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Introduction: Highly aggressive thoracic neoplasms characterized by SMARCA4 (BRG1) deficiency and undifferentiated round cell or rhabdoid morphology have been recently described and proposed to represent thoracic sarcomas. However, it remains unclear whether such tumors may instead represent sarcomatoid carcinomas, and how their clinicopathologic characteristics compare with those of nonsarcomatoid SMARCA4-deficient non–small cell lung carcinomas (SD-NSCC). Methods: We identified 22 SMARCA4-deficient thoracic sarcomatoid tumors (SD-TSTs) with round cell and/or rhabdoid morphology and 45 SD-NSCCs, and comprehensively analyzed their clinicopathologic, immunohistochemical, and genomic characteristics using 341–468 gene next-generation sequencing and other molecular platforms. Results: The relationship of SD-TSTs with NSCC was supported by (1) the presence of NSCC components juxtaposed with sarcomatoid areas in five cases, (2) focal expression of NSCC lineage markers TTF1 or p40 in four additional cases, (3) smoking history in all except one patient (mean = 51 pack-years), accompanied by genomic smoking signature, and (4) high tumor mutation burden (mean = 14.2 mutations per megabase) and mutations characteristic of NSCC in a subset. Compared with SD-NSCCs, SD-TSTs exhibited considerably larger primary tumor size (p < 0.0001), worse survival (p = 0.004), and more frequent presentation at younger age (30–50 years) despite heavier smoking history. Distinctive pathologic features of SD-TSTs included consistent lack of adhesion molecule claudin-4, SMARCA2 (BRM) codeficiency, and frequent expression of stem cell markers. Conclusions: SD-TSTs represent primarily smoking-associated undifferentiated/de-differentiated carcinomas rather than primary thoracic sarcomas. Despite their histogenetic relationship with NSCC, these tumors have unique clinicopathologic characteristics, supporting their recognition as a distinct entity. Further studies are warranted to determine therapeutic approaches to this novel class of exceptionally aggressive thoracic tumors.

Ethnopharmacological relevance Shenqi Fuzheng (SQ) is a renowned traditional Chinese medicine extracted from Radix Codonopsis and Radix Astragali. Although SQ is widely used to treat myocardial ischemia-reperfusion (I/R) injury, the molecular mechanisms supporting its clinical application remain elusive. Aim of the study The purpose of current study was to understand its cardioprotective effects at the molecular level using network pharmacology approach. Materials and method In an I/R injury animal model, the beneficial pharmacological activities of SQ were confirmed by decreased infarct range observed on drug treated rats versus control group. Additionally, several serum biochemical indicators were in concord with this observation. Subsequently, a microarray experiment was performed to reveal the influence on injured heart at the gene expression level by this TCM injection. We then proposed a network analysis algorithm NTRA to discover the key nodes based on both disease network structure and transcriptomics. Using NRIODN, a method developed by our group previously, the holistic changes on the gene network induced by for I/R injury and SQ treatment were evaluated. Results Pathway enrichment analysis of highly ranked genes by NTRA showed that PPAR and apoptosis pathways were highly related to I/R injury. Finally, western blot results showed increased level of the PPARα and BAX protein in the heart after injection treatment which confirmed the hypothesis. Conclusion In conclusion, our results suggest that SQ injection exerts protective effect against myocardial ischemia-reperfusion injury through multiple pathways, including myocardial energy metabolism improvement, cell adhesion inhibition, inflammatory reaction perturbation, myocardial apoptosis reduction and ventricular remodeling avoidance.

Summary Selecting appropriate cell lines to represent a disease is crucial for the success of biomedical research, because the usage of less relevant cell lines could deliver misleading results. However, systematic guidance on cell line selection is unavailable. Here we developed a clinical Genomics-guided Prioritizing Strategy for Cancer Cell Lines (CCL-cGPS) and help to guide this process. Statistical analyses revealed CCL-cGPS selected cell lines were among the most appropriate models. Moreover, we observed a linear correlation between the drug response and CCL-cGPS score of cell lines for breast and thyroid cancers. Using RT4 cells selected by CCL-GPS, we identified mebendazole and digitoxin as candidate drugs against bladder cancer and validate their promising anticancer effect through in vitro and in vivo experiments. Additionally, a web tool was developed. In conclusion, CCL-cGPS bridges the gap between tumors and cell lines, presenting a helpful guide to select the most suitable cell line models., Graphical Abstract, Highlights • Cell lines were ranked by the resemblance of transcriptional signatures to tumors • Among 44 tumor subtypes, CCL-cGPS provides proper cell lines for each subtype • CCL-cGPS was verified by the computational analysis, in vitro and in vivo assays • A web tool was developed to guide the selection of the most suitable cell lines, Cancer; Cancer Systems Biology; Genomics

