ArticleMethods in molecular biology (Clifton, N.J.)2022
Computational Design of Structured and Functional Peptide Macrocycles.
Article in Methods in molecular biology (Clifton, N.J.), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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Who cites it
4 citing papers in PubMed.
- Cyclic Peptides in Modern Drug Discovery: Trends and Therapeutic Directions.Journal of medicinal chemistry · 2026Review
- A simple method for developing lysine targeted covalent protein reagents.Nature communications · 2023Article
- Harnessing protein folding neural networks for peptide-protein docking.Nature communications · 2022Article
- Design of Protein Segments and Peptides for Binding to Protein Targets.Biodesign research · 2022Review
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Structure-based computational design methods have been developed to create proteins in silico with diverse shapes and sizes that accurately fold in vitro, from 7-residue macrocycles to megadalton-scale self-assembling nanomaterials. Precise control over protein shape has further enabled design and optimization of functional therapeutic proteins, including agonists, antagonists, enzymes, and vaccines. Computational design of functional peptides of smaller size presents a persistent challenge, with few successful examples to date. Herein we describe validated general methods for computational design of peptides using the Rosetta molecular modeling suite and discuss outstanding challenges and future directions.
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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.