DrugCentral 2023 extends human clinical data and integrates veterinary drugs.

DrugCentral monitors new drug approvals and standardizes drug information. The current update contains 285 drugs (131 for human use). New additions include: (i) the integration of veterinary drugs (154 for animal use only), (ii) the addition of 66 documented off-label uses and iii) the identification of adverse drug events from pharmacovigilance data for pediatric and geriatric patients. Additional enhancements include chemical substructure searching using SMILES and 'Target Cards' based on UniProt accession codes. Statistics of interests include the following: (i) 60% of the covered drugs are on-market drugs with expired patent and exclusivity coverage, 17% are off-market, and 23% are on-market drugs with active patents and exclusivity coverage; (ii) 59% of the drugs are oral, 33% are parenteral and 18% topical, at the level of the active ingredients; (iii) only 3% of all drugs are for animal use only; however, 61% of the veterinary drugs are also approved for human use; (iv) dogs, cats and horses are by far the most represented target species for veterinary drugs; (v) the physicochemical property profile of animal drugs is very similar to that of human drugs. Use cases include azaperone, the only sedative approved for swine, and ruxolitinib, a Janus kinase inhibitor.

Exploring DrugCentral: from molecular structures to clinical effects.

DrugCentral, accessible at https://drugcentral.org , is an open-access online drug information repository. It covers over 4950 drugs, incorporating structural, physicochemical, and pharmacological details to support drug discovery, development, and repositioning. With around 20,000 bioactivity data points, manual curation enhances information from several major digital sources. Approximately 724 mechanism-of-action (MoA) targets offer updated drug target insights. The platform captures clinical data: over 14,300 on- and off-label uses, 27,000 contraindications, and around 340,000 adverse drug events from pharmacovigilance reports. DrugCentral encompasses information from molecular structures to marketed formulations, providing a comprehensive pharmaceutical reference. Users can easily navigate basic drug information and key features, making DrugCentral a versatile, unique resource. Furthermore, we present a use-case example where we utilize experimentally determined data from DrugCentral to support drug repurposing. A minimum activity threshold t should be considered against novel targets to repurpose a drug. Analyzing 1156 bioactivities for human MoA targets suggests a general threshold of 1 µM: t = 6 when expressed as - log[Activity(M)]). This applies to 87% of the drugs. Moreover, t can be refined empirically based on water solubility (S): t = 3 - logS, for logS < - 3. Alongside the drug repurposing classification scheme, which considers intellectual property rights, market exclusivity protections, and market accessibility, DrugCentral provides valuable data to prioritize candidates for drug repurposing programs efficiently.

DrugCentral 2021 supports drug discovery and repositioning.

DrugCentral is a public resource (http://drugcentral.org) that serves the scientific community by providing up-to-date drug information, as described in previous papers. The current release includes 109 newly approved (October 2018 through March 2020) active pharmaceutical ingredients in the US, Europe, Japan and other countries; and two molecular entities (e.g. mefuparib) of interest for COVID19. New additions include a set of pharmacokinetic properties for ∼1000 drugs, and a sex-based separation of side effects, processed from FAERS (FDA Adverse Event Reporting System); as well as a drug repositioning prioritization scheme based on the market availability and intellectual property rights forFDA approved drugs. In the context of the COVID19 pandemic, we also incorporated REDIAL-2020, a machine learning platform that estimates anti-SARS-CoV-2 activities, as well as the 'drugs in news' feature offers a brief enumeration of the most interesting drugs at the present moment. The full database dump and data files are available for download from the DrugCentral web portal.

Pharmacology and Molecular Mechanisms of Clinically Relevant Estrogen Estetrol and Estrogen Mimic BMI-135 for the Treatment of Endocrine-Resistant Breast Cancer.