Background Previous studies reported that early progression of disease (POD) after initial therapy predicted poor overall survival (OS) in patients with follicular lymphoma (FL). Here, we investigated whether pre-treatment imaging modality had an impact on prognostic significance of POD. Methods In this retrospective study, we identified 1088 patients with grade I–IIIA FL; of whom, 238 patients with stage II–IV disease were initially treated with rituximab, cyclophosphamide, doxorubicin, vincristine and prednisone (R-CHOP), and 346 patients were treated with rituximab-based chemotherapy. Patients (N = 484) from the FOLL05 study served as an independent validation cohort. We risk-stratified patients based on pre-treatment radiographic imaging (positron-emission tomography [PET] versus computed tomography [CT]) and early POD status using event-defining and landmark analyses. A competing risk analysis evaluated the association between early POD and histologic transformation. Results In the discovery cohort, patients with POD within 24 months (PFS24) of initiating R-CHOP therapy had a 5-year OS of 57.6% for CT-staged patients compared with 70.6% for PET-staged patients. In the validation cohort, the 5-year OS for patients with early POD was 53.9% and 100% in CT- and PET-staged patients, respectively. The risk of histologic transformation in patients whose disease progressed within one year of initiating therapy was higher in CT-staged patients than in PET-staged patients (16.7% versus 6.3%, respectively), which was associated with a 9.7-fold higher risk of death. Conclusion In FL, pre-treatment PET staging reduced the prognostic impact of early POD compared with CT staging. Patients with early POD and no histologic transformation have an extended OS with standard therapy.

The global rise of metallo-β-lactamases (MBLs) is problematic due to their ability to inactivate most β-lactam antibiotics. MBL inhibitors that could be co-administered with and restore the efficacy of β-lactams are highly sought after. In this study, we employ virtual screening of candidate MBL inhibitors without thiols or carboxylates to avoid off-target effects using the Avalanche software package, followed by experimental validation of the selected compounds. As target enzymes we chose the clinically relevant B1 MBLs NDM-1, IMP-1, and VIM-2. Among 32 compounds selected from a ~1.5 million compound library, 6 exhibited IC(50) values < 40 μM against NDM-1 and/or IMP-1. The most potent inhibitors of NDM-1, IMP-1, and VIM-2 had IC(50) values of 19 ± 2 μM, 14 ± 1 μM, and 50 ± 20 μM, respectively. While chemically diverse, the most potent inhibitors all contain combinations of hydroxyl, ketone, ester, amide, or sulfonyl groups. Docking studies suggest that these electron-dense moieties are involved in Zn(II) coordination and interaction with protein residues. These novel scaffolds could serve as the basis for further development of MBL inhibitors. A procedure for renaming NDM-1 residues to conform to the class B β-lactamase (BBL) numbering scheme is also included.

Background Cancer is a heterogeneous disease with many genetic variations. Lines of evidence have shown copy number variations (CNVs) of certain genes are involved in development and progression of many cancers through the alterations of their gene expression levels on individual or several cancer types. However, it is not quite clear whether the correlation will be a general phenomenon across multiple cancer types. Methods In this study we applied a bioinformatics approach integrating CNV and differential gene expression mathematically across 1025 cell lines and 9159 patient samples to detect their potential relationship. Results Our results showed there is a close correlation between CNV and differential gene expression and the copy number displayed a positive linear influence on gene expression for the majority of genes, indicating that genetic variation generated a direct effect on gene transcriptional level. Another independent dataset is utilized to revalidate the relationship between copy number and expression level. Further analysis show genes with general positive linear influence on gene expression are clustered in certain disease-related pathways, which suggests the involvement of CNV in pathophysiology of diseases. Conclusions This study shows the close correlation between CNV and differential gene expression revealing the qualitative relationship between genetic variation and its downstream effect, especially for oncogenes and tumor suppressor genes. It is of a critical importance to elucidate the relationship between copy number variation and gene expression for prevention, diagnosis and treatment of cancer.

