Research

Depression is a common mental disorder that can often manifest as a depressed mood, impaired cognitive functioning,  and loss of enjoyment. Its physical manifestations often include symptoms such as fatigue and sleep disturbance.^1,2 In the worst cases, depression can lead to suicide,^3,4 which has tragically claimed more than 700,000 lives.⁵ Especially in recent years, owing to the COVID-19 outbreak, reasons such as company bankruptcy and collapse, worker unemployment, and home isolation have led to a breakdown of psychological defenses, which has resulted in a dramatic increase in the incidence of depression.⁶ A study published in The Lancet entitled “Global prevalence and burden of depressive and anxiety disorders in 204 countries and territories in 2020 due to the COVID-19 pandemic” reported that the number of people with depression increased by 27.6% globally following the COVID-19 pandemic.⁷ This means that the pandemic has increased the number of depressed people worldwide by a quarter. As a result, depression has now become a serious mental disorder worldwide and has attracted much attention from scientists.

In research on the pathogenesis of depression,⁸ although several hypotheses have been proposed—including the monoamine neurotransmitter hypothesis^,9 oxidative stress dysfunction,¹⁰ cytokine abnormalities,¹¹ neurotrophic deficiency,^12,13 HPA axis abnormalities, and the ‘gut–brain axis’^14,15—their molecular links remain poorly defined. Notably, HPA axis hyperactivity is known to suppress neurotrophic factor expression,¹⁶ while gut-brain axis dysfunction  may impair PI3K-Akt signaling via inflammatory cytokines,¹⁵ both of which overlap with the pathways targeted in this study. Thus, exploring small molecules that regulate these intersecting pathways (PI3K-Akt, MAPK, neurotrophins) could bridge these fragmented hypotheses. The onset of depression is closely related to the physiological, psychological, and social environment,¹⁷ but further research is needed. Currently, many types of antidepressants are available, such as monoamine oxidase inhibitors, tricyclic antidepressants, 5-hydroxytryptamine reuptake inhibitors, and 5-hydroxytryptamine and norepinephrine reuptake inhibitors. However, many antidepressants are ineffective and are even associated with serious adverse effects.¹⁸ According to the literature, current antidepressants provide relief in only 30%–40% of patients.^19,20 More effective drugs with few side effects are needed to treat depression, but developing new drugs is time consuming and costly. Repurposing old drugs plays an important role in the treatment of many diseases. For example, arsenic trioxide was used in ancient China to treat maladies such as hemorrhoids; current research has shown that it can be used to treat acute promyelocytic leukemia.²¹ Thalidomide was originally used to treat pregnancy vomiting in pregnant women, but recent studies have shown that its inhibitory effect on the inflammatory response can be applied in many diseases^.22 In view of the abovementioned examples, the “new use of old drugs” provides new ideas and directions for the development of medicine.^23,24 Among such repurposable drugs, pyrimethamine, pifithrin-mu, and mibefradil were selected for in vivo validation based on three criteria: (1) their predicted ability to reverse depressionrelated gene signatures (via CMAP, raw connectivity score < −0.6);^25,26 (2) limited prior association with depression, unlike scopolamine (already in Phase II trials²⁷) and estradiol (gender-dependent effects²⁸); and (3) reported roles in inflammation or neuroprotection—pyrimethamine modulates T cell activity,²⁹ pifithrin-mu inhibits microglial activation,³⁰ and mibefradil regulates calcium signaling,³¹ all of which intersect with depression-related pathways.

Bioinformatics is the study of all aspects of acquisition, processing, storage, dissemination, analysis, and interpretation of biological information via computers as tools.³² The main research areas of bioinformatics are genomics, proteomics, and systems biology.³³ Currently, bioinformatics techniques have been applied in many fields, such as gene identification analysis, genetic coding, and drug design.^34–36 In recent years, studies have been conducted to identify new therapeutic drugs for diseases via bioinformatics, which has contributed greatly to research into related diseases.^37–39 However, current strategies for repurposing antidepressant drugs often exhibit limited conversion efficiency, primarily due to the reliance on single-database screening approaches or the absence of in vivo validation. Numerous candidate compounds identified through bioinformatics analyses remain unverified in animal models, underscoring the urgent need to establish a systematic framework encompassing “screening – prediction -validation”. To address this gap, the present study investigates key targets and signaling pathways associated with depression using bioinformatics tools, aiming to identify potential therapeutic agents. Furthermore, the study integrates molecular docking techniques with animal experiments to validate the efficacy of these candidates, with the objective of offering novel insights into depression research and treatment. By combining multi-omics data (GEO, CMAP) with WGCNA and immune-related pathway analysis, complemented by rigorous in vivo experiments, this study addresses a critical research gap. This approach not only enhances the credibility of candidate compounds but also establishes a reproducible model for antidepressant drug discovery.

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^{https://doi.org/10.2147/DDDT.S537918}