For centuries, cannabis-derived preparations have been employed for the treatment of various medical conditions, including cancer and neuropathic pain [11]. However, their therapeutic application has been limited by associated addictive properties. This limitation underwent a significant transformation in the 1980s and 1990s with the identification of cannabinoid receptors, particularly the cannabinoid type II receptor (CB2R), which is predominantly localized in immune cells and peripheral tissues. CB2R exerts critical regulatory functions in immune modulation, inflammatory responses, and neuroprotection [5]. Importantly, its activation does not induce psychoactive effects, thereby positioning it as a major focus of pharmacological research [12]. Accumulating evidence indicates that CB2R modulators represent promising candidates for the treatment of idiopathic pulmonary fibrosis (IPF) [13]. For example, CB2R-deficient mice develop more rapid and severe lung fibrosis, whereas activation of CB2R attenuates bleomycin-induced pulmonary fibrosis in murine models [14,15]. In contrast, inhibition of CB2R counteracts this protective effect [16], although certain studies suggest that CB2R antagonists may also offer therapeutic advantages [17]. Despite ongoing controversies concerning the relative efficacy of agonists versus antagonists, these findings collectively highlight the therapeutic potential of targeting CB2R in IPF.

The integration of artificial intelligence (AI) into drug screening has revolutionized the field by effectively modeling the nonlinear relationships inherent in pharmacological systems. AI’s capability to process complex, high-dimensional datasets has substantially accelerated the drug discovery process. AI-driven drug screening predominantly utilizes two strategies: (i) ligand-based screening, which exploits the structural and physicochemical properties of known bioactive compounds to predict the biological activity of novel molecules; and (ii) structure-based screening, which leverages the three-dimensional architecture of target proteins to predict ligand binding and associated pharmacological effects [18,19]. These complementary methodologies form the foundation of modern AI-based virtual screening. In this study, we constructed a library of drug-like small molecules sourced from commercial databases and performed pretraining to derive molecular descriptors. Simultaneously, we extracted the binding pocket features of CB2R from a pretrained protein dataset. The preprocessed molecular and protein data were subsequently fed into a predictive screening platform to estimate protein-ligand binding affinities. Using the mean squared error (MSE) loss function, we ranked the binding potential of each molecule to CB2R, ultimately identifying COCA as the compound with the highest binding affinity, warranting its selection for subsequent pharmacological evaluation. However, direct binding of COCA to CB2R, while strongly suggested by our computational model, awaits future experimental validation using techniques such as radioligand binding or SPR assays.

Pirfenidone, a broad-spectrum antifibrotic agent, inhibits fibroblast proliferation, suppresses collagen synthesis, and reduces extracellular matrix deposition, thus improving pulmonary fibrosis [20]. It was used as the positive control in this study. Intratracheal administration of bleomycin (BLM) is a standard method for establishing an idiopathic pulmonary fibrosis (IPF) model in mice [21,22]. BLM-treated mice showed reduced food intake, weight loss, and increased lung coefficients due to inflammatory cell infiltration and ECM deposition; BALF cell counts were also elevated. COCA treatment reduced weight loss, inflammation, and lung coefficient increases. Histopathological analysis confirmed serous exudation, inflammation, and collagen buildup in the BLM group by HE and Masson’s staining, indicating successful model induction. These changes were significantly reduced in the COCA group. IL-6, a pleiotropic cytokine, regulates cell growth, differentiation, immune responses, and hematopoiesis [6]. During acute inflammation, damaged cells undergo lipid peroxidation, triggering inflammatory cell activation and IL-6 secretion. IL-6 activates STAT3, MAPK, PKB/Akt, and NF-κB pathways in turn, exacerbating inflammation. TNF-α, a pro-inflammatory cytokine produced by macrophages/monocytes during acute inflammation, mediates intracellular signaling cascades that culminate in necrosis or apoptosis [23]. It is primarily secreted by macrophages and plays a pivotal role in amplifying inflammation while promoting cell proliferation and differentiation; thus perpetuating inflammatory responses in pulmonary fibrosis [24]. In this study, serum levels of IL-6 and TNF-α were significantly decreased in the COCA treatment group compared to the BLM group, indicating a reduction in inflammatory activity. This was supported by reduced bronchoalveolar lavage fluid (BALF) cell counts. Collagen type I (Col-I) and collagen type III (Col-III), primarily synthesized by myofibroblasts, are key components of the extracellular matrix (ECM). Upregulated expression of these collagens reflects ECM accumulation and serves as critical biomarkers for idiopathic pulmonary fibrosis (IPF) [25,26]. In the COCA treatment groups, both fluorescence intensity and expression levels of Col-I and Col-III were markedly decreased, suggesting attenuation of fibrotic changes. Compared with pirfenidone, COCA exhibited comparable or enhanced therapeutic efficacy across most evaluated parameters, indicating that it mitigates pulmonary fibrosis through suppression of inflammatory responses, similar to pirfenidone.

