Sulfonamides as anticancer agents: A brief review on sulfonamide derivatives as inhibitors of various proteins overexpressed in cancer.

Sulfonamides have gained prominence as versatile agents in cancer therapy, effectively targeting a spectrum of cancer-associated enzymes. This review provides an extensive exploration of their multifaceted roles in cancer biology. Sulfonamides exhibit adaptability by acting as tyrosine kinase inhibitors, disrupting pivotal signaling pathways in cancer progression. Moreover, they disrupt pH regulation mechanisms in cancer cells as carbonic anhydrase inhibitors, inhibiting growth, and survival. Sulfonamides also serve as aromatase inhibitors, interfering with estrogen synthesis in hormone-driven cancers. Inhibition of matrix metalloproteinases presents an opportunity to impede cancer cell invasion and metastasis. Additionally, their emerging role as histone deacetylase inhibitors offers promising prospects in epigenetic-based cancer therapies. These diverse roles underscore sulfonamides as invaluable tools for innovative anti-cancer treatments, warranting further exploration for enhanced clinical applications and patient outcomes.

Nonacidic thiophene-based derivatives as potential analgesic and design, synthesis, biological evaluation, and metabolic stability study.

Nonsteroidal anti-inflammatory drugs represent one of the most popularly used classes of drugs. However, their long-term administration is associated with various side effects including gastrointestinal ulceration. One of the major reasons of NSAIDs ulcerogenicity is direct damage of the epithelial lining cells by the acidic moieties present in many drugs. Another drawback for this acidic group is its rapid metabolism and clearance through Phase II conjugation. Three series of thiophene and thienopyrimidine derivatives were designed and synthesized as nonacidic anti-inflammatory agents. In vivo testing of their analgesic activity indicated that compounds 2b and 7a-d showed higher PI values than that of the positive control drugs, indomethacin and celecoxib. The latter compounds 2b and 7a-d were subjected to further anti-inflammatory activity testing where they showed comparable percentage edema inhibition to that of indomethacin and celecoxib. Compounds 2b, 7a, 7c, and 7d inhibited PGE2 synthesis by 61.10%-74.54% (71.47% for indomethacin, and 80.11% for celecoxib). The same compounds inhibited the expression of rat mPGES-1 and cPGES3 by 74%-83% (77% for indomethacin, and 82% for celecoxib) and 48%-70% (62% for indomethacin, and 70% for celecoxib), respectively. The stability of the most active compound 2b in Nonenzymatic gastrointestinal fluids and in human plasma was tested. Additionally, studying the metabolic stability of compound 2b in S9 rat liver fraction showed that it displayed a slow in vitro clearance with half-life time 1.5-fold longer than indomethacin. The metabolites of 2b were predicted via UPLC-MS/MS. In silico ADMET profiling study was also included.

Spectrophotometric determination of olanzapine, fluoxetine HCL and its impurity using univariate and chemometrics methods reinforced by latin hypercube sampling: Validation and eco-friendliness assessments.

Novel univariate and chemometrics-aided UV spectrophotometric methods were tailored to undergo the fundamentals of green and white analytical chemistry for the simultaneous estimation of a ternary mixture of olanzapine (OLA), fluoxetine HCL (FLU), and its toxic impurity 4-(Trifluoromethyl) phenol (FMP) without any prior separation. The dual-wavelength ratio spectrum univariate method was used to determine OLA and FLU in the presence of FMP in the range of (4-20) and (5-50) µg/ml, respectively. In compliance with the International Conference on Harmonization (ICH) standards, the technique was validated and established Remarkable accuracy (98-102%) and precision (< 2%) with limits of quantification (LOQs) of 0.432 and 2.002 µg/ml, respectively. Partial least squares (PLS) and artificial neural networks (ANNs) are chemometric methodologies that have advantages over the univariate method and use significant innovations employing Latin hypercube sampling (LHS), allowing the generation of a reliable validation set to guarantee the effectiveness and sustainability of these models. The concentration ranges used were (2-20), (2-20), and (5-50) µg/ml; for PLS, the LOQs were 0.602, 0.508, and 1.429 µg/ml, and the root mean square errors of prediction (RMSEPs) were 0.087, 0.048, and 0.159 for OLA, FMP, and FLU, respectively; and for ANNs, the LOQs were 0.551, 0.465, and 0.965 µg/ml, with RMSEPs of 0.056, 0.047, and 0.087 for OLA, FMP, and FLU, respectively. The developed methods yield a greener National Environmental Methods Index (NEMI) with an eco-scale assessment (ESA) score of 90 and a complementary Green Analytical Procedure Index (complex GAPI) in quadrants with an analytical greenness metric (AGREE) score of 0.8. The Red‒Green-Blue 12 algorithm (RGB 12) scored 88.9, outperforming on reported methods and demonstrating widespread practical and environmental approval. Statistical analysis revealed no noteworthy differences (P > 0.05) among the proposed and published techniques. Both pure powders and pharmaceutical capsules were analyzed via these methods.