Macrocycles & constrained peptides
Cyclic Peptide Design for Improved Stability and Bioavailability
Cyclic peptides occupy a privileged position in drug discovery — combining the target engagement capability of peptides with improved metabolic stability, reduced conformational flexibility, and enhanced membrane permeability. Designing cyclic peptides that achieve the right balance of rigidity, activity, and developability requires sophisticated computational methods. We apply AI-assisted design to engineer cyclic peptides and macrocycles for your therapeutic or research application.
The Cyclic Peptide Design Challenge
Cyclization dramatically expands the design space — head-to-tail, side-chain-to-side-chain, disulfide, and backbone cyclization each impose different conformational constraints and have different effects on stability, activity, and bioavailability. Selecting the right cyclization strategy and optimizing the sequence within that constraint is a complex multidimensional problem.
Computational methods that model the conformational ensemble of cyclic peptides, predict membrane permeability, and optimize for target engagement within the constrained scaffold can significantly accelerate cyclic peptide development.
Our Cyclic Peptide Design Approach
Cyclization strategy selection
Computational analysis of cyclization options — head-to-tail, disulfide, lactam, staple — to identify the approach best suited to the target and application.
Conformational ensemble modeling
Prediction of the conformational ensemble of cyclic candidates to identify bioactive conformations and guide sequence optimization.
Permeability optimization
Design for passive membrane permeability using Lipinski-beyond-rule-of-5 frameworks and computational permeability prediction.
Stability engineering
Optimization of protease resistance and metabolic stability through cyclization and non-natural amino acid incorporation.
Cyclic Peptide Design Workflow
Target and application definition
Define the target, binding requirements, and key developability objectives.
Cyclization strategy analysis
Computational assessment of cyclization options for the target and application.
Cyclic candidate design
AI-assisted generation of cyclic peptide sequences optimized within the selected scaffold.
Conformational and property prediction
Prediction of bioactive conformation, permeability, stability, and target affinity.
Candidate prioritization
Selection of priority candidates for synthesis and experimental validation.
Optimization cycles
Iterative refinement based on experimental data.
What Can Be Evaluated
What You May Receive
Cyclic peptide candidate library
Designed cyclic sequences with predicted activity, permeability, and stability profiles.
Cyclization strategy report
Analysis of cyclization options and rationale for the selected approach.
Conformational analysis
Predicted bioactive conformations and binding mode analysis for priority candidates.
Optimization strategy
Recommended modifications to improve permeability, stability, or potency.
Deliverables depend on project scope and target characteristics. Permeability and activity outcomes cannot be guaranteed computationally.
Who This Is For
Medicinal chemists
Teams exploring macrocycle and constrained peptide space for targets where linear peptides have insufficient stability or permeability.
Drug discovery groups
Programs targeting intracellular or oral-delivery applications where cyclic peptide properties are advantageous.
Biotech companies
Companies developing cyclic peptide therapeutics or macrocycle-based drug candidates.
Screen Your Cyclic Peptide Candidate
Use our free tools to assess the physicochemical properties and drug-likeness of your cyclic peptide sequence before committing to synthesis. The Peptide Property Analyzer calculates MW, pI, and GRAVY; the Drug-Likeness Predictor estimates membrane permeability and solubility.
Frequently Asked Questions
Design Cyclic Peptides with Improved Stability and Permeability
Submit your target and cyclic peptide design objectives. We will assess the macrocycle design opportunity and outline a computational approach for your program.
Confidential project discussions available under NDA.