗粒体内成分作用网络,利用DAVID及String数据库分别对共有靶点进行生物过程、通路富集及网络拓扑分析,明确丹荷颗粒降脂作用关键靶点及成分,再建立油酸诱导的HepG2细胞脂质堆积模型验证关键成分的降脂药效,最后结合相关成分在制剂中的含量、稳定性、特征性综合确定质量标志物。结果发现,丹荷颗粒体内成分作用于CES1、ADORA2A、ADORA1、APOB、LDLR、PPARA、PPARG、INSR、ESR2、ESR1共10个高脂血症疾病靶点,主要参与脂质代谢过程以及PPAR、cAMP信号通路,其中LDLR、PPARA、PPARG可能是关键靶点,而网络中与关键靶点直接作用的成分为白藜芦醇、柚皮素。白藜芦醇和柚皮素均可降低油酸诱导的HepG2细胞内脂滴数量,改善细胞脂质堆积严重程度,并显著降低细胞内甘油三酯含量,可能为关键成分;鉴于入体成分白藜芦醇和柚皮素来源于制剂中虎杖苷及柚皮苷,且制剂中虎杖苷及柚皮苷特征明显、含量丰富、稳定,故虎杖苷及柚皮苷可作为丹荷颗粒治疗高脂血症的质量标志物。该研究为丹荷颗粒质量标准的建立提供了合理的候选质控指标。     

Virtual screening of approved drugs as potential SARS-CoV-2 main protease inhibitors

The global emergency caused by COVID-19 makes the discovery of drugs capable of inhibiting SARS-CoV-2 a priority, to reduce the mortality and morbidity of this disease. Repurposing approved drugs can provide therapeutic alternatives that promise rapid and ample coverage because they have a documented safety record, as well as infrastructure for large-scale production. The main protease of SARS-CoV-2 (Mpro) is an excellent therapeutic target because it is critical for viral replication; however, Mpro has a highly flexible active site that must be considered when performing computer-assisted drug discovery. In this work, potential inhibitors of the main protease (Mpro) of SARS-Cov-2 were identified through a docking-assisted virtual screening procedure. A total of 4384 drugs, all approved for human use, were screened against three conformers of Mpro. The ligands were further studied through molecular dynamics simulations and binding free energy analysis. A total of nine currently approved molecules are proposed as potential inhibitors of SARS-CoV-2. These molecules can be further tested to speed the development of therapeutics against COVID-19.     

Network pharmacology-based screening of the active ingredients and potential targets of the genus of Pithecellobium marthae (Britton & Killip) Niezgoda & Nevl for application to Alzheimer’s disease

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder associated with synaptic dysfunction, pathological accumulation of β-amyloid (Aβ), and neuronal loss. Given the prevalence of AD and the lack of effective long-term therapies, there is a pressing need to discover viable leads that can be developed into clinically approved drugs with disease-modifying effects. The analysis of current reported literatures confirms the importance of the plants of Pithecellobium genus as candidate against AD. Hence, it is necessary to identify selective anti-dementia agents from this genus. To explore potential compounds with marked effect on AD in Pithecellobium genus, a compound database based on the methods of network pharmacology prediction was established in this paper by constructing the compound-disease target network. The result showed that the most effective compound in the plants of this genus might be (7′R,8′R)-7′-methoxyl strebluslignanol, and the most potential target might be Macrophage colony-stimulating factor 1 receptor.     

Multifunctional Small Molecules as Potential Anti-Alzheimer’s Disease Agents

Alzheimer’s disease (AD) is a severe multifactorial neurodegenerative disorder characterized by a progressive loss of neurons in the brain. Despite research efforts, the pathogenesis and mechanism of AD progression are not yet completely understood. There are only a few symptomatic drugs approved for the treatment of AD. The multifactorial character of AD suggests that it is important to develop molecules able to target the numerous pathological mechanisms associated with the disease. Thus, in the context of the worldwide recognized interest of multifunctional ligand therapy, we report herein the synthesis, characterization, physicochemical and biological evaluation of a set of five (1a–e) new ferulic acid-based hybrid compounds, namely feroyl-benzyloxyamidic derivatives enclosing different substituent groups, as potential anti-Alzheimer’s disease agents. These hybrids can keep both the radical scavenging activity and metal chelation capacity of the naturally occurring ferulic acid scaffold, presenting also good/mild capacity for inhibition of self-Aβ aggregation and fairly good inhibition of Cu-induced Aβ aggregation. The predicted pharmacokinetic properties point towards good absorption, comparable to known oral drugs.     

Computational network pharmacological research of Chinese medicinal plants for chronic kidney disease

The interaction between drug molecules and target proteins is the basis of pharmacological action. The pharmacodynamic mechanism of Chinese medicinal plants for chronic kidney disease (CKD) was studied by molecular docking and complex network analysis. It was found that the interaction network of components-proteins of Chinese medicinal plants is different from the interaction network of components-proteins of drugs. The action mechanism of Chinese medicinal plants is different from that of drugs. We also found the interaction network of components-proteins of tonifying herbs is different from the interaction network of components-proteins of evil expelling herbs using complex network research approach. It illuminates the ancient classification theory of Chinese medicinal plants. This computational approach could identify the pivotal components of Chinese medicinal plants and their key target proteins rapidly. The results provide data for development of multi-component Chinese medicine.     