Traditional Chinese medicine(TCM) is a research area with highly original innovation features,and is also a Chinese name card to the world. However,TCM owns a unique theoretical system which is quite different from western modern medicine,leading to an awkward situation of deficient modern social identity as well as poor international spread. Therefore,how to establish a research strategy in line with the characteristics of TCM itself to systematically interpret the unique scientific connotation of TCM is always a public hot topic. Based on persistent practical exploration and scientific consideration in TCM,our group firstly promoted the concept of traditional Chinese medicine chemical biology(TCM chemical biology,TCMCB). The major idea of TCMCB is to clarify the nature of TCM regulating life progress to link TCM to modern medicine by using TCM components as chemical tools. Notably,TCMCB mainly focuses on TCM target identification and TCM-guided disease molecular mechanism exploration,further to clarify the basic law of TCM mediating disease process. Finally,TCMCB-guided scientific studies can help explain TCM theory and promote the developmentof modern innovative drugs based on identified targets using TCM active components. Moreover,TCMCB is of vital importance for investigating the scientific nature of biological progress and the pattern of disease occurrence and development,indicating a key significance for modern life science and medicine. This review introduces the definition of TCMCB as well as its academic thought,research method,technology system and scientific significance,for providing new research ideas and scientific thoughts for TCM development.

The assessment of drug toxicity, especially hepatotoxicity, is a critical task in drug development process. To assist with early detection, various in silico approaches have been demonstrated to identify drugs with high hepatotoxicity potential. In this study, based on detailed review on previous reports on drug-induced cholestatic liver injury, we developed a network-based approach to predict cholestatic potential of chemicals using toxicogenomic data. First, the cholestasis network was constructed with 57 relevant genes and 78 connections between genes. Taking only genes in the disease network into account, the evaluation model was trained by genomic data of 17 typical chemicals associated with cholestasis and yielded the prediction accuracy at 88%. The performance of this model was further challenged by an X-permutation test and an external set of 98 chemicals. Among them, 14 chemicals were marked with high risk of inducing cholestasis by our approach. A survey of published literatures confirmed that 71.43% of our predicted chemicals have been shown to induce cholestatic liver injury experimentally and approximately 93% of them have been implicated to promote liver injury to various extents. Together, we concluded that network-based approaches greatly facilitate further understanding of molecular mechanisms for cholestatic liver injury and this concept could be easily generalized to other biological-relevant side-effect assessments.

As a major adverse drug reaction associated with traditional Chinese medicine injections (TCMIs), an anaphylactoid reaction has attracted a significant amount of attention from regulatory agencies and research communities. To ensure safe and effective use of TCMIs in the clinic, it is of great importance to identify the causative chemical responsible for the anaphylactoid reaction observed. Ginsenoside Rd (Rd) is one of the main active components in several TCMIs which have been recently reported to cause an anaphylactoid reaction. In this study, the possibility of an Rd-induced anaphylactoid reaction was first evaluated using general toxicological assessments. As a result, the in vitro model showed that Rd treatment could directly induce β-hexosaminidase release in RBL-2H3 cells through mast cell degranulation. Further in vivo studies revealed that cutaneous vascular permeability and plasma histamine levels were significantly increased in Rd-treated mice, strengthening the fact that Rd could induce an anaphylactoid reaction. Moreover, a comprehensive metabolomic approach was established to investigate the effects of an Rd-induced anaphylactoid reaction in mice using liquid chromatography-electrospray ionization-time-of-flight-mass spectrometry. Our results evinced that alterations in the metabolites related to inflammation and allergy diseases were observed during the early stage of an anaphylactoid reaction, including glycerophospholipids, corticosteroid hormones, bile acids, sterol lipids, and fatty acids, suggesting that the disturbances in lipid metabolism may be involved in the Rd-induced anaphylactoid reaction, such as glycerophospholipid and steroid hormone metabolism. Thus, Rd may be an allergenic factor inducing an anaphylactoid reaction in Rd-contained TCMIs.

Antibiotic resistance in bacteria is ever changing and adapting, as once-novel β-lactam antibiotics are losing their efficacy, primarily due to the production of β-lactamases. Metallo-β-lactamases (MBLs) efficiently inactivate a broad range of β-lactam antibiotics, including carbapenems, and are often coexpressed with other antibacterial resistance factors. The rapid dissemination of MBLs and lack of novel antibacterials pose an imminent threat to global health. In an effort to better counter these resistance-conferring β-lactamases, an investigation of their natural evolution and resulting substrate specificity was employed. In this study, we elucidated the effects of different amino acid substitutions at position 67 in IMP-type MBLs on the ability to hydrolyze and confer resistance to a range of β-lactam antibiotics. Wild-type β-lactamases IMP-1 and IMP-10 and mutants IMP-1-V67A and IMP-1-V67I were characterized biophysically and biochemically, and MICs for Escherichia coli cells expressing these enzymes were determined. We found that all variants exhibited catalytic efficiencies ( k cat / K m ) equal to or higher than that of IMP-1 against all tested β-lactams except penicillins, against which IMP-1 and IMP-1-V67I showed the highest k cat / K m values. The substrate-specific effects of the different amino acid substitutions at position 67 are discussed in light of their side chain structures and possible interactions with the substrates. Docking calculations were employed to investigate interactions between different side chains and an inhibitor used as a β-lactam surrogate. The differences in binding affinities determined experimentally and computationally seem to be governed by hydrophobic interactions between residue 67 and the inhibitor and, by inference, the β-lactam substrates.

