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.

Thyroid receptor ß: A promising target for developing novel anti-androgenetic alopecia drugs.

Androgenetic alopecia (AGA) significantly impacts the self-confidence and mental well-being of people. Recent research has revealed that thyroid receptor ß (TRß) agonists can activate hair follicles and effectively stimulate hair growth. This review aims to comprehensively elucidate the specific mechanism of action of TRß in treating AGA from various perspectives, highlighting its potential as a drug target for combating AGA. Moreover, this review provides a thorough summary of the research advances in TRß agonist candidates with anti-AGA efficacy and outlines the structure-activity relationships (SARs) of TRß agonists. We hope that this review will provide practical information for the development of effective anti-alopecia drugs.

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.

Deep learning for advancing peptide drug development: Tools and methods in structure prediction and design.

Peptides can bind challenging disease targets with high affinity and specificity, offering enormous opportunities for addressing unmet medical needs. However, peptides' unique features, including smaller size, increased structural flexibility, and limited data availability, pose additional challenges to the design process compared to proteins. This review explores the dynamic field of peptide therapeutics, leveraging deep learning to enhance structure prediction and design. Our exploration encompasses various facets of peptide research, ranging from dataset curation handling to model development. As deep learning technologies become more refined, we channel our efforts into peptide structure prediction and design, aligning with the fundamental principles of structure-activity relationships in drug development. To guide researchers in harnessing the potential of deep learning to advance peptide drug development, our insights comprehensively explore current challenges and future directions of peptide therapeutics.

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.

Discovery of matrix metalloproteinase inhibitors as anti-skin photoaging agents.

Photodamage is the result of prolonged exposure of the skin to sunlight. This exposure causes an overexpression of matrix metalloproteinases (MMPs), leading to the abnormal degradation of collagen in the skin tissue and resulting in skin aging and damage. This review presents a detailed overview of MMPs as a potential target for addressing skin aging. Specifically, we elucidated the precise mechanisms by which MMP inhibitors exert their anti-photoaging effects. Furthermore, we comprehensively analyzed the current research progress on MMP inhibitors that demonstrate significant inhibitory activity against MMPs and anti-skin photoaging effects. The review also provides insights into the structure-activity relationships of these inhibitors. Our objective in conducting this review is to provide valuable practical information to researchers engaged in investigations on anti-skin photoaging.

Elemene Antitumor Drugs Development Based on "Molecular Compatibility Theory" and Clinical Application: A Retrospective and Prospective Outlook.

Elemene, derived from Curcuma wenyujin, one of the "8 famous genuine medicinal materials of Zhejiang province," exhibits remarkable antitumor activity. It has gained wide recognition in clinical practice for effectiveness on tumors. Dr. XIE Tian, introduced the innovative concept of "molecular compatibility theory" by combining Chinese medicine principles, specifically the "monarch, minister, assistant, and envoy" theory, with modern biomedical technology. This groundbreaking approach, along with a systematic analysis of Chinese medicine and modern biomedical knowledge, led to the development of elemene nanoliposome formulations. These novel formulations offer numerous advantages, including low toxicity, well-defined composition, synergistic effects on multiple targets, and excellent biocompatibility. Following the principles of the "molecular compatibility theory", further exploration of cancer treatment strategies and methods based on elemene was undertaken. This comprehensive review consolidates the current understanding of elemene's potential antitumor mechanisms, recent clinical investigations, advancements in drug delivery systems, and structural modifications. The ultimate goal of this review is to establish a solid theoretical foundation for researchers, empowering them to develop more effective antitumor drugs based on the principles of "molecular compatibility theory".

Click chemistry-aided drug discovery: A retrospective and prospective outlook.

Click chemistry has emerged as a valuable tool for rapid compound synthesis, presenting notable advantages and convenience in the exploration of potential drug candidates. In particular, in situ click chemistry capitalizes on enzymes as reaction templates, leveraging their favorable conformation to selectively link individual building blocks and generate novel hits. This review comprehensively outlines and introduces the extensive use of click chemistry in compound library construction, and hit and lead discovery, supported by specific research examples. Additionally, it discusses the limitations and precautions associated with the application of click chemistry in drug discovery. Our intention for this review is to contribute to the development of a modular synthetic approach for the rapid identification of drug candidates.

Discovery of plant-derived anti-tumor natural products: Potential leads for anti-tumor drug discovery.

Natural products represent a paramount source of novel drugs. Numerous plant-derived natural products have demonstrated potent anti-tumor properties, thereby garnering considerable interest in their potential as anti-tumor drugs. This review compiles an overview of 242 recently discovered natural products, spanning the period from 2018 to the present. These natural products, which include 69 terpenoids, 42 alkaloids, 39 flavonoids, 21 steroids, 14 phenylpropanoids, 5 quinolines and 52 other compounds, are characterized by their respective chemical structures, anti-tumor activities, and mechanisms of action. By providing an essential reference and fresh insights, this review aims to support and inspire researchers engaged in the fields of natural products and anti-tumor drug discovery.

