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AIScaffold: A Web-Based Tool for Scaffold Diversification Using Deep Learning
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DOI：10.1021/acs.jcim.0c00867.png)
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Abstract
En 中文
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 (littps://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.
Keywords:
MOLECULAR DESIGN
SCORING FUNCTION
MODELS
PREDICTION
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