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Updated: Mar 15, 2026

Constructing Cyclic Peptides Using an On-Tether Sulfonium Center

Constructing Cyclic Peptides Using an On-Tether Sulfonium Center

Published on: September 28, 2022

Computational methods to design cyclic peptides.

Sean M McHugh¹, Julia R Rogers¹, Sarah A Solomon¹

¹Department of Chemistry, Tufts University, Medford, MA 02155, United States.

Current Opinion in Chemical Biology

|September 5, 2016

Summary

This summary is machine-generated.

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Computational methods are advancing cyclic peptide (CP) design for protein-protein interaction (PPI) modulation. Overcoming challenges in predicting CP structure and energetics is key for developing therapeutics.

Area of Science:

Medicinal Chemistry
Computational Biology
Biochemistry

Background:

Cyclic peptides (CPs) show potential as modulators of protein-protein interactions (PPIs).
Current limitations in predicting CP structure and bioavailability hinder their therapeutic development.
Computer-aided design of CPs could accelerate their use in research and medicine.

Purpose of the Study:

To describe computational methods for generating cyclic peptide libraries for virtual screening.
To highlight current efforts in predicting the conformations of cyclic peptides.
To outline the path towards robust computational design of active cyclic peptides.

Main Methods:

Generation of cyclic peptide libraries for virtual screening.
Computational approaches for predicting cyclic peptide conformations.

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Last Updated: Mar 15, 2026

Constructing Cyclic Peptides Using an On-Tether Sulfonium Center

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Analysis of challenges in sampling conformational space and energetics of cyclic peptides.

Main Results:

Development of computational methods for CP library generation and virtual screening.
Progress in predicting CP conformations, enabling envisioning of computational design.
Identification of significant challenges in CP conformational sampling and energetic prediction.

Conclusions:

Advances in computational methods are paving the way for designing cyclic peptides.
Accurate prediction of CP structure and energetics remains a critical hurdle.
Solving these challenges is essential for reliable design of potent cyclic peptide therapeutics.