Peptide-based therapies have attracted considerable interest in the treatment of cancer, diabetes, bacterial infections, and neurodegenerative diseases due to their promising therapeutic properties and enhanced safety profiles. This review provides a comprehensive overview of the major trends in peptide drug discovery and development, emphasizing preclinical strategies aimed at improving peptide stability, specificity, and pharmacokinetic properties. It assesses the current applications and challenges of peptide-based drugs in these diseases, illustrating the pharmaceutical areas where peptide-based drugs demonstrate significant potential. Furthermore, this review analyzes the obstacles that must be overcome in the future, aiming to provide valuable insights and references for the continued advancement of peptide-based drugs.
Humans ; Peptides/pharmacology* ; Animals ; Neoplasms/drug therapy* ; Drug Discovery ; Neurodegenerative Diseases/drug therapy* ; Diabetes Mellitus/drug therapy*

Pure drug nanomedicines (PDNs) encompass active pharmaceutical ingredients (APIs), including macromolecules, biological compounds, and functional components. They overcome research barriers and conversion thresholds associated with nanocarriers, offering advantages such as high drug loading capacity, synergistic treatment effects, and environmentally friendly production methods. This review provides a comprehensive overview of the latest advancements in PDNs, focusing on their essential components, design theories, and manufacturing techniques. The physicochemical properties and in vivo behaviors of PDNs are thoroughly analyzed to gain an in-depth understanding of their systematic characteristics. The review introduces currently approved PDN products and further explores the opportunities and challenges in expanding their depth and breadth of application. Drug nanocrystals, drug-drug cocrystals (DDCs), antibody-drug conjugates (ADCs), and nanobodies represent the successful commercialization and widespread utilization of PDNs across various disease domains. Self-assembled pure drug nanoparticles (SAPDNPs), a next-generation product, still require extensive translational research. Challenges persist in transitioning from laboratory-scale production to mass manufacturing and overcoming the conversion threshold from laboratory findings to clinical applications.
Nanomedicine ; Humans ; Nanoparticles/chemistry* ; Pharmaceutical Preparations/chemistry* ; Animals ; Drug Carriers/chemistry*

Natural products (NPs) have long held a significant position in various fields such as medicine, food, agriculture, and materials. The chemical space covered by NPs is extensive but often underexplored. Therefore, high-throughput and efficient methodologies for the annotation and discovery of NPs are desired to address the complexity and diversity of NP-based systems. Mass spectrometry (MS) has emerged as a powerful platform for the annotation and discovery of NPs. MS databases provide vital support for the structural characterization of NPs by integrating extensive mass spectral data and sample information. Additionally, the released annotation methodologies, based on a variety of informatics tools, continuously improve the ability to annotate the structure and properties of compounds. This review examines the current mainstream databases and annotation methodologies, focusing on their advantages and limitations. Prospects for future technological advancements are then discussed in terms of novel applications and research objectives. Through a systematic overview, this review aims to provide valuable insights and a reference for MS-based NPs annotation, thereby promoting the discovery of novel natural entities.
Biological Products/chemistry* ; Mass Spectrometry/methods* ; Databases, Factual ; Drug Discovery/methods* ; Humans

The bioactivity-guided isolation of potentially active natural products has been widely utilized in pharmaceutical discovery. In this study, by screening fungal extracts against coxsackievirus B3 (CVB3), three new aspochalasins, templichalasins A‒C (1‒3), along with six known aspochalasins (4‒9) were isolated from an active extract derived from the endophytic fungus Aspergillus templicola LHWf045. Compound 1 features a unique 5/6/5/7/5 pentacyclic ring system, while compounds 2 and 3 possess unusual 5/6/6/7 tetracyclic skeletons. Their structures were characterized through extensive spectroscopic analyses, electronic circular dichroism (ECD) calculations, and single-crystal X-ray diffraction analysis. Additionally, we demonstrated that compound 4 can be readily converted into compounds 1‒3 under mild acidic conditions and proposed a plausible mechanism for this conversion. Bioactivity evaluation of compounds 1‒9 against CVB3 revealed the inhibitory effects of all compounds against the virus. Notably, compound 9 exhibited superior antiviral activity, surpassing the commercial drug ribavirin in selectivity index (SI) value.
Antiviral Agents/isolation & purification* ; Aspergillus/chemistry* ; Molecular Structure ; Enterovirus B, Human/drug effects* ; Endophytes/chemistry* ; Cytochalasins/isolation & purification* ; Drug Discovery ; Humans

