Aldehyde oxidase mediated drug metabolism: an underpredicted obstacle in drug discovery and development

Atypical applications of transverse diffusion of laminar flow profiles methodology for in-capillary reactions in capillary electrophoresis

Capillary electrophoresis (CE) is a powerful separation technique offering quick and efficient analyses in various fields of bioanalytical chemistry. It is characterized by many well-known advantages, but one, which is perhaps the most important for this application field, is somewhat overlooked. It is the possibility to perform chemical and biochemical reactions at the nL scale inside the separation capillary. There are two basic formats applicable for this purpose, heterogeneous and homogeneous. In the former, one reactant is immobilized onto a particle or monolithic support or directly on the capillary wall, and the other is injected. In the latter, the reactant mixing inside a capillary is based on electromigration or diffusion. One of the diffusion-based methodologies, termed Transverse Diffusion of Laminar Flow Profiles, is the subject of this review. Since most studies utilizing in-capillary reactions in CE focus on enzymes, which are being continuously and exhaustively reviewed, this review covers the atypical applications of this methodology, but still in the bioanalytical field. As can be seen from the demonstrated applications, they are not limited to reactions, but can also be utilized for other biochemical systems.

Nanozyme as a rising star for metabolic disease management

Nanozyme, characterized by outstanding and inherent enzyme-mimicking properties, have emerged as highly promising alternatives to natural enzymes owning to their exceptional attributes such as regulation of oxidative stress, convenient storage, adjustable catalytic activities, remarkable stability, and effortless scalability for large-scale production. Given the potent regulatory function of nanozymes on oxidative stress and coupled with the fact that reactive oxygen species (ROS) play a vital role in the occurrence and exacerbation of metabolic diseases, nanozyme offer a unique perspective for therapy through multifunctional activities, achieving essential results in the treatment of metabolic diseases by directly scavenging excess ROS or regulating pathologically related molecules. The rational design strategies, nanozyme-enabled therapeutic mechanisms at the cellular level, and the therapies of nanozyme for several typical metabolic diseases and underlying mechanisms are discussed, mainly including obesity, diabetes, cardiovascular disease, diabetic wound healing, and others. Finally, the pharmacokinetics, safety analysis, challenges, and outlooks for the application of nanozyme are also presented. This review will provide some instructive perspectives on nanozyme and promote the development of enzyme-mimicking strategies in metabolic disease therapy.

Transfer learning enhanced graph neural network for aldehyde oxidase metabolism prediction and its experimental application

Aldehyde oxidase (AOX) is a molybdoenzyme that is primarily expressed in the liver and is involved in the metabolism of drugs and other xenobiotics. AOX-mediated metabolism can result in unexpected outcomes, such as the production of toxic metabolites and high metabolic clearance, which can lead to the clinical failure of novel therapeutic agents. Computational models can assist medicinal chemists in rapidly evaluating the AOX metabolic risk of compounds during the early phases of drug discovery and provide valuable clues for manipulating AOX-mediated metabolism liability. In this study, we developed a novel graph neural network called AOMP for predicting AOX-mediated metabolism. AOMP integrated the tasks of metabolic substrate/non-substrate classification and metabolic site prediction, while utilizing transfer learning from 13C nuclear magnetic resonance data to enhance its performance on both tasks. AOMP significantly outperformed the benchmark methods in both cross-validation and external testing. Using AOMP, we systematically assessed the AOX-mediated metabolism of common fragments in kinase inhibitors and successfully identified four new scaffolds with AOX metabolism liability, which were validated through in vitro experiments. Furthermore, for the convenience of the community, we established the first online service for AOX metabolism prediction based on AOMP, which is freely available at https://aomp.alphama.com.cn.