Anti-inflammatory action of new hybrid N-acyl-[1,2]dithiolo-[3,4-c]quinoline-1-thione.

IF 2.3 3区环境科学与生态学 Q3 CHEMISTRY, MULTIDISCIPLINARY

SAR and QSAR in Environmental Research Pub Date : 2024-05-01 Epub Date: 2024-05-22 DOI:10.1080/1062936X.2024.2347965

S M Medvedeva, A Petrou, M Fesatidou, A Gavalas, A A Geronikaki, P I Savosina, D S Druzhilovskiy, V V Poroikov, K S Shikhaliev, V G Kartsev

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引用次数: 0

Abstract

Most of pharmaceutical agents display a number of biological activities. It is obvious that testing even one compound for thousands of biological activities is not practically possible. A computer-aided prediction is therefore the method of choice in this case to select the most promising bioassays for particular compounds. Using the PASS Online software, we determined the probable anti-inflammatory action of the 12 new hybrid dithioloquinolinethiones derivatives. Chemical similarity search in the World-Wide Approved Drugs (WWAD) and DrugBank databases did not reveal close structural analogues with the anti-inflammatory action. Experimental testing of anti-inflammatory activity of the synthesized compounds in the carrageenan-induced inflammation mouse model confirmed the computational predictions. The anti-inflammatory activity of the studied compounds (2a, 3a-3k except for 3j) varied between 52.97% and 68.74%, being higher than the reference drug indomethacin (47%). The most active compounds appeared to be 3h (68.74%), 3k (66.91%) and 3b (63.74%) followed by 3e (61.50%). Thus, based on the in silico predictions a novel class of anti-inflammatory agents was discovered.

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新型混合 N-酰基-[1,2]二硫环戊-[3,4-c]喹啉-1-硫酮的抗炎作用。

大多数药剂都具有多种生物活性。显然，即使对一种化合物进行数千种生物活性的测试，实际上也是不可能的。因此，在这种情况下，计算机辅助预测是为特定化合物选择最有前景的生物测定方法的首选。通过使用 PASS 在线软件，我们确定了 12 种新的混合二硫代喹啉硫醚衍生物可能具有的抗炎作用。在世界批准药物数据库（WWAD）和药物数据库（DrugBank）中进行的化学相似性搜索没有发现具有抗炎作用的近似结构类似物。在角叉菜胶诱导的炎症小鼠模型中对合成化合物的抗炎活性进行的实验测试证实了计算预测。研究化合物（2a、3a-3k，3j 除外）的抗炎活性介于 52.97% 和 68.74% 之间，高于参考药物吲哚美辛（47%）。活性最强的化合物似乎是 3h（68.74%）、3k（66.91%）和 3b（63.74%），其次是 3e（61.50%）。由此可见，根据硅学预测，我们发现了一类新型抗炎药物。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

SAR and QSAR in Environmental Research 环境科学-毒理学

CiteScore

5.20

自引率

20.00%

发文量

审稿时长

>24 weeks

期刊介绍： SAR and QSAR in Environmental Research is an international journal welcoming papers on the fundamental and practical aspects of the structure-activity and structure-property relationships in the fields of environmental science, agrochemistry, toxicology, pharmacology and applied chemistry. A unique aspect of the journal is the focus on emerging techniques for the building of SAR and QSAR models in these widely varying fields. The scope of the journal includes, but is not limited to, the topics of topological and physicochemical descriptors, mathematical, statistical and graphical methods for data analysis, computer methods and programs, original applications and comparative studies. In addition to primary scientific papers, the journal contains reviews of books and software and news of conferences. Special issues on topics of current and widespread interest to the SAR and QSAR community will be published from time to time.