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Updated: Jun 18, 2025
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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules
Published on: July 25, 2013
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Progress in the application of artificial intelligence in molecular generation models based on protein structure
Chengcheng Xu1, Lidan Zheng1, Qing Fan1
1Laboratory of Molecular Design and Drug Discovery, School of Science, China Pharmaceutical University, 639 Longmian Avenue, Nanjing, 211198, China.
European Journal of Medicinal Chemistry
|August 4, 2024
Summary
This study reviews artificial intelligence (AI) molecular generation models using protein structures for drug discovery. It categorizes models, details their design, and discusses future opportunities and challenges in this AI-driven field.
Area of Science:
- Computational chemistry and bioinformatics
- Artificial intelligence in drug discovery
Background:
- Molecular generation models are advancing drug discovery.
- Protein structure-based approaches are a novel research direction.
Purpose of the Study:
- To summarize research methods and developments in protein structure-based molecular generation models.
- To provide a framework for future model development.
Main Methods:
- Categorization of molecular generation models based on protein structures.
- Analysis of architectural frameworks.
- Detailed examples of model design and implementation.
Main Results:
- Overview of various protein structure-based molecular generation models.
- Identification of key architectural components.
- Discussion of practical applications and design considerations.
Conclusions:
- Protein structure-based molecular generation is a promising AI-driven approach for drug discovery.
- Further research is needed to address current challenges and unlock full potential.
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