Suppr超能文献

药物-靶标相互作用预测的计算模型开发:综述。

Computational Model Development of Drug-Target Interaction Prediction: A Review.

机构信息

College of Computer Science, Shenyang Aerospace University, Shenyang, 110136, China.

School of Mathematics, Liaoning University, Shenyang, 110036, China.

出版信息

Curr Protein Pept Sci. 2019;20(6):492-494. doi: 10.2174/1389203720666190123164310.

Abstract

In the medical field, drug-target interactions are very important for the diagnosis and treatment of diseases, they also can help researchers predict the link between biomolecules in the biological field, such as drug-protein and protein-target correlations. Therefore, the drug-target research is a very popular study in both the biological and medical fields. However, due to the limitations of manual experiments in the laboratory, computational prediction methods for drug-target relationships are increasingly favored by researchers. In this review, we summarize several computational prediction models of the drug-target connections during the past two years, and briefly introduce their advantages and shortcomings. Finally, several further interesting research directions of drug-target interactions are listed.

摘要

在医学领域,药物-靶标相互作用对于疾病的诊断和治疗非常重要,它们还可以帮助研究人员预测生物领域中生物分子之间的联系,如药物-蛋白和蛋白-靶标相关性。因此,药物-靶标研究在生物和医学领域都是非常热门的研究方向。然而,由于实验室中手动实验的局限性,药物-靶标关系的计算预测方法越来越受到研究人员的青睐。在这篇综述中,我们总结了过去两年中几种药物-靶标连接的计算预测模型,并简要介绍了它们的优缺点。最后,列出了几个药物-靶标相互作用的进一步有趣的研究方向。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验