HDAC7, a member of class IIa HDACs, plays a pivotal regulatory role in tumor, immune, fibrosis, and angiogenesis, rendering it a potential therapeutic target. Nevertheless, due to the high similarity in the enzyme active sites of class IIa HDACs, inhibitors encounter challenges in discerning differences among them. Furthermore, the substitution of key residue in the active pocket of class IIa HDACs renders them pseudo-enzymes, leading to a limited impact of enzymatic inhibitors on their function. In this study, proteolysis targeting chimera (PROTAC) technology was employed to develop HDAC7 drugs. We developed an exceedingly selective HDAC7 PROTAC degrader B14 which showcased superior inhibitory effects on cell proliferation compared to TMP269 in various diffuse large B cell lymphoma (DLBCL) and acute myeloid leukemia (AML) cells. Subsequent investigations unveiled that B14 disrupts BCL6 forming a transcriptional inhibition complex by degrading HDAC7, thereby exerting proliferative inhibition in DLBCL. Our study broadened the understanding of the non-enzymatic functions of HDAC7 and underscored the importance of HDAC7 in the treatment of hematologic malignancies, particularly in DLBCL and AML.

With the rapid development of artificial intelligence technology,small molecule generation models have emerged as a significant research direction in the field of drug discovery.These models,including Generative Adversarial Networks(GANs),Variational Autoencoders(VAEs),and diffusion models,have proven to possess remarkable capabilities in optimizing drug properties and generating complex molecular structures.This article comprehensively analyzes the application of the aforementioned advanced technologies in the drug discovery process,demonstrating how they supplement and enhance traditional drug design methods.At the same time,it addresses the challenges facing current methods in terms of data quality,model complexity,computational cost,and generalization ability,with a prospect of future research directions.

While neuroblastoma accounts for 15% of childhood tumor-related deaths, treatments against neuroblastoma remain scarce and mainly consist of cytotoxic chemotherapeutic drugs. Currently, maintenance therapy of differentiation induction is the standard of care for neuroblastoma patients in clinical, especially high-risk patients. However, differentiation therapy is not used as a first-line treatment for neuroblastoma due to low efficacy, unclear mechanism, and few drug options. Through compound library screening, we accidently found the potential differentiation-inducing effect of AKT inhibitor Hu7691. The protein kinase B (AKT) pathway is an important signaling pathway for regulating tumorigenesis and neural differentiation, yet the relation between the AKT pathway and neuroblastoma differentiation remains unclear. Here, we reveal the anti-proliferation and neurogenesis effect of Hu7691 on multiple neuroblastoma cell lines. Further evidence including neurites outgrowth, cell cycle arrest, and differentiation mRNA marker clarified the differentiation-inducing effect of Hu7691. Meanwhile, with the introduction of other AKT inhibitors, it is now clear that multiple AKT inhibitors can induce neuroblastoma differentiation. Furthermore, silencing AKT was found to have the effect of inducing neuroblastoma differentiation. Finally, confirmation of the therapeutic effects of Hu7691 is dependent on inducing differentiation in vivo, suggesting that Hu7691 is a potential molecule against neuroblastoma. Through this study, we not only define the key role of AKT in the progression of neuroblastoma differentiation but also provide potential drugs and key targets for the application of differentiation therapies for neuroblastoma clinically.