Skip to content
DraconiticResearch
Search Sources API
197,768 studies31 sourcesUpdated 37 min ago
PreprintCC BY 4.0arXiv

Computational De Novo Design of Miniprotein Candidate Neutralizers Targeting the IL-23 Cytokine Subunit p19

Abstract

Interleukin-23 (IL-23) drives T-helper-17 inflammation underlying inflammatory bowel disease and psoriasis; anti-p19 antibodies are clinically effective but large, costly, and injectable. De novo miniproteins are an attractive alternative, yet published designs target the IL-23 receptor; the IL-23 cytokine itself has not been addressed. A further obstacle is that the standard confidence score (ipTM) tracks construct length rather than interface quality. We computationally design miniprotein binders against the IL-23R-binding face of p19 (PDB 3DUH) and score every design with ipSAE, a length-robust interface metric derived from AlphaFold-initial-guess predicted aligned error. A conventional RFdiffusion/ProteinMPNN/ColabFold pipeline yields no reliable predicted interface across 972 designs (best ipSAE 0.30), and a scoring artifact, in which single-sequence ColabFold under-rates binder pLDDT by approximately 56 points, explains an earlier misleading "binders do not fold" signal. An interface-optimized hallucination method (BindCraft), scored identically, yields 42 of 50 designs above ipSAE 0.60 (best 0.804). An AlphaFold-independent geometric check reproduces the conventional failure: no top-ranked conventional design reaches the buried area or interface hydrogen-bond count of the weakest lead. Five all-alpha-helical leads (72-104 residues) collectively engage all six targeted hotspots; two dock within the intact p40/p19 heterodimer and all show favorable Rosetta energetics. A p40-alone counter-screen returns ipSAE 0.00 for all five, indicating no spurious p40 interface. To our knowledge, these are the first computationally proposed de novo miniprotein candidates designed to occlude the IL-23R-binding face of IL-23 p19. All results require experimental validation.

Related

  1. X-ray structure of the human Nijmegen breakage syndrome forkhead-associated/BRCA1 C-terminal domain and computational docking of candidate radiosensitizers
    Masaki Unno, Kenichi Kitanishi, Kenji Ite +5
    Acta Crystallographica Section F: Structural Biology CommunicationsPeer-reviewedPublisher termsFull textMolecular biology & gene regulationPMC
  2. Computational identification of candidate biomarkers and compounds associated with skeletal muscle insulin sensitivity improvement mediated by physical activity: an integrative multi-omics and computational chemistry study.
    Hong Liu, Zicheng Liang, Jun Tan +1
    Frontiers in bioinformaticsPeer-reviewedCC BYFull textMolecular biology & gene regulationEurope PMC
  3. Computational designing of multiepitope based vaccine (MEBV) candidate against human metapneumovirus (HMPV) using immunoinformatics approach
    Sajid Naeem, Amna Rasheed, Aqsa Khan +3
    Scientific ReportsPeer-reviewedCC BYFull textMolecular biology & gene regulationDOAJ
  4. De novo design of miniprotein inhibitors of bacterial adhesins
    Adam M. Chazin-Gray, Tuscan R. Thompson, Edward D. B. Lopatto +27
    Nature CommunicationsPeer-reviewedCC BY-NC-ND 4.0Full textMolecular biology & gene regulationCrossref
  5. Identification of candidate HLA-E binding peptides from Mycobacterium tuberculosis using phage secretome library screening and computational modeling
    Nkanyezi Masondo, Michelle Lucille Gordon, Thamsanqa Emmanuel Chiliza
    Frontiers in Cellular and Infection MicrobiologyPeer-reviewedCC BY 4.0Full textMolecular biology & gene regulationPMC
BibTeX
@misc{paladugu2026computational,
  title = {{Computational De Novo Design of Miniprotein Candidate Neutralizers Targeting the IL-23 Cytokine Subunit p19}},
  author = {Raghav Paladugu and Fardina Fathmiul Alam},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2610.32779},
  eprint = {2610.32779},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2610.32779},
  note = {CC BY 4.0},
}
RIS
TY  - UNPB
TI  - Computational De Novo Design of Miniprotein Candidate Neutralizers Targeting the IL-23 Cytokine Subunit p19
AU  - Raghav Paladugu
AU  - Fardina Fathmiul Alam
PY  - 2026
DA  - 2026/10/23
PB  - arXiv
DO  - 10.48550/arxiv.2610.32779
UR  - https://arxiv.org/abs/2610.32779
AB  - Interleukin-23 (IL-23) drives T-helper-17 inflammation underlying inflammatory bowel disease and psoriasis; anti-p19 antibodies are clinically effective but large, costly, and injectable. De novo miniproteins are an attractive alternative, yet published designs target the IL-23 receptor; the IL-23 cytokine itself has not been addressed. A further obstacle is that the standard confidence score (ipTM) tracks construct length rather than interface quality. We computationally design miniprotein binders against the IL-23R-binding face of p19 (PDB 3DUH) and score every design with ipSAE, a length-robust interface metric derived from AlphaFold-initial-guess predicted aligned error. A conventional RFdiffusion/ProteinMPNN/ColabFold pipeline yields no reliable predicted interface across 972 designs (best ipSAE 0.30), and a scoring artifact, in which single-sequence ColabFold under-rates binder pLDDT by approximately 56 points, explains an earlier misleading "binders do not fold" signal. An interface-optimized hallucination method (BindCraft), scored identically, yields 42 of 50 designs above ipSAE 0.60 (best 0.804). An AlphaFold-independent geometric check reproduces the conventional failure: no top-ranked conventional design reaches the buried area or interface hydrogen-bond count of the weakest lead. Five all-alpha-helical leads (72-104 residues) collectively engage all six targeted hotspots; two dock within the intact p40/p19 heterodimer and all show favorable Rosetta energetics. A p40-alone counter-screen returns ipSAE 0.00 for all five, indicating no spurious p40 interface. To our knowledge, these are the first computationally proposed de novo miniprotein candidates designed to occlude the IL-23R-binding face of IL-23 p19. All results require experimental validation.
ER  -