Category: quinoxaline

Huff, Chelsea A. published the artcilePhotoredox-Catalyzed Hydroxymethylation of Heteroaromatic Bases, Computed Properties of 375815-87-5, the publication is Journal of Organic Chemistry (2016), 81(16), 6980-6987, database is CAplus and MEDLINE.

We report the development of a method for room-temperature C-H hydroxymethylation of heteroarenes. A key enabling advance in this work was achieved by implementing visible light photoredox catalysis that proved to be applicable to many classes of heteroarenes and tolerant of diverse functional groups found in druglike mols.

Journal of Organic Chemistry published new progress about 375815-87-5. 375815-87-5 belongs to quinoxaline, auxiliary class Neuronal Signaling,AChR,Natural product, name is 7,8,9,10-Tetrahydro-6H-6,10-methanoazepino[4,5-g]quinoxaline (2R,3R)-2,3-dihydroxysuccinate, and the molecular formula is C17H19N3O6, Computed Properties of 375815-87-5.

Referemce:
https://en.wikipedia.org/wiki/Quinoxaline,
Quinoxaline | C8H6N2 | ChemSpider

Werner, Felix-Martin published the artcileLong-term Administration of Antipsychotic Drugs in Schizophrenia and Influence of Substance and Drug Abuse on the Disease Outcome, Application of 7,8,9,10-Tetrahydro-6H-6,10-methanoazepino[4,5-g]quinoxaline (2R,3R)-2,3-dihydroxysuccinate, the publication is Current Drug Abuse Reviews (2017), 10(1), 19-24, database is CAplus and MEDLINE.

A review. Many schizophrenic patients with a long-term administration of antipsychotic drugs do not regularly adhere to the prescribed pharmacotherapy. Antipsychotic drugs constitute a palliative, but not a curative treatment, and the long-term effect of these drugs is not secure. Patients tend to consume nicotine and alc., as well as some patients consume drugs such as cannabis and amphetamines. The objective of this mini-review is to examine the reasons for the high tendency of schizophrenic patients to consume alc., nicotine and drugs and in addition to suggest measures to reduce the abuse of substances and drugs. The effects of substances such as alc. and nicotine and drugs such as cannabis and amphetamines on the disease outcome will be mentioned. Previous reviews on the psychotic disorders and the pharmacol. treatment were used to examine the effects of substances and drugs on schizophrenic symptoms and to investigate appropriate measures to improve medication adherence and the renouncement of consuming substances and drugs. A possible coherence between the function of single susceptibility genes and the alteration of neurotransmitters is mentioned. The mechanism of action of the most important secondgeneration antipsychotic drugs and their indications are described. The tendency of schizophrenic patients to consume alc. and nicotine and in addition the effect of both substances to possibly worsen psychotic symptoms are pointed out. The effect of nicotinergic agonists to support smoking cessation is described. The different compounds of cannabis, tetrahydrocannabidiol (a psychotomimetic) and cannabidiol (exerts antipsychotic actions), are mentioned. Because a reduced adherence to the pharmacotherapy is frequently combined with the abuse of substances, addnl. drugs, psychoeducation and the administration of long-acting injectable antipsychotic drugs could reduce the abuse of substances and drugs; these strategies could help to maintain the antipsychotic administration. The abuse of drugs and substances might be combined with a reduced adherence to the antipsychotic pharmacotherapy. Drugs and substances might in some cases worsen the psychotic symptoms. Appropriate measures to reduce substance and drug abuse as well as to improve the adherence to the antipsychotic pharmacotherapy are cognitive behavioral therapy, psychoeducation and the administration of long-acting injectable antipsychotic drugs. Some new drugs, for example the cannabis compound cannabidiol that shows antipsychotic properties and β-varenicline, a nicotinergic cholinergic agonist, might be administered when substance abuse (cannabis, nicotine) occurs.

Current Drug Abuse Reviews published new progress about 375815-87-5. 375815-87-5 belongs to quinoxaline, auxiliary class Neuronal Signaling,AChR,Natural product, name is 7,8,9,10-Tetrahydro-6H-6,10-methanoazepino[4,5-g]quinoxaline (2R,3R)-2,3-dihydroxysuccinate, and the molecular formula is C8H6ClF3, Application of 7,8,9,10-Tetrahydro-6H-6,10-methanoazepino[4,5-g]quinoxaline (2R,3R)-2,3-dihydroxysuccinate.

