Artificial intelligence-guided discovery of anticancer lead compounds from plants and associated microorganisms

Cancer chemoprevention: signaling pathways and strategic approaches

Although cancer chemopreventive agents have been confirmed to effectively protect high-risk populations from cancer invasion or recurrence, only over ten drugs have been approved by the U.S. Food and Drug Administration. Therefore, screening potent cancer chemopreventive agents is crucial to reduce the constantly increasing incidence and mortality rate of cancer. Considering the lengthy prevention process, an ideal chemopreventive agent should be nontoxic, inexpensive, and oral. Natural compounds have become a natural treasure reservoir for cancer chemoprevention because of their superior ease of availability, cost-effectiveness, and safety. The benefits of natural compounds as chemopreventive agents in cancer prevention have been confirmed in various studies. In light of this, the present review is intended to fully delineate the entire scope of cancer chemoprevention, and primarily focuses on various aspects of cancer chemoprevention based on natural compounds, specifically focusing on the mechanism of action of natural compounds in cancer prevention, and discussing in detail how they exert cancer prevention effects by affecting classical signaling pathways, immune checkpoints, and gut microbiome. We also introduce novel cancer chemoprevention strategies and summarize the role of natural compounds in improving chemotherapy regimens. Furthermore, we describe strategies for discovering anticancer compounds with low abundance and high activity, revealing the broad prospects of natural compounds in drug discovery for cancer chemoprevention. Moreover, we associate cancer chemoprevention with precision medicine, and discuss the challenges encountered in cancer chemoprevention. Finally, we emphasize the transformative potential of natural compounds in advancing the field of cancer chemoprevention and their ability to introduce more effective and less toxic preventive options for oncology.

Molecular insights fast-tracked: AI in biosynthetic pathway research

Covering: 2000 to 2025This review explores the potential of artificial intelligence (AI) in addressing challenges and accelerating molecular insights in biosynthetic pathway research, which is crucial for developing bioactive natural products with applications in pharmacology, agriculture, and biotechnology. It provides an overview of various AI techniques relevant to this research field, including machine learning (ML), deep learning (DL), natural language processing, network analysis, and data mining. AI-powered applications across three main areas, namely, pathway discovery and mining, pathway design, and pathway optimization, are discussed, and the benefits and challenges of integrating omics data and AI for enhanced pathway research are also elucidated. This review also addresses the current limitations, future directions, and the importance of synergy between AI and experimental approaches in unlocking rapid advancements in biosynthetic pathway research. The review concludes with an evaluation of AI's current capabilities and future outlook, emphasizing the transformative impact of AI on biosynthetic pathway research and the potential for new opportunities in the discovery and optimization of bioactive natural products.

Targeting Ferroptosis in Rare Neurological Disorders Including Pediatric Conditions: Innovations and Therapeutic Challenges

Ferroptosis, characterized by iron dependency and lipid peroxidation, has emerged as a key mechanism underlying neurodegeneration in rare neurological disorders. These conditions, often marked by significant therapeutic gaps and high unmet medical needs, present unique challenges for intervention development. This review examines the involvement of ferroptosis in rare neurological disease pathogenesis, focusing on its role in oxidative damage and neuronal dysfunction. We explore recent pharmacological advancements, including iron chelators, lipid peroxidation blockers, and antioxidant-based strategies, designed to target ferroptosis. While these approaches show promise, challenges such as disease heterogeneity, limited diagnostic tools, and small patient cohorts hinder progress. Furthermore, we discuss the translational and regulatory barriers to implementing ferroptosis-based therapies in clinical practice. By addressing these obstacles and fostering innovative solutions, this review underscores the potential of ferroptosis-targeting strategies to revolutionize treatment paradigms for rare neurological disorders.

Comprehensive applications of the artificial intelligence technology in new drug research and development

Purpose

Target-based strategy is a prevalent means of drug research and development (R&D), since targets provide effector molecules of drug action and offer the foundation of pharmacological investigation. Recently, the artificial intelligence (AI) technology has been utilized in various stages of drug R&D, where AI-assisted experimental methods show higher efficiency than sole experimental ones. It is a critical need to give a comprehensive review of AI applications in drug R &D for biopharmaceutical field.

