115175-17-2

Usage

Uses

Used in Pharmaceutical Research and Development:
3-AMINO-N-(4-CHLOROPHENYL)BENZAMIDE is used as a potential drug candidate for its demonstrated biological activities, including its anticancer and anti-inflammatory properties. It is valued for its ability to target specific biological receptors, making it a subject of interest for the development of new therapeutic agents.
Used in Anticancer Applications:
In the field of oncology, 3-AMINO-N-(4-CHLOROPHENYL)BENZAMIDE is utilized as a compound with potential anticancer properties. Its interaction with biological receptors suggests that it could be developed into a treatment for various types of cancer, potentially offering new avenues for cancer therapy.
Used in Anti-inflammatory Applications:
3-AMINO-N-(4-CHLOROPHENYL)BENZAMIDE is also considered for its anti-inflammatory potential, making it a candidate for the treatment of inflammatory conditions. Its ability to modulate inflammatory responses could lead to the development of new medications for a range of inflammatory diseases.
Used in Drug Design:
Due to its receptor interaction capabilities, 3-AMINO-N-(4-CHLOROPHENYL)BENZAMIDE is used in the design of drugs that target specific biological pathways. This targeted approach can lead to more effective treatments with fewer side effects, as compared to non-specific drugs.

InChI:InChI=1/C13H11ClN2O/c14-10-4-6-12(7-5-10)16-13(17)9-2-1-3-11(15)8-9/h1-8H,15H2,(H,16,17)

Upstream product

• 121-90-4 m-nitrobenzoic acid chloride 
• 121-92-6 3-nitrobenzoic acid 
• 99514-24-6 N-(4-chloro-phenyl)-3-nitro-benzamide 

Downstream Products

• 251446-22-7 5-Acetyl-1-ethyl-2-oxo-2,3-dihydro-1H-indole-3-carboxylic acid [3-(4-chloro-phenylcarbamoyl)-phenyl]-amide 
• 1233188-81-2 3-(2-chloro-acetylamino)-N-(4-chloro-phenyl)-benzamide 
• 1414781-47-7 C₁₄H₁₁ClN₂OS₂*C₆H₁₂N₂ 

Relevant academic research and scientific papers

Synthesis and in Vitro and in Vivo anticoagulant and antiplatelet activities of amidino- and non-amidinobenzamides

Three amidino- and ten non-amidinobenzamides were synthesized as 3-aminobenzoic acid scaffold-based anticoagulant and antiplatelet compounds. The anticoagulant activities of thirteen synthesized compounds 1-13, and 2b and 3b as prodrugs were preliminary evaluated by screening the prolongation of activated partial thromboplastin time (aPTT) and prothrombin time (PT) in vitro. From the aPTT results obtained, two amidinobenzamides, N-(3′-amidinophenyl)-3-(thiophen-2″-ylcarbonylamino) benzamide (1, 33.2 ± 0.7 s) and N-(4′-amidinophenyl)-3-(thiophen-2″-ylcarbonylamino) benzamide (2, 43.5 ± 0.6 s) were selected to investigate the further anticoagulant and antiplatelet activities. The aPTT results of 1 (33.2± 0.7 s) and 2 (43.5 ± 0.6 s) were compared with heparin (62.5 ± 0.8 s) in vitro at 30 μM. We investigated the effect of 1 and 2 on blood anticoagulant activity (ex vivo) and on tail bleeding time (in vivo) on mice. A tail cutting/bleeding time assay revealed that both 1 and 2 prolonged bleeding time in mice at a dose of 24.1 g/mouse and above. Compounds 1 and 2 dose-dependently inhibited thrombin-catalyzed fibrin polymerization and platelet aggregation. In addition, 1 and 2 were evaluated on the inhibitory activities of thrombin and FXa as well as the generation of thrombin and FXa in human umbilical vein endothelial cells (HUVECs). Collectively, 1 and 2 possess some antiplatelet and anticoagulant activities and offer a basis for development of a novel antithrombotic product.

Elaborate ligand-based pharmacophore exploration and QSAR analysis guide the synthesis of novel pyridinium-based potent β-secretase inhibitory leads

β-Secretase (BACE) inhibitors have potential as anti-Alzheimer's disease treatments prompting us to explore the pharmacophoric space of 129 known BACE inhibitors. QSAR analysis was employed to select optimal combination of pharmacophoric models and 2D physicochemical descriptors capable of explaining bioactivity variation (r2 = 0.88, F = 60.48, rLOO2 = 0.85, rPRESS2 against 25 external test inhibitors = 0.71). We were obliged to use ligand efficiency as the response variable because the logarithmic transformation of bioactivities failed to access self-consistent QSAR models. Three pharmacophoric models emerged in the successful QSAR equation suggesting at least three binding modes accessible to ligands within BACE binding pocket. QSAR equation and pharmacophoric models were validated through ROC curves and were employed to guide synthesis of novel pyridinium-based BACE inhibitors. The best inhibitor illustrated an IC50 value of 1.0 μM against BACE.