TY - JOUR

T1 - Artificial Intelligence and Cheminformatics-Guided Modern Privileged Scaffold Research

AU - Qiu, Han-Yue

AU - Clausen, Rasmus Praetorius

AU - He, Yun

AU - Zhu, Hai-Liang

PY - 2021

Y1 - 2021

N2 - 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.

AB - 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.

KW - Artificial intelligence

KW - Machine learning

KW - Deep learning

KW - Cheminformatics

KW - Privileged scaffold

KW - Drug discovery

U2 - 10.2174/1568026621666210512020434

DO - 10.2174/1568026621666210512020434

M3 - Review

C2 - 33982652

VL - 21

SP - 2593

EP - 2608

JO - Current Topics in Medicinal Chemistry

JF - Current Topics in Medicinal Chemistry

SN - 1568-0266

IS - 28

ER -