Methods

Relevant literatures about AI-assisted drug R&D were collected from the public databases (Including Google Scholar, Web of Science, PubMed, IEEE Xplore Digital Library, Springer, and ScienceDirect) through a keyword searching strategy with the following terms [("Artificial Intelligence" OR "Knowledge Graph" OR "Machine Learning") AND ("Drug Target Identification" OR "New Drug Development")].

Results

In this review, we first introduced common strategies and novel trends of drug R&D, followed by characteristic description of AI algorithms widely used in drug R&D. Subsequently, we depicted detailed applications of AI algorithms in target identification, lead compound identification and optimization, drug repurposing, and drug analytical platform construction. Finally, we discussed the challenges and prospects of AI-assisted methods for drug discovery.

Conclusion

Collectively, this review provides comprehensive overview of AI applications in drug R&D and presents future perspectives for biopharmaceutical field, which may promote the development of drug industry.

Uncovering the scientific landscape: A bibliometric and Visualized Analysis of artificial intelligence in Traditional Chinese Medicine

The emergence of artificial intelligence (AI) technology has presented new challenges and opportunities for Traditional Chinese Medicine (TCM), aiming to provide objective assessments and improve clinical effectiveness. However, there is a lack of comprehensive analyses on the research trajectory, key directions, current trends, and future perspectives in this field. This research aims to comprehensively update the progress of AI in TCM over the past 24 years, based on data from the Web of Science database covering January 1, 2000, to March 1, 2024. Using advanced analytical tools, we conducted detailed bibliometric and visual analyses. The results highlight China's predominant influence, contributing 54.35 % of the total publications and playing a key role in shaping research in this field. Significant productivity was observed at institutions such as the China Academy of Chinese Medical Sciences, Beijing University of Chinese Medicine, and Shanghai University of Traditional Chinese Medicine, with Wang Yu being the most prolific contributor. The journal Molecules contributed the most publications in this field. This study identified hepatocellular carcinoma, chemical and drug-induced liver injury, Papillon-Lefèvre disease, Parkinson's disease, and anorexia as the most significant disorders researched. This comprehensive bibliometric assessment benefits both seasoned researchers and newcomers, offering quick access to essential information and fostering the generation of innovative ideas in this field.

Review of Personalized Medicine and Pharmacogenomics of Anti-Cancer Compounds and Natural Products

In recent years, the FDA has approved numerous anti-cancer drugs that are mutation-based for clinical use. These drugs have improved the precision of treatment and reduced adverse effects and side effects. Personalized therapy is a prominent and hot topic of current medicine and also represents the future direction of development. With the continuous advancements in gene sequencing and high-throughput screening, research and development strategies for personalized clinical drugs have developed rapidly. This review elaborates the recent personalized treatment strategies, which include artificial intelligence, multi-omics analysis, chemical proteomics, and computation-aided drug design. These technologies rely on the molecular classification of diseases, the global signaling network within organisms, and new models for all targets, which significantly support the development of personalized medicine. Meanwhile, we summarize chemical drugs, such as lorlatinib, osimertinib, and other natural products, that deliver personalized therapeutic effects based on genetic mutations. This review also highlights potential challenges in interpreting genetic mutations and combining drugs, while providing new ideas for the development of personalized medicine and pharmacogenomics in cancer study.

Integrating artificial intelligence into the modernization of traditional Chinese medicine industry: a review

Traditional Chinese medicine (TCM) is the practical experience and summary of the Chinese nation for thousands of years. It shows great potential in treating various chronic diseases, complex diseases and major infectious diseases, and has gradually attracted the attention of people all over the world. However, due to the complexity of prescription and action mechanism of TCM, the development of TCM industry is still in a relatively conservative stage. With the rise of artificial intelligence technology in various fields, many scholars began to apply artificial intelligence technology to traditional Chinese medicine industry and made remarkable progress. This paper comprehensively summarizes the important role of artificial intelligence in the development of traditional Chinese medicine industry from various aspects, including new drug discovery, data mining, quality standardization and industry technology of traditional Chinese medicine. The limitations of artificial intelligence in these applications are also emphasized, including the lack of pharmacological research, database quality problems and the challenges brought by human-computer interaction. Nevertheless, the development of artificial intelligence has brought new opportunities and innovations to the modernization of traditional Chinese medicine. Integrating artificial intelligence technology into the comprehensive application of Chinese medicine industry is expected to overcome the major problems faced by traditional Chinese medicine industry and further promote the modernization of the whole traditional Chinese medicine industry.