Saponins associated with Panax notoginseng (P. notoginseng) demonstrate significant therapeutic efficacy across multiple diseases. However, certain high-yield saponins face limited clinical applications due to their reduced pharmacological efficacy. This study synthesized and evaluated 36 saponin-1,2,3-triazole derivatives of ginsenosides Rg1/Rb1 and notoginsenoside R1 for anti-adipogenesis activity in vitro. The research revealed that the ginsenosides Rg1-1,2,3-triazole derivative a17 demonstrates superior adipogenesis inhibitory effects. Structure-activity relationships (SARs) analysis indicates that incorporating an amidyl-substituted 1,2,3-triazole into the saponin side chain via Click reaction enhances anti-adipogenesis activity. Additionally, several other derivatives exhibit general adipogenesis inhibition. Compound a17 demonstrated enhanced potency compared to the parent ginsenoside Rg1. Mechanistic investigations revealed that a17 exhibits dose-dependent inhibition of adipogenesis in vitro, accompanied by decreased expression of preadipocytes. Peroxisome proliferator-activated receptor γ (PPARγ), fatty acid synthase (FAS), and fatty acid binding protein 4 (FABP4) adipogenesis regulators. These findings establish the ginsenoside Rg1-1,2,3-triazole derivative a17 as a promising adipocyte differentiation inhibitor and potential therapeutic agent for obesity and associated metabolic disorders. This research provides a foundation for developing effective therapeutic approaches for various metabolic syndromes.
Adipogenesis/drug effects* ; Triazoles/chemical synthesis* ; Ginsenosides/chemical synthesis* ; Saponins/chemical synthesis* ; Animals ; Mice ; Structure-Activity Relationship ; PPAR gamma/genetics* ; 3T3-L1 Cells ; Adipocytes/metabolism* ; Panax notoginseng/chemistry* ; Drug Design ; Molecular Structure ; Humans ; Cell Differentiation/drug effects* ; Fatty Acid-Binding Proteins/genetics*

Microorganisms, abundant in nature, are prolific producers of a diverse array of natural products (NPs) that are fundamental in the development of innovative therapeutics. Despite their significant potential, the field faces considerable challenges, including the continuous emergence of potential health threats, as well as novel pathogen strains and viruses. The advent and implementation of advanced technologies, such as culture strategies, genomics mining, and artificial intelligence (AI), are facilitating a paradigm shift in pharmaceutical research, introducing innovative methodologies and perspectives. The development and maturation of these technologies have enhanced the exploration of microbial-derived NPs, thereby advancing pharmaceutical research and development. This review synthesizes recent developments in this context, emphasizing their applications in pharmaceutical discovery and development. Through systematic analysis and synthesis, it provides objective insights into the promising prospects and future direction of this essential field.
Biological Products/chemistry* ; Drug Discovery ; Humans ; Artificial Intelligence ; Bacteria/metabolism*

Recent years have witnessed significant advances in the development of novel techniques and methodologies for identifying active ingredients in traditional Chinese medicine (TCM), substantially advancing research and development efforts. Spectrum-effect correlation analysis, affinity ultrafiltration, high-content screening (HCS) imaging, and cell membrane chromatography (CMC) have emerged as essential tools, effectively linking TCM chemical constituents to their biological effects, thereby enabling efficient active ingredient screening. Additionally, molecular interaction analysis provides deeper insights into TCM-biomolecule interaction mechanisms, enhancing understanding of its therapeutic potential. Computer-aided techniques facilitate TCM active ingredient identification, optimizing the screening process for efficiency and cost-effectiveness. Molecular probe technology, as an emerging methodology, enables precise and rapid screening for novel therapeutic drug discovery. Ongoing technological advancement in this field indicates promising future developments, potentially leading to more effective and targeted TCM-based therapies.
Drugs, Chinese Herbal/chemistry* ; Medicine, Chinese Traditional/methods* ; Humans ; Drug Discovery/methods* ; Animals

Accurate prediction of drug-target interactions (DTIs) plays a pivotal role in drug discovery, facilitating optimization of lead compounds, drug repurposing and elucidation of drug side effects. However, traditional DTI prediction methods are often limited by incomplete biological data and insufficient representation of protein features. In this study, we proposed KG-CNNDTI, a novel knowledge graph-enhanced framework for DTI prediction, which integrates heterogeneous biological information to improve model generalizability and predictive performance. The proposed model utilized protein embeddings derived from a biomedical knowledge graph via the Node2Vec algorithm, which were further enriched with contextualized sequence representations obtained from ProteinBERT. For compound representation, multiple molecular fingerprint schemes alongside the Uni-Mol pre-trained model were evaluated. The fused representations served as inputs to both classical machine learning models and a convolutional neural network-based predictor. Experimental evaluations across benchmark datasets demonstrated that KG-CNNDTI achieved superior performance compared to state-of-the-art methods, particularly in terms of Precision, Recall, F1-Score and area under the precision-recall curve (AUPR). Ablation analysis highlighted the substantial contribution of knowledge graph-derived features. Moreover, KG-CNNDTI was employed for virtual screening of natural products against Alzheimer's disease, resulting in 40 candidate compounds. 5 were supported by literature evidence, among which 3 were further validated in vitro assays.
Alzheimer Disease/drug therapy* ; Biological Products/therapeutic use* ; Humans ; Neural Networks, Computer ; Machine Learning ; Drug Discovery/methods* ; Algorithms ; Drug Evaluation, Preclinical/methods*

Studies on specific transient receptor potential melastatin 2 (TRPM2) channel inhibitors can deepen our understanding of the pathological mechanism of related diseases, and allow discovery of novel, effective targets and drugs for therapy. The development of TRPM2 channel inhibitors can be broadly classified into four categories with distinct characteristics: reutilization and structural modification of homologous ion channel modulators to produce a diverse array of TRPM2 channel inhibitors with strong inhibitory effects; TRPM2 channel inhibitors based on channel gating mechanism with high specificity; inhibitors identified through high-throughput screening with novel chemical structures; inhibitors developed from natural antioxidants with higher safety. In recent years, the application of computer-aided drug design has significantly accelerated the development of TRPM2 channel inhibitors. Several promising compounds such as ZA18, A1 and D9 have been discovered, and it is expected that more potent and selective TRPM2 channel inhibitor scaffolds will be discovered in the future. This article reviews the advances on the studies of TRPM2 channel inhibitors, aiming to provide insights for further research and clinical application of TRPM2 channel inhibitors.
TRPM Cation Channels/antagonists & inhibitors* ; Humans ; Drug Design

The unique characteristics of the deep space environment, microgravity, cosmic radiation, and extreme temperature fluctuations, are emerging as major driving forces for pharmaceutical innovation. These factors provide new avenues for optimizing drug formulations, improving crystal structure quality, and accelerating the discovery of therapeutic targets. Advances in deep space research not only help overcome critical bottlenecks in terrestrial drug development but also promote progress in structure-based drug design and deepen understanding of cellular stress-response mechanisms. Current progress in space-based pharmaceutical research primarily includes the study of disease mechanisms under microgravity, protein crystallization in microgravity, and drug development utilizing deep space radiation and resources. However, the operational complexity, high costs, and limited data reproducibility of space experiments remain key challenges hindering widespread application. Looking ahead, with the integration of automation, artificial intelligence analysis, and on-orbit manufacturing, deep space drug development is expected to achieve greater scalability and precision, opening a new frontier in biopharmaceutical science.
Drug Design ; Drug Development/methods* ; Humans ; Weightlessness ; Space Flight ; Artificial Intelligence ; Extraterrestrial Environment