Referemce:
https://en.wikipedia.org/wiki/Quinoxaline,
Quinoxaline | C8H6N2 | ChemSpider

Broccatelli, Fabio published the artcileBDDCS Class Prediction for New Molecular Entities, COA of Formula: C17H19N3O6, the publication is Molecular Pharmaceutics (2012), 9(3), 570-580, database is CAplus and MEDLINE.

The Biopharmaceutics Drug Disposition Classification System (BDDCS) was successfully employed for predicting drug-drug interactions (DDIs) with respect to drug metabolizing enzymes (DMEs), drug transporters and their interplay. The major assumption of BDDCS is that the extent of metabolism (EoM) predicts high vs. low intestinal permeability rate, and vice versa, at least when uptake transporters or paracellular transport is not involved. We recently published a collection of over 900 marketed drugs classified for BDDCS. We suggest that a reliable model for predicting BDDCS class, integrated with in vitro assays, could anticipate disposition and potential DDIs of new mol. entities (NMEs). Here we describe a computational procedure for predicting BDDCS class from mol. structures. The model was trained on a set of 300 oral drugs, and validated on an external set of 379 oral drugs, using 17 descriptors calculated or derived from the VolSurf+ software. For each mol., a probability of BDDCS class membership was given, based on predicted EoM, FDA solubility (FDAS) and their confidence scores. The accuracy in predicting FDAS was 78% in training and 77% in validation, while for EoM prediction the accuracy was 82% in training and 79% in external validation. The actual BDDCS class corresponded to the highest ranked calculated class for 55% of the validation mols., and it was within the top two ranked more than 92% of the time. The unbalanced stratification of the data set did not affect the prediction, which showed highest accuracy in predicting classes 2 and 3 with respect to the most populated class 1. For class 4 drugs a general lack of predictability was observed A linear discriminant anal. (LDA) confirming the degree of accuracy for the prediction of the different BDDCS classes is tied to the structure of the data set. This model could routinely be used in early drug discovery to prioritize in vitro tests for NMEs (e.g., affinity to transporters, intestinal metabolism, intestinal absorption and plasma protein binding). We further applied the BDDCS prediction model on a large set of medicinal chem. compounds (over 30,000 chems.). Based on this application, we suggest that solubility, and not permeability, is the major difference between NMEs and drugs. We anticipate that the forecast of BDDCS categories in early drug discovery may lead to a significant R&D cost reduction

Molecular Pharmaceutics published new progress about 375815-87-5. 375815-87-5 belongs to quinoxaline, auxiliary class Neuronal Signaling,AChR,Natural product, name is 7,8,9,10-Tetrahydro-6H-6,10-methanoazepino[4,5-g]quinoxaline (2R,3R)-2,3-dihydroxysuccinate, and the molecular formula is C17H19N3O6, COA of Formula: C17H19N3O6.

Referemce:
https://en.wikipedia.org/wiki/Quinoxaline,
Quinoxaline | C8H6N2 | ChemSpider

Hoffman, Keith B. published the artcileA Pharmacovigilance Signaling System Based on FDA Regulatory Action and Post-Marketing Adverse Event Reports, Category: quinoxaline, the publication is Drug Safety (2016), 39(6), 561-575, database is CAplus and MEDLINE.

Many serious drug adverse events (AEs) only manifest well after regulatory approval. Therefore, the development of signaling methods to use with post-approval AE databases appears vital to comprehensively assess real-world drug safety. However, with millions of potential drug-AE pairs to analyze, the issue of focus is daunting. Our objective was to develop a signaling platform that focuses on AEs with historically demonstrated regulatory interest and to analyze such AEs with a disproportional reporting method that offers broad signal detection and acceptable false-pos. rates. We analyzed over 1500 US FDA regulatory actions (safety communications and drug label changes) from 2008 to 2015 to construct a list of eligible signal AEs. The FDA Adverse Event Reporting System (FAERS) was used to evaluate disproportional reporting rates, constrained by min. case counts and confidence interval limits, of these selected AEs for 109 training drugs. This step led to 45 AEs that appeared to have a low likelihood of being added to a label by FDA, so they were removed from the signal eligible list. We measured disproportional reporting for the final group of eligible AEs on a test group of 29 drugs that were not used in either the eligible list construction or the training steps. In a group of 29 test drugs, our model reduced the number of potential drug-AE signals from 41,834 to 97 and predicted 73 % of individual drug label changes. The model also predicted at least one AE-drug pair label change in 66 % of all the label changes for the test drugs. By concentrating on AE types with already demonstrated interest to FDA, we constructed a signaling system that provided focus regarding drug-AE pairs and suitable accuracy with regard to the issuance of FDA labeling changes. We suggest that focus on historical regulatory actions may increase the utility of pharmacovigilance signaling systems.

