Suppr超能文献

基于苯并噻唑-2-胺衍生物的设计,作为镇痛和抗炎药物。

based Designing of benzothiazol-2-amine Derivatives as Analgesic and Anti-inflammatory Agents.

机构信息

Central Facility of Instrumentation, SOS School of Pharmacy, IFTM University, 244001, Moradabad, India.

Department of Pharmacognosy, College of Pharmacy, King Khalid University, Abha, 62529, Saudi Arabia.

出版信息

Antiinflamm Antiallergy Agents Med Chem. 2024;23(4):230-260. doi: 10.2174/0118715230296273240725065839.

Abstract

BACKGROUND

Benzo[d]thiazoles represent a significant class of heterocyclic compounds renowned for their diverse pharmacological activities, including analgesic and antiinflammatory properties. This molecular scaffold holds substantial interest among medicinal chemists owing to its structural versatility and therapeutic potential. Incorporating the benzo[d]thiazole moiety into drug molecules has been extensively investigated as a strategy to craft novel therapeutics with heightened efficacy and minimized adverse effects.

AIMS

The aim of the present research work was to design, synthesize and characterize the new benzo[d]thiazol-2-amine derivatives as potent analgesic and anti-inflammatory agents.

MATERIALS AND METHODS

The synthesis of the presented benzo[d]thiazol-2-amine derivatives was performed by condensing-(4-chlorobenzylidene) benzo[d]thiazol-2-amine with a number of substituted phenols in the presence of potassium iodide and anhydrous potassium carbonate in dry acetone. IR spectroscopy, 1HNMR spectroscopy, 13CNMR spectroscopy and Mass spectroscopy methods were used to characterize the structural properties of all 13 newly synthesized derivatives. The molecular properties of these newly synthesized derivatives were estimated to study the attributes of drug-like candidates. Benzo[d]thiazol-2-amine derivatives were molecularly docked with selective enzymes COX-1 and COX-2. Analgesic and anti-inflammatory activities of synthesized compounds were evaluated by using albino rats.

RESULTS

Findings of the research suggested that compounds G3, G4, G6, G8 and G11 possess higher binding affinity than diclofenac sodium, when docking was performed with enzyme COX-1. Compounds G1, G3, G6, G8 and G10 showed lower binding affinity than Indomethacin when docking was performed with enzyme COX-2. evaluation of the COX-1 and COX-2 enzyme inhibitory activities was performed for synthesized compounds.

DISCUSSION

Compounds G10 and G11 exhibited significant COX-1 and COX-2 enzyme inhibitory action with an IC value of 5.0 and 10 μM, respectively. Using the hot plate method and the carrageenan-induced rat paw edema model, the synthesized compounds were screened for their biological activities, including analgesic and anti-inflammatory activities. Highest analgesic action was exhibited by derivative G11 and the compound G10 showed the highest anti-inflammatory response. Inhibition of COX may be considered as a mechanism of action of these compounds.

CONCLUSION

It was concluded that synthesized derivatives G10 and G11 exhibited significant analgesic and anti-inflammatory effect; therefore, the said compounds may be subjected to further clinical investigation for establishing these as future compounds for the treatment of pain and inflammation.

摘要

背景

苯并[d]噻唑是一类具有重要意义的杂环化合物,以其多种药理学活性而闻名,包括镇痛和抗炎特性。由于其结构的多功能性和治疗潜力,这种分子支架在药物化学家中间引起了极大的兴趣。将苯并[d]噻唑部分纳入药物分子中,已被广泛研究作为一种策略,以制造具有更高疗效和最小不良反应的新型治疗药物。

目的

本研究工作的目的是设计、合成和表征新型苯并[d]噻唑-2-胺衍生物作为有效的镇痛和抗炎剂。

材料和方法

通过在干燥的丙酮中用碘化钾和无水碳酸钾使-(4-氯亚苄基)苯并[d]噻唑-2-胺与一系列取代的苯酚缩合,合成了所提出的苯并[d]噻唑-2-胺衍生物。使用红外光谱、1HNMR 光谱、13CNMR 光谱和质谱方法对所有 13 种新合成的衍生物的结构性质进行了表征。估计这些新合成衍生物的分子性质,以研究类药候选物的属性。用选择性酶 COX-1 和 COX-2 对苯并[d]噻唑-2-胺衍生物进行分子对接。用白化大鼠评估合成化合物的镇痛和抗炎活性。

结果

研究结果表明,当与酶 COX-1 对接时,化合物 G3、G4、G6、G8 和 G11 比双氯芬酸钠具有更高的结合亲和力。当与酶 COX-2 对接时,化合物 G1、G3、G6、G8 和 G10 的结合亲和力低于吲哚美辛。对合成化合物进行了 COX-1 和 COX-2 酶抑制活性的评价。

讨论

化合物 G10 和 G11 对 COX-1 和 COX-2 酶具有显著的抑制作用,其 IC 值分别为 5.0 和 10 μM。用热板法和角叉菜胶诱导的大鼠足肿胀模型对合成化合物进行了生物活性筛选,包括镇痛和抗炎活性。衍生物 G11 表现出最强的镇痛作用,化合物 G10 表现出最强的抗炎反应。抑制 COX 可能被认为是这些化合物的作用机制。

结论

综上所述,合成衍生物 G10 和 G11 表现出显著的镇痛和抗炎作用;因此,这些化合物可能会进一步进行临床研究,以确定它们是否可以作为治疗疼痛和炎症的未来化合物。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验