The systemic effects of traditional Chinese medicine (TCM) seem to be a Gordian knot, impossible to untie for decades. With the advent of transcriptomics, a useful sword is provided to cut the knot and shed some light on complex bioprocesses and intrinsic connections among them. Here, we revisit studies on TCM ZHENGs using this approach, highlight its applications on elucidating the potential scientific basis of ZHENG and investigating mechanisms of action for the TCM formula, and demonstrating its unique role in novel TCM drug design and discovery through active ingredient detection from TCM and compatibility theory study of TCM. The limitations and future perspectives of transcriptomics approaches to TCM study are also discussed.

Summary Recent advancements in single-cell RNA sequencing (scRNA-seq) have facilitated the classification of thousands of cells through transcriptome profiling, wherein accurate cell type identification is critical for mechanistic studies. In most current analysis protocols, cell type-based cluster annotation is manually performed and heavily relies on prior knowledge, resulting in poor replicability of cell type annotation. This study aimed to introduce a single-cell Cluster-based Automatic Annotation Toolkit for Cellular Heterogeneity (scCATCH, https://github.com/ZJUFanLab/scCATCH). Using three benchmark datasets, the feasibility of evidence-based scoring and tissue-specific cellular annotation strategies were demonstrated by high concordance among cell types, and scCATCH outperformed Seurat, a popular method for marker genes identification, and cell-based annotation methods. Furthermore, scCATCH accurately annotated 67%–100% (average, 83%) clusters in six published scRNA-seq datasets originating from various tissues. The present results show that scCATCH accurately revealed cell identities with high reproducibility, thus potentially providing insights into mechanisms underlying disease pathogenesis and progression., Graphical Abstract, Highlights • Construction of a comprehensive tissue-specific reference database of cell markers • Paired comparisons to identify potential marker genes for clusters to ensure accuracy • Evidence-based scoring and annotation for clustered cells from scRNA-seq data • Accurate and replicable annotation on cell types of clusters without prior knowledge, Quantitative Genetics; Cell Biology; Bioinformatics; Automation in Bioinformatics

The inception of network pharmacology comes from the advance in “multi-target, multi-drug” paradigm and opens up a new field for pharmaceutical science. Traditional Chinese medicine (TCM) is well-known for its use of medicinal herb combinations to treat the functional disorders induced by diseases through a holistic view, which naturally followed the principal of network pharmacology. In this review, the methodologies of network pharmacology in TCM studies were summarized. Specifically, the methodologies for network construction and network analysis were discussed in detail by following several TCM study cases. The perspectives for TCM network pharmacology were also provided.

Current chemical markers based quality assessment methods largely fail to reflect intrinsic chemical complexity and multiple mechanisms of action of botanical drugs (BD). The development of novel quality markers is greatly needed. Here we propose bioactive chemical markers (BCM), defined as a group of chemo-markers that exhibit similar pharmacological activities comparable to the whole BD, which can therefore be used to effectively assess the quality of BD. As a proof-of-concept, a BCM-based strategy was developed and applied to Xuesaitong Injection (XST) for assessing the efficacy and consistency of different batches. Firstly, systemic characterization of chemical profile of XST revealed a total number of 97 compounds. Secondly, notoginsenoside R1, ginsenoside Rg1, Re, Rb1 and Rd were identified as BCM of XST on treating cardiovascular and cerebrovascular diseases according to Adjusted Efficacy Score following an in vivo validation. Analytical method for quantification of BCM was then developed to ensure the efficacy of XST. Finally, chemical fingerprinting was developed and used to evaluate the batch-to-batch consistency. Our present case study on XST demonstrates that BCM-based strategy offers a rational approach for quality assessment of BD and provides a workflow for chemistry, manufacturing, and controls (CMC) study of BD required by regulatory authority.