Combined RNA-expression and 2D-PAGE-screening identifies comprehensive interaction networks affected after bortezomib or enzastaurin exposure of mantle cell lymphoma

Despite recent advances in treatment, mantle cell lymphoma (MCL) still represents a disease with dismal prognosis due to its progressive clinical course, high rate of therapy refractory cases and frequent relapses. During recent years, the proteasome inhibitor bortezomib and enzastaurin, an inhibitor of protein kinase c have been explored in MCL. In relapsed disease enzastaurin achieved disease stabilization in a subset of patients. Bortezomib in relapsed and refractory MCL achieves response rates of 30-40%. To identify signal pathways and manifold interactions regulating cellular response to molecular targeted approaches several high throughput screening methods were applied. A combined network analysis of the identified target molecules based on both RNA array expression data and a survey of cellular protein levels resulted in a unified interaction network more comprehensive (bortezomib: 394 and enzastaurin: 174 molecules) than the networks of the individual screening techniques (329/44 and 117/36 molecules respectively). Interestingly, although none of the target molecules were matched in both RNA-expression and protein level analysis they were mapped nonetheless to common pathways. Additionally, the ranking of identified pathways allowed an improved characterization of the observed induction of cell apoptosis.     

基于液相色谱-质谱联用的代谢组学技术研究Pokemon诱导的胞内脂代谢变化

Pokemon是一种转录抑制因子,能够通过影响染色质的重组或直接与抑癌基因结合而抑制抑癌基因的转录,促使肿瘤形成。该文利用基于液相色谱-质谱联用的代谢组学技术研究了Pokemon在肝癌中调控细胞代谢的作用机制。通过脂质转染,获得了Pokemon高表达的HL7702细胞,分别收集转染后不同时间点的细胞。利用基于液相色谱-质谱联用技术的代谢组学方法,分析胞内代谢物的成分。根据多元统计分析的结果选出差异显著的候选代谢物,通过数据库（METLIN和HMDB）检索、二级图谱比对进行结构解析,确证了36种代谢物。通过KEGG数据库检索发现这些代谢物主要与脂质合成相关。进一步分析发现脂质合成途径中乙酰辅酶羧化酶和脂肪酸合成酶均被激活。结果显示,Pokemon可通过激活细胞中脂质合成通路而影响细胞的代谢。     

Uncovering the anticancer mechanism of petroleum extracts of Farfarae Flos against Lewis lung cancer by metabolomics and network pharmacology analysis

Lung cancer shows the highest incidence rate in the world. Thus, it has become increasingly important to find therapeutic drugs to treat lung cancer. Farfarae Flos (FF) has been used in traditional Chinese medicine to treat pulmonary diseases such as cough, bronchitis and asthmatic disorders. In this study, the anti-proliferation effects of petroleum extracts of FF (PEFF) on Lewis lung cancer cells and the corresponding mechanisms were studied using cell metabolomics. Fifteen differential metabolites in the cell extracts and the corresponding medium related to the anti-proliferation effect of PEFF were identified, which were probably involved in pyruvate metabolism and glycine, serine and threonine metabolism. For the cellular uptake compounds in PEFF, six metabolites derived from two prototype compounds were also tentatively identified by UHPLC-Q-Orbitrap high-resolution MS. Network pharmacology analysis demonstrated that the anti-proliferation mechanism of PEFF was also probably related to the target genes, including, Aurora-A, glutathione S-transferase Mu 1 (GSTM1), glutathione S-transferase P 1 (GSTP1), progesterone receptor and heme oxygenase-1 (HO-1), and further associated with the proteoglycans and PI3K/Akt signaling pathway. Cell metabolomics and network pharmacology analysis provided a holistic method to investigate the anti-proliferation mechanisms of PEFF. However, further studies were still needed to validate the potential target genes, pathways and active compounds in PEFF.     

Nanochaperone‐Based Strategies to Control Protein Aggregation Linked to Conformational Diseases

The generation of highly organized amyloid fibrils is associated with a wide range of conformational pathologies, including primarily neurodegenerative diseases. Such disorders are characterized by misfolded proteins that lose their normal physiological roles and acquire toxicity. Recent findings suggest that proteostasis network impairment may be one of the causes leading to the accumulation and spread of amyloids. These observations are certainly contributing to a new focus in anti‐amyloid drug design, whose efforts are so far being centered on single‐target approaches aimed at inhibiting amyloid aggregation. Chaperones, known to maintain proteostasis, hence represent interesting targets for the development of novel therapeutics owing to their potential protective role against protein misfolding diseases. In this minireview, research on nanoparticles that can either emulate or help molecular chaperones in recognizing and/or correcting protein misfolding is discussed. The nascent concept of “nanochaperone” may indeed set future directions towards the development of cost‐effective, disease‐modifying drugs to treat several currently fatal disorders.