Long-term estrogen deprivation (LTED) with tamoxifen (TAM) or aromatase inhibitors leads to endocrine-resistance, whereby physiologic levels of estrogen kill breast cancer (BC). Estrogen therapy is effective in treating patients with advanced BC after resistance to TAM and aromatase inhibitors develops. This therapeutic effect is attributed to estrogen-induced apoptosis via the estrogen receptor (ER). Estrogen therapy can have unpleasant gynecologic and nongynecologic adverse events. Here, we study estetrol (E4) and a model Selective Human ER Partial Agonist (ShERPA) BMI-135. Estetrol and ShERPA TTC-352 are being evaluated in clinical trials. These agents are proposed as safer estrogenic candidates compared with 17ß-estradiol (E2) for the treatment of endocrine-resistant BC. Cell viability assays, real-time polymerase chain reaction, luciferase reporter assays, chromatin immunoprecipitation, docking and molecular dynamics simulations, human unfolded protein response (UPR) RT2 PCR profiler arrays, live cell microscopic imaging and analysis, and annexin V staining assays were conducted. Our work was done in eight biologically different human BC cell lines and one human endometrial cancer cell line, and results were compared with full agonists estrone, E2, and estriol, a benchmark partial agonist triphenylethylene bisphenol (BPTPE), and antagonists 4-hydroxytamoxifen and endoxifen. Our study shows the pharmacology of E4 and BMI-135 as less-potent full-estrogen agonists as well as their molecular mechanisms of tumor regression in LTED BC through triggering a rapid UPR and apoptosis. Our work concludes that the use of a full agonist to treat BC is potentially superior to a partial agonist given BPTPE's delayed induction of UPR and apoptosis, with a higher probability of tumor clonal evolution and resistance. SIGNIFICANCE STATEMENT: Given the unpleasant gynecologic and nongynecologic adverse effects of estrogen treatment, the development of safer estrogens for endocrine-resistant breast cancer (BC) treatment and hormone replacement therapy remains a priority. The naturally occurring estrogen estetrol and Selective Human Estrogen-Receptor Partial Agonists are being evaluated in endocrine-resistant BC clinical trials. This work provides a comprehensive evaluation of their pharmacology in numerous endocrine-resistant BC models and an endometrial cancer model and their molecular mechanisms of tumor regression through the unfolded protein response and apoptosis.

The Structure-Function Relationship of Angular Estrogens and Estrogen Receptor Alpha to Initiate Estrogen-Induced Apoptosis in Breast Cancer Cells.

High-dose synthetic estrogen therapy was the standard treatment of advanced breast cancer for three decades until the discovery of tamoxifen. A range of substituted triphenylethylene synthetic estrogens and diethylstilbestrol were used. It is now known that low doses of estrogens can cause apoptosis in long-term estrogen deprived (LTED) breast cancer cells resistant to antiestrogens. This action of estrogen can explain the reduced breast cancer incidence in postmenopausal women over 60 who are taking conjugated equine estrogens and the beneficial effect of low-dose estrogen treatment of patients with acquired aromatase inhibitor resistance in clinical trials. To decipher the molecular mechanism of estrogens at the estrogen receptor (ER) complex by different types of estrogens-planar [17ß-estradiol (E2)] and angular triphenylethylene (TPE) derivatives-we have synthesized a small series of compounds with either no substitutions on the TPE phenyl ring containing the antiestrogenic side chain of endoxifen or a free hydroxyl. In the first week of treatment with E2 the LTED cells undergo apoptosis completely. By contrast, the test TPE derivatives act as antiestrogens with a free para-hydroxyl on the phenyl ring that contains an antiestrogenic side chain in endoxifen. This inhibits early E2-induced apoptosis if a free hydroxyl is present. No substitution at the site occupied by the antiestrogenic side chain of endoxifen results in early apoptosis similar to planar E2 The TPE compounds recruit coregulators to the ER differentially and predictably, leading to delayed apoptosis in these cells. SIGNIFICANCE STATEMENT: In this paper we investigate the role of the structure-function relationship of a panel of synthetic triphenylethylene (TPE) derivatives and a novel mechanism of estrogen-induced cell death in breast cancer, which is now clinically relevant. Our study indicates that these TPE derivatives, depending on the positioning of the hydroxyl groups, induce various conformations of the estrogen receptor's ligand-binding domain, which in turn produces differential recruitment of coregulators and subsequently different apoptotic effects on the antiestrogen-resistant breast cancer cells.

Off-Patent Drug Repositioning.

