While the analysis so far confirms known drugs and their mechanisms of action in cell-lines, LCB is useful for discovering potential mechanisms for new drugs. The benezensulfonamide derivative, the fifth drug on the list, has no known targets or mechanisms. The experimental canvas shows that this perturbation is relatively strong (Figure
Benzenesulfonamide
It is a derivative of benzene and sulfonamide, and is used in various pharmaceutical and research applications.
Benzenesulfonamide and its derivatives have been studied for their potential therapeutic effects, such as antifungal, antimicrobial, and anti-inflammatory properties.
Researchers utilize benzenesulfonamide in medicinal chemistry, organic synthesis, and drug discovery efforts to explore its utility and optimize its performance.
This MeSH term provides a concise, informative overview of this important chemical moiety and its applications in the biomedical sciences.
Most cited protocols related to «Benzenesulfonamide»
While the analysis so far confirms known drugs and their mechanisms of action in cell-lines, LCB is useful for discovering potential mechanisms for new drugs. The benezensulfonamide derivative, the fifth drug on the list, has no known targets or mechanisms. The experimental canvas shows that this perturbation is relatively strong (Figure
where all terms were computed on the training dataset. The last term comprises the value of the mean squared error ( ) between the predicted and actual values of the target variable and two penalties on the number of positive values ( and outliers ( ). The first penalty is associated with the formally acceptable predicated values since the models were trained against the values of solubility expressed as the logarithm of the mole fraction and, as such, should always be positive. The latter penalty directs the acceptance of models with as few as possible outlying data points, defined as 3 times higher than the standard deviation. The first two terms in Equation (1) were obtained from the learning curve analysis (LCA) of the scikit-learn 1.2.2 library [51 ] and provide information on the model’s performance for different training set sizes. It is worth mentioning that LCA utilizes cross-validation (CV), which was set here to a 5-fold CV of the training dataset. The and values were obtained from the learning curve analysis, which provides information on the model’s ability to generalize to new, unseen data. The learning curve analysis (LCA) was performed using the sklearn.model_selection.learning_curve function from the scikit-learn library [51 ]. Since LCA can be computationally expensive, here, only two-point computations were performed by including 50% to 100% of the total data. The final model’s assessments via LCA were conducted using 20-point computations. The values included in the custom loss correspond to the mean MAE values obtained on the largest training set size. Hence, such a custom loss function combines the two types of components providing information on the model’s accuracy and ability to generalize to new, unseen data. Overall, this approach is regarded as a robust and reliable solubility prediction model that can be used for various applications and screening for new solvents.
The final performance of all models was evaluated using loss values characterizing test and validation subsets. The ensemble model (EM) was defined by the inclusion of the subset of regression models with the lowest values of both criteria, and the final predictions were averaged over selected models.
suspension of 6-amino-3-methyl-3,4-dihydroquinazolin-2(1H)-one (
(10 mL) was added pyridine (0.20 mL, 2.48 mmol, 5.9 equiv), followed
by 2-methoxybenzene-1-sulfonyl chloride (130 mg, 0.631 mmol, 1.5 equiv).
After 2 h, the solvent was evaporated and the residue was partitioned
between ethyl acetate and aqueous 2 M HCl. The organic layer was collected,
washed with water and brine, dried over magnesium sulfate, filtered,
and concentrated to a residue. The residue was dissolved in dimethyl
sulfoxide (DMSO, ∼1 mL) and purified by automated HPLC to provided
the desired material (50 mg, 34%). 1H NMR (400 MHz, DMSO-d6) δ 2.78 (s, 3H), 3.91 (s, 3H), 4.25
(s, 2H), 6.59 (d, J = 9.16 Hz, 1H), 6.79–6.81
(m, 2H), 6.97 (t, J = 7.5 Hz, 1H), 7.14 (d, J = 8.2 Hz, 1H), 7.52–7.56 (m, 1H), 7.68 (dd, J = 1.4, 7.8 Hz, 1H), 9.09 (s, 1H), 9.64 (s, 1H); HRMS [M
+ H] for C16H18N3O4S,
calcd 348.1013, found 348.1019; LCMS [M + H] = 384.1, >99% (t = 1.23 min).
Most recents protocols related to «Benzenesulfonamide»
Example 54
A microwave vessel was charged with N-[3-(5-bromo-1H-pyrazolo[3,4-b]pyridine-3-carbonyl)-2,6-difluorophenyl]methanesulfonamide (60.0 mg, 0.139 mmol), XPhos Pd G3 (3.53 mg, 0.00417 mmol) and [4-(1H-tetrazol-5-yl)phenyl]boronic acid (31.7 mg, 0.167 mmol) and purged with argon. Degassed 1,4-dioxane (0.464 mL) and degassed aqueous 1.5 M Potassium Carbonate (0.325 mL, 0.487 mmol) were added and the mixture was heated to 110° C. under microwave irradiation for 60 minutes. After cooling, the mixture was diluted with EtOAc and neutralized with sat. NH4Cl solution. The organic phase was concentrated under reduced pressure and the product isolated by flash chromatography (DCM+MeOH (+1% formic acid) 5% to 15%), triturated with MeOH and dried at 100° C. in a vacuum oven to yield N-[2,6-difluoro-3-[5-[4-(1H-tetrazol-5-yl)phenyl]-1H-pyrazolo[3,4-b]pyridine-3-carbonyl]phenyl]methanesulfonamide (21.0 mg, 0.0423 mmol, 30% yield).
