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DRAR-CPI: a server for identifying drug repositioning potential and adverse drug reactions via the chemical–protein interactome

机译:DRAR-CPI:通过化学-蛋白质相互作用组识别药物重新定位潜力和药物不良反应的服务器

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摘要

Identifying new indications for existing drugs (drug repositioning) is an efficient way of maximizing their potential. Adverse drug reaction (ADR) is one of the leading causes of death among hospitalized patients. As both new indications and ADRs are caused by unexpected chemical–protein interactions on off-targets, it is reasonable to predict these interactions by mining the chemical–protein interactome (CPI). Making such predictions has recently been facilitated by a web server named DRAR-CPI. This server has a representative collection of drug molecules and targetable human proteins built up from our work in drug repositioning and ADR. When a user submits a molecule, the server will give the positive or negative association scores between the user’s molecule and our library drugs based on their interaction profiles towards the targets. Users can thus predict the indications or ADRs of their molecule based on the association scores towards our library drugs. We have matched our predictions of drug–drug associations with those predicted via gene-expression profiles, achieving a matching rate as high as 74%. We have also successfully predicted the connections between anti-psychotics and anti-infectives, indicating the underlying relevance of anti-psychotics in the potential treatment of infections, vice versa. This server is freely available at http://cpi.bio-x.cn/drar/.
机译:识别现有药物的新适应症(重新定位药物)是最大限度地发挥其潜力的有效方法。药物不良反应(ADR)是住院患者死亡的主要原因之一。由于新的适应症和ADR都是由于脱靶分子上意外的化学-蛋白质相互作用引起的,因此通过挖掘化学-蛋白质相互作用组(CPI)预测这些相互作用是合理的。最近,通过名为DRAR-CPI的Web服务器促进了做出此类预测。该服务器具有代表性的药物分子和可靶向人类蛋白质的集合,这些分子是根据我们在药物重新定位和ADR中的工作而建立的。当用户提交分子时,服务器将根据用户分子与我们的库药物对靶标的相互作用情况给出正或负的关联分数。因此,用户可以根据与我们的图书馆药物的关联得分来预测其分子的适应症或ADR。我们将药物-药物关联的预测与通过基因表达谱预测的预测相匹配,匹配率高达74%。我们还成功地预测了抗精神病药和抗感染药之间的联系,表明了抗精神病药在潜在的感染治疗中的潜在相关性,反之亦然。该服务器可从http://cpi.bio-x.cn/drar/免费获得。

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