Overview of class I HDAC modulators: Inhibitors and degraders.

Class I histone deacetylases (HDACs) are closely associated with the development of a diverse array of diseases, including cancer, neurodegenerative disorders, HIV, and inflammatory diseases. Considering the essential roles in tumorigenesis, class I HDACs have emerged as highly desirable targets for therapeutic strategies, particularly in the field of anticancer drug development. However, the conventional class I HDAC inhibitors faced several challenges such as acquired resistance, inherent toxicities, and limited efficacy in inhibiting non-enzymatic functions of HDAC. To address these problems, novel strategies have emerged, including the development of class I HDAC dual-acting inhibitors, targeted protein degradation (TPD) technologies such as PROTACs, molecular glues, and HyT degraders, as well as covalent inhibitors. This review provides a comprehensive overview of class I HDAC enzymes and inhibitors, by initially introducing their structure and biological roles. Subsequently, we focus on the recent advancements of class I HDAC modulators, including isoform-selective class I inhibitors, dual-target inhibitors, TPDs, and covalent inhibitors, from the perspectives of rational design principles, pharmacodynamics, pharmacokinetics, and clinical progress. Finally, we also provide the challenges and outlines future prospects in the realm of class I HDAC-targeted drug discovery for cancer therapeutics.

Development and validation of early prediction models for new-onset functional impairment in patients after being transferred from the ICU.

A significant number of intensive care unit (ICU) survivors experience new-onset functional impairments that impede their activities of daily living (ADL). Currently, no effective assessment tools are available to identify these high-risk patients. This study aims to develop an interpretable machine learning (ML) model for predicting the onset of functional impairment in critically ill patients. Data for this study were sourced from a comprehensive hospital in China, focusing on adult patients admitted to the ICU from August 2022 to August 2023 without prior functional impairments. A least absolute shrinkage and selection operator (LASSO) model was utilized to select predictors for inclusion in the model. Four models, logistic regression, support vector machine (SVM), random forest (RF), and extreme gradient boosting (XGBoost), were constructed and validated. Model performance was assessed using the area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV). Additionally, the DALEX package was employed to enhance the interpretability of the final models. The study ultimately included 1,380 patients, with 684 (49.6%) exhibiting new-onset functional impairment on the seventh day after leaving the ICU. Among the four models evaluated, the SVM model demonstrated the best performance, with an AUC of 0.909, accuracy of 0.838, sensitivity of 0.902, specificity of 0.772, PPV of 0.802, and NPV of 0.886. ML models are reliable tools for predicting new-onset functional impairments in critically ill patients. Notably, the SVM model emerged as the most effective, enabling early identification of patients at high risk and facilitating the implementation of timely interventions to improve ADL.

Overview of epigenetic degraders based on PROTAC, molecular glue, and hydrophobic tagging technologies.

Epigenetic pathways play a critical role in the initiation, progression, and metastasis of cancer. Over the past few decades, significant progress has been made in the development of targeted epigenetic modulators (e.g., inhibitors). However, epigenetic inhibitors have faced multiple challenges, including limited clinical efficacy, toxicities, lack of subtype selectivity, and drug resistance. As a result, the design of new epigenetic modulators (e.g., degraders) such as PROTACs, molecular glue, and hydrophobic tagging (HyT) degraders has garnered significant attention from both academia and pharmaceutical industry, and numerous epigenetic degraders have been discovered in the past decade. In this review, we aim to provide an in-depth illustration of new degrading strategies (2017-2023) targeting epigenetic proteins for cancer therapy, focusing on the rational design, pharmacodynamics, pharmacokinetics, clinical status, and crystal structure information of these degraders. Importantly, we also provide deep insights into the potential challenges and corresponding remedies of this approach to drug design and development. Overall, we hope this review will offer a better mechanistic understanding and serve as a useful guide for the development of emerging epigenetic-targeting degraders.

Degradation of oxalic acid by the mycoparasite Coniothyrium minitans plays an important role in interacting with Sclerotinia sclerotiorum.

Coniothyrium minitans (Cm) is a mycoparasite of the phytopathogenic fungus Sclerotinia sclerotiorum (Ss). Ss produces a virulence factor oxalic acid (OA) which is toxic to plants and also to Cm, and Cm detoxifies OA by degradation. In this study, two oxalate decarboxylase genes, Cmoxdc1 and Cmoxdc2, were cloned from Cm strain Chy-1. OA and low pH induced expression of Cmoxdc1, but not Cmoxdc2. Cmoxdc1 was partially responsible for OA degradation, whereas Cmoxdc2 had no effect on OA degradation. Disruption of Cmoxdc1 in Cm reduced its ability to infect Ss in dual cultures where OA accumulated. Compared with Chy-1, the Cmoxdc1-disrupted mutants had reduced expression levels of two mycoparasitism-related genes chitinase (Cmch1) and ß-1,3-glucanase (Cmg1), and had no detectable activity of extracellular proteases in the presence of OA. On the other hand, the cultural filtrates of the Cmoxdc1-disrupted mutants in OA-amended media showed enhanced antifungal activity, possibly because of increased production of antifungal substances under acidic pH condition resulted from reduced Cmoxdc1-mediated OA degradation. This study provides direct genetic evidence of OA degradation regulating mycoparasitism and antibiosis of Cm against Ss, and sheds light on the sophisticated strategies of Cm in interacting with metabolically active mycelia and dormant sclerotia of Ss.