Category: 40180-04-9

Burckhardt, Birgitta Christina published the artcileElectrophysiologic characterization of an organic anion transporter cloned from winter flounder kidney (fROAT), Recommanded Product: 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid, the main research area is flounder kidney anion transporter; sequence Pseudopleuronectes anion transporter.

The 2-electrode voltage clamp technique was used to demonstrate translocation of p-aminohippurate (PAH) and related compounds such as loop diuretics in Xenopus laevis oocytes expressing the renal organic anion transporter from winter flounder kidney (fROAT). In fROAT-expressing oocytes, PAH (0.1 mM) induced a depolarization of 4.2 mV and at a holding potential of -60 mV an inward current of -22.6 nA. PAH-induced current and the current calculated from [3H]PAH uptake were of similar magnitude. Depolarization, inward current, and current-to-uptake relation indicated exchange of the monovalent PAH with a divalent anion, possibly α-ketoglutarate (α-KG), causing net efflux of 1 neg. charge. The kinetic anal. of PAH-induced currents revealed that translocation is dependent on membrane potential, saturable with an apparent Km of 58 μM, and sensitive to probenecid and furosemide. In contrast to probenecid and furosemide, the loop diuretics bumetanide, ethacrynic acid, and tienilic acid and the nephrotoxic mycotoxin ochratoxin A elicited inward currents indicating translocation through fROAT. Substrate-dependent currents provide a tool to elucidate the structure/function relationship of the renal organic anion transporter.

Journal of the American Society of Nephrology published new progress about Anion transporters Role: BAC (Biological Activity or Effector, Except Adverse), BSU (Biological Study, Unclassified), PRP (Properties), BIOL (Biological Study). 40180-04-9 belongs to class benzothiophene, name is 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid, and the molecular formula is C13H8Cl2O4S, Recommanded Product: 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid.

Referemce:
Benzothiophene – Wikipedia,
Benzothiophene | C8H6S – PubChem

Nettles, James H. published the artcileFlexible three-dimensional pharmacophores as descriptors of dynamic biological space, COA of Formula: C13H8Cl2O4S, the main research area is flexibility three dimensional pharmacophore fuzzy pattern Algorithm modeling docking.

Development of a pharmacophore hypothesis related to small-mol. activity is pivotal to chem. optimization of a series, since it defines features beneficial or detrimental to activity. Although crystal structures may provide detailed three-dimensional interaction information for one mol. with its receptor, docking a different ligand to that model often leads to unreliable results due to protein flexibility. Graham Richards’ laboratory was one of the first groups to utilize “”fuzzy”” pattern recognition algorithms taken from the field of image processing to solve problems in protein modeling. Thus, descriptor “”fuzziness”” was partly able to emulate conformational flexibility of the target while simultaneously enhancing the speed of the search. In this work, we extend these developments to a ligand-based method for describing and aligning mols. in flexible chem. space termed FEature POint PharmacophoreS (FEPOPS), which allows exploration of dynamic biol. space. We develop a novel, combinatorial algorithm for mol. comparisons and evaluate it using the WOMBAT dataset. The new approach shows superior retrospective virtual screening performance than earlier shape-based or charge-based algorithms. Addnl., we use target prediction to evaluate how FEPOPS alignments match the mols. biol. activity by identifying the atoms and features that make the key contributions to overall chem. similarity. Overall, we find that FEPOPS are sufficiently fuzzy and flexible to find not only new ligand scaffolds, but also challenging mols. that occupy different conformational states of dynamic biol. space as from induced fits.

Journal of Molecular Graphics & Modelling published new progress about 5-HT2C receptors Role: BSU (Biological Study, Unclassified), PRP (Properties), BIOL (Biological Study). 40180-04-9 belongs to class benzothiophene, name is 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid, and the molecular formula is C13H8Cl2O4S, COA of Formula: C13H8Cl2O4S.

Referemce:
Benzothiophene – Wikipedia,
Benzothiophene | C8H6S – PubChem

Liu, Ruifeng published the artcile2D SMARTCyp Reactivity-Based Site of Metabolism Prediction for Major Drug-Metabolizing Cytochrome P450 Enzymes, Formula: C13H8Cl2O4S, the main research area is SMARTCyp cytochrome P450 3A4 2D6 2C9 2C19 1A2 human.

