Develop Targeted Protein Drug Carriers through a High-Throughput Screening Platform and Rational Design.

Protein-based drugs offer advantages, such as high specificity, low toxicity, and minimal side effects compared to small molecule drugs. However, delivery of proteins to target tissues or cells remains challenging due to the instability, diverse structures, charges, and molecular weights of proteins. Polymers have emerged as a leading choice for designing effective protein delivery systems, but identifying a suitable polymer for a given protein is complicated by the complexity of both proteins and polymers.

Enhanced compound-protein binding affinity prediction by representing protein multimodal information via a coevolutionary strategy.

Due to the lack of a method to efficiently represent the multimodal information of a protein, including its structure and sequence information, predicting compound-protein binding affinity (CPA) still suffers from low accuracy when applying machine-learning methods. To overcome this limitation, in a novel end-to-end architecture (named FeatNN), we develop a coevolutionary strategy to jointly represent the structure and sequence features of proteins and ultimately optimize the mathematical models for predicting CPA. Furthermore, from the perspective of data-driven approach, we proposed a rational method that can utilize both high- and low-quality databases to optimize the accuracy and generalization ability of FeatNN in CPA prediction tasks.

Release and removal of algal organic matter during prechlorination and coagulation treatment of cyanobacteria-laden water: Are we on track?

A better understanding of the physicochemical properties and fate of algae-derived organic matter (AOM) in water treatments significantly benefits the control of algae-derived disinfection byprodcuts and process parameter optimization. In this study, we conducted a comprehensive investigation of the release and treatability of dissolved organic matter during prechlorination and postcoagulation treatments of cyanobacteria-laden source water via size-exclusion chromatography-tandem diode array detector, fluorescence detector and organic carbon detector. The results revealed that the allochthonous humic substances could protect algal cell membrane from damage during prechlorination at a low level of chlorine dose.