Targeting ferroptosis unveils a new era for traditional Chinese medicine: a scientific metrology study

In the past 11 years, there has been a surge in studies exploring the regulatory effect of Traditional Chinese Medicine (TCM) on ferroptosis. However, a significant gap persists in comprehensive scientometric analysis and scientific mapping research, especially in tracking the evolution, primary contributors, and emerging research focal points. This study aims to comprehensively update the advancements in targeting ferroptosis with various TCMs during the previous 11 years. The data, covering the period from 1 January 2012, to 30 November 2023, were retrieved from the Web of Science database. For in-depth scientometric and visualized analyses, a series of advanced analytical instruments were employed. The findings highlight China's predominant role, accounting for 71.99% of total publications and significantly shaping research in this domain. Noteworthy productivity was observed at various institutions, including Guangzhou University of Chinese Medicine, Chengdu University of Traditional Chinese Medicine, and Zhejiang University. Thomas Efferth emerged as the foremost author within this field, while Frontiers in Pharmacology boasted the highest publication count. This study pinpointed hepatocellular carcinoma, chemical and drug-induced liver injury, mitochondrial diseases, acute kidney injury, and liver failure as the most critical disorders addressed in this research realm. The research offers a comprehensive bibliometric evaluation, enhancing our understanding of the present status of TCM therapy in managing ferroptosis-related diseases. Consequently, it aids both seasoned researchers and newcomers by accelerating access to vital information and fostering innovative concept extraction within this specialized field.

Structures, Biosynthesis, and Bioactivity of Oligomycins from the Marine-Derived Streptomyces sp. FXY-T5

Oligomycins are potent antifungal and antitumor agents. Mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based metabolomic fingerprinting analysis of marine-derived actinomycetes in our in-house library provided an oligomycin-producing strain, Streptomyces sp. FXY-T5. Chemical investigation led to the discovery of five new oligomycins, 24-lumooligomycin B (1), 4-lumooligomycin B (2), 6-lumooligomycin B (3), 40-homooligomycin B (4), and 15-hydroxy-oligomycin B (5), together with seven biosynthetically related known derivatives. Their structures were assigned by MS, NMR, electronic circular dichroism (ECD), and single-crystal X-ray diffraction analyses. The biosynthesis pathway of oligomycins was first proposed based on the analysis of a type I modular polyketide synthase (PKS) system and targeted gene disruption. As expected, the isolated oligomycins showed significant antiagricultural fungal pathogen activity and antiproliferative properties from which the possible structure-activity relationships were first suggested. More importantly, oligomycins induced significant G1-phase cell cycle arrest on cancer cells and significantly attenuated their Cyclin D1 and PCNA expression through a β-catenin signaling pathway.

Exploring the artificial intelligence and machine learning models in the context of drug design difficulties and future potential for the pharmaceutical sectors

Artificial intelligence (AI), particularly deep learning as a subcategory of AI, provides opportunities to accelerate and improve the process of discovering and developing new drugs. The use of AI in drug discovery is still in its early stages, but it has the potential to revolutionize the way new drugs are discovered and developed. As AI technology continues to evolve, it is likely that AI will play an even greater role in the future of drug discovery. AI is used to identify new drug targets, design new molecules, and predict the efficacy and safety of potential drugs. The inclusion of AI in drug discovery can screen millions of compounds in a matter of hours, identifying potential drug candidates that would have taken years to find using traditional methods. AI is highly utilized in the pharmaceutical industry by optimizing processes, reducing waste, and ensuring quality control. This review covers much-needed topics, including the different types of machine-learning techniques, their applications in drug discovery, and the challenges and limitations of using machine learning in this field. The state-of-the-art of AI-assisted pharmaceutical discovery is described, covering applications in structure and ligand-based virtual screening, de novo drug creation, prediction of physicochemical and pharmacokinetic properties, drug repurposing, and related topics. Finally, many obstacles and limits of present approaches are outlined, with an eye on potential future avenues for AI-assisted drug discovery and design.

