ArticleChemMedChem2017
Computational Macrocyclization: From de novo Macrocycle Generation to Binding Affinity Estimation.
Article in ChemMedChem, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Cryo-EM structures of Cdr1 reveal snapshots of substrate transport and diverse inhibitor recognition.Science advances · 2026Article
- Exploring the macrocyclic chemical space for heuristic drug design with deep learning models.Communications chemistry · 2025Article
- The maximal and current accuracy of rigorous protein-ligand binding free energy calculations.Communications chemistry · 2023Article
- Macrocyclization of linear molecules by deep learning to facilitate macrocyclic drug candidates discovery.Nature communications · 2023Article
- Best practices for constructing, preparing, and evaluating protein-ligand binding affinity benchmarks [Article v0.1].Living journal of computational molecular science · 2022Article
- Machine learning-accelerated quantum mechanics-based atomistic simulations for industrial applications.Journal of computer-aided molecular design · 2021Article
- Improving the Accuracy of Protein Thermostability Predictions for Single Point Mutations.Biophysical journal · 2020Article
- Adapting free energy perturbation simulations for large macrocyclic ligands: how to dissect contributions from direct binding and free ligand flexibility.Chemical science · 2020Article
- Best Practices for Alchemical Free Energy Calculations [Article v1.0].Living journal of computational molecular science · 2020Article
- Large scale relative protein ligand binding affinities using non-equilibrium alchemy.Chemical science · 2019Article
- Fast, efficient fragment-based coordinate generation for Open Babel.Journal of cheminformatics · 2019Article
- Predicting Binding Free Energies of PDE2 Inhibitors. The Difficulties of Protein Conformation.Scientific reports · 2018Article
- Computational Macrocyclization: From de novo Macrocycle Generation to Binding Affinity Estimation.ChemMedChem · 2017Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Macrocycles play an increasing role in drug discovery, but their synthesis is often demanding. Computational tools that suggest macrocyclization based on a known binding mode and that estimate the binding affinity of these macrocycles could have a substantial impact on the medicinal chemistry design process. For both tasks, we established a workflow with high practical value. For five diverse pharmaceutical targets we show that the effect of macrocyclization on binding can be calculated robustly and accurately. Applying this method to macrocycles designed by LigMac, a search tool for de novo macrocyclization, our results suggest that we have a robust protocol in hand to design macrocycles and prioritize them prior to synthesis.
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