新药开发一直面临着高投入低产出的困境.药物重定位(drug repositioning)是解决这一问题的有效方法,因而成为现今药物研究的热点之一.目前流行的方法主要是基于药物小分子的相似性或关联性(化学结构、副作用、表达谱和小分子-蛋白作用关系等),预测药物的新功能.由于仅仅依赖药物-药物之间的关系,这些新功能限制在现有药物的功能空间之内.本研究中提出一种以疾病为导向,基于pathway谱的药物-疾病关联性评估方法来预测药物的新功能.考虑到药物在临床应用中除了作用于预先设定的主要治疗靶点以外,还能作用于其他一些额外的靶点,而这往往是产生副作用或是新的治疗功能的原因.该方法充分利用药物的已有靶点信息,认为药物通过作用于多条疾病相关蛋白影响的pathway,达到调节疾病的病理过程的目的.以2010年全球最热销的8个药做测试,美国食品药品监督管理局(Food and Drug Administration,FDA)批准的主治功能排在前10的位置,超过60%的预测功能可以得到文献的直接支持.它可以作为以往方法的有效补充,为药物的重定位以及毒副作用评估提供一种新的视角.
Finding new applications for existing pharmaceuticals,known as drug repositioning,is a validated strategy for resolving the problem of high expenditure but low productivity in drug discovery.Currently,the prevalent computational methods for drug repositioning are focused mainly on the similarity or relevance between known drugs based on their "features",including chemical structure,side effects,gene expression profile,and/or chemical-protein interactome.However,such drug-oriented methods may constrain the newly predicted functions to the pharmacological functional space of the existing drugs.Clinically,many drugs have been found to bind "off-target"(i.e.to receptors other than their primary targets),which can lead to undesirable effects.In this study,which integrates known drug target information,we propose a disease-oriented strategy for evaluating the relationship between drugs and disease based on their pathway profile.The basic hypothesis of this method is that drugs exerting a therapeutic effect may not only directly target the disease-related proteins but also modulate the pathways involved in the pathological process.Upon testing eight of the global best-selling drugs in 2010(each with more than three targets),the FDA(Food and Drug Administration,USA)-approved therapeutic function of each was included in the top 10 predicted indications.On average,60% of predicted results made using our method are proved by literature.This approach could be used to complement existing methods and may provide a new perspective in drug repositioning and side effect evaluation.
Investigation of the potential therapeutic mechanisms of drug candidates is an essential step in the process of new drug discovery.With the rapid development of systems biology,recent network analyses of proteins,drugs,and diseases have enabled great progress in delineating the molecule mechanisms of drug candidates.However,most analyses perform a direct association between gene/protein and disease levels without considering the intermediate biological pathways regulated by the drugs.Given that a protein performs its biological roles through pathways,we propose using a novel pathway-pathway network analysis to investigate the potential therapeutic functions of the drug candidates.Many studies have demonstrated that salvianolic acid B(SalB) of Salvia miltiorrhiza is an effective therapy for cardiovascular diseases(CVD).Using molecular docking methods to identify direct interacting targets of Sal B,we collected all Sal B-regulated proteins with supporting experimental evidence in PubMed abstracts.FDA-approved CVD drugs and their corresponding targets were also collected.From a traditional drug-protein network analysis,we found that Sal B could affect ACE and REN of the renin-angiotensin-aldosterone system to relax vessels and alleviate hypertension.Subsequent pathway-pathway network analysis was attempted to study the mechanisms of Sal B in treating CVD,and demonstrated that Sal B regulates immunity/inflammation,apoptosis,ion transport and basic metabolism processes in the treatment of CVD.Regulating the immune/inflammation process may be the major mechanism of Sal B.We believe that pathwaypathway network analysis is a novel method for studying the therapeutic mechanisms of herbal ingredients.
YE LiHE YuanYE HaoLIU XuePingYANG LinLinCAO ZhiWeiTANG KaiLin
Drugs sharing similar therapeutic function may not bind to the same group of targets.However,their targets may be involved in similar pathway profiles which are associated with certain pathological process.In this study,pathway fingerprint was introduced to indicate the profile of significant pathways being influenced by the targets of drugs.Then drug−drug network was further constructed based on significant similarity of pathway fingerprints.In this way,the functions of a drug may be hinted by the enriched therapeutic functions of its neighboring drugs.In the test of 911 FDA approved drugs with more than one known target,471 drugs could be connected into networks.760 significant associations of drug−therapeutic function were generated,among which around 60%of them were supported by scientific literatures or ATC codes of drug functional classification.Therefore,pathway fingerprints may be useful to further study on the potential function of known drugs,or the unknown function of new drugs.
