Development of a neuroprotective potential algorithm for medicinal plants
Date of Original Version
Medicinal plants are promising candidates for Alzheimer's disease (AD) research but there is lack of systematic algorithms and procedures to guide their selection and evaluation. Herein, we developed a Neuroprotective Potential Algorithm (NPA) by evaluating twenty-three standardized and chemically characterized Ayurvedic medicinal plant extracts in a panel of bioassays targeting oxidative stress, carbonyl stress, protein glycation, amyloid beta (Aβ) fibrillation, acetylcholinesterase (AChE) inhibition, and neuroinflammation. The twenty-three herbal extracts were initially evaluated for: 1) total polyphenol content (Folin-Ciocalteu assay), 2) free radical scavenging capacity (DPPH assay), 3) ferric reducing antioxidant power (FRAP assay), 4) reactive carbonyl species scavenging capacity (methylglyoxal trapping assay), 5) anti-glycative effects (BSA-fructose, and BSA-methylglyoxal assays) and, 6) anti-Aβ fibrillation effects (thioflavin-T assay). Based on assigned index scores from the initial screening, twelve extracts with a cumulative NPA score ≥40 were selected for further evaluation for their: 1) inhibitory effects on AChE activity, 2) in vitro anti-inflammatory effects on murine BV-2 microglial cells (Griess assay measuring levels of lipopolysaccharide-induced nitric oxide species), and 3) in vivo neuroprotective effects on Caenorhabditis elegans post induction of Aβ1-42 induced neurotoxicity and paralysis. Among these, four extracts had a cumulative NPA score ≥60 including Phyllanthus emblica (amla; Indian gooseberry), Mucuna pruriens (velvet bean), Punica granatum (pomegranate) and Curcuma longa (turmeric; curcumin). These extracts also showed protective effects on H2O2 induced cytotoxicity in differentiated cholinergic human neuronal SH-SY5Y and murine BV-2 microglial cells and reduced tau protein levels in the SH-SY5Y neuronal cells. While published animal data support the neuroprotective effects of several of these Ayurvedic medicinal plant extracts, some remain unexplored for their anti-AD potential. Therefore, the NPA may be utilized, in part, as a strategy to help guide the selection of promising medicinal plant candidates for future AD-based research using animal models.
Liu, Weixi, Hang Ma, Nicholas A. DaSilva, Kenneth N. Rose, Shelby L. Johnson, Lu Zhang, Chunpeng Wan, Joel A. Dain, and Navindra P. Seeram. "Development of a neuroprotective potential algorithm for medicinal plants." Neurochemistry International 100, (2016): 164-177. doi:10.1016/j.neuint.2016.09.014.