Cytochrome P 450 (CYP) 3A4, 2D6, 2C9, 2C19, and 1A2 are the most important drug-metabolizing enzymes in the human liver. Knowledge of which parts of a drug mol. are subject to metabolic reactions catalyzed by these enzymes is crucial for rational drug design to mitigate ADME/toxicity issues. SMARTCyp, a recently developed 2D ligand structure-based method, is able to predict site-specific metabolic reactivity of CYP3A4 and CYP2D6 substrates with an accuracy that rivals the best and more computationally demanding 3D structure-based methods. In this article, the SMARTCyp approach was extended to predict the metabolic hotspots for CYP2C9, CYP2C19, and CYP1A2 substrates. This was accomplished by taking into account the impact of a key substrate-receptor recognition feature of each enzyme as a correction term to the SMARTCyp reactivity. The corrected reactivity was then used to rank order the likely sites of CYP-mediated metabolic reactions. For 60 CYP1A2 substrates, the observed major sites of CYP1A2 catalyzed metabolic reactions were among the top-ranked 1, 2, and 3 positions in 67%, 80%, and 83% of the cases, resp. The results were similar to those obtained by MetaSite and the reactivity + docking approach. For 70 CYP2C9 substrates, the observed sites of CYP2C9 metabolism were among the top-ranked 1, 2, and 3 positions in 66%, 86%, and 87% of the cases, resp. These results were better than the corresponding results of StarDrop version 5.0, which were 61%, 73%, and 77%, resp. For 36 compounds metabolized by CYP2C19, the observed sites of metabolism were found to be among the top-ranked 1, 2, and 3 sites in 78%, 89%, and 94% of the cases, resp. The computational procedure was implemented as an extension to the program SMARTCyp 2.0. With the extension, the program can now predict the site of metabolism for all five major drug-metabolizing enzymes with an accuracy similar to or better than that achieved by the best 3D structure-based methods. Both the Java source code and the binary executable of the program are freely available to interested users.

Journal of Chemical Information and Modeling published new progress about Algorithm (SMARTCyp, 2D ligand structure-based method). 40180-04-9 belongs to class benzothiophene, name is 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid, and the molecular formula is C13H8Cl2O4S, Formula: C13H8Cl2O4S.

Referemce:
Benzothiophene – Wikipedia,
Benzothiophene | C8H6S – PubChem

Bonierbale, Eric published the artcileOpposite Behaviors of Reactive Metabolites of Tienilic Acid and Its Isomer toward Liver Proteins: Use of Specific Anti-Tienilic Acid-Protein Adduct Antibodies and the Possible Relationship with Different Hepatotoxic Effects of the Two Compounds, Recommanded Product: 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid, the main research area is tienilic acid hepatotoxicity immunity cytochrome P450.

Tienilic acid (TA) is responsible for an immune-mediated drug-induced hepatitis in humans, while its isomer (TAI) triggers a direct hepatitis in rats. In this study, we describe an immunol. approach developed for studying the specificity of the covalent binding of these two compounds For this purpose, two different coupling strategies were used to obtain TA-carrier protein conjugates. In the first strategy, the drug was linked through its carboxylic acid function to amine residues of carrier proteins (BSA-N-TA and casein-N-TA), while in the second strategy, the thiophene ring of TA was attached to proteins through a short 3-thiopropanoyl linker, the corresponding conjugates (BSA-S-5-TA and βLG-S-5-TA) thus preferentially presenting the 2,3-dichlorophenoxyacetic moiety of the drug for antibody recognition. The BSA-S-5-TA conjugate proved to be 30 times more immunogenic than BSA-N-TA. Anti-TA-protein adduct antibodies were obtained after immunization of rabbits with BSA-S-5-TA (1/35000 titer against βLG-S-5-TA in ELISA). These antibodies strongly recognized the 2,3-dichlorophenoxyacetic moiety of TA but poorly the part of the drug engaged in the covalent binding with the proteins. This powerful tool was used in immunoblots to compare TA or TAI adduct formation in human liver microsomes as well as on microsomes from yeast expressing human liver cytochrome P 450 2C9. TA displayed a highly specific covalent binding focused on P 450 2C9 which is the main cytochrome P 450 responsible for its hepatic activation in humans. On the contrary, TAI showed a nonspecific alkylation pattern, targeting many proteins upon metabolic activation. Nevertheless, this nonspecific covalent binding could be completely shifted to a thiol trapping agent like GSH. The difference in alkylation patterns for these two compounds is discussed with regard to their distinct toxicities. A relationship between the specific covalent binding of P 450 2C9 by TA and the appearance of the highly specific anti-LKM2 autoantibodies (known to specifically recognize P 450 2C9) in patients affected with TA-induced hepatitis is strongly suggested.

