Investigation of Potential Mechanisms of Yerba Santa Compounds Against Alzheimer’s Disease
Year: 2026
Type: article
Abstract: spp.) is a medicinal plant with reported anti-inflammatory and neuroprotective properties, although its molecular mechanisms remain poorly understood. This study investigated whether chemically characterized Yerba Santa compounds show predicted docking interactions with neuroinflammation-related protein targets implicated in AD. Thirty-six ligand structures, representing 30 mass spectrometry peak assignments, were docked against 30 neuroinflammation-related proteins using the MolSoft ICM molecular docking platform. To improve reproducibility, each ligand-target pair was evaluated by replicated docking simulations followed by statistical analysis, with apo and holo targets evaluated against separate statistical references and expanded docking where applicable. Under the apo -25 kcal/mol screening reference, 11 ligand-target pairs were retained after BH-FDR correction and expanded docking for the apo C1r-C1s (PDB:6F39). Separately, 23 holo ligand-target pairs were retained after comparison with their corresponding redocked native-ligand references: Complement C1q (PDB:2JG8), GABA-A receptor α1β2γ2 (PDB:6D6U), and NLRP3 (PDB:7PZC). The pairs retained under these separate criteria involved multiple Yerba Santa compounds, predominantly flavonoids, while Rosmarinic acid (L21) was retained for both Complement C1q (PDB:2JG8) and NLRP3 (PDB:7PZC). These findings support a selective predicted multi-target interaction profile for Yerba Santa compounds and identify complement signaling, GABA-A receptor-associated neurotransmission, and NLRP3 inflammasome signaling as testable pathways for future experimental studies of neuroinflammation in AD.
Source: Molecules
Institutions: Villanova University, University of Pennsylvania
Language: English
Subfield: Cellular and Molecular Neuroscience
Field: Neuroscience
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,258
Funder: National Institute on Aging
Awards: Translational big data analytic approaches to advance drug repurposing for Alzheimer's disease, Centrally-linked longitudinal peripheral biomarkers of AD in multi-ethnic populations, Artificial Intelligence Strategies for Alzheimer's Disease Research, Ultrascale Machine Learning to Empower Discovery in Alzheimers Disease Biobanks
OpenAlex ID: W7222949585