Discovery and bioassay of disubstituted ß-elemene-NO donor conjugates: synergistic enhancement in the treatment of leukemia.

Natural products are essential sources of antitumor drugs. One such molecule, ß-elemene, is a potent antitumor compound extracted from Curcuma wenyujin. In the present investigation, a series of novel 13,14-disubstituted nitric oxide (NO)-donor ß-elemene derivatives were designed, with ß-elemene as the foundational compound, and subsequently synthesized to evaluate their therapeutic potential against leukemia. Notably, the derivative labeled as compound 13d demonstrated a potent anti-proliferative activity against the K562 cell line, with a high NO release. In vivo studies indicated that compound 13d could effectively inhibit tumor growth, exhibiting no discernible toxic manifestations. Specifically, a significant tumor growth inhibition rate of 62.9% was observed in the K562 xenograft tumor mouse model. The accumulated data propound the potential therapeutic application of compound 13d in the management of leukemia.

Discovery of anti-inflammatory natural flavonoids: Diverse scaffolds and promising leads for drug discovery.

Natural products have been utilized for medicinal purposes for millennia, endowing them with a rich source of chemical scaffolds and pharmacological leads for drug discovery. Among the vast array of natural products, flavonoids represent a prominent class, renowned for their diverse biological activities and promising therapeutic advantages. Notably, their anti-inflammatory properties have positioned them as promising lead compounds for developing novel drugs combating various inflammatory diseases. This review presents a comprehensive overview of flavonoids, highlighting their manifold anti-inflammatory activities and elucidating the underlying pathways in mediating inflammation. Furthermore, this review encompasses systematical classification of flavonoids, related anti-inflammatory targets, involved in vitro and in vivo test models, and detailed statistical analysis. We hope this review will provide researchers engaged in active natural products and anti-inflammatory drug discovery with practical information and potential leads.

Design, synthesis and biological evaluation of novel histone deacetylase (HDAC) inhibitors derived from ß-elemene scaffold.

ß-Elemene is the major active ingredient of TCM anticancer drug elemene extracts. To further improve its antitumor activity and poor solubility, a polar HDACi pharmacophore was incorporated its scaffold. Systematic SAR studies led to the discovery of compounds 27f and 39f, which exhibited potent inhibitory activity against HDACs (HDAC1: IC50 = 22 and 9 nM; HDAC6: 8 and 14 nM, respectively). In cellular levels, 27f and 39f significantly inhibited cell proliferation of five tumour cell lines (IC50: 0.79 - 4.42 µM). Preliminary mechanistic studies indicated that 27f and 39f efficiently induced cell apoptosis. Unexpectedly, compound 39f could also stimulate cell cycle arrest in G1 phase. Further in vivo study in WSU-DLCL-2 xenografted mouse model validated the antitumor activities of 27f, without significant toxicity. The results suggest the therapeutic potential of these HDACs inhibitors in lymphoma and provide valuable insight and understanding for further structural optimisation around ß-elemene scaffold.

Combination of chemotherapy and gaseous signaling molecular therapy: Novel ß-elemene nitric oxide donor derivatives against leukemia.

This study aimed to design and synthesize active hybrids of ß-elemene and nitric oxide (NO) donor pharmacophore as potential agents for treating leukemia. Derivatives reported herein exerted better inhibitory effects against human chronic myeloid leukemia K562 cells compared to ß-elemene (IC50 > 100 µM). The most potent compound 18f showed an IC50 value of 0.53 µM against K562 cells, as well as a high NO release level in vitro. In the K562 xenograft tumor mice model, compound 18f effectively inhibited the growth of the tumor, with a significant inhibition rate of 73.18%. After treatment with compound 18f, the body weight of mice did not decrease, indicating that it possessed good safety profile. All these proved that compound 18f was an excellent potential agent against leukemia.

Novel druggable mechanism of Parkinson's disease: Potential therapeutics and underlying pathogenesis based on ferroptosis.

