Category: 92-36-4

Wang, Junmei published the artcileDevelopment of Reliable Aqueous Solubility Models and Their Application in Druglike Analysis, COA of Formula: C14H12N2S, the publication is Journal of Chemical Information and Modeling (2007), 47(4), 1395-1404, database is CAplus and MEDLINE.

In this work, two reliable aqueous solubility models, ASMS (aqueous solubility based on mol. surface) and ASMS-LOGP (aqueous solubility based on mol. surface using calculated log P (ClogP) as a descriptor), were constructed by using atom type classified solvent accessible surface areas and several mol. descriptors for a diverse data set of 1708 mols. For ASMS (without using ClogP as a descriptor), the leave-one-out q² and root-mean-square error (RMSE) were 0.872 and 0.748 log unit, resp. ASMS-LOGP was slightly better than ASMS (q² = 0.886, RMSE = 0.705). Both models were extensively validated by three cross-validation tests and encouraging predictability was achieved. High throughput aqueous solubility prediction was conducted for a number of data sets extracted from several widely used databases. The authors found that real drugs are about 20-fold more soluble than the so-called druglike mols. in the ZINC database, which have no violation of Lipinski’s “Rule of 5” at all. Specifically, oral drugs are about 16-fold more soluble, while injection drugs are 50-60-fold more soluble If the criterion of a mol. to be soluble is set to -5 log unit, about 85% of real drugs are predicted as soluble; in contrast only 50% of druglike mols. in ZINC are soluble The authors concluded that the two models could be served as a rule in druglike anal. and an efficient filter in prioritizing compound libraries prior to high throughput screenings (HTS).

Journal of Chemical Information and Modeling published new progress about 92-36-4. 92-36-4 belongs to thiazole, auxiliary class Organic Pigment, name is 2-(4-Aminophenyl)-6-methylbenzothiazole, and the molecular formula is C26H26N4O7, COA of Formula: C14H12N2S.

Referemce:
https://pubchem.ncbi.nlm.nih.gov/compound/thiazole,
Thiazole | chemical compound | Britannica

Payaz, Deniz Uzeroglu published the artcileSynthesis carbonic anhydrase enzyme inhibition and antioxidant activity of novel benzothiazole derivatives incorporating glycine, methionine, alanine, and phenylalanine moieties, Related Products of thiazole, the publication is Journal of Enzyme Inhibition and Medicinal Chemistry (2019), 34(1), 343-349, database is CAplus and MEDLINE.

Thirteen novel benzothiazole derivatives incorporating glycine, methionine, alanine, and phenylalanine were synthesized by facile acylation reactions through benzotriazole or DCC mediated reactions and their structures were identified by ¹H-NMR, 13C-NMR, and FT-IR spectroscopic techniques and elemental anal. The carbonic anhydrase (CA, EC 4.2.1.1) inhibitory activity of the new compounds was assessed against four human (h) isoforms, hCA I, hCA II, hCA V, and hCA XIII. Some of the synthesized compounds showed good in vitro carbonic anhydrase inhibitory properties, with inhibition constants in the micromolar level. The new amino acid benzothiazole conjugates found to be more effective against hCA V and hCA II inhibition. In vitro antioxidant activities of the novel compounds were determined by DPPH method. Most of the synthesized compounds showed moderate to low antioxidant activities compared to the control antioxidant compounds (BHA and α-tocopherol).

Journal of Enzyme Inhibition and Medicinal Chemistry published new progress about 92-36-4. 92-36-4 belongs to thiazole, auxiliary class Organic Pigment, name is 2-(4-Aminophenyl)-6-methylbenzothiazole, and the molecular formula is C14H12N2S, Related Products of thiazole.

Referemce:
https://pubchem.ncbi.nlm.nih.gov/compound/thiazole,
Thiazole | chemical compound | Britannica

Tomczyk, Danuta published the artcileApplication of column chromatography in the analysis of intermediates and dyes. III. Photometric determination of dehydrothio-p-toluidine in crude product, Related Products of thiazole, the publication is Chemia Analityczna (Warsaw, Poland) (1974), 19(6), 1247-51, database is CAplus.

Crude dehydrothio-p-toluidine (I) [92-36-4] dissolved in EtOH was separated by chromatog. on a cellulose powder column with EtOH as the mobile phase followed by photometric determination of collected I at 460 nm after its reaction with p-Me2NC6H4CHO. Standard deviation was 0.75% for the crude product containing 65% I and time of determination was 2.5 hr.

Chemia Analityczna (Warsaw, Poland) published new progress about 92-36-4. 92-36-4 belongs to thiazole, auxiliary class Organic Pigment, name is 2-(4-Aminophenyl)-6-methylbenzothiazole, and the molecular formula is C4H8F3NO, Related Products of thiazole.

Referemce:
https://pubchem.ncbi.nlm.nih.gov/compound/thiazole,
Thiazole | chemical compound | Britannica

Megill, Andrea published the artcileA tetra(ethylene glycol) derivative of benzothiazole aniline enhances Ras-mediated spinogenesis, Name: 2-(4-Aminophenyl)-6-methylbenzothiazole, the publication is Journal of Neuroscience (2013), 33(22), 9306-9318, database is CAplus and MEDLINE.

