ChemHub: a knowledgebase of functional chemicals for synthetic biology studies

High-throughput prediction of enzyme promiscuity based on substrate-product pairs

The screening of enzymes for catalyzing specific substrate-product pairs is often constrained in the realms of metabolic engineering and synthetic biology. Existing tools based on substrate and reaction similarity predominantly rely on prior knowledge, demonstrating limited extrapolative capabilities and an inability to incorporate custom candidate-enzyme libraries. Addressing these limitations, we have developed the Substrate-product Pair-based Enzyme Promiscuity Prediction (SPEPP) model. This innovative approach utilizes transfer learning and transformer architecture to predict enzyme promiscuity, thereby elucidating the intricate interplay between enzymes and substrate-product pairs. SPEPP exhibited robust predictive ability, eliminating the need for prior knowledge of reactions and allowing users to define their own candidate-enzyme libraries. It can be seamlessly integrated into various applications, including metabolic engineering, de novo pathway design, and hazardous material degradation. To better assist metabolic engineers in designing and refining biochemical pathways, particularly those without programming skills, we also designed EnzyPick, an easy-to-use web server for enzyme screening based on SPEPP. EnzyPick is accessible at http://www.biosynther.com/enzypick/.

MycotoxinDB: A Data-Driven Platform for Investigating Masked Forms of Mycotoxins

Mycotoxins are likely to be converted into masked forms when subjected to plant metabolism or food processing. These masked forms of mycotoxins together with their prototypes may cause mixture toxicity effects, causing adverse effects on animal welfare and productivity. The structure elucidation of masked mycotoxins is the most challenging task in mycotoxin research due to the limitations of traditional analysis methods. To assist in the rapid identification of masked mycotoxins, we developed a data-driven online prediction tool, MycotoxinDB, based on reaction rules. Using MycotoxinDB, we identified seven masked DONs from wheat samples. Given its widespread applications, we expect that MycotoxinDB will become an indispensable tool in future mycotoxin research. MycotoxinDB is freely available at: http://www.mycotoxin-db.com/.

Recent Development of MOF-Based Photothermal Agent for Tumor Ablation

Metal-organic frameworks (MOFs) are 3D-architecture compounds of metal ions and organic molecules with sufficient and permanent porosity, showing great potential as a versatile platform to load various functional moieties to endow the hybrid materials with specific applications. Currently, a variety of photothermal nanometals have been embedded into organic ligands for integrating the unique photothermal effects with the merits of MOFs to improve their performances for cancer therapy. In this review, we have summarized a series of novel MOF-based photothermal materials for this unique therapeutic modality against tumors from three main aspects according to their chemical compositions and structures, i) metal-doped MOF, ii) organic-doped MOF, and iii) polymer-coated MOF. In addition, we have summarized the latest developments and characteristics of MOF-based photothermal agents, such as good biocompatibility, low toxicity, and responsive photothermal conversion without destroying the structure of hybrid photothermal agent. At last, we addressed the future perspectives of MOF-based photothermal agent in the field of phototherapy.