ArticleJournal of chemical information and modeling2023
Computational Prediction of Cyclic Peptide Structural Ensembles and Application to the Design of Keap1 Binders.
Article in Journal of chemical information and modeling, 2023. 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, 16 citations in OpenAlex.
- Cyclic Peptides as Modulators of Protein-Protein Interactions: A Survival Guide from Discovery Platforms to AI-Driven Design.International journal of molecular sciences · 2026Review
- StrEAMM-Thioether: Efficient Structure Prediction for Thioether-Linked Cyclic Peptides.The journal of physical chemistry. B · 2026Article
- CyclicMPNN: Stable Cyclic Peptide Sequence Generation.bioRxiv : the preprint server for biology · 2026Article
- Robust Conformational Space Exploration of Cyclic Peptides by Combining Different MD Protocols and Force Fields.Journal of chemical theory and computation · 2025Article
- Computational Design of a Bicyclic Peptide Inhibitor Targeting the ICOS/ICOS-L Protein-Protein Interaction.Chemical biology & drug design · 2025Article
- Unsupervised learning of collective variables for conformational sampling of cyclic peptides.Methods in enzymology · 2025Article
- Article
- Tackling Undruggable Targets with Designer Peptidomimetics and Synthetic Biologics.Chemical reviews · 2024Review
- Ginsenoside Rg3 attenuates myocardial ischemia/reperfusion-induced ferroptosis via the keap1/Nrf2/GPX4 signaling pathway.BMC complementary medicine and therapies · 2024Article
- Assessing the Performance of Peptide Force Fields for Modeling the Solution Structural Ensembles of Cyclic Peptides.The journal of physical chemistry. B · 2024Article
Corrections and comments
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Authors and funding
9 authors at 2 institutions in 2 countries.
Funding
Abstract
The Nrf2 transcription factor is a master regulator of the cellular response to oxidative stress, and Keap1 is its primary negative regulator. Activating Nrf2 by inhibiting the Nrf2-Keap1 protein-protein interaction has shown promise for treating cancer and inflammatory diseases. A loop derived from Nrf2 has been shown to inhibit Keap1 selectively, especially when cyclized, but there are no reliable design methods for predicting an optimal macrocyclization strategy. In this work, we employed all-atom, explicit-solvent molecular dynamics simulations with enhanced sampling methods to predict the relative degree of preorganization for a series of peptides cyclized with a set of bis-thioether "staples". We then correlated these predictions to experimentally measured binding affinities for Keap1 and crystal structures of the cyclic peptides bound to Keap1. This work showcases a computational method for designing cyclic peptides by simulating and comparing their entire solution-phase ensembles, providing key insights into designing cyclic peptides as selective inhibitors of protein-protein interactions.
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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.