Genetics, age, environmental factors, and oxidative stress have all been implicated in the development of Parkinson's disease (PD); however, a complete understanding of its pathology remains elusive. At present, there is no cure for PD, and currently available therapeutics are insufficient to meet patient needs. Ferroptosis, a distinctive iron-dependent cell death mode characterized by lipid peroxidation and oxidative stress, has pathophysiological features similar to those of PD, including iron accumulation, reactive oxygen species-induced oxidative damage, and mitochondrial dysfunction. Ferroptosis has been identified as a specific pathway of neuronal death and is closely related to the pathogenesis of PD. Despite the similarities in the biological targets involved in PD pathogenesis and ferroptosis, the relationship between novel targets in PD and ferroptosis has been neglected in the literature. In this review, the mechanism of ferroptosis is discussed, and the potential therapeutic targets implicated in both PD and ferroptosis are compared. Furthermore, the anti-PD effects of several ferroptosis inhibitors, as well as clinical studies thereof, and the identification of novel lead compounds for the treatment of PD and the inhibition of ferroptosis are reviewed. It is hoped that this review can promote research to further elucidate the relationship between ferroptosis and PD and provide new strategies for the development of novel ferroptosis-targeting PD therapy.

Microwave-assisted rapid synthesis of chiral oxazolines.

Chiral oxazoline compounds play an extremely important role in asymmetric synthesis and drug discovery. Herein a simpler, greener and more efficient microwave-assisted protocol to rapidly access chiral oxazolines is developed using aryl nitriles or cyano-containing compounds and chiral ß-amino alcohols as starting materials. The reaction proceeds smoothly in the presence of a recoverable heterogeneous catalyst in either concentrated solution or under solvent-free conditions. The advantages of this method include rapidness, convenience, environmental protection, high atom economy, and excellent yields. The protocol should find wider application in the community in the future.

Design, synthesis and antitumor efficacy evaluation of a series of novel ß-elemene-based macrocycles.

ß-Elemene is the major constituent of the antitumor drugs elemene extract approved in China. By incorporating macrocyclization strategy into the ß-elemene skeleton, we designed a series of novel macrocycles retaining three key carbon-carbon double bonds. Four different methods have been successfully developed for these challenging ring systems. A total of twenty-eight 14- to 24-membered macrocycles were synthesized. Most of these macrocycles exhibited good antitumor activity against several cancer cell lines (PC-3, A549, U87MG, U251 and HCT116), with up to 40 folds improvement of activity comparing to ß-elemene. Additionally, X-ray single crystal structures of compounds Ic, Ip, and IIh were successfully solved as the proof of macrocycle formation. The results warrant the further investigation of this novel class macrocycles in pharmacokinetic and pharmacodynamics studies, which will be reported in due course.

Novel hydroxyl carboximates derived from ß-elemene: design, synthesis and anti-tumour activities evaluation.

A series of novel N-alkyl-N-hydroxyl carboximates derived from ß-elemene were fortuitously discovered. Most of them showed more potent anti-proliferative activities than their lead compound ß-elemene (1). Notably, compound 11i exhibited significant inhibitory effects on the proliferation of three lung cell lines (H1975, A549 and H460) and several other tumour cell lines (H1299, U87MG, MV4-11, and SU-DHL-2). Preliminary mechanistic studies revealed that compound 11i could significantly induce cell apoptosis. Further in vivo study in the H460 xenograft mouse model validated the anti-tumour activities of 11i with a greater tumour growth inhibition (TGI, 68.3%) than ß-elemene and SAHA (50.1% and 55.9% respectively) at 60 mg/kg ip dosing, without obvious body weight loss and toxicity. Thus, such N-alkyl-N-hydroxyl carboximate class of compounds exemplified as 11i demonstrated potent anticancer activities both in vitro and in vivo, and should warrant further investigation for potential anticancer therapy.

From theory to experiment: transformer-based generation enables rapid discovery of novel reactions.

Deep learning methods, such as reaction prediction and retrosynthesis analysis, have demonstrated their significance in the chemical field. However, the de novo generation of novel reactions using artificial intelligence technology requires further exploration. Inspired by molecular generation, we proposed a novel task of reaction generation. Herein, Heck reactions were applied to train the transformer model, a state-of-art natural language process model, to generate 4717 reactions after sampling and processing. Then, 2253 novel Heck reactions were confirmed by organizing chemists to judge the generated reactions. More importantly, further organic synthesis experiments were performed to verify the accuracy and feasibility of representative reactions. The total process, from Heck reaction generation to experimental verification, required only 15 days, demonstrating that our model has well-learned reaction rules in-depth and can contribute to novel reaction discovery and chemical space exploration.

Natural terpenoids with anti-inflammatory activities: Potential leads for anti-inflammatory drug discovery.

Natural products are mainly secondary metabolites produced by plants, microorganisms, and animals, which are still abundant in modern drug discovery. Terpenoids are the most diverse group of natural products, attracting extensive attention owing to their various biological activities. This manuscript reviewed the chemical structures, anti-inflammatory activities, and mechanisms of action of 281 terpenoid natural products reported from 2010 to the present. Their biological targets and both in vitro and in vivo screening models were also surveyed and statistically summarized. This review will provide potential anti-inflammatory lead compounds and helpful information to researchers engaged in natural products and anti-inflammatory drug discovery.