The tetra(ethylene glycol) derivative of benzothiazole aniline, BTA-EG₄, is a novel amyloid-binding small mol. that can penetrate the blood-brain barrier and protect cells from Aβ-induced toxicity. However, the effects of Aβ-targeting mols. on other cellular processes, including those that modulate synaptic plasticity, remain unknown. We report here that BTA-EG₄ decreases Aβ levels, alters cell surface expression of amyloid precursor protein (APP), and improves memory in wild-type mice. Interestingly, the BTA-EG₄-mediated behavioral improvement is not correlated with LTP, but with increased spinogenesis. The higher dendritic spine d. reflects an increase in the number of functional synapses as determined by increased miniature EPSC (mEPSC) frequency without changes in presynaptic parameters or postsynaptic mEPSC amplitude. Addnl., BTA-EG₄ requires APP to regulate dendritic spine d. through a Ras signaling-dependent mechanism. Thus, BTA-EG₄ may provide broad therapeutic benefits for improving neuronal and cognitive function, and may have implications in neurodegenerative disease therapy.

Journal of Neuroscience published new progress about 92-36-4. 92-36-4 belongs to thiazole, auxiliary class Organic Pigment, name is 2-(4-Aminophenyl)-6-methylbenzothiazole, and the molecular formula is C14H12N2S, Name: 2-(4-Aminophenyl)-6-methylbenzothiazole.

Referemce:
https://pubchem.ncbi.nlm.nih.gov/compound/thiazole,
Thiazole | chemical compound | Britannica

Mosier, Philip D. published the artcilePredicting the Genotoxicity of Thiophene Derivatives from Molecular Structure, Computed Properties of 92-36-4, the publication is Chemical Research in Toxicology (2003), 16(6), 721-732, database is CAplus and MEDLINE.

We report several binary classification models that directly link the genetic toxicity of a series of 140 thiophene derivatives with information derived from the compounds’ mol. structure. Genetic toxicity was measured using an SOS Chromotest. IMAX (maximal SOS induction factor) values were recorded for each of the 140 compounds both in the presence and in the absence of S9 rat liver homogenate. Compounds were classified as genotoxic if IMAX ≥ 1.5 in either test or nongenotoxic if IMAX < 1.5 for both tests. The mol. structures were represented by numerical descriptors that encoded the topol., geometric, electronic, and polar surface area properties of the thiophene derivatives The classification models used were linear discriminant anal. (LDA), k-nearest neighbor classification (k-NN), and the probabilistic neural network (PNN). These were used in conjunction with either a genetic algorithm or a generalized simulated annealing to find optimal subsets of descriptors for each classifier. The quality of the resulting models was determined by the number of misclassified compounds, with preference given to models that produced fewer false neg. classifications. Model sizes ranged from seven descriptors for LDA to three descriptors for k-NN and PNN. Very good classification results were obtained with all three classifiers. Classification rates for the LDA, k-NN, and PNN models were 80, 85, and 85%, resp., for the prediction set compounds Addnl., a consensus model was generated that incorporated all three of the basic model types. This consensus model correctly predicted the genotoxicity of 95% of the prediction set compounds

Chemical Research in Toxicology published new progress about 92-36-4. 92-36-4 belongs to thiazole, auxiliary class Organic Pigment, name is 2-(4-Aminophenyl)-6-methylbenzothiazole, and the molecular formula is C14H12N2S, Computed Properties of 92-36-4.

Referemce:
https://pubchem.ncbi.nlm.nih.gov/compound/thiazole,
Thiazole | chemical compound | Britannica

Mattioni, Brian E. published the artcilePredicting the Genotoxicity of Secondary and Aromatic Amines Using Data Subsetting To Generate a Model Ensemble, Category: thiazole, the publication is Journal of Chemical Information and Computer Sciences (2003), 43(3), 949-963, database is CAplus and MEDLINE.

Binary quant. structure-activity relationship (QSAR) models are developed to classify a data set of 334 aromatic and secondary amine compounds as genotoxic or nongenotoxic based on information calculated solely from chem. structure. Genotoxic endpoints for each compound were determined using the SOS Chromotest in both the presence and absence of an S9 rat liver homogenate. Compounds were considered genotoxic if assay results indicated a pos. genotoxicity hit for either the S9 inactivated or S9 activated assay. Each compound in the data set was encoded through the calculation of numerical descriptors that describe various aspects of chem. structure (e.g. topol., geometric, electronic, polar surface area). Furthermore, five addnl. descriptors that focused on the secondary and aromatic nitrogen atoms in each mol. were calculated specifically for this study. Descriptor subsets were examined using a genetic algorithm search engine interfaced with a k-Nearest Neighbor fitness evaluator to find the most information-rich subsets, which ultimately served as the final predictive models. Models were chosen for their ability to minimize the total number of misclassifications, with special attention given to those models that possessed fewer occurrences of pos. toxicity hits being misclassified as nontoxic (false negatives). In addition, a subsetting procedure was used to form an ensemble of models using different combinations of compounds in the training and prediction sets. This was done to ensure that consistent results could be obtained regardless of training set composition The procedure also allowed for each compound to be externally validated three times by different training set data with the resultant predictions being used in a “majority rules” voting scheme to produce a consensus prediction for each member of the data set. The individual models produced an average training set classification rate of 71.6% and an average prediction set classification rate of 67.7%. However, the model ensemble was able to correctly classify the genotoxicity of 72.2% of all prediction set compounds