CB2R expression was markedly upregulated in lung tissues of BLM-induced IPF mice, especially in fibrotic areas [16], and increased rapidly during the early inflammatory phase [27]. The control group also showed elevated CB2R levels, likely due to stress from sham surgery and saline treatment，whereas it was markedly reduced in the treatment group. This observation may be associated with the intrinsic properties of GPCRs. As noted by Nobel Laureate in Chemistry Robert Lefkowitz in a review published in the Journal of Biological Chemistry [28]: “Upon ligand binding and activation, G protein-coupled receptors (GPCRs) undergo agonist-induced downregulation and internalization via the GRKs/β-arrestin system.” This mechanism serves as a well-documented negative feedback loop that prevents overstimulation and maintains cellular homeostasis—thereby explaining why agonists often lead to reduced receptor levels. As a representative member of the GPCR family, cannabinoid receptor type 2 (CB2R) exhibits highly dynamic and regulatable expression. Under pathological conditions such as inflammation, tissue injury, and fibrosis, CB2R expression is markedly upregulated [29]. In the bleomycin (BLM) model group, BLM-induced lung injury likely elicits an endogenous compensatory upregulation of CB2R [30]. However, upon exposure to agonists, cell surface CB2R undergoes rapid internalization, leading to decreased detectable protein levels—a finding fully consistent with our Western blot results [31]. Consequently, the observed reduction in CB2R protein levels in the treatment groups strengthens, rather than undermines, the conclusion that COCA functions as a potent agonist of CB2R. How CB2R regulates IPF is still not fully understood. Studies suggest that the PI3K/Akt [32] and TGF-β1/Smad [33] pathways are involved in CB2R’s effects on immune regulation, cytokine suppression, and ECM remodeling. CB2R activation also enhances the Nrf2/Smad7 pathway, which reduces TGF-β1-induced EMT [34]. Western blot results showed higher expression of Nrf2 and Smad7 in the treatment groups, which is consistent with a potential role of this pathway in the anti-fibrotic effects of COCA.

In conclusion, AI-driven virtual screening serves as a powerful approach for the rapid identification of ligand candidates targeting specific receptor structures, holding great promise for accelerating drug discovery. Our experimental findings indicate that COCA, a CB2R ligand, exerts protective effects against BLM-induced pulmonary fibrosis (PF) in mice were associated with an upregulation of Nrf2 and Smad7 proteins， our data suggest that the mechanism of action of COCA may involve the Nrf2/Smad7 pathway.This mechanism contributes to the downregulation of inflammatory mediators, suppression of pulmonary inflammation, and reduction of alveolar wall damage and collagen deposition, thereby effectively inhibiting PF progression. These results support COCA as a promising therapeutic candidate for pulmonary fibrosis. The precise causal role of the Nrf2/Smad7 pathway in COCA’s action remains to be fully established through future mechanistic studies. We have framed our current findings as generating a strong hypothesis for future investigation.