Analytical Data:
-
- 1H NMR (200 MHz, DMSO) δ 14.85 (s, 1H), 9.75 (s, 1H), 9.10 (d, J=2.1 Hz, 1H), 8.86 (d, J=2.2 Hz, 1H), 8.25-8.00 (m, 4H), 7.97-7.81 (m, 1H), 7.41 (td, J=8.9, 1.3 Hz, 1H), 3.12 (s, 3H);
MS: [M−1]−=495.2.
A microwave vessel was charged with N-[3-(5-bromo-1H-pyrazolo[3,4-b]pyridine-3-carbonyl)-2,6-difluorophenyl]methanesulfonamide (60.0 mg, 0.139 mmol), XPhos Pd G3 (5.89 mg, 0.00696 mmol) and (4-Carbamoylphenyl)boronic acid (27.5 mg, 0.167 mmol) and purged with argon. Degassed 1,4-dioxane (0.464 mL) and degassed aqueous 1.5 M Potassium Carbonate (0.325 mL, 0.487 mmol) were added and the mixture was heated to 110° C. under microwave irradiation for 60 minutes. After cooling, the mixture was diluted with EtOAc and neutralized with sat. NH4Cl solution. The solvents were removed under reduced pressure and the product isolated by flash chromatography (DCM+MeOH, 5% to 15%) and dried at 100° C. in a vacuum oven to yield 4-[3-[2,4-difluoro-3-(methanesulfonamido)benzoyl]-1H-pyrazolo[3,4-b]pyridin-5-yl]benzamide (40.0 mg, 0.0789 mmol, 57% yield).
Analytical Data:
-
- 1H NMR (200 MHz, DMSO) δ 9.06 (d, J=1.9 Hz, 1H), 8.82 (d, J=2.0 Hz, 1H), 8.14-7.80 (m, 6H), 7.49-7.33 (m, 2H), 3.11 (s, 3H);
MS: [M−1]−=470.3
A microwave vessel was charged with N-[3-(5-bromo-1H-pyrazolo[3,4-b]pyridine-3-carbonyl)-2,6-difluorophenyl]methanesulfonamide (60.0 mg, 0.139 mmol), XPhos Pd G3 (5.89 mg, 0.00696 mmol) and 4-(4,4,5,5-tetramethyl-1,3,2-dioxaborolan-2-yl)benzenesulfonamide (47.3 mg, 0.167 mmol) and purged with argon. Degassed 1,4-dioxane (0.464 mL) and degassed aqueous 1.5 M potassium carbonate (0.325 mL, 0.487 mmol) were added and the mixture was heated to 110° C. under microwave irradiation for 60 minutes. After cooling, the mixture was diluted with EtOAc and neutralized with sat. NH4Cl solution. The solvents were removed under reduced pressure and the product isolated by flash chromatography (DCM+EtOAc, 50% to 100%) and dried at 100° C. in a vacuum oven to yield 4-[3-[2,4-difluoro-3-(methanesulfonamido)benzoyl]-1H-pyrazolo[3,4-b]pyridin-5-yl]benzenesulfonamide (31.0 mg, 0.0574 mmol, 41% yield). 1H NMR (200 MHz, DMSO) δ 9.07 (d, J=2.1 Hz, 1H), 8.84 (d, J=2.1 Hz, 1H), 8.12-7.78 (m, 4H), 7.50-7.32 (m, 2H), 3.11 (s, 3H); [M−1]−=506.2.
by flash column chromatography
(0–30% EtOAc in petroleum ether) yielded
a colorless oil (48 mg, 34%). 1H NMR (400 MHz, DMSO-d6): δ 9.90 (s, 1H), 7.88–7.79 (m,
2H), 7.63–7.57 (m, 2H), 7.52–7.46 (m, 1H), 7.43–7.35
(m, 3H), exchangeable proton not visible. 13C{1H} NMR (101 MHz, DMSO-d6): δ 192.8,
164.5 (d, J = 251.9 Hz), 138.5, 137.1, 135.6 (d, J = 2.6 Hz), 130.3, 129.8 (d, J = 9.6 Hz),
126.2, 125.7, 119.3, 116.7 (d, J = 22.9 Hz). 19F{1H} NMR (376 MHz, DMSO-d6): δ −106.5. νmax: 1688, 1332,
1150 cm–1. HRMS: m/z calculated for C13H11NO3FS+, 280.0444 [M + H]+. Found m/z, 280.0445, Δ = 0.4 ppm. Data consistent with that
available in the literature.23 (link)
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More about "Benzenesulfonamide"
It is a derivative of both benzene and sulfonamide, making it a valuable compound in various pharmaceutical, research, and industrial applications.
Benzenesulfonamide and its derivatives have been extensively studied for their potential therapeutic effects, including antifungal, antimicrobial, and anti-inflammatory properties.
Researchers in the fields of medicinal chemistry, organic synthesis, and drug discovery utilize benzenesulfonamide to explore its utility and optimize its performance.
Related compounds like DMSO (dimethyl sulfoxide), sulfadiazine, celecoxib, and T0901317 also share structural similarities and have been investigated for their own unique applications.
Sodium hydroxide (NaOH) and silica gel 60 F254 are commonly used in the synthesis and purification of benzenesulfonamide derivatives.
Analytical techniques like mass spectrometry, using an Agilent 6320 Ion Trap mass spectrometer, and chromatography, employing silica gel, are often employed to characterize and analyze benzenesulfonamide and its analogues.
Bovine serum albumin (BSA) may also be utilized in benzenesulfonamide-based assays or experiments.
The versatility and potential of benzenesulfonamide make it an important chemical moiety in the biomedical sciences, with researchers continually exploring new applications and optimizing its performance through innovative approaches and techniques.