Chemical Research in Toxicology published new progress about Caseins Role: ADV (Adverse Effect, Including Toxicity), BUU (Biological Use, Unclassified), RCT (Reactant), BIOL (Biological Study), USES (Uses), RACT (Reactant or Reagent) (conjugate with tienilic acid). 40180-04-9 belongs to class benzothiophene, name is 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid, and the molecular formula is C13H8Cl2O4S, Recommanded Product: 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid.

Referemce:
Benzothiophene – Wikipedia,
Benzothiophene | C8H6S – PubChem

Dang, Na Le published the artcileComputational Approach to Structural Alerts: Furans, Phenols, Nitroaromatics, and Thiophenes, Formula: C13H8Cl2O4S, the main research area is furan phenol nitroarom thiophene metabolism toxicity modeling toxicophore.

Structural alerts are commonly used in drug discovery to identify mols. likely to form reactive metabolites, and thereby become toxic. Unfortunately, as useful as structural alerts are, they do not effectively model if, when, and why metabolism renders safe mols. toxic. Toxicity due to a specific structural alert is highly conditional, depending on the metabolism of the alert, the reactivity of its metabolites, dosage, and competing detoxification pathways. A systems approach, which explicitly models these pathways, could more effectively assess the toxicity risk of drug candidates. In this study, the authors demonstrated that math. models of P 450 metabolism can predict the context-specific probability that a structural alert will be bioactivated in a given mol. This study focuses on the furan, phenol, nitroarom., and thiophene alerts. Each of these structural alerts can produce reactive metabolites through certain metabolic pathways, but not always. The authors tested whether the metabolism modeling approach, XenoSite, can predict when a given mol.’s alerts will be bioactivated. Specifically, the authors used models of epoxidation, quinone formation, reduction, and sulfur-oxidation to predict the bioactivation of furan-, phenol-, nitroarom.-, and thiophene-containing drugs. The authors’ models separated bioactivated and not-bioactivated furan-, phenol-, nitroarom.-, and thiophene-containing drugs with AUC performances of 100%, 73%, 93%, and 88%, resp. Metabolism models accurately predict whether alerts are bioactivated and thus serve as a practical approach to improve the interpretability and usefulness of structural alerts. The authors expect that this same computational approach can be extended to most other structural alerts and later integrated into toxicity risk models. This advance is one necessary step towards the authors’ long-term goal of building comprehensive metabolic models of bioactivation and detoxification to guide assessment and design of new therapeutic mols.

Chemical Research in Toxicology published new progress about Biological detoxification. 40180-04-9 belongs to class benzothiophene, name is 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid, and the molecular formula is C13H8Cl2O4S, Formula: C13H8Cl2O4S.

Referemce:
Benzothiophene – Wikipedia,
Benzothiophene | C8H6S – PubChem

Shin, Young G. published the artcileComparison of metabolic soft spot predictions of CYP3A4, CYP2C9 and CYP2D6 substrates using MetaSite and StarDrop, Safety of 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid, the main research area is site of metabolism CYP3A4 CYP2C9 CYP2D6 substrate MetaSite StarDrop.

Metabolite identification study plays an important role in determining the sites of metabolic liability of new chem. entities (NCEs) in drug discovery for lead optimization. Here we compare the two predictive software, MetaSite and StarDrop, available for this purpose. They work very differently but are used to predict the site of oxidation by major human cytochrome P 450 (CYP) isoforms. Neither software can predict non-CYP catalyzed metabolism nor the rates of metabolism For the purpose of comparing the two software packages, we tested known probe substrate for these enzymes, which included 12 substrates of CYP3A4 and 18 substrates of CYP2C9 and CYP2D6 were analyzed by each software and the results were compared. It is possible that these known substrates were part of the training set but we are not aware of it. To assess the performance of each software we assigned a point system for each correct prediction. The total points assigned for each CYP isoform exptl. were compared as a percentage of the total points assigned theor. for the first choice prediction for all substrates for each isoform. Our results show that MetaSite and StarDrop are similar in predicting the correct site of metabolism by CYP3A4 (78% vs 83%, resp.). StarDrop appears to do slightly better in predicting the correct site of metabolism by CYP2C9 and CYP2D6 metabolism (89% and 93%, resp.) compared to MetaSite (63% and 70%, resp.). The sites of metabolism (SOM) from 34 inhouse NCEs incubated in human liver microsomes or human hepatocytes were also evaluated using two prediction software packages and the results showed comparable SOM predictions. What makes this comparison challenging is that the contribution of each isoform to the intrinsic clearance (Clint) is not known. Overall the software were comparable except for MetaSite performing better for CYP2D6 and that MetaSite has a liver model that is absent in StarDrop that predicted with 82% accuracy.

