A 3D pocket-aware and evolutionary conserved interaction guided diffusion model for molecular optimization

2025/05/09 by Qiao, Anjie, Hao Zhang, Qianmu Yuan +16
Biochemistry, Genetics and Molecular Biology · Computer Science · Medicine · #Biomolecules (q-bio.BM) #Chemical Physics (physics.chem-ph) #Computational Drug Discovery Methods #FOS: Biological sciences #FOS: Computer and information sciences #FOS: Physical sciences #Gene Regulatory Network Analysis #Machine Learning (cs.LG) #Monoclonal and Polyclonal Antibodies Research

paper · pdf · doi:10.48550/arxiv.2505.05874

openalex publication_date 2025/05/09 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Generating molecules that bind to specific protein targets via diffusion models has shown good promise for structure-based drug design and molecule optimization. Especially, the diffusion models with binding interaction guidance enables molecule generation with high affinity through forming favorable interaction within protein pocket. However, the generated molecules may not form interactions with the highly conserved residues, which are important for protein functions and bioactivities of the ligands. Herein, we developed a new 3D target-aware diffusion model DiffDecip, which explicitly incorporates the protein-ligand binding interactions and evolutionary conservation information of protein residues into both diffusion and sampling process, for molecule optimization through scaffold decoration. The model performance revealed that DiffDecip outperforms baseline model DiffDec on molecule optimization towards higher affinity through forming more non-covalent interactions with highly conserved residues in the protein pocket.

Citations

• DecompDiff: Diffusion Models with Decomposed Priors for Structure-Based Drug Design
• Improving protein expression, stability, and function with ProteinMPNN
• 3D Equivariant Diffusion for Target-Aware Molecule Generation and Affinity Prediction
• DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding
• Structure-based Drug Design with Equivariant Diffusion Models
• Equivariant 3D-Conditional Diffusion Models for Molecular Linker Design
• Flow Matching for Generative Modeling
• ColabFold: making protein folding accessible to all
• A 3D Generative Model for Structure-Based Drug Design
• Improving language models by retrieving from trillions of tokens
• Variational Diffusion Models
• Score-Based Generative Modeling through Stochastic Differential Equations
• Denoising Diffusion Probabilistic Models
• Deep Unsupervised Learning using Nonequilibrium Thermodynamics

Related

• A 3D pocket-aware and affinity-guided diffusion model for lead optimization
• BInD: Bond and Interaction-generating Diffusion Model for Multi-objective Structure-based Drug Design
• Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization
• Binding-Adaptive Diffusion Models for Structure-Based Drug Design
• DiffBP: Generative Diffusion of 3D Molecules for Target Protein Binding