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Raghav Paladugu

Publications and source records attributed to Raghav Paladugu.

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

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.

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