Combinatorial Chemistry & High Throughput Screening published new progress about Computer program (MetaSite). 40180-04-9 belongs to class benzothiophene, name is 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid, and the molecular formula is C13H8Cl2O4S, Safety of 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid.

Referemce:
Benzothiophene – Wikipedia,
Benzothiophene | C8H6S – PubChem

Aleo, Michael D. published the artcileEvaluating the role of multidrug resistance protein 3 (MDR3) inhibition in predicting drug-induced liver injury using 125 pharmaceuticals, Name: 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid, the main research area is MDR3 inhibition screening drug induced liver injury risk assessment; ABCB4 inhibitor screening drug induced liver injury prognosis.

The role of bile salt export protein (BSEP) inhibition in drug-induced liver injury (DILI) has been investigated widely, while inhibition of the canalicular multidrug resistant protein 3 (MDR3) has received less attention. This transporter plays a pivotal role in secretion of phospholipids into bile and functions coordinately with BSEP to mediate the formation of bile acid-containing biliary micelles. Therefore, inhibition of MDR3 in human hepatocytes was examined across 125 drugs (70 of Most-DILI-concern and 55 of No-DILI-concern). Of these tested, 41% of Most-DILI-concern and 47% of No-DILI-concern drugs had MDR3 IC50 values of <50 μM. A better distinction across DILI classifications occurred when systemic exposure was considered where safety margins of 50-fold had low sensitivity (0.29), but high specificity (0.96). Anal. of phys. chem. property space showed that basic compounds were twice as likely to be MDR3 inhibitors as acids, neutrals, and zwitterions and that inhibitors were more likely to have polar surface area (PSA) values of <100 Å2 and cPFLogD values between 1.5 and 5. These descriptors, with different cutoffs, also highlighted a group of compounds that shared dual potency as MDR3 and BSEP inhibitors. Nine drugs classified as Most-DILI-concern compounds (four withdrawn, four boxed warning, and one liver injury warning in their approved label) had intrinsic potency features of <20 μM in both assays, thereby reinforcing the notion that multiple inhibitory mechanisms governing bile formation (bile acid and phospholipid efflux) may confer addnl. risk factors that play into more severe forms of DILI as shown by others for BSEP inhibitors combined with multidrug resistance-associated protein (MRP2, MRP3, MRP4) inhibitory properties. Avoiding phys. property descriptors that highlight dual BSEP and MDR3 inhibition or testing drug candidates for inhibition of multiple efflux transporters (e.g., BSEP, MDR3, and MRPs) may be an effective strategy for prioritizing drug candidates with less likelihood of causing clin. DILI. Chemical Research in Toxicology published new progress about Bile (formation). 40180-04-9 belongs to class benzothiophene, name is 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid, and the molecular formula is C13H8Cl2O4S, Name: 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid.

Referemce:
Benzothiophene – Wikipedia,
Benzothiophene | C8H6S – PubChem

Fourches, Denis published the artcileCheminformatics Analysis of Assertions Mined from Literature that Describe Drug-Induced Liver Injury in Different Species, Recommanded Product: 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid, the main research area is cheminformatics drug toxicity liver injury species difference QSAR model.

Drug-induced liver injury is one of the main causes of drug attrition. The ability to predict the liver effects of drug candidates from their chem. structures is critical to help guide exptl. drug discovery projects toward safer medicines. In this study, the authors have compiled a data set of 951 compounds reported to produce a wide range of effects in the liver in different species, comprising humans, rodents, and nonrodents. The liver effects for this data set were obtained as assertional metadata, generated from MEDLINE abstracts using a unique combination of lexical and linguistic methods and ontol. rules. The authors have analyzed this data set using conventional cheminformatics approaches and addressed several questions pertaining to cross-species concordance of liver effects, chem. determinants of liver effects in humans, and the prediction of whether a given compound is likely to cause a liver effect in humans. The authors found that the concordance of liver effects was relatively low (∼39-44%) between different species, raising the possibility that species specificity could depend on specific features of chem. structure. Compounds were clustered by their chem. similarity, and similar compounds were examined for the expected similarity of their species-dependent liver effect profiles. In most cases, similar profiles were observed for members of the same cluster, but some compounds appeared as outliers. The outliers were the subject of focused assertion regeneration from MEDLINE as well as other data sources. In some cases, addnl. biol. assertions were identified, which were in line with expectations based on compounds’ chem. similarities. The assertions were further converted to binary annotations of underlying chems. (i.e., liver effect vs. no liver effect), and binary quant. structure-activity relationship (QSAR) models were generated to predict whether a compound would be expected to produce liver effects in humans. Despite the apparent heterogeneity of data, models have shown good predictive power assessed by external 5-fold cross-validation procedures. The external predictive power of binary QSAR models was further confirmed by their application to compounds that were retrieved or studied after the model was developed. To the best of the authors’ knowledge, this is the first study for chem. toxicity prediction that applied QSAR modeling and other cheminformatics techniques to observational data generated by the means of automated text mining with limited manual curation, opening up new opportunities for generating and modeling chem. toxicol. data.

