mlsanityData to 14 Oct 2026

A Survey of Generative AI for de novo Drug Design: New Frontiers in Molecule and Protein Generation

arXiv 2402.08703 ↗First posted 13 Feb 2024q-bio.BM cs.AI cs.LGcited by 29

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Abstract (arXiv)

Artificial intelligence (AI)-driven methods can vastly improve the historically costly drug design process, with various generative models already in widespread use. Generative models for de novo drug design, in particular, focus on the creation of novel biological compounds entirely from scratch, representing a promising future direction. Rapid development in the field, combined with the inherent complexity of the drug design process, creates a difficult landscape for new researchers to enter. In this survey, we organize de novo drug design into two overarching themes: small molecule and protein generation. Within each theme, we identify a variety of subtasks and applications, highlighting important datasets, benchmarks, and model architectures and comparing the performance of top models. We take a broad approach to AI-driven drug design, allowing for both micro-level comparisons of various methods within each subtask and macro-level observations across different fields. We discuss parallel challenges and approaches between the two applications and highlight future directions for AI-driven de novo drug design as a whole. An organized repository of all covered sources is available at https://github.com/gersteinlab/GenAI4Drug.

Key facts. Cited by 29 papers in the map (data through 14 Oct 2026). Builds on 76 of its 223 references that are in the map. First posted on arXiv 13 Feb 2024.

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76 of 223 references.

References · 76

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Citing papers per year: 2024: 3; 2025: 13; 2026: 13.

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  1. 2025Flow Matching Meets Biology and Life Science: A Surveycited by 14
  2. 2025A Survey of Large Language Models for Text-Guided Molecular Discovery: from Molecule Generation to Optimizationcited by 13
  3. 2026Proteo-R1: Reasoning Foundation Models for De Novo Protein Designcited by 6
  4. 2024MAMMAL -- Molecular Aligned Multi-Modal Architecture and Languagecited by 4
  5. 2025AbFlowNet: Optimizing Antibody-Antigen Binding Energy via Diffusion-GFlowNet Fusioncited by 4
  6. 2025PolyConf: Unlocking Polymer Conformation Generation through Hierarchical Generative Modelscited by 3
  7. 2026Dynamics-inspired Structure Hallucination for Protein-protein Interaction Modelingcited by 3
  8. 2025VALID-Mol: a Systematic Framework for Validated LLM-Assisted Molecular Designcited by 2
  9. 2025An Auditable Agent Platform For Automated Molecular Optimisationcited by 2
  10. 2025SpecMER: Fast Protein Generation with K-mer Guided Speculative Decodingcited by 2
  11. 2025Predictive Feature Caching for Training-free Acceleration of Molecular Geometry Generationcited by 2
  12. 2026Exponential capacity scaling of classical GANs compared to hybrid latent style-based quantum GANscited by 2
17 more
  1. 2024Recent advances in interpretable machine learning using structure-based protein representationscited by 1
  2. 2024REBIND: Enhancing ground-state molecular conformation via force-based graph rewiringcited by 1
  3. 2025DMol: A Highly Efficient and Chemical Motif-Preserving Molecule Generation Platformcited by 1
  4. 2026AFD-INSTRUCTION: A Comprehensive Antibody Instruction Dataset with Functional Annotations for LLM-Based Understanding and Designcited by 1
  5. 2026Foundation-Model Surrogates Enable Data-Efficient Active Learning for Materials Discoverycited by 1
  6. 2026Toward Better Geometric Representations for Molecule Generative Modelscited by 1
  7. 2026Don't Retrain, Just Reuse: Recovering Dual-Target Molecules from Single-Target Diffusion Modelscited by 1
  8. 2025Active Learning-Guided Seq2Seq Variational Autoencoder for Multi-target Inhibitor Generationcited by 0
  9. 2025Attribution assignment for deep-generative sequence models enables interpretability analysis using positive-only datacited by 0
  10. 2025MSCoD: An Enhanced Bayesian Updating Framework with Multi-Scale Information Bottleneck and Cooperative Attention for Structure-Based Drug Designcited by 0
  11. 2025seqme: a Python library for evaluating biological sequence designcited by 0
  12. 2026Logos: An evolvable reasoning engine for rational molecular designcited by 0
  13. 2026Latent Style-based Quantum Wasserstein GAN for Drug Designcited by 0
  14. 2026Rethinking Scientific Discovery in the Agentic Eracited by 0
  15. 2026CheMLFlow: An Open-Source Platform for Cheminformatics and Materials Informatics Applicationscited by 0
  16. 2026MolBioKG: Grounding Out-of-Graph Molecules in Biomedical Knowledge Graphs via Multi-Resolution Structural Anchoringcited by 0
  17. 2026MARCO: Multi-Round Agentic Reinforcement for Conditional Molecular Optimizationcited by 0