In silico modeling of blood-brain barrier (BBB) permeability plays an important role in early discovery of central nervous system (CNS) drugs due to its high-throughput and cost-effectiveness. Natural products (NP) have demonstrated considerable therapeutic efficacy against several CNS diseases. However, BBB permeation property of NP is scarcely evaluated both experimentally and computationally. It is well accepted that significant difference in chemical spaces exists between NP and synthetic drugs, which calls into doubt on suitability of available synthetic chemical based BBB permeability models for the evaluation of NP. Herein poor discriminative performance on BBB permeability of NP are first confirmed using internal constructed and previously published drug-derived computational models, which warrants the need for NP-oriented modeling. Then a quantitative structure-property relationship (QSPR) study on a NP dataset was carried out using four different machine learning methods including support vector machine, random forest, Naive Bayes and probabilistic neural network with 67 selected features. The final consensus model was obtained with approximate 90% overall accuracy for the cross-validation study, which is further taken to predict passive BBB permeability of a large dataset consisting of over 10,000 compounds from traditional Chinese medicine (TCM). For 32 selected TCM molecules, their predicted BBB permeability were evaluated by in vitro parallel artificial membrane permeability assay and overall accuracy for in vitro experimental validation is around 81%. Interestingly, our in silico model successfully predicted different BBB permeation potentials of parent molecules and their known in vivo metabolites. Finally, we found that the lipophilicity, the number of hydrogen bonds and molecular polarity were important molecular determinants for BBB permeability of NP. Our results suggest that the consensus model proposed in current work is a reliable tool for prioritizing potential CNS active NP across the BBB, which would accelerate their development and provide more understanding on their mechanisms, especially those with pharmacologically active metabolites.

Quality control is critical for ensuring the safety and effectiveness of drugs. Current quality control method for botanical drugs is mainly based on chemical testing. However, chemical testing alone may not be sufficient as it may not capture all constituents of botanical drugs. Therefore, it is necessary to establish a bioassay correlating with the drug’s known mechanism of action to ensure its potency and activity. Herein we developed a multiple biomarker assay to assess the quality of botanicals using microfluidics, where enzyme inhibition was employed to indicate the drug’s activity and thereby evaluate biological consistency. This approach was exemplified on QiShenYiQi Pills using thrombin and angiotensin converting enzyme as “quality biomarkers”. Our results demonstrated that there existed variations in potency across different batches of the intermediates and preparations. Compared with chromatographic fingerprinting, the bioassay provided better discrimination ability for some abnormal samples. Moreover, the chip could function as “affinity chromatography” to identify bioactive phytochemicals bound to the enzymes. This work proposed a multiple-biomarker strategy for quality assessment of botanical drugs, while demonstrating for the first time the feasibility of microfluidics in this field.

Carbapenems can be an effective treatment of infections with multidrug-resistant Gram-negative bacteria such as Pseudomonas aeruginosa,1 Acinetobacter spp.,2 Klebsiella pneumoniae,3 and other Enterobacteriaceae.4 They are semi-synthetic or synthetic β-lactam compounds that are distinguished from other β-lactam compounds such as penicillins and cephalosporins by the absence of a sulfur atom in the bicyclic core and a different stereochemistry at Cα of the β-lactam ring (in penicillins and carbapenems, this atom is usually referred to as C6; in cephalosporins as C7) (Figure 1). The most popular carbapenem antibiotics are imipenem5, 6 (Merck, 1985), meropenem7, 8 (Sumitomo Pharmaceuticals and AstraZeneca, 1996), ertapenem9, 10 (Merck, 2005), and doripenem11, 12 (Shionogi Co. and Johnson & Johnson, 2005) (Figure 2). All of these broad-spectrum drugs are used intravenously. Carbapenems are considered to be drugs of last resort due to the fact that they are not inactivated by and effectively inhibit many β-lactamases (most Ambler class A and C β-lactamases13), while these enzymes efficiently hydrolyze penicillins and cephalosporins. β-Lactamases hydrolyze the β-lactam ring of β-lactam antibiotics blocking peptidyltransferase (also referred to as penicillin binding protein or PBP) activity that is critical for the peptidoglycan biosynthesis of the bacterial cell wall.14 β-Lactam antibiotics inhibit peptidyltransferase by forming a stable acyl-enzyme intermediate after an active-site serine of pepdityltransferase cleaves the β-lactam ring through a nucleophilic attack.15 Similar to peptidyltransferase, most β-lactamases contain an active site serine, which exerts a nucleophilic attack on and cleaves the β-lactam ring, resulting in turnover by the enzyme. These enzymes are referred to as serine β-lactamases (SBLs) and, based on sequence and structural homology, have been grouped into classes A, C, and D by Ambler.13 CTX-M β-lactamases are a group of class A SBLs expressed by Enterobacteriaceae that confer resistance toward the third-generation cephalosporin cefotaxime (Figure 3).16 As a consequence, carbapenems are frequently used to treat infections with Enterobacteriaceae expressing these enzymes. The increased use of carbapenems drives the emergence of carbapenem resistance mechanisms. Open in a separate window Figure 1 Chemical structures of the bicyclic cores of different classes of β-lactam antibiotics. The penem core is found in penicillins and consists of a β-lactam ring fused with a tetrahydrodrothiazole ring. The cephem core is found in cephalosporins and consists of a β-lactam ring fused with a dihydrothiazine ring. The carbapenem core consists of a β-lactam ring fused with a dihydropyrrole ring. Heavy atoms of the bicyclic systems are numbered according to common use rather than according to the IUPAC nomenclature to facilitate comparisons between the different antibiotics. Note that the numbering of the R groups is arbitrary; here we started labeling R groups from the ones attached to the core atoms with the lowest number.