Drug Safety published new progress about 375815-87-5. 375815-87-5 belongs to quinoxaline, auxiliary class Neuronal Signaling,AChR,Natural product, name is 7,8,9,10-Tetrahydro-6H-6,10-methanoazepino[4,5-g]quinoxaline (2R,3R)-2,3-dihydroxysuccinate, and the molecular formula is C17H19N3O6, Category: quinoxaline.

Referemce:
https://en.wikipedia.org/wiki/Quinoxaline,
Quinoxaline | C8H6N2 | ChemSpider

Zheng, Lin published the artcileThe calcimimetic agent cinacalcet inhibits hepatocellular carcinoma via YAP/TAZ suppression, Safety of 7,8,9,10-Tetrahydro-6H-6,10-methanoazepino[4,5-g]quinoxaline (2R,3R)-2,3-dihydroxysuccinate, the publication is Pharmazie (2021), 76(10), 511-514, database is CAplus and MEDLINE.

The lack of effective strategies remains a pivotal challenge for hepatocellular carcinoma (HCC) treatment. YAP/ TAZ is a promising target for effective drugs against HCC. In this study, we profiled the regulatory effect of 98 drugs on transcriptional activity of YAP/TAZ and identified the calcimimetic agent cinacalcet as a potent YAP inhibitor. Cinacalcet inhibited YAP expression in HCC models at both transcriptional and protein levels, and ultimately arrested cell proliferation of HCC. Overexpression of YAP weakened the anticancer efficacy of cinacalcet, indicating that YAP was responsible for the antineoplastic activity of cinacalcet. Collectively, this study suggested cinacalcet as a feasible anticancer drug for HCC via its inhibition on YAP/TAZ.

Pharmazie published new progress about 375815-87-5. 375815-87-5 belongs to quinoxaline, auxiliary class Neuronal Signaling,AChR,Natural product, name is 7,8,9,10-Tetrahydro-6H-6,10-methanoazepino[4,5-g]quinoxaline (2R,3R)-2,3-dihydroxysuccinate, and the molecular formula is C10H10O2, Safety of 7,8,9,10-Tetrahydro-6H-6,10-methanoazepino[4,5-g]quinoxaline (2R,3R)-2,3-dihydroxysuccinate.

Referemce:
https://en.wikipedia.org/wiki/Quinoxaline,
Quinoxaline | C8H6N2 | ChemSpider

Di Rocco, Daniel A. published the artcileLate-stage functionalization of biologically active heterocycles through photoredox catalysis, Quality Control of 375815-87-5, the publication is Angewandte Chemie, International Edition (2014), 53(19), 4802-4806, database is CAplus and MEDLINE.

The direct C-H functionalization of heterocycles has become an increasingly valuable tool in modern drug discovery. However, the introduction of small alkyl groups, such as Me, by this method has not been realized in the context of complex mol. synthesis since existing methods rely on the use of strong oxidants and elevated temperatures to generate the requisite radical species. Herein, the authors report the use of stable organic peroxides activated by visible-light photoredox catalysis to achieve the direct methyl-, ethyl-, and cyclopropylation of a variety of biol. active heterocycles. The simple protocol, mild reaction conditions, and unique tolerability of this method make it an important tool for drug discovery.

Angewandte Chemie, International Edition published new progress about 375815-87-5. 375815-87-5 belongs to quinoxaline, auxiliary class Neuronal Signaling,AChR,Natural product, name is 7,8,9,10-Tetrahydro-6H-6,10-methanoazepino[4,5-g]quinoxaline (2R,3R)-2,3-dihydroxysuccinate, and the molecular formula is C17H19N3O6, Quality Control of 375815-87-5.

Referemce:
https://en.wikipedia.org/wiki/Quinoxaline,
Quinoxaline | C8H6N2 | ChemSpider