ArticleACS omega2025
Improving Stereochemical Limitations in Protein-Ligand Complex Structure Prediction.
Article in ACS omega, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
What it found
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Who cites it
10 citing papers in PubMed.
- On the generalization and usability of cofolding models for GPCR drug discovery.npj drug discovery · 2026Article
- Navigating the uncharted: AI-driven advances in protein structure, dynamics, interactions and ligand interactions for understudied families.BioData mining · 2026Review
- Single-Sequence Deep Learning Delivers Crystal-Quality Models of Covalent K-Ras G12 Hotspot Complexes.IUBMB life · 2026Article
- Distance-Restraint-Guided Diffusion Models for Sampling Protein Conformational Changes and Ligand Dissociation Pathways.Journal of chemical theory and computation · 2026Article
- Physical Implausibility of Carbohydrate Ligands in Results of Deep Learning-Based Cofolding Methods.Journal of chemical information and modeling · 2026Article
- AI-Based Prediction of PROTAC- and Molecular Glue-Mediated Ternary Complexes: A Comparative Evaluation of AlphaFold 3 and Boltz-2.Archiv der Pharmazie · 2026Article
- 4″-Methyl-ACS chemical biology · 2026Article
- The transformative impact of AI-enabled AlphaFold 3: evolution, current status, and future prospects in structural biology.Frontiers in artificial intelligence · 2026Review
- CCD2MD: A Suite of Packages for Preparing Co-Folded Outputs for Molecular Dynamics Simulations.Journal of chemical information and modeling · 2025Article
- Boltz-1 Democratizing Biomolecular Interaction Modeling.bioRxiv : the preprint server for biology · 2025Article
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
AlphaFold3 has revolutionized biology by enabling the prediction of protein complexes with various biomolecules, including small molecular ligands. However, the ligand structures predicted by the model often contain stereochemical errors. In this study, our comprehensive evaluation of AlphaFold3 and its clone model, Boltz-1, demonstrated significant limitations in the ligand stereochemistry of their predicted structures, including chirality, bond lengths, and bond angles. To address this issue, we developed the restraint-guided inference method that applies stereochemical restraints during the reverse diffusion process. This approach perfectly reproduces the chirality specified in the input chemical structure and improves bond and angle geometries of ligands, while maintaining comparable performance in binding pose prediction. Our method provides a practical solution to the stereochemical errors in predicting protein-ligand complexes, thereby enhancing structure prediction applications in structural biology and drug discovery.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.