Bile salts, the major end metabolites of cholesterol, vary significantly in structure across vertebrate species, suggesting that nuclear receptors binding these molecules may show adaptive evolutionary changes. We compared across species the bile salt specificity of the major transcriptional regulator of bile salt synthesis, the farnesoid X receptor (FXR). We found that FXRs have changed specificity for primary bile salts across species by altering the shape and size of the ligand binding pocket. In particular, the ligand binding pockets of sea lamprey (Petromyzon marinus) and zebrafish (Danio rerio) FXRs, as predicted by homology models, are flat and ideal for binding planar, evolutionarily early bile alcohols. In contrast, human FXR has a curved binding pocket best suited for the bent steroid ring configuration typical of evolutionarily more recent bile acids. We also found that the putative FXR from the sea squirt Ciona intestinalis, a chordate invertebrate, was completely insensitive to activation by bile salts but was activated by sulfated pregnane steroids, suggesting that the endogenous ligands of this receptor may be steroidal in nature. Our observations present an integrated picture of the coevolution of bile salt structure and of the binding pocket of their target nuclear receptor FXR.

Liver X receptors (LXRs) are key regulators of lipid and cholesterol metabolism in mammals. Little is known, however, about the function and evolution of LXRs in non-mammalian species. The present study reports the cloning of LXRs from African clawed frog (Xenopus laevis), Western clawed frog (Xenopus tropicalis), and zebrafish (Danio rerio), and their functional characterization and comparison with human and mouse LXRs. Additionally, an ortholog of LXR in the chordate invertebrate Ciona intestinalis was cloned and functionally characterized. Ligand specificities of the frog and zebrafish LXRs were very similar to LXRalpha and LXRbeta from human and mouse. All vertebrate LXRs studied were activated robustly by the synthetic ligands T-0901317 and GW3965 and by a variety of oxysterols. In contrast, Ciona LXR was not activated by T-0901317 or GW3965 but was activated by a limited number of oxysterols, as well as some androstane and pregnane steroids. Pharmacophore analysis, homology modeling, and docking studies of Ciona LXR predict a receptor with a more restricted ligand-binding pocket and less intrinsic disorder in the ligand-binding domain compared to vertebrate LXRs. The results suggest that LXRs have a long evolutionary history, with vertebrate LXRs diverging from invertebrate LXRs in ligand specificity.

Human serum albumin (HSA) binding is one of important pharmacokinetic properties of drug, which is closely related to in vivo distribution and may ultimately influence its clinical efficacy. Compared to conventional drug, limited information on this transportation process is available for medicinal herbs, which significantly hampers our understanding on their pharmacological effects, particularly when herbs and drug are co-administrated as polytherapy to the ailment. Several lines of evidence suggest the existence of Salvia miltiorrhiza-Warfarin interaction. Since Warfarin is highly HSA bound in the plasma with selectivity to site I, it is critical to evaluate the possibility of HSA-related herb-drug interaction. Herein an integrated approach was employed to analyze the binding of chemicals identified in S. miltiorrhiza to HSA. Molecular docking simulations revealed filtering criteria for HSA site I compounds that include docking score and key molecular determinants for binding. For eight representative ingredients from the herb, their affinity and specificity to HSA site I was measured and confirmed fluorometrically, which helps to improve the knowledge of interaction mechanisms between this herb and HSA. Our results indicated that several compounds in S. miltiorrhiza were capable of decreasing the binding constant of Warfarin to HSA site I significantly, which may increase free drug concentration in vivo, contributing to the herb-drug interaction observed clinically. Furthermore, the significance of HSA mediated herb-drug interactions was further implied by manual mining on the published literatures on S. miltiorrhiza.

