ArticlePloS one2017
A computational approach for designing D-proteins with non-canonical amino acid optimised binding affinity.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Protocol for DesigningJournal of computational biology : a journal of computational molecular cell biology · 2024Article
- DexDesign: an OSPREY-based algorithm for designing de novo D-peptide inhibitors.Protein engineering, design & selection : PEDS · 2024Article
- D-Peptide and D-Protein Technology: Recent Advances, Challenges, and Opportunities.Chembiochem : a European journal of chemical biology · 2023Review
- Protocol for iterative optimization of modified peptides bound to protein targets.Journal of computer-aided molecular design · 2022Article
- Biomolecular simulation based machine learning models accurately predict sites of tolerability to the unnatural amino acid acridonylalanine.Scientific reports · 2021Article
- D-Amino acid substituted peptides as potential alternatives of homochiral L-configurations.Amino acids · 2021Article
- Predicting changes in protein stability caused by mutation using sequence-and structure-based methods in a CAGI5 blind challenge.Human mutation · 2019Article
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3 authors.
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Abstract
Redesigning protein surface topology to improve target binding holds great promise in the search for highly selective therapeutics. While significant binding improvements can be achieved using natural amino acids, the introduction of non-canonical residues vastly increases sequence space and thus the chance to significantly out-compete native partners. The potency of protein inhibitors can be further enhanced by synthesising mirror image, D-amino versions. This renders them non-immunogenic and makes them highly resistant to proteolytic degradation. Current experimental design methods often preclude the use of D-amino acids and non-canonical amino acids for a variety of reasons. To address this, we build an in silico pipeline for D-protein designs featuring non-canonical amino acids. For a test scaffold we use an existing D-protein inhibitor of VEGF: D-RFX001. We benchmark the approach by recapitulating previous experimental optimisation with canonical amino acids. Subsequent incorporation of non-canonical amino acids allows designs that are predicted to improve binding affinity by up to -7.18 kcal/mol.
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