MacroGuide: Topological Guidance for Macrocycle Generation
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Abstract (arXiv)
Macrocycles are ring-shaped molecules that offer a promising alternative to small-molecule drugs due to their enhanced selectivity and binding affinity against difficult targets. Despite their chemical value, they remain underexplored in generative modeling, likely owing to their scarcity in public datasets and the challenges of enforcing topological constraints in standard deep generative models. We introduce MacroGuide: Topological Guidance for Macrocycle Generation, a diffusion guidance mechanism that uses Persistent Homology to steer the sampling of pretrained molecular generative models toward the generation of macrocycles, in both unconditional and conditional (protein pocket) settings. At each denoising step, MacroGuide constructs a Vietoris-Rips complex from atomic positions and promotes ring formation by optimizing persistent homology features. Empirically, applying MacroGuide to pretrained diffusion models increases macrocycle generation rates from 1% to 99%, while matching or exceeding state-of-the-art performance on key quality metrics such as chemical validity, diversity, and PoseBusters checks.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 30 of its 61 references that are in the map. First posted on arXiv 16 Feb 2026.
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30 of 61 references.
References · 30
- 2020Denoising Diffusion Probabilistic Modelscited by 20,851
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18 more
- 2024Gradient Guidance for Diffusion Models: An Optimization Perspectivecited by 59
- 2023Navigating the Design Space of Equivariant Diffusion-Based Generative Models for De Novo 3D Molecule Generationcited by 50
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- 2026Generating Cyclic Conformers with Flow Matching in Cremer-Pople Coordinatescited by 2
- 2025Topology Guidance: Controlling the Outputs of Generative Models via Vector Field Topologycited by 1
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- 2025DMol: A Highly Efficient and Chemical Motif-Preserving Molecule Generation Platform
- 2025MolGuidance: Advanced Guidance Strategies for Conditional Molecular Generation with Flow Matching
- 2025SynCoGen: Synthesizable 3D Molecule Generation via Joint Reaction and Coordinate Modeling
- 2025A collaborative constrained graph diffusion model for the generation of realistic synthetic molecules
- 2026Equivariant Asynchronous Diffusion: An Adaptive Denoising Schedule for Accelerated Molecular Conformation Generation
- 2025SiDGen: Structure-informed Diffusion for Generative modeling of Ligands for Proteins
- 2025Chain-of-Generation: Progressive Latent Diffusion for Text-Guided Molecular Design