Protocol for Designing <i>De Novo</i> Noncanonical Peptide Binders in OSPREY
D-peptides, the mirror image of canonical L-peptides, offer numerous biological advantages that make them effective therapeutics. This article details how to use DexDesign, the newest OSPREY-based algorithm, for designing these D-peptides <i>de novo</i>. OSPREY physics-based models precisely mimic energy-equivariant reflection operations, enabling the generation of D-peptide scaffolds from L-peptide templates. Due to the scarcity of D-peptide:L-protein structural data, DexDesign calls a geometric hashing algorithm, Method of Accelerated Search for Tertiary Ensemble Representatives, as a subroutine to produce a synthetic structural dataset. DexDesign enables mixed-chirality designs with a new user interface and also reduces the conformation and sequence search space using three new design techniques: Minimum Flexible Set, Inverse Alanine Scanning, and K*-based Mutational Scanning.
Authors
- Pei Zhou (ORCID: https://orcid.org/0000-0002-7823-3416)
- Henry Childs (ORCID: https://orcid.org/0009-0000-7657-9926)
- Nathan Guerin (ORCID: https://orcid.org/0000-0001-8378-7854)
- Bruce R. Donald (ORCID: https://orcid.org/0000-0001-6884-4398)
Institutions
- Duke University (US)
Publication Details
- Journal
- Journal of Computational Biology
- Published
- 2024-10-01
- DOI
- https://doi.org/10.1089/cmb.2024.0669
- Primary Topic
- Chemical Synthesis and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health