AIScaffold: A Web-Based Tool for Scaffold Diversification Using Deep Learning.

Journal: Journal of chemical information and modeling
Published Date: Dec 28, 2020

Abstract

Molecular scaffolds are widely used in drug design. Many methods and tools have been developed to utilize the information in scaffolds. Scaffold diversification is frequently used by medicinal chemists in tasks such as lead compound optimization, but tools for scaffold diversification are still lacking. Here, we propose AIScaffold (https://iaidrug.stonewise.cn), a web-based tool for scaffold diversification using the deep generative model. This tool can perform large-scale (up to 500,000 molecules) diversification in several minutes and recommend the top 500 (top 0.1%) molecules. Features such as site-specific diversification are also supported. This tool can facilitate the scaffold diversification process for medicinal chemists, thereby accelerating drug design.

Authors

  • Junyong Lai
    State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, Beijing 100191, P. R. China.
  • Xiangbin Li
    Stonewise, No. 19 Zhongguancun Street, Haidian District, 100080 Beijing, P. R. China.
  • Yanxing Wang
    State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, 100191 Beijing, P. R. China.
  • Shiqiu Yin
    Stonewise, No. 19 Zhongguancun Street, Haidian District, 100080 Beijing, P. R. China.
  • Jielong Zhou
    Stonewise , Haidian Middle Street 15 , Haidian District, 100080 Beijing , China.
  • Zhenming Liu
    State Key Laboratory of Natural and Biomimetic Drugs, School of Pharmaceutical Sciences, Peking University, 100191 Beijing, P. R. China.

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