Drug repositioning strategies were employed to explore new therapeutic indications for existing drugs that may exhibit dual negative mGluR1/5 modulating activities as potential treatments for neuropathic pain. A customized in silico-in vitro-in vivo drug repositioning scheme was assembled and implemented to search available drug libraries for compounds with dual mGluR1/5 antagonistic activities, that were then evaluated using in vitro functional assays and, for validated hits, in an established animal model for neuropathic pain. Tizoxanide, the primary active metabolite of the FDA approved drug nitazoxanide, fit in silico pharmacophore models constructed for both mGluR1 and mGluR5. Subsequent calcium (Ca++) mobilization functional assays confirmed that tizoxanide exhibited appreciable antagonist activity for both mGluR1 and mGluR5 (IC50 = 1.8 μM and 1.2 μM, respectively). The in vivo efficacy of nitazoxanide administered by intraperitoneal injection was demonstrated in a rat model for neuropathic pain. The major aim of the present study was to demonstrate the utility of an in silico-in vitro-in vivo drug repositioning protocol to facilitate the repurposing of approved drugs for new therapeutic indications. As an example, this particular investigation successfully identified nitazoxanide and its metabolite tizoxanide as dual mGluR1/5 negative modulators. A key finding is the vital importance for drug screening libraries to include the structures of drug active metabolites, such as those emanating from prodrugs which are estimated to represent 5–7% of marketed drugs.

Human immunodeficiency virus (HIV) protease inhibitors (PIs) have been used successfully in extending the life span of people infected with HIV. The use of PIs has also been associated with dyslipidemia and an increased risk of cardiovascular disease, but the underlying mechanisms remain elusive. Several PIs have been implicated in activating the nuclear receptor pregnane X receptor (PXR), which acts as a xenobiotic sensor to regulate xenobiotic metabolism in the liver and intestine. Recent studies indicate that PXR may also play an important role in the regulation of lipid homeostasis. In the present study, we identified amprenavir, a widely used HIV PI, as a potent PXR-selective agonist. Computational docking studies combined with site-direct mutagenesis identified several key residues within the ligand-binding pocket of PXR that constitute points of interaction with amprenavir. Amprenavir efficiently activated PXR and induced PXR target gene expression in vitro and in vivo. Short-term exposure to amprenavir significantly increased plasma total cholesterol and atherogenic low-density lipoprotein cholesterol levels in wild-type mice, but not in PXR-deficient mice. Amprenavir-mediated PXR activation stimulated the expression of several key intestinal genes involved in lipid homeostasis. These findings provide critical mechanistic insight for understanding the impact of PIs on cardiovascular disease and demonstrate a potential role of PXR in mediating the adverse effects of HIV PIs in humans.

The pregnane X receptor (PXR) is an important transcriptional regulator of the expression of xenobiotic metabolism and transporter genes. The receptor is promiscuous, binding many structural classes of molecules that act as agonists at the ligand-binding domain, triggering up-regulation of genes, increasing the metabolism and excretion of therapeutic agents, and causing drug-drug interactions. It has been suggested that human PXR antagonists represent a means to counteract such interactions. Several azoles have been hypothesized to bind the activation function-2 (AF-2) surface on the exterior of PXR when agonists are concurrently bound in the ligand-binding domain. In the present study, we have derived novel computational models for PXR agonists using different series of imidazoles, steroids, and a set of diverse molecules with experimental PXR agonist binding data. We have additionally defined a novel pharmacophore for the steroidal agonist site. All agonist pharmacophores showed that hydrophobic features are predominant. In contrast, a qualitative comparison with the corresponding PXR antagonist pharmacophore models using azoles and biphenyls showed that they are smaller and hydrophobic with increased emphasis on hydrogen bonding features. Azole antagonists were docked into a proposed hydrophobic binding pocket on the outer surface at the AF-2 site and fitted comfortably, making interactions with key amino acids involved in charge clamping. Combining computational and experimental data for different classes of molecules provided strong evidence for agonists and antagonists binding distinct regions on PXR. These observations bear significant implications for future discovery of molecules that are more selective and potent antagonists.

The physiological roles of estrogen in sexual differentiation and development, female and male reproductive processes, and bone health are complex and diverse. Numerous natural and synthetic chemical compounds, commonly known as endocrine disrupting chemicals (EDCs), have been shown to alter the physiological effects of estrogen in humans and wildlife. As such, these EDCs may cause unanticipated and even undesirable effects. Large-scale in vitro and in vivo screening of chemicals to assess their estrogenic activity would demand a prodigious investment of time, labor, and money and would require animal testing on an unprecedented scale. Approaches in silico are increasingly recognized as playing a vital role in screening and prioritizing chemicals to extend limited resources available for experimental testing. Here, we evaluated a multistep procedure that is suitable for in silico (virtual) screening of large chemical databases to identify compounds exhibiting estrogenic activity. This procedure incorporates Shape Signatures, a novel computational tool that rapidly compares molecules on the basis of similarity in shape, polarity, and other bio-relevant properties. Using 4-hydroxy tamoxifen (4-OH TAM) and diethylstilbestrol (DES) as input queries, we employed this scheme to search a sample database of approximately 200,000 commercially available organic chemicals for matches (hits). Of the eight compounds identified computationally as potentially (anti)estrogenic, biological evaluation confirmed two as heretofore unknown estrogen antagonists. Subsequent radioligand binding assays confirmed that two of these three compounds exhibit antiestrogenic activities comparable to 4-OH TAM. Molecular modeling studies of these ligands docked inside the binding pocket of estrogen receptor alpha (ERalpha) elucidated key ligand-receptor interactions that corroborate these experimental findings. The present study demonstrates the utility of our computational scheme for this and related applications in drug discovery, predictive toxicology, and virtual screening.

