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DPDR-CPI, a server that predicts Drug Positioning and Drug Repositioning via Chemical-Protein Interactome

机译:DPDR-CPI,一种通过化学蛋白蛋白酶预测药物定位和药物重新定位的服务器

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The cost of developing a new drug has increased sharply over the past years. To ensure a reasonable return-on-investment, it is useful for drug discovery researchers in both industry and academia to identify all the possible indications for early pipeline molecules. For the first time, we propose the term computational "drug candidate positioning" or "drug positioning", to describe the above process. It is distinct from drug repositioning, which identifies new uses for existing drugs and maximizes their value. Since many therapeutic effects are mediated by unexpected drug-protein interactions, it is reasonable to analyze the chemical-protein interactome (CPI) profiles to predict indications. Here we introduce the server DPDR-CPI, which can make real-time predictions based only on the structure of the small molecule. When a user submits a molecule, the server will dock it across 611 human proteins, generating a CPI profile of features that can be used for predictions. It can suggest the likelihood of relevance of the input molecule towards ~1,000 human diseases with top predictions listed. DPDR-CPI achieved an overall AUROC of 0.78 during 10-fold cross-validations and AUROC of 0.76 for the independent validation. The server is freely accessible via http://cpi.bio-x.cn/dpdr/.
机译:在过去几年中,开发新药的成本急剧增加。为确保合理的投资回报,它对工业和学术界的药物发现研究人员有用,以确定早期管道分子的所有可能的适应症。我们首次提出术语计算“药物候选定位”或“药物定位”,以描述上述过程。它与药物重新定位不同,这识别出现有药物的新用途,并最大限度地提高其价值。由于许多治疗效果是由意外的药物 - 蛋​​白质相互作用介导的,因此分析化学蛋白质互联蛋白酶(CPI)型材以预测适应症是合理的。在这里,我们介绍了服务器DPDR-CPI,其只能在小分子的结构上基于实时预测。当用户提交分子时,服务器将跨611个人蛋白播放,生成可用于预测的功能的CPI分布。它可以建议输入分子与最高预测中的输入分子对〜1,000人疾病的相关性。 DPDR-CPI在10倍的交叉验证期间实现了0.78的整体氧化氢,为独立验证的0.76的Auroc。通过http://cpi.bio-x.cn/dpdr/可以自由访问服务器。

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