ArticleJournal of chemical theory and computation2017
Extended Concerted Rotation Technique Enhances the Sampling Efficiency of the Computational Peptide-Design Algorithm.
Article in Journal of chemical theory and computation, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 16 citations in OpenAlex.
- Integrating biophysical modeling, quantum computing, and AI to discover plastic-binding peptides that combat microplastic pollution.PNAS nexus · 2025Article
- Design of 8-mer peptides that block Clostridioides difficile toxin A in intestinal cells.Communications biology · 2023Article
- Design of 8-mer Peptides that BlockbioRxiv : the preprint server for biology · 2023Article
- Sequence patterns and signatures: Computational and experimental discovery of amyloid-forming peptides.PNAS nexus · 2022Article
- Article
- De novo design of peptides that coassemble into β sheet-based nanofibrils.Science advances · 2021Article
Corrections and comments
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Authors and funding
4 authors at 2 institutions in 1 country.
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Abstract
To enhance the sampling efficiency of our computational peptide-design algorithm in conformational space, the concerted rotation (CONROT) technique is extended to enable larger conformational perturbations of peptide chains. This allows us to make relatively large peptide conformation changes during the process of designing peptide sequences to bind with high affinity to a specific target. Searches conducted using the new algorithm identified six potential λ N(2-22) peptide variants, called B1-B6, which bind to boxB RNA with high affinity. The results of explicit-solvent atomistic molecular dynamics simulations revealed that four of the evolved peptides, viz. B1, B2, B3, and B5, are excellent candidate binders to the target boxB RNA as they have lower binding free energies than the original λ N(2-22) peptide. Three of the four peptides, B2, B3, and B5, result from searches that contain both sequence and conformation changes, indicating that adding backbone motif changes to the peptide-design algorithm improves its performance considerably.
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