Drug repositioning aims to reuse "old" drugs to treat diseases outside their approved indication(s). Composition-of-matter patents and FDA exclusivities can hinder the immediate availability of some drugs to be repositioned (repurposed). Here, we analyze data from the FDA Orange Book and use current on-market patent validity and exclusivities to classify drugs into on-patent (ONP), off-patent (OFP), and off-market (OFM) sets. In the absence of an unanimously accepted definition for small molecules, these sets include organic molecules and peptides with molecular weight between 100 and 1250, which resulted in 237 ONP drugs, 320 OFM, and 996 OFP drugs, respectively. We discuss the differences between the three categories in terms of primary molecular properties, chemical diversity, mechanism-of-action target classes, and therapeutic areas and comment on the enrichment of OFP drugs in the near future. Given the intellectual property landscape, and in the absence of specific property rights, we suggest that drugs should be prioritized as follows, to improve the repositioning strategy: (i) OFP, (ii) OFM, and (iii) ONP, respectively.

Endoxifen, 4-Hydroxytamoxifen and an Estrogenic Derivative Modulate Estrogen Receptor Complex Mediated Apoptosis in Breast Cancer.

Estrogen therapy was used to treat advanced breast cancer in postmenopausal women for decades until the introduction of tamoxifen. Resistance to long-term estrogen deprivation (LTED) with tamoxifen and aromatase inhibitors used as a treatment of breast cancer inevitably occurs, but unexpectedly low-dose estrogen can cause regression of breast cancer and increase disease-free survival in some patients. This therapeutic effect is attributed to estrogen-induced apoptosis in LTED breast cancer. Here, we describe modulation of the estrogen receptor (ER) liganded with antiestrogens (endoxifen and 4-hydroxytamoxifen) and an estrogenic triphenylethylene (TPE), ethoxytriphenylethylene (EtOXTPE), on estrogen-induced apoptosis in LTED breast cancer cells. Our results show that the angular TPE estrogen (EtOXTPE) is able to induce the ER-mediated apoptosis only at a later time compared with planar estradiol in these cells. Using real-time polymerase chain reaction, chromatin immunoprecipitation, western blotting, molecular modeling, and X-ray crystallography techniques, we report novel conformations of the ER complex with an angular estrogen EtOXTPE and endoxifen. We propose that alteration of the conformation of the ER complexes, with changes in coactivator binding, governs estrogen-induced apoptosis through the protein kinase regulated by RNA-like endoplasmic reticulum kinase sensor system to trigger an unfolded protein response.

Enhancing Molecular Promiscuity Evaluation Through Assay Profiles.

PURPOSE: The growing amount of heterogeneous bioactivity data requires effective strategies to assess the promiscuity/selectivity of small-molecules and aid drug discovery. In the current study, we aim to evaluate the potential of assay profiles (APs, i.e., unique combinations of assay-related features describing how activity determinations were performed and reported) in molecular promiscuity analysis. METHODS: Using PubChem bioactivity data, we computed for all Molecular Libraries Small Molecule Repository (MLSMR library) compounds the frequency of hits score (FoH, i.e., the ratio between the number of times the compound was found active and the number of times it was tested), which were subsequently fit into 32 theoretical APs. The promiscuity of drugs and non-drugs was compared at different levels of test results. RESULTS: We found 8 dominant APs, indicating that compounds tested in more than ten assays (or against ten targets) and found active at least once tend to reach near to maximum hit rates in scientific literature and confirmatory assays (e.g., 95% of the drugs show FoH scores >0.93). Primary and high-throughput screening testing results in very low hit rates (e.g., 95% of the compounds show FoH scores <0.11), promoting a different perspective of promiscuity. In general, drugs exert higher promiscuity compared to non-drugs. Targets and classes of drugs are also discussed within the main APs. CONCLUSION: APs contain relevant features and are suited for big data promiscuity analysis. The activity data of the main APs are freely available on www.chembioinf.ro .

Modeling Kinase Inhibition Using Highly Confident Data Sets.

