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Generative AI for the Design of Molecules: Advances and Challenges.

Yan Sun^1,2, Lianghong Chen², Zihao Jing²

¹Department of Biochemistry, University of Western Ontario, London, Ontario N6A 5C1, Canada.

Journal of Chemical Information and Modeling

|November 18, 2025

Summary

Generative artificial intelligence (AI) enables de novo molecular design for drug discovery and biomaterials. This review highlights AI architectures, applications, and future challenges for creating novel molecules with desired properties.

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Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Protein WISDOM: A Workbench for In silico De novo Design of BioMolecules

Published on: July 25, 2013

Area of Science:

Chemistry, Computer Science, Bioinformatics

Background:

Traditional molecular design methods are costly and inefficient.
Predictive machine learning models have limitations in precision medicine.
Generative AI offers a paradigm shift for de novo molecular creation.

Purpose of the Study:

To survey the rapidly evolving field of generative AI for molecular design.
To introduce generative architectures and optimization strategies.
To examine applications and challenges in AI-driven molecular design.

Main Methods:

Review of generative AI architectures (VAEs, GANs, normalizing flows, diffusion models).
Analysis of optimization strategies (sampling, training, postgeneration).
Examination of applications in small and large molecule design.

Main Results:

Generative AI demonstrates unprecedented capabilities in designing molecules with complex requirements.
AI-driven discovery of novel antibiotics with in vivo efficacy showcases translational potential.
Key challenges and future directions for generative molecular design are identified.

Conclusions:

Generative AI is revolutionizing molecular design for drug discovery and biomaterials.
Addressing challenges like data scarcity and multimodal fusion is crucial for future advancements.
Optimizing multiple objectives with uncertainty-aware strategies will enhance molecular design systems.