Chemical Research in Toxicology published new progress about Chemoinformatics. 40180-04-9 belongs to class benzothiophene, name is 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid, and the molecular formula is C13H8Cl2O4S, Recommanded Product: 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid.

Referemce:
Benzothiophene – Wikipedia,
Benzothiophene | C8H6S – PubChem

Shah, Falgun published the artcileSetting clinical exposure levels of concern for drug-induced liver injury (DILI) using mechanistic in vitro assays, Recommanded Product: 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid, the main research area is drug induced liver injury assay hepatotoxicity BSEP mitochondria inhibition; Liver Toxicity Knowledge Base; drug-induced liver injury; plasma exposure; safety margin.

Severe drug-induced liver injury (DILI) remains a major safety issue due to its frequency of occurrence, idiosyncratic nature, poor prognosis, and diverse underlying mechanisms. Numerous exptl. approaches have been published to improve human DILI prediction with modest success. A retrospective anal. of 125 drugs (70 = most-DILI, 55 = no-DILI) from the Food and Drug Administration Liver Toxicity Knowledge Base was used to investigate DILI prediction based on consideration of human exposure alone or in combination with mechanistic assays of hepatotoxic liabilities (cytotoxicity, bile salt export pump inhibition, or mitochondrial inhibition/uncoupling). Using this dataset, human plasma Cmax,total ≥ 1.1 μM alone distinguished most-DILI from no-DILI compounds with high sensitivity/specificity (80/73%). Accounting for human exposure improved the sensitivity/specificity for each assay and helped to derive predictive safety margins. Compounds with plasma Cmax,total ≥ 1.1 μM and triple liabilities had significantly higher odds ratio for DILI than those with single/dual liabilities. Using this approach, a subset of recent pharmaceuticals with evidence of liver injury during clin. development was recognized as potential hepatotoxicants. In summary, plasma Cmax,total ≥ 1.1 μM along with multiple mechanistic liabilities is a major driver for predictions of human DILI potential. In applying this approach during drug development the challenge will be generating accurate estimates of plasma Cmax, total at efficacious doses in advance of generating true exposure data from clin. studies. In the meantime, drug candidates with multiple hepatotoxic liabilities should be deprioritized, since they have the highest likelihood of causing DILI in case their efficacious plasma Cmax,total in humans is higher than anticipated.

Toxicological Sciences published new progress about Drug discovery. 40180-04-9 belongs to class benzothiophene, name is 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid, and the molecular formula is C13H8Cl2O4S, Recommanded Product: 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid.

Referemce:
Benzothiophene – Wikipedia,
Benzothiophene | C8H6S – PubChem

Agatonovic-Kustrin, Snezana published the artcileMolecular Structural Characteristics Important in Drug-HSA Binding, Formula: C13H8Cl2O4S, the main research area is acecainide analgesics antibiotic anticancer protein binding structure activity relationship.

A non-linear quant. structure activity relationship (QSAR) model based on 350 drug mols. was developed as a predictive tool for drug protein binding, by correlating exptl. measured protein binding values with ten calculated mol. descriptors using a radial basis function (RBF) neural network. The developed model has a statistically significant overall correlation value (r > 0.73), a high efficiency ratio (0.986), and a good predictive squared correlation coefficient (q2) of 0.532, which is regarded as producing a robust and high quality QSAR model. The developed model may be used for the screening of drug candidate mols. that have high protein binding data, filtering out compounds that are unlikely to be protein bound, and may assist in the dose adjustment for drugs that are highly protein bound. The advantage of using such a model is that the percentage of a potential drug candidate that is protein bound (PB (%)) can be simply predicted from its mol. structure.

Combinatorial Chemistry & High Throughput Screening published new progress about Analgesics. 40180-04-9 belongs to class benzothiophene, name is 2-(2,3-Dichloro-4-(thiophene-2-carbonyl)phenoxy)acetic acid, and the molecular formula is C13H8Cl2O4S, Formula: C13H8Cl2O4S.

Referemce:
Benzothiophene – Wikipedia,
Benzothiophene | C8H6S – PubChem