School of Pharmaceutical Sciences and Innovative Drug Research Centre, Chongqing University, Chongqing 401331, China.
Department of Drug Design and Pharmacology, Faculty of Health and Medical Sciences, University of Copenhagen, Universitetsparken 2, 2100 Copenhagen, Denmark.
Curr Top Med Chem. 2021;21(28):2593-2608. doi: 10.2174/1568026621666210512020434.
With the rapid development of computer science in scopes of theory, software, and hardware, artificial intelligence (mainly in form of machine learning and more complex deep learning) combined with advanced cheminformatics is playing an increasingly important role in drug discovery process. This development has also facilitated privileged scaffold-related research. By definition, a privileged scaffold is a structure that frequently occurs in diverse bioactive molecules, either has a diverse family affinity or is selective to multiple family members in a superfamily, whilst it is different from the"frequent hitters", or the "pan-assay interference compounds". The long history of the use of this concept has witnessed a functional shift from stand-alone technology towards an integrated component in the drug discovery toolbox. Meanwhile, continuous efforts have been dedicated to deepening the understandings of the features of known privileged scaffolds. In this contribution, we focus on the current privileged scaffold-related research driven by state-of-art artificial intelligence approaches and cheminformatics. Representative cases with an emphasis on distinct research aspects are presented, including an update of the knowledge on privileged scaffolds, proofof- concept tools, and workflows to identify privileged scaffolds and to carry on de novo design, informatic SAR models with diversely complex data sets to provide an instructive prediction on new potential molecules bearing privileged scaffolds.
随着计算机科学在理论、软件和硬件方面的快速发展，人工智能（主要以机器学习和更复杂的深度学习形式）与先进的化学信息学相结合，在药物发现过程中发挥着越来越重要的作用。这种发展也促进了特权支架相关的研究。根据定义，特权支架是一种在各种生物活性分子中频繁出现的结构，要么具有多样化的家族亲和力，要么对超家族中的多个家族成员具有选择性，而与“频繁命中者”或“泛分析干扰化合物”不同。这一概念的悠久历史见证了它从独立技术向药物发现工具包中的集成组件的功能转变。同时，人们一直在努力加深对已知特权支架特征的理解。在这篇文章中，我们专注于当前由最先进的人工智能方法和化学信息学驱动的特权支架相关研究。重点介绍了具有独特研究方面的代表性案例，包括对特权支架知识的更新、概念验证工具以及识别特权支架和进行从头设计的工作流程，以及使用各种复杂数据集的信息 SAR 模型，为具有特权支架的新潜在分子提供有指导意义的预测。
