Development and characterization of a reserpine-induced mouse model of depression: An integrated in-vivo and in-silico approach.

Depression is a complex neuropsychiatric disorder characterized by affective, cognitive, and somatic dysfunctions, yet its pathophysiology remains poorly understood. Reliable preclinical models are essential for elucidating disease mechanisms and identifying therapeutic alternatives. The present study aimed to develop and characterize a reserpine-induced mouse model of depression using an integrated in-vivo and in-silico approach. Adult male Swiss mice (8-12 weeks) received oral reserpine (0.75 mg/kg BW/day) for 14 consecutive days. Behavioral assessments revealed significant reductions in food intake, body weight, and sucrose preference, alongside increased immobility time and impaired spatial memory. Biochemical analyses demonstrated elevated oxidative stress markers and diminished antioxidant enzyme activity in brain tissue. Neurochemical profiling confirmed significant depletion of key monoamines (serotonin, dopamine, norepinephrine, and histamine), increased acetylcholinesterase activity, and elevated serum corticosterone and liver enzymes (ALT and AST). Genotoxic and apoptotic evaluations indicated substantial DNA damage, increased apoptosis, and reduced cell viability. Histopathological observations further confirmed neurodegenerative changes and disrupted neuronal architecture in critical brain regions associated with mood and cognition, indicating compromised neuroplasticity. Complementary, molecular docking studies further demonstrated strong binding affinities of reserpine with key molecular targets involved in oxidative stress and neurotransmission, providing a mechanistic support for the observed pathophysiological changes. Overall, the present study establishes a robust and multidimensional model that captures behavioral, biochemical, and structural aspects of depression. The integration of experimental and computational approaches highlights the model's utility for advancing mechanistic insights and facilitating the development of novel antidepressant strategies.