Synthetically Feasible De Novo Molecular Design of Leads Based on a Reinforcement Learning Model: AI-Assisted Discovery of an Anti-IBD Lead Targeting CXCR4.

Artificial intelligence (AI) de novo molecular generation provides leads with novel structures for drug discovery. However, the target affinity and synthesizability of the generated molecules present critical challenges for the successful application of AI technology. Therefore, we developed an advanced reinforcement learning model to bridge the gap between the theory of de novo molecular generation and the practical aspects of drug discovery. This model utilizes chemical reaction templates and commercially available building blocks as a starting point and employs forward reaction prediction to generate molecules, while real-time docking and drug-likeness predictions are conducted to ensure synthesizability and drug-likeness. We applied this model to design active molecules targeting the inflammation-related receptor CXCR4 and successfully prepared them according to the AI-proposed synthetic routes. Several molecules exhibited potent anti-CXCR4 and anti-inflammatory activity in subsequent in vitro and in vivo assays. The top-performing compound XVI alleviated symptoms related to inflammatory bowel disease and showed reasonable pharmacokinetic properties.

Artificial Intelligence-Assisted Optimization of Antipigmentation Tyrosinase Inhibitors: De Novo Molecular Generation Based on a Low Activity Lead Compound.

Artificial intelligence (AI) de novo molecular generation is a highly promising strategy in the drug discovery, with deep reinforcement learning (RL) models emerging as powerful tools. This study introduces a fragment-by-fragment growth RL forward molecular generation and optimization strategy based on a low activity lead compound. This process integrates fragment growth-based reaction templates, while target docking and drug-likeness prediction were simultaneously performed. This comprehensive approach considers molecular similarity, internal diversity, synthesizability, and effectiveness, thereby enhancing the quality and efficiency of molecular generation. Finally, a series of tyrosinase inhibitors were generated and synthesized. Most compounds exhibited more improved activity than lead, with an optimal candidate compound surpassing the effects of kojic acid and demonstrating significant antipigmentation activity in a zebrafish model. Furthermore, metabolic stability studies indicated susceptibility to hepatic metabolism. The proposed AI structural optimization strategies will play a promising role in accelerating the drug discovery and improving traditional efficiency.

Small-molecule agents for treating skin diseases.

Skin diseases are a class of common and frequently occurring diseases that significantly impact daily lives. Currently, the limited effective therapeutic drugs are far from meeting the clinical needs; most drugs typically only provide symptomatic relief rather than a cure. Developing small-molecule drugs with improved efficacy holds paramount importance for treating skin diseases. This review aimed to systematically introduce the pathogenesis of common skin diseases in daily life, list related drugs applied in the clinic, and summarize the clinical research status of candidate drugs and the latest research progress of candidate compounds in the drug discovery stage. Also, it statistically analyzed the number of publications and global attention trends for the involved skin diseases. This review might provide practical information for researchers engaged in dermatological drugs and further increase research attention to this disease area.

CXCR4/CXCL12 axis: "old" pathway as "novel" target for anti-inflammatory drug discovery.

Inflammation is the body's defense response to exogenous or endogenous stimuli, involving complex regulatory mechanisms. Discovering anti-inflammatory drugs with both effectiveness and long-term use safety is still the direction of researchers' efforts. The inflammatory pathway was initially identified to be involved in tumor metastasis and HIV infection. However, research in recent years has proved that the CXC chemokine receptor type 4 (CXCR4)/CXC motif chemokine ligand 12 (CXCL12) axis plays a critical role in the upstream of the inflammatory pathway due to its chemotaxis to inflammatory cells. Blocking the chemotaxis of inflammatory cells by CXCL12 at the inflammatory site may block and alleviate the inflammatory response. Therefore, developing CXCR4 antagonists has become a novel strategy for anti-inflammatory therapy. This review aimed to systematically summarize and analyze the mechanisms of action of the CXCR4/CXCL12 axis in more than 20 inflammatory diseases, highlighting its crucial role in inflammation. Additionally, the anti-inflammatory activities of CXCR4 antagonists were discussed. The findings might help generate new perspectives for developing anti-inflammatory drugs targeting the CXCR4/CXCL12 axis.

Cloning of NAD-SDH cDNA from plum fruit and its expression and characterization.

A full-length cDNA consisting of 1444 bp for NAD dependent sorbitol dehydrogenase (NAD-SDH) was cloned from fruit of plum (Prunus salicina var. cordata cv. Younai) by means of RT-PCR and RACE. The cDNA containing an open reading frame (ORF) of 1101 bp encoded a polypeptide of 367 amino acid residues. The maltose binding protein fusion SDH (MBP-SDH) was expressed and partially purified from Escherichia coli cells, and biochemical properties of MBP-SDH and SDH cleaved from the fusion protein by factor Xa were characterized. The MBP-SDH had the specific affinity for NAD and was able to oxidize sorbitol, xylitol, l-ribitol and mannitol but not ethyl alcohol, arabitol and other polyols. The optimum pH for the oxidation of sorbitol and the reduction of fructose was 9.0 and 7.0, respectively; the maximum reaction rate occurred when temperature increased up to 50 °C in the presence of sorbitol. The MBP-SDH with a subunit of 80 kDa appears to be a hexamer. Its molecular weight was 478.6 kDa estimated by gel filtration and 493.2 kDa estimated using native linear gradient PAGE. The K(m) values for sorbitol, NAD, fructose and NADH were 95.86 mM, 0.31 mM, 1.04 M and 0.038 mM, respectively. However, when MBP was cleaved from the fusion enzyme, the SDH exists as a homotetramer with the native molecular weight of 164.8 kDa estimated by gel filtration. The K(m) values were 111.8 mM, 0.35 mM, 1.25 M and 0.048 mM for sorbitol, NAD, fructose and NADH, respectively. The MBP-SDH and the SDH were similar with respect to their kinetic characteristics despite their difference in quaternary structures.