Tamoxifen has been used for many years to target estrogen receptor signalling in breast cancer cells. Tamoxifen is also an agonist of the G protein-coupled estrogen receptor (GPER), a GPCR ubiquitously expressed in tissues that mediates the acute response to estrogens. Here we report that tamoxifen promotes mechanical quiescence in hepatic stellate cells (HSCs), stromal fibroblast-like cells whose activation triggers and perpetuates liver fibrosis in hepatocellular carcinomas. This mechanical deactivation is mediated by the GPER/RhoA/myosin axis and induces YAP deactivation. We report that tamoxifen decreases the levels of hypoxia-inducible factor-1 alpha (HIF-1α) and the synthesis of extracellular matrix proteins through a mechanical mechanism that involves actomyosin-dependent contractility and mechanosensing of tissue stiffness. Our results implicate GPER-mediated estrogen signalling in the mechanosensory-driven activation of HSCs and put forward estrogenic signalling as an option for mechanical reprogramming of myofibroblast-like cells in the tumour microenvironment. Tamoxifen, with half a century of safe clinical use, might lead this strategy of drug repositioning.
Betulin (lup-20(29)-ene-3β, 28-diol) is a naturally occurring triterpene, which is found in substantial amounts from the outer bark of birch trees. A library of 51 structurally diverse semisynthetic betulin derivatives was screened against five bacterial strains, Enterobacter aerogenes, Escherichia coli, Enterococcus faecalis, Pseudomonas aeruginosa, Staphylococcus aureus and a fungal strain Candida albicans, using broth microdilution assays. Primary antimicrobial screening at 50 µM concentration led to the identification of five compounds showing antimicrobial properties (inhibition of growth by >70% against one or more microbial strains). According to the dose-response results, 28-O-(N-acetylanthraniloyl)betulin (compound 5) was the most active, showing MIC90 of 6.25 µM against two Gram-positive bacteria, E. faecalis and S. aureus. However, the activity of this compound was affected by albumin binding, which was demonstrated by the loss of activity in a host-pathogen co-culture assay as well as in the antibacterial assay in the presence of increased concentration of albumin. Furthermore, the effects on mammalian cells were evaluated by cytotoxicity assessment on hepatocyte cell culture after 24 h exposure to the compounds. Betulinic aldehyde (18), betulin-28-oxime (31) and hetero cycloadduct with acetoxy groups at carbon atoms 3 and 28 and ethyl substituent at the triazolo ring (43) displayed cytotoxicity towards hepatocytes, with IC50 values of 47, 25 and 16 µM, respectively. The IC50 value for 28-O-(N-acetylanthraniloyl)betulin (5) was 56 µM. The current study presents an insight into using betulin scaffold for developing derivatives with antibacterial potential, and furthermore the necessity of in-depth analysis of found actives through selectivity profiling and follow-up studies including in silico ADMET predictions.
ABCC2 is a transporter with key influence on liver and kidney pharmacokinetics. In order to explore the structure–activity relationships of compounds that modulate ABCC2, and by doing so gain insights into drug–drug interactions, we screened a library of 432 compounds for modulators of radiolabeled β-estradiol 17-(β-D-glucuronide) (EG) and fluorescent 2′,7′-dichlorofluorescin transport (CDCF) in membrane vesicles. Following the primary screen at 80 μM, dose–response curves were used to investigate in detail 86 compounds, identifying 16 low μM inhibitors and providing data about the structure–activity relationships in four series containing 19, 24, 10, and eight analogues. Measurements with the CDCF probe were consistently more robust than for the EG probe. Only one compound was clearly probe-selective with 50-fold difference in the IC50s obtained by the two assays. We built 24 classification models using the SVM and fused-XY Kohonen methods, revealing molecular descriptors related to number of rings, solubility and lipophilicity as important to distinguish inhibitors from inactive compounds. This study is to our best knowledge the first to provide details about structure–activity relationships in ABCC2 modulation.
We developed a computational workflow to mine the Protein Data Bank for isosteric replacements that exist in different binding site environments but have not necessarily been identified and exploited in compound design. Taking phosphate groups as examples, the workflow was used to construct 157 data sets, each composed of a reference protein complexed with AMP, ADP, ATP, or pyrophosphate as well other ligands. Phosphate binding sites appear to have a high hydration content and large size, resulting in U-shaped bioactive conformations recurrently found across unrelated protein families. A total of 16 413 replacements were extracted, filtered for a significant structural overlap on phosphate groups, and sorted according to their SMILES codes. In addition to the classical isosteres of phosphate, such as carboxylate, sulfone, or sulfonamide, unexpected replacements that do not conserve charge or polarity, such as aryl, aliphatic, or positively charged groups, were found.
Numerous methods are available for use as part of a virtual screening strategy but, as yet, no single method is able to guarantee both a level of confidence comparable to experimental screening and a level of computing efficiency that could drastically cut the costs of early phase drug discovery campaigns. Here, we present VSM-G (virtual screening manager for computational grids), a virtual screening platform that combines several structure-based drug design tools. VSM-G aims to be as user-friendly as possible while retaining enough flexibility to accommodate other in silico techniques as they are developed. In order to illustrate VSM-G concepts, we present a proof-of-concept study of a fast geometrical matching method based on spherical harmonics expansions surfaces. This technique is implemented in VSM-G as the first module of a multiple-step sequence tailored for high-throughput experiments. We show that, using this protocol, notable enrichment of the input molecular database can be achieved against a specific target, here the liver-X nuclear receptor. The benefits, limitations and applicability of the VSM-G approach are discussed. Possible improvements of both the geometrical matching technique and its implementation within VSM-G are suggested.
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