ArticleScientific reports2018
High throughput evaluation of macrocyclization strategies for conformer stabilization.
Article in Scientific reports, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed, 33 citations in OpenAlex.
- A Build, Couple, Pair (B/C/P) Strategy in the Synthesis of Diindole Fused Diazamacrocycles: An Attempt to a Green Synthetic Approach.ACS omega · 2025Article
- Exploring Sources, Biological Functions, and Potential Applications of the Ubiquitous Marine Cyclic Dipeptide: A Concise Review of Cyclic Glycine-Proline.Marine drugs · 2024Review
- Addressing Challenges of Macrocyclic Conformational Sampling in Polar and Apolar Solvents: Lessons for Chameleonicity.Journal of chemical information and modeling · 2023Article
- Synthesis of Large Macrocycles with Chiral Sulfur Centers via Enantiospecific SuFEx and SuPhenEx Click Reactions.The Journal of organic chemistry · 2023Article
- Discovery of Cyclic Peptide Inhibitors Targeting PD-L1 for Cancer Immunotherapy.Journal of medicinal chemistry · 2022Article
- Identification of Anti-Frontiers in microbiology · 2020Article
- Docking Flexible Cyclic Peptides withJournal of chemical theory and computation · 2019Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
While macrocyclization of a linear compound to stabilize a known bioactive conformation can be a useful strategy to increase binding potency, the difficulty of macrocycle synthesis can limit the throughput of such strategies. Thus computational techniques may offer the higher throughput required to screen large numbers of compounds. Here we introduce a method for evaluating the propensity of a macrocyclic compound to adopt a conformation similar that of a known active linear compound in the binding site. This method can be used as a fast screening tool for prioritizing macrocycles by leveraging the assumption that the propensity for the known bioactive substructural conformation relates to the affinity. While this method cannot to identify new interactions not present in the known linear compound, it could quickly differentiate compounds where the three dimensional geometries imposed by the macrocyclization prevent adoption of conformations with the same contacts as the linear compound in their conserved region. Here we report the implementation of this method using an RMSD-based structural descriptor and a Boltzmann-weighted propensity calculation and apply it retrospectively to three macrocycle linker optimization design projects. We found the method performs well in terms of prioritizing more potent compounds.
Identifiers
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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.