Journal of Chemical Information and Computer Sciences published new progress about 92-36-4. 92-36-4 belongs to thiazole, auxiliary class Organic Pigment, name is 2-(4-Aminophenyl)-6-methylbenzothiazole, and the molecular formula is C14H12N2S, Category: thiazole.

Referemce:
https://pubchem.ncbi.nlm.nih.gov/compound/thiazole,
Thiazole | chemical compound | Britannica

Bentzien, Joerg published the artcileAn in Silico Method for Predicting Ames Activities of Primary Aromatic Amines by Calculating the Stabilities of Nitrenium Ions, COA of Formula: C14H12N2S, the publication is Journal of Chemical Information and Modeling (2010), 50(2), 274-297, database is CAplus and MEDLINE.

In this paper, the authors describe an in silico first principal approach to predict the mutagenic potential of primary aromatic amines. This approach is based on the so-called “nitrenium hypothesis”, which was developed by Ford et al. in the early 1990s. This hypothesis asserts that the mutagenic effect for this class of mols. is mediated through the transient formation of a nitrenium ion and that the stability of this cation is correlated with the mutagenic potential. Here the authors use quantum mech. calculations at different levels of theory (semiempirical AM1, ab initio HF/3-21G, HF/6-311G(d,p), and DFT/B3LYP/6-311G(d,p)) to compute the stability of nitrenium ions. When applied to a test set of 257 primary aromatic amines, the authors show that this method can correctly differentiate between Ames active and inactive compounds, and furthermore that it is able to rationalize and predict SAR trends within structurally related chem. series. For this test set, the AM1 nitrenium stability calculations are found to provide a good balance between speed and accuracy, resulting in an overall accuracy of 85%, and sensitivity and specificity of 91% and 72%, resp. The nitrenium-based predictions are also compared to the com. software packages DEREK, MULTICASE, and the MOE-Toxicophore descriptor. One advantage of the approach presented here is that the calculation of relative stabilities results in a continuous spectrum of activities and not a simple yes/no answer. This allows the authors to observe and rationalize subtle trends due to the different electrostatic properties of the organic mols. The authors’ results strongly indicate that nitrenium ion stability calculations should be used as a complementary approach to assist the medicinal chemist in prioritizing and selecting nonmutagenic primary aromatic amines during preclin. drug discovery programs.

Journal of Chemical Information and Modeling published new progress about 92-36-4. 92-36-4 belongs to thiazole, auxiliary class Organic Pigment, name is 2-(4-Aminophenyl)-6-methylbenzothiazole, and the molecular formula is C14H12N2S, COA of Formula: C14H12N2S.

Referemce:
https://pubchem.ncbi.nlm.nih.gov/compound/thiazole,
Thiazole | chemical compound | Britannica

Qiu, Yunguang published the artcileTREK Channel Family Activator with a Well-Defined Structure-Activation Relationship for Pain and Neurogenic Inflammation, Synthetic Route of 92-36-4, the publication is Journal of Medicinal Chemistry (2020), 63(7), 3665-3677, database is CAplus and MEDLINE.

TWIK-related K⁺ (TREK) channels are potential analgesic targets. However, selective activators for TREK with both defined action mechanism and analgesic ability for chronic pain have been lacking. Here, we report (1S,3R)-3-((4-(6-methylbenzo[d]thiazol-2-yl)phenyl)carbamoyl)cyclopentane-1-carboxylic acid (C3001a), a selective activator for TREK, against other two-pore domain K⁺ (K2P) channels. C3001a binds to the cryptic binding site formed by P1 and TM4 in TREK-1, as suggested by computational modeling and exptl. anal. Furthermore, we identify the carboxyl group of C3001a as a structural determinant for binding to TREK-1/2 and the key residue that defines the subtype selectivity of C3001a. C3001a targets TREK channels in the peripheral nervous system to reduce the excitability of nociceptive neurons. In neuropathic pain, C3001a alleviated spontaneous pain and cold hyperalgesia. In a mouse model of acute pancreatitis, C3001a alleviated mech. allodynia and inflammation. Together, C3001a represents a lead compound which could advance the rational design of peripherally acting analgesics targeting K2P channels without opioid-like adverse effects.

Journal of Medicinal Chemistry published new progress about 92-36-4. 92-36-4 belongs to thiazole, auxiliary class Organic Pigment, name is 2-(4-Aminophenyl)-6-methylbenzothiazole, and the molecular formula is C14H12N2S, Synthetic Route of 92-36-4.

Referemce:
https://pubchem.ncbi.nlm.nih.gov/compound/thiazole,
Thiazole | chemical compound | Britannica