在当前的生物大数据时代,它们正在迅速填充生物化学空间,电子多药理学药物设计方法有助于解码结构-多活性关系(SMARts)。当前的计算方法可以同时预测或分类多个属性,帮助了一代人,identification,策展,优先次序,优化,和分子的再利用。计算方法在药物化学中产生了机遇和挑战,药理学,食品化学,毒理学,生物信息学,和化学信息学。预计计算机引导的SMARts可以促进药物设计和药物再利用活动的完全自动化,促进新生物靶标的预测,副作用和脱靶效果,和药物-药物相互作用。
In the current era of biological big data, which are rapidly populating the biological chemical space, in silico polypharmacology drug design approaches help to decode structure-multiple activity relationships (SMARts). Current computational methods can predict or categorize multiple properties simultaneously, which aids the generation, identification, curation, prioritization, optimization, and repurposing of molecules. Computational methods have generated opportunities and challenges in medicinal chemistry, pharmacology, food chemistry, toxicology, bioinformatics, and
chemoinformatics. It is anticipated that computer-guided SMARts could contribute to the full automatization of drug design and drug repurposing campaigns, facilitating the prediction of new biological targets, side and off-target effects, and drug-drug interactions.