吲哚抑制剂在炎性疾病中增加hnps-PLA2亲和力的研究

Q2 Medicine

In Silico Biology Pub Date : 2010-02-15 DOI:10.1145/1722024.1722056

Amit Nagal, Swapnil R. Jaiswal, H. Yadav, M. Mohan, P. Ghosh

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引用次数: 0

摘要

有许多药物用于治疗炎症疾病，如非甾体抗炎药，但有限制，鼓励更多的研究炎症相关疾病。磷脂酶A2 (PLA2s)是催化磷脂的sn-2酰基酯链水解，产生脂肪酸和溶血磷脂的酶。它们的酶活性是花生四烯酸形成和随后合成白三烯和前列腺素的限速步骤。目前基于结构的药物设计方法对各种hnps-PLA2吲哚抑制剂衍生物的分析和比较对接研究表明，它们与其他分子相比具有更好的作用。ADME研究表明，吲哚衍生物有可能成为一种安全的药物

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Study of indole inhibitors to increase the affinity of hnps-PLA2 in inflammatory disease

There are many Drug used in the treatment of inflammation disease like NSAIDS but there limitation encouraging more research in inflammatory related diseases. Phospholipases A2 (PLA2s) are enzymes that catalyze the hydrolysis of the sn-2 acyl ester linkage of phospholipids, producing fatty acids and lysophospholipids. Their enzymatic activity is a rate-limiting step in the formation of arachidonic acid and subsequently in the synthesis of leukotrienes and prostaglandins. The current Structure Based Drug Designing approach analysis and comparative docking studies of various hnps-PLA2 indole inhibitor derivatives have shown that they act better in compare with other molecules. ADME studies shows that indole derivatives would be potential of being a safe drug

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来源期刊

In Silico Biology Computer Science-Computational Theory and Mathematics

CiteScore

2.20

自引率

0.00%

发文量

期刊介绍： The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.