Protein kinases form a consistent class of promising drug targets, and several efforts have been made to predict the activities of small molecules against a representative part of the kinome. This study continues our previous work ( Bora , A. ; Avram , S. ; Ciucanu , I. ; Raica , M. ; Avram , S. Predictive Models for Fast and Effective Profiling of Kinase Inhibitors . J. Chem. Inf. MODEL: 2016 , 56 , 895 - 905 ; www.chembioinf.ro ) aiming to build and measure the performance of ligand-based kinase inhibitor prediction models. Here we analyzed kinase-inhibitor pairs with multiple activity points extracted from the ChEMBL database and identified the main sources of inconsistency. Our results indicate that lower IC50 values are usually less affected by errors and reflect more accurately the structure-activity relationship of the molecules against the target, ideally for quantitative structure-activity relationship studies. Further, we modeled the activities of 104 kinases using unbiased target-specific activity points. The performance of predictors built on extended connectivity fingerprints (ECFP4) and two-dimensional pharmacophore fingerprints (PFPs) are compared by means of tolerance intervals (TIs) (95%/95%) in virtual screening (VS) and classification tasks using external random ( RandSets) and diversity-based ( DivSets) test sets. We found that the two encodings perform superior to each other on different kinases in VS and that PFP models perform consistently better in classifying actives (higher sensitivity). Next, we combined the two encodings into a single one (PFPECFP) and demonstrated that especially in VS (as indicated by the exponential receiver operating curve enrichment metric (eROCE)), for the vast majority of kinases the model performance increased compared with the individual fingerprint models. These findings are highlighted in the more challenging DivSets compared with RandSets. The current paper explores the boundaries of inhibitor predictors for individual kinases to enhance VS and ultimately aid the discovery of novel compounds with desirable polypharmacology.

CHEMICAL AND BIOLOGICAL DESCRIPTOR INTEGRATION IMPROVES COMPUTATIONAL MODELING OF IN VIVO RAT TOXICITY.

Computational toxicology is a new discipline in the area of computational molecular sciences, which is rapidly developing as a result of the public interest stirred by several European and US initiatives. Here, we report the use of primary high throughput screening (HTS) data as biological descriptors to complement the chemical descriptors for the modelling of the acute toxicity. The combination of biological and chemical descriptors was performed on the median lethal dose following oral administration in rats (rat LD50). The hybrid model developed based on chemical and biological descriptors is superior to models based on the chemical or biological description alone. Using this model, besides the accurately prediction of a compound's toxicity we also identified molecular fragments whose presence may contribute to increase or decrease of the toxicity.

Defining the conformation of the estrogen receptor complex that controls estrogen-induced apoptosis in breast cancer.

Development of acquired antihormone resistance exposes a vulnerability in breast cancer: estrogen-induced apoptosis. Triphenylethylenes (TPEs), which are structurally similar to 4-hydroxytamoxifen (4OHT), were used for mechanistic studies of estrogen-induced apoptosis. These TPEs all stimulate growth in MCF-7 cells, but unlike the planar estrogens they block estrogen-induced apoptosis in the long-term estrogen-deprived MCF7:5C cells. To define the conformation of the TPE:estrogen receptor (ER) complex, we employed a previously validated assay using the induction of transforming growth factor α (TGFα) mRNA in situ in MDA-MB 231 cells stably transfected with wild-type ER (MC2) or D351G ER mutant (JM6). The assays discriminate ligand fit in the ER based on the extremes of published crystallography of planar estrogens or TPE antiestrogens. We classified the conformation of planar estrogens or angular TPE complexes as "estrogen-like" or "antiestrogen-like" complexes, respectively. The TPE:ER complexes did not readily recruit the coactivator steroid receptor coactivator-3 (SRC3) or ER to the PS2 promoter in MCF-7 and MCF7:5C cells, and molecular modeling showed that they prefer to bind to the ER in an antagonistic fashion, i.e., helix 12 not sealing the ligand binding domain (LBD) effectively, and therefore reduce critical SRC3 binding. The fully activated ER complex with helix 12 sealing the LBD is suggested to be the appropriate trigger to initiate rapid estrogen-induced apoptosis.

Exploring the biological promiscuity of high-throughput screening hits through DFT calculations.

The goal of this study is the understanding of biologically promiscuous compounds (frequent hitters) in HTS outcomes through their chemical behavior estimated via reactivity descriptors. Chemical reactivity is often an undesirable property due to the lack in biological selectivity of compounds comprised in HTS libraries. In this study the reactivity indexes have been computed within the DFT formalism, at different levels of theory, for two classes of representative compounds compiled from PubChem database, one comprising frequent hitters and the second one comprising rare hitters (biologically more selective compounds). We found that frequent hitters exert increased reactivity, mainly due to their electrophilic character, compared to the more selective class of compounds.

