Computationally Guided Design of Two Novel Phosphodiesterase-4 Inhibitors for Treatment of Plaque Psoriasis
Year: 2026
Type: preprint
Abstract: ABSTRACT Plaque psoriasis is a chronic inflammatory skin disease characterized by itchy, scaly skin. Although there is currently no cure for this disease, it can be managed with medication, such as phosphodiesterase-4 (PDE4) inhibitors. Current PDE4 inhibitors are limited and show adverse effects. With the goal to develop better PDE4 inhibitors for the treatment of plaque psoriasis, two novel drug candidates were designed with computational studies, and observed to have better ADMET properties compared to Roflumilast. A homology analysis was performed to determine the best model organism for preclinical studies of the novel candidates.
Authors: Annie Liu, Emma R. M. James, Justine B. Siegel
Institution: University of California, Davis
Language: English
Subfield: Drug Discovery
Domain: Life Sciences
Open Access status: green
Awards: Leveraging Machine Learning to Explore the Effects of the Design2Data Course-based Undergraduate Research Experience, G4078261464, RCN-UBE: Data-to-Design Course-based Undergraduate Research Experience ? protein modeling and characterization to enhance student learning and improve computational protein design, RCN-UBE: Design to Data Network: expanding a faculty community of practice to broaden and diversify participation in undergraduate research
OpenAlex ID: W7223339375