Use AfCycDesign

Features

• Utilizes AlphaFold2 for macrocyclic peptide design.
• Designed for accurate structure prediction and design of cyclic peptides.
• Addresses challenges in designing cyclic peptides due to limited structural data.
• Predicts native cyclic peptide structures with high confidence.
• Impressive accuracy, with 36 out of 49 cases closely matching native structures (pLDDT > 0.85, RMSD < 1.5 Å).
• Offers computational methods for designing peptide backbones generated by different sampling techniques.
• Enables De novo design of novel macrocyclic peptides.
• Extensive structural diversity sampling for cyclic peptides (7-13 amino acids).
• Identifies around 10,000 unique design candidates with high-confidence folding predictions.
• Validation through X-ray crystal structures closely matching design models (RMSD < 1.0 Å).
• Provides a basis for custom-designing peptides for targeted therapeutic applications.

Statistics

Neurosnap periodically calculates runtime statistics based on job execution data. These estimates provide a general guideline for how long your job may take, but actual runtimes can vary significantly depending on factors like input size or settings used.