ChemProt: a disease chemical biology database.

Systems pharmacology is an emergent area that studies drug action across multiple scales of complexity, from molecular and cellular to tissue and organism levels. There is a critical need to develop network-based approaches to integrate the growing body of chemical biology knowledge with network biology. Here, we report ChemProt, a disease chemical biology database, which is based on a compilation of multiple chemical-protein annotation resources, as well as disease-associated protein-protein interactions (PPIs). We assembled more than 700,000 unique chemicals with biological annotation for 30,578 proteins. We gathered over 2-million chemical-protein interactions, which were integrated in a quality scored human PPI network of 428,429 interactions. The PPI network layer allows for studying disease and tissue specificity through each protein complex. ChemProt can assist in the in silico evaluation of environmental chemicals, natural products and approved drugs, as well as the selection of new compounds based on their activity profile against most known biological targets, including those related to adverse drug events. Results from the disease chemical biology database associate citalopram, an antidepressant, with osteogenesis imperfect and leukemia and bisphenol A, an endocrine disruptor, with certain types of cancer, respectively. The server can be accessed at http://www.cbs.dtu.dk/services/ChemProt/.

Estrogen Receptor Complex to Trigger or Delay Estrogen-Induced Apoptosis in Long-Term Estrogen Deprived Breast Cancer.

Antiestrogen therapy of breast cancer has been a "gold standard" of treatment of estrogen receptor (ER)-positive breast cancer for decades. Resistance to antiestrogen therapy may develop, however, a vulnerability in long-term estrogen deprived (LTED) breast cancer cells was discovered. LTED breast cancer cells may undergo estrogen-induced apoptosis within a week of treatment with estrogen in vitro. This phenomenon has been also validated in vivo and in the clinic. The molecular ER-mediated mechanism of action of estrogen-induced apoptosis was deciphered, however, the relationship between the structure of estrogenic ligands and the activity of the ER in LTED breast cancer cells remained a mystery until recently. In this review we provide an overview of the structure-activity relationship of various estrogens with different chemical structures and the modulation of estrogen-induced apoptosis in LTED breast cancer cells resistant to antihormone therapy. We provide analysis of evidence gathered over more than a decade of structure-activity relationship studies by our group on the role of the change in the conformation of the estrogen receptor and the biological activities of different classes of estrogens and the receptor as well in LTED breast cancer.

The selective estrogen receptor modulator bazedoxifene inhibits hormone-independent breast cancer cell growth and down-regulates estrogen receptor α and cyclin D1.

Bazedoxifene (BZA) is a third-generation selective estrogen receptor modulator (SERM) that has been approved for the prevention and treatment of postmenopausal osteoporosis. It has antitumor activity; however, its mechanism of action remains unclear. In the present study, we characterized the effects of BZA and several other SERMs on the proliferation of hormone-dependent MCF-7 and T47D breast cancer cells and hormone-independent MCF-7:5C and MCF-7:2A cells and examined its mechanism of action in these cells. We found that all of the SERMs inhibited the growth of MCF-7, T47D, and MCF-7:2A cells; however, only BZA and fulvestrant (FUL) inhibited the growth of hormone-independent MCF-7:5C cells. Cell cycle analysis revealed that BZA and FUL induced G(1) blockade in MCF-7:5C cells; however, BZA down-regulated cyclin D1, which was constitutively overexpressed in these cells, whereas FUL suppressed cyclin A. Further analysis revealed that small interfering RNA knockdown of cyclin D1 reduced the basal growth of MCF-7:5C cells, and it blocked the ability of BZA to induce G(1) arrest in these cells. BZA also down-regulated estrogen receptor-α (ERα) protein by increasing its degradation and suppressing cyclin D1 promoter activity in MCF-7:5C cells. Finally, molecular modeling studies demonstrated that BZA bound to ERα in an orientation similar to raloxifene; however, a number of residues adopted different conformations in the induced-fit docking poses compared with the experimental structure of ERα-raloxifene. Together, these findings indicate that BZA is distinct from other SERMs in its ability to inhibit hormone-independent breast cancer cell growth and to regulate ERα and cyclin D1 expression in resistant cells.

