计算分析预测药物靶点用于... 的治疗管理

Computational Analysis to Predict Drug Targets for the Therapeutic Management of sub. .

机构信息

Department of Biotechnology, Institute of Applied Sciences & Humanities, GLA University, Mathura (U.P.), India.

Department of Botany, Babu Shivnath Agrawal College, Mathura (U.P.), India.

出版信息

Curr Drug Discov Technol. 2023;20(4):e100323214551. doi: 10.2174/1570163820666230310140613.

DOI:10.2174/1570163820666230310140613

PMID:36896903

Abstract

BACKGROUND

Mycobacterium avium sp. paratuberculosis (MAP) is a pathogen, which causes paratuberculosis in animals; it has also been found to be associated with a number of autoimmune disorders in humans. The emergence of drug resistance has also been found in this bacillus during disease management.

OBJECTIVE

The present study's focus was to identify potential therapeutic targets for the therapeutic management of Mycobacterium avium sp. paratuberculosis infection by in silico analysis.

METHODS

Differentially-expressed genes (DEGs) can be good drug targets, which can be identified from microarray studies. We used gene expression profile GSE43645 to identify differentiallyexpressed genes. An integrated network of upregulated DEGs was constructed with the STRING database and the constructed network was analyzed and visualized by Cytoscape. Clusters in the proteinprotein interaction (PPI) network were identified by the Cytoscape app ClusterViz. MAP proteins predicted in clusters were analyzed for their non-homology with the human proteins, and homologous proteins were excluded. Essential proteins and cellular localization analysis and the physicochemical characteristics prediction were also done. Finally, the druggability of the target proteins and drugs that can block the targets was predicted using the DrugBank database and confirmed by molecular docking. Structural prediction and verification of drug target proteins were also carried out.

RESULTS

Two drug targets, MAP_1210 (inhA) and MAP_3961 (aceA), encoding enoyl acyl carrier protein reductase and isocitrate lyase enzymes, respectively, were finally predicted as potential drug targets.

CONCLUSION

Both of these proteins have been predicted as drug targets in other mycobacterial species also, supporting our results. However, further experiments are required to confirm these results.

摘要

背景

禽分枝杆菌副结核亚种（MAP）是一种病原体，可引起动物副结核病；还发现它与人类的许多自身免疫性疾病有关。在疾病管理过程中，这种杆菌也出现了耐药性。

目的

本研究通过计算机分析，旨在确定禽分枝杆菌副结核亚种感染治疗管理的潜在治疗靶点。

方法

差异表达基因（DEGs）可以作为药物靶点，可从基因表达谱研究中识别。我们使用基因表达谱 GSE43645 来识别差异表达基因。使用 STRING 数据库构建上调 DEGs 的综合网络，并通过 Cytoscape 分析和可视化构建的网络。使用 Cytoscape 应用程序 ClusterViz 识别蛋白质-蛋白质相互作用（PPI）网络中的簇。分析簇中预测的 MAP 蛋白与人类蛋白的非同源性，并排除同源蛋白。还进行了必需蛋白和细胞定位分析以及理化特性预测。最后，使用 DrugBank 数据库预测目标蛋白的药物可及性和可阻断靶点的药物，并通过分子对接进行验证。还进行了药物靶蛋白的结构预测和验证。