Numerous c-mesenchymal-epithelial transition (c-MET) inhibitors have been reported as potential anticancer agents. However, most fail to enter clinical trials owing to poor efficacy or drug resistance. To date, the scaffold-based chemical space of small-molecule c-MET inhibitors has not been analyzed. In this study, we constructed the largest c-MET dataset, which included 2,278 molecules with different structures, by inhibiting the half maximal inhibitory concentration (IC₅₀) of kinase activity. No significant differences in drug-like properties were observed between active molecules (1,228) and inactive molecules (1,050), including chemical space coverage, physicochemical properties, and absorption, distribution, metabolism, excretion, and toxicity (ADMET) profiles. The higher chemical diversity of the active molecules was downscaled using t-distributed stochastic neighbor embedding (t-SNE) high-dimensional data. Further clustering and chemical space networks (CSNs) analyses revealed commonly used scaffolds for c-MET inhibitors, such as M5, M7, and M8. Activity cliffs and structural alerts were used to reveal "dead ends" and "safe bets" for c-MET, as well as dominant structural fragments consisting of pyridazinones, triazoles, and pyrazines. Finally, the decision tree model precisely indicated the key structural features required to constitute active c-MET inhibitor molecules, including at least three aromatic heterocycles, five aromatic nitrogen atoms, and eight nitrogen-oxygen atoms. Overall, our analyses revealed potential structure-activity relationship (SAR) patterns for c-MET inhibitors, which can inform the screening of new compounds and guide future optimization efforts.

BACKGROUNDNon-small cell lung cancer (NSCLC) is one of the most common malignant tumors. Despite the advances in therapy over the years, its mortality remains high. The aim of this study was to evaluate the expression of small ubiquitin-like modifier (SUMO) proteases 1 (SENP1) in NSCLC tissues and its role in the regulation of vascular endothelial growth factor (VEGF) expression. We also investigated the association between the expression level of SENP1 and the clinicopathological features and survival of the patients.

METHODSA SENP1 small interfering RNA (siRNA) was constructed and transfected into the NSCLC cells. VEGF gene expression was analyzed by real-time polymerase chain reaction (RT-PCR). Immunohistochemistry staining was used to assess the expression of SENP1 in 100 NSCLC patients and its association with the clinicopathological features and survival was analyzed.

RESULTSVEGF expression was significantly higher in NSCLC tissues than in normal lung tissues. Inhibition of SENP1 by siRNA was associated with decreased VEGF expression. SENP1 was over-expressed in 55 of the 100 NSCLC samples (55%) and was associated with a moderate and low histological tumor grade (3.6%, 38.2%, and 58.2% in high, moderate and low differentiated tumors, respectively, P = 0.046), higher T stage (10.9% in T1, and 89.1% in T2 and T3 tumor samples, P < 0.001) and TNM stage (10.9% in stage I, and 89.1% in stages II and III tumor samples, P < 0.001). The rate of lymph node metastasis was significantly higher in the SENP1 over-expression group (76.4%) than that in the SENP1 low expression group (33.3%, P < 0.001). Sixty three patients received postoperative chemotherapy, including 34 with SENP1 over-expression and 29 with SENP1 low expression. Among the 34 patients with SENP1 over-expression, 22 (64.7%) patients developed recurrence or metastasis, significantly higher than those in the low expression group 27.6% (8/29) (P = 0.005). Multivariate Cox regression analysis showed that lymph node metastasis (P = 0.015), TNM stage (P = 0.001), and SENP1 expression level (P = 0.002) were independent prognostic factors for the survival of NSCLC patients.

CONCLUSIONSSENP1 may be a promising predictor of survival, a predictive factor of chemo-sensitivity for NSCLC patients, and potentially a desirable drug target for lung carcinoma target therapy.

Antineoplastic Agents ; therapeutic use ; Blotting, Western ; Carcinoma, Non-Small-Cell Lung ; drug therapy ; genetics ; metabolism ; Cell Line, Tumor ; Cysteine Endopeptidases ; Endopeptidases ; genetics ; metabolism ; Female ; Humans ; Immunohistochemistry ; In Vitro Techniques ; Lung Neoplasms ; drug therapy ; genetics ; metabolism ; Male ; Reverse Transcriptase Polymerase Chain Reaction