A crowdsourcing evaluation of the NIH chemical probes.

Between 2004 and 2008, the US National Institutes of Health Molecular Libraries and Imaging initiative pilot phase funded 10 high-throughput screening centers, resulting in the deposition of 691 assays into PubChem and the nomination of 64 chemical probes. We crowdsourced the Molecular Libraries and Imaging initiative output to 11 experts, who expressed medium or high levels of confidence in 48 of these 64 probes.

Rapid Induction of the Unfolded Protein Response and Apoptosis by Estrogen Mimic TTC-352 for the Treatment of Endocrine-Resistant Breast Cancer.

Patients with long-term estrogen-deprived breast cancer, after resistance to tamoxifen or aromatase inhibitors develops, can experience tumor regression when treated with estrogens. Estrogen's antitumor effect is attributed to apoptosis via the estrogen receptor (ER). Estrogen treatment can have unpleasant gynecologic and nongynecologic adverse events; thus, the development of safer estrogenic agents remains a clinical priority. Here, we study synthetic selective estrogen mimics (SEM) BMI-135 and TTC-352, and the naturally occurring estrogen estetrol (E4), which are proposed as safer estrogenic agents compared with 17ß-estradiol (E2), for the treatment of endocrine-resistant breast cancer. TTC-352 and E4 are being evaluated in breast cancer clinical trials. Cell viability assays, real-time PCR, immunoblotting, ERE DNA pulldowns, mass spectrometry, X-ray crystallography, docking and molecular dynamic simulations, live cell imaging, and Annexin V staining were conducted in 11 biologically different breast cancer models. Results were compared with the potent full agonist E2, less potent full agonist E4, the benchmark partial agonist triphenylethylene bisphenol (BPTPE), and antagonists 4-hydroxytamoxifen and endoxifen. We report ERα's regulation and coregulators' binding profiles with SEMs and E4 We describe TTC-352's pharmacology as a weak full agonist and antitumor molecular mechanisms. This study highlights TTC-352's benzothiophene scaffold that yields an H-bond with Glu353, which allows Asp351-to-helix 12 (H12) interaction, sealing ERα's ligand-binding domain, recruiting E2-enriched coactivators, and triggering rapid ERα-induced unfolded protein response (UPR) and apoptosis, as the basis of its anticancer properties. BPTPE's phenolic OH yields an H-Bond with Thr347, which disrupts Asp351-to-H12 interaction, delaying UPR and apoptosis and increasing clonal evolution risk.

Highly efficient synthesis and characterization of the GPR30-selective agonist G-1 and related tetrahydroquinoline analogs.

The GPR30 agonist probe G-1 and structural analogs were efficiently synthesized using multicomponent or stepwise Sc(III)-catalyzed aza-Diels-Alder cyclization. Optimization of solvent and reaction temperature provided enhanced endo-diastereoselectivity.

Detection of intracellular granularity induction in prostate cancer cell lines by small molecules using the HyperCyt high-throughput flow cytometry system.

Prostate cancer is a leading cause of death among men due to the limited number of treatment strategies available for advanced disease. Discovery of effective chemotherapeutics involves the identification of agents that inhibit cancer cell growth. Increases in intracellular granularity have been observed during physiological processes that include senescence, apoptosis, and autophagy, making this phenotypic change a useful marker for identifying small molecules that induce cellular growth arrest or death. In this regard, epithelial-derived cancer cell lines appear uniquely susceptible to increased intracellular granularity following exposure to chemotherapeutics. We have established a novel flow cytometry approach that detects increases in side light scatter in response to morphological changes associated with intracellular granularity in the androgen-sensitive LNCaP and androgen-independent PC3 human prostate cancer cell lines. A cell-based assay was developed to screen for small molecule inducers of intracellular granularity using the HyperCyt high-throughput flow cytometry platform. Validation was performed using the Prestwick Chemical Library, where known modulators of LNCaP intracellular granularity, such as testosterone, were identified. Nonandrogenic inducers of granularity were also detected. A further screen of approximately 25,000 small molecules led to the identification of a class of aryl-oxazoles that increased intracellular granularity in both cell lines, often leading to cell death. The most potent agents exhibited submicromolar efficacy in LNCaP and PC3 cells.