Trigonelline hydrochloride attenuates silica-induced pulmonary fibrosis by orchestrating fibroblast to myofibroblast differentiation.

BACKGROUND: Silicosis represents a paramount occupational health hazard globally, with its incidence, morbidity, and mortality on an upward trajectory, posing substantial clinical dilemmas due to limited effective treatment options available. Trigonelline (Trig), a plant alkaloid extracted mainly from coffee and fenugreek, have diverse biological properties such as protecting dermal fibroblasts against ultraviolet radiation and has the potential to inhibit collagen synthesis. However, it's unclear whether Trig inhibits fibroblast activation to attenuate silicosis-induced pulmonary fibrosis is unclear. METHODS: To evaluate the therapeutic efficacy of Trig in the context of silicosis-related pulmonary fibrosis, a mouse model of silicosis was utilized. The investigation seeks to elucidated Trig's impact on the progression of silica-induced pulmonary fibrosis by evaluating protein expression, mRNA levels and employing Hematoxylin and Eosin (H&E), Masson's trichrome, and Sirius Red staining. Subsequently, we explored the mechanism underlying of its functions. RESULTS: In vivo experiment, Trig has been demonstrated the significant efficacy in mitigating SiO2-induced silicosis and BLM-induced pulmonary fibrosis, as evidenced by improved histochemical staining and reduced fibrotic marker expressions. Additionally, we showed that the differentiation of fibroblast to myofibroblast was imped in Trig + SiO2 group. In terms of mechanism, we obtained in vitro evidence that Trig inhibited fibroblast-to-myofibroblast differentiation by repressing TGF-ß/Smad signaling according to the in vitro evidence. Notably, our finding indicated that Trig seemed to be safe in mice and fibroblasts. CONCLUSION: In summary, Trig attenuated the severity of silicosis-related pulmonary fibrosis by alleviating the differentiation of myofibroblasts, indicating the development of novel therapeutic approaches for silicosis fibrosis.

MTMol-GPT: De novo multi-target molecular generation with transformer-based generative adversarial imitation learning.

De novo drug design is crucial in advancing drug discovery, which aims to generate new drugs with specific pharmacological properties. Recently, deep generative models have achieved inspiring progress in generating drug-like compounds. However, the models prioritize a single target drug generation for pharmacological intervention, neglecting the complicated inherent mechanisms of diseases, and influenced by multiple factors. Consequently, developing novel multi-target drugs that simultaneously target specific targets can enhance anti-tumor efficacy and address issues related to resistance mechanisms. To address this issue and inspired by Generative Pre-trained Transformers (GPT) models, we propose an upgraded GPT model with generative adversarial imitation learning for multi-target molecular generation called MTMol-GPT. The multi-target molecular generator employs a dual discriminator model using the Inverse Reinforcement Learning (IRL) method for a concurrently multi-target molecular generation. Extensive results show that MTMol-GPT generates various valid, novel, and effective multi-target molecules for various complex diseases, demonstrating robustness and generalization capability. In addition, molecular docking and pharmacophore mapping experiments demonstrate the drug-likeness properties and effectiveness of generated molecules potentially improve neuropsychiatric interventions. Furthermore, our model's generalizability is exemplified by a case study focusing on the multi-targeted drug design for breast cancer. As a broadly applicable solution for multiple targets, MTMol-GPT provides new insight into future directions to enhance potential complex disease therapeutics by generating high-quality multi-target molecules in drug discovery.

Structural insight into the subclass B1 metallo-ß-lactamase AFM-1.

The emergence of drug-resistant bacteria, facilitated by metallo-beta-lactamases (MBLs), presents a significant obstacle to the effective use of antibiotics in the management of clinical drug-resistant bacterial infections. AFM-1 is a MBL derived from Alcaligenes faecalis and shares 86% homology with the NDM-1 family. Both AFM-1 and NDM-1 demonstrate the ability to hydrolyze ampicillin and other ß-lactam antibiotics, however, their substrate affinities vary, and the specific reason for this variation remains unknown. We present the high-resolution structure of AFM-1. The active center of AFM-1 binds two zinc ions, and the conformation of the key amino acid residues in the active center is in accordance with that of NDM-1. However, the substrate-binding pocket of AFM-1 is considerably smaller than that of NDM-1. Additionally, the mutation of amino acid residues in the Loop3 region, as compared to NDM-1, results in the formation of a dense hydrophobic patch comprised of hydrophobic amino acid residues in this area, which facilitates substrate binding. Our findings lay the foundation for understanding the molecular mechanism of AFM-1 with a high affinity for substrates and provide a novel theoretical foundation for addressing the issue of drug resistance caused by B1 MBLs.

Cellular and molecular mechanisms of fibrosis and resolution in bleomycin-induced pulmonary fibrosis mouse model revealed by spatial transcriptome analysis.

The bleomycin-induced pulmonary fibrosis mouse model is commonly used in idiopathic pulmonary fibrosis research, but its cellular and molecular changes and efficiency as a model at the molecular level are not fully understood. In this study, we used spatial transcriptome technology to investigate the cellular and molecular changes in the lungs of bleomycin-induced pulmonary fibrosis mouse models. Our analyses revealed cell dynamics during fibrosis in epithelial cells, mesenchymal cells, immunocytes, and erythrocytes with their spatial distribution available. We confirmed the differentiation of the alveolar type II (AT2) cell type expressing Krt8, and we inferred their trajectories from both the AT2 cells and club cells. In addition to the fibrosis process, we also noticed evidence of self-resolving, especially to identify possible self-resolving related genes, including Prkca. Our findings provide insights into the cellular and molecular mechanisms underlying fibrosis resolution and represent the first spatiotemporal transcriptome dataset of the bleomycin-induced fibrosis mouse model.