Neutrophil Extracellular Traps (NETs) Are Associated with Type 2 Diabetes and Diabetic Foot Ulcer Related Amputation: A Prospective Cohort Study.

INTRODUCTION: The prevalence of diabetes mellitus and its sequelae has been on the rise, and diabetic foot ulcer (DFU) is the leading cause of non-traumatic lower limb amputation globally. The rising occurrence and financial burden associated with DFU necessitate improved clinical assessment and treatment. Diabetes has been found to enhance the formation of neutrophil extracellular traps (NETs) by neutrophils, and excessive NETs have been implicated in tissue damage and impaired wound healing. However, there is as yet insufficient evidence to clarify the value of NETs in assessing and predicting outcomes of DFU. METHODS: We designed this prospective study with three cohorts formed from type 2 diabetes mellitus (T2DM) patients with DFU (n = 200), newly diagnosed T2DM patients (n = 42), and healthy donors (n = 38). Serum levels of NETs were detected for all groups, and the prognostic value for DFU-related amputation was analyzed. RESULTS: The results showed that serum NET levels of the DFU group were significantly higher than in the T2DM group (P < 0.05), which also had significantly elevated serum NET levels compared to healthy donors (P < 0.05). Multivariate Cox regression showed that serum NET levels, diabetic foot surgical history, and Wagner grade were the risk factors for amputation (P < 0.05), and these three variables also exhibited the highest coefficient values in additional Lasso Cox regression. For patients with DFU, Kaplan-Meier curves showed that high serum NET levels associated with higher amputation probability (HR = 0.19, P < 0.01) and ROC curve based on NET value showed good validity for amputation (AUC: 0.727, CI 0.651-0.803). CONCLUSION: Elevated serum NET levels serve as an easily accessible serological prognostic marker for assessing the risk of DFU-related amputation, thereby offering evaluation metrics for healthcare providers. Further investigations are necessary to understand the mechanisms driving this relationship.

Generative deep learning enables the discovery of a potent and selective RIPK1 inhibitor.

The retrieval of hit/lead compounds with novel scaffolds during early drug development is an important but challenging task. Various generative models have been proposed to create drug-like molecules. However, the capacity of these generative models to design wet-lab-validated and target-specific molecules with novel scaffolds has hardly been verified. We herein propose a generative deep learning (GDL) model, a distribution-learning conditional recurrent neural network (cRNN), to generate tailor-made virtual compound libraries for given biological targets. The GDL model is then applied to RIPK1. Virtual screening against the generated tailor-made compound library and subsequent bioactivity evaluation lead to the discovery of a potent and selective RIPK1 inhibitor with a previously unreported scaffold, RI-962. This compound displays potent in vitro activity in protecting cells from necroptosis, and good in vivo efficacy in two inflammatory models. Collectively, the findings prove the capacity of our GDL model in generating hit/lead compounds with unreported scaffolds, highlighting a great potential of deep learning in drug discovery.

Discovery of benzo[d]oxazol-2(3H)-one derivatives as a new class of TNIK inhibitors for the treatment of colorectal cancer.

Colorectal cancer (CRC) is one of the most commonly diagnosed cancer types and Traf2- and Nck-interacting kinase (TNIK) has been thought as a potential target for CRC treatment. Herein we report the discovery and structure-activity relationship (SAR) of benzo[d]oxazol-2(3H)-one derivatives as a new class of TNIK inhibitors. The most potent compound 8g showed an IC50 value of 0.050 µM against TNIK. It effectively suppressed proliferation and migration of colorectal cancer cells. Western blot analysis indicated that 8g could inhibit aberrant transcription activation of Wnt signaling. Collectively, this study provides a potential lead compound for subsequent drug discovery targeting TNIK.

Discovery of 3,4-Dihydrobenzo[f][1,4]oxazepin-5(2H)-one Derivatives as a New Class of Selective TNIK Inhibitors and Evaluation of Their Anti-Colorectal Cancer Effects.

The Traf2- and Nck-interacting protein kinase (TNIK) is a downstream signal protein of the Wnt/ß-catenin pathway and has been thought of as a potential target for the treatment of colorectal cancer (CRC) that is often associated with dysregulation of Wnt/ß-catenin signaling pathway. Herein, we report the discovery of a series of 3,4-dihydrobenzo[f][1,4]oxazepin-5(2H)-one derivatives as a new class of TNIK inhibitors. Structure-activity relationship (SAR) analyses led to the identification of a number of potent TNIK inhibitors with compound 21k being the most active one (IC50: 0.026 ± 0.008 µM). This compound also displayed excellent selectivity for TNIK against 406 other kinases. Compound 21k could efficiently suppress CRC cell proliferation and migration in in vitro assays and exhibited considerable antitumor activity in the HCT116 xenograft mouse model. It also showed favorable pharmacokinetic properties. Overall, 21k could be a promising lead compound for drug discovery targeting TNIK and deserves further studies.

Structural Optimization and Structure-Activity Relationship Studies of 6,6-Dimethyl-4-(phenylamino)-6H-pyrimido[5,4-b][1,4]oxazin-7(8H)-one Derivatives as A New Class of Potent Inhibitors of Pan-Trk and Their Drug-Resistant Mutants.

Tropomyosin receptor kinases (TrkA, TrkB, and TrkC) are attractive therapeutic targets for multiple cancers. Two first-generation small-molecule Trks inhibitors, larotrectinib and entrectinib, have just been approved to use clinically. However, the drug-resistance mutations of Trks have already emerged, which calls for new-generation Trks inhibitors. Herein, we report the structural optimization and structure-activity relationship studies of 6,6-dimethyl-4-(phenylamino)-6H-pyrimido[5,4-b][1,4]oxazin-7(8H)-one derivatives as a new class of pan-Trk inhibitors. The prioritized compound 11g exhibited low nanomolar IC50 values against TrkA, TrkB, and TrkC and various drug-resistant mutants. It also showed good kinase selectivity. 11g displayed excellent in vitro antitumor activity and strongly suppressed Trk-mediated signaling pathways in intact cells. In in vivo studies, compound 11g exhibited good antitumor activity in BaF3-TEL-TrkA and BaF3-TEL-TrkCG623R allograft mouse models without exhibiting apparent toxicity. Collectively, 11g could be a promising lead compound for drug discovery targeting Trks and deserves further investigation.