Integrative Computational Approaches to Protein Structure and Drug Design in POEMS Syndrome

Abstract

POEMS syndrome is a rare multisystem disorder associated with plasma cell dyscrasia, characterized by neurological, endocrine, hematological, and dermatological symptoms. Although the clinical features are well recognized, the underlying molecular mechanisms remain unclear. Current evidence suggests that abnormal cytokine signaling, immune dysregulation, and altered plasma cell function play key roles in disease development. In this study, we examined the molecular characteristics and interaction profiles of EHD1, STAT3, KLHL6, and LTB proteins involved in POEMS syndrome and explored potential therapeutic candidates using computational methods. Protein sequences were obtained from public databases and analyzed with protein–protein interaction and functional gene network tools, including STRING, HuRI, and GeneMANIA. The three-dimensional structures of these proteins were modeled through homology modeling and validated with standard structural assessment techniques. Molecular docking was performed with a selected set of FDA-approved drugs to assess potential protein–ligand interactions, with binding modes analyzed via molecular visualization software. Interaction network analysis revealed that EHD1 primarily functions in vesicular trafficking and endocytic recycling, while STAT3 serves as a central mediator of cytokine signaling. Additionally, KLHL6 is associated with plasma cell regulation and metabolic processes, and LTB is involved in immune and inflammatory pathways. Structural validation confirmed that the modeled proteins were suitable for docking studies. Several FDA-approved drugs, including Dasatinib, Simvastatin, Celecoxib, Niclosamide, Acitretin, and Cholesterol, exhibited favorable docking scores with the target proteins, indicating potential multi-target interactions. Overall, this computational work offers insights into the molecular networks and structural features linked to POEMS syndrome and identifies candidate compounds for future experimental testing. While the results are based on in silico analyses, they provide a foundation for future research aimed at better understanding and treating POEMS disorder.