Tyrosinase is the key enzyme involved in the human pigmentation process, as well as the undesired browning of fruits and vegetables. Compounds inhibiting tyrosinase catalytic activity are an important class of cosmetic and dermatological agents which show high potential as depigmentation agents used for skin lightening. The multi-step protocol employed for the identification of novel tyrosinase inhibitors incorporated the Shape Signatures computational algorithm for rapid screening of chemical libraries. This algorithm converts the size and shape of a molecule, as well its surface charge distribution and other bio-relevant properties, into compact histograms (signatures) that lend themselves to rapid comparison between molecules. Shape Signatures excels at scaffold hopping across different chemical families, which enables identification of new actives whose molecular structure is distinct from other known actives. Using this approach, we identified a novel class of depigmentation agents that demonstrated promise for skin lightening product development.

In the present study, values of the binding energy (BE) were calculated for the rat androgen receptor on a data set of 25 steroidal and nonsteroidal compounds for which published values of the observed binding affinity (K(i)) are available. A correlation between BE and pK(i) was evident (r(2) = 0.50) for the entire data set and became more pronounced when the steroids and nonsteroids were plotted separately (r(2) congruent with 0.76). Including BE as an additional descriptor to supplement the default steric-electrostatic descriptors in comparative molecular field analysis dramatically improved the predictive ability of the resulting three-dimensional quantitative structure-activity relationship models. We also demonstrate that the observed loss in ligand specificity between the wild-type (wt) AR and the T877A mutant AR associated with androgen-independent prostate cancer is reflected in decreased BE values (i.e., higher binding affinity) for the antiandrogen pharmaceutical hydroxyflutamide and for several nonandrogenic endogenous steroids, most notably cortisol, corticosterone, 17beta-estradiol, progesterone, and 17alpha-hydroxyprogesterone.

Background The farnesoid X receptor (FXR), pregnane X receptor (PXR), and vitamin D receptor (VDR) are three closely related nuclear hormone receptors in the NR1H and 1I subfamilies that share the property of being activated by bile salts. Bile salts vary significantly in structure across vertebrate species, suggesting that receptors binding these molecules may show adaptive evolutionary changes in response. We have previously shown that FXRs from the sea lamprey (Petromyzon marinus) and zebrafish (Danio rerio) are activated by planar bile alcohols found in these two species. In this report, we characterize FXR, PXR, and VDR from the green-spotted pufferfish (Tetraodon nigriviridis), an actinopterygian fish that unlike the zebrafish has a bile salt profile similar to humans. We utilize homology modelling, docking, and pharmacophore studies to understand the structural features of the Tetraodon receptors. Results Tetraodon FXR has a ligand selectivity profile very similar to human FXR, with strong activation by the synthetic ligand GW4064 and by the primary bile acid chenodeoxycholic acid. Homology modelling and docking studies suggest a ligand-binding pocket architecture more similar to human and rat FXRs than to lamprey or zebrafish FXRs. Tetraodon PXR was activated by a variety of bile acids and steroids, although not by the larger synthetic ligands that activate human PXR such as rifampicin. Homology modelling predicts a larger ligand-binding cavity than zebrafish PXR. We also demonstrate that VDRs from the pufferfish and Japanese medaka were activated by small secondary bile acids such as lithocholic acid, whereas the African clawed frog VDR was not. Conclusions Our studies provide further evidence of the relationship between both FXR, PXR, and VDR ligand selectivity and cross-species variation in bile salt profiles. Zebrafish and green-spotted pufferfish provide a clear contrast in having markedly different primary bile salt profiles (planar bile alcohols for zebrafish and sterically bent bile acids for the pufferfish) and receptor selectivity that matches these differences in endogenous ligands. Our observations to date present an integrated picture of the co-evolution of bile salt structure and changes in the binding pockets of three nuclear hormone receptors across the species studied.