Targeting ferroptosis opens new avenues for the development of novel therapeutics

Ferroptosis is an iron-dependent form of regulated cell death with distinct characteristics, including altered iron homeostasis, reduced defense against oxidative stress, and abnormal lipid peroxidation. Recent studies have provided compelling evidence supporting the notion that ferroptosis plays a key pathogenic role in many diseases such as various cancer types, neurodegenerative disease, diseases involving tissue and/or organ injury, and inflammatory and infectious diseases. Although the precise regulatory networks that underlie ferroptosis are largely unknown, particularly with respect to the initiation and progression of various diseases, ferroptosis is recognized as a bona fide target for the further development of treatment and prevention strategies. Over the past decade, considerable progress has been made in developing pharmacological agonists and antagonists for the treatment of these ferroptosis-related conditions. Here, we provide a detailed overview of our current knowledge regarding ferroptosis, its pathological roles, and its regulation during disease progression. Focusing on the use of chemical tools that target ferroptosis in preclinical studies, we also summarize recent advances in targeting ferroptosis across the growing spectrum of ferroptosis-associated pathogenic conditions. Finally, we discuss new challenges and opportunities for targeting ferroptosis as a potential strategy for treating ferroptosis-related diseases.

Fungal Endophytes: Microfactories of Novel Bioactive Compounds with Therapeutic Interventions; A Comprehensive Review on the Biotechnological Developments in the Field of Fungal Endophytic Biology over the Last Decade

The seminal discovery of paclitaxel from endophytic fungus Taxomyces andreanae was a milestone in recognizing the immense potential of endophytic fungi as prolific producers of bioactive secondary metabolites of use in medicine, agriculture, and food industries. Following the discovery of paclitaxel, the research community has intensified efforts to harness endophytic fungi as putative producers of lead molecules with anticancer, anti-inflammatory, antimicrobial, antioxidant, cardio-protective, and immunomodulatory properties. Endophytic fungi have been a valuable source of bioactive compounds over the last three decades. Compounds such as taxol, podophyllotoxin, huperzine, camptothecin, and resveratrol have been effectively isolated and characterized after extraction from endophytic fungi. These findings have expanded the applications of endophytic fungi in medicine and related fields. In the present review, we systematically compile and analyze several important compounds derived from endophytic fungi, encompassing the period from 2011 to 2022. Our systematic approach focuses on elucidating the origins of endophytic fungi, exploring the structural diversity and biological activities exhibited by these compounds, and giving special emphasis to the pharmacological activities and mechanism of action of certain compounds. We highlight the tremendous potential of endophytic fungi as alternate sources of bioactive metabolites, with implications for combating major global diseases. This underscores the significant role that fungi can play in the discovery and development of novel therapeutic agents that address the challenges posed by prevalent diseases worldwide.

Pentagalloyl Glucose: A Review of Anticancer Properties, Molecular Targets, Mechanisms of Action, Pharmacokinetics, and Safety Profile

Pentagalloyl glucose (PGG) is a natural hydrolyzable gallotannin abundant in various plants and herbs. It has a broad range of biological activities, specifically anticancer activities, and numerous molecular targets. Despite multiple studies available on the pharmacological action of PGG, the molecular mechanisms underlying the anticancer effects of PGG are unclear. Here, we have critically reviewed the natural sources of PGG, its anticancer properties, and underlying mechanisms of action. We found that multiple natural sources of PGG are available, and the existing production technology is sufficient to produce large quantities of the required product. Three plants (or their parts) with maximum PGG content were Rhus chinensis Mill, Bouea macrophylla seed, and Mangifera indica kernel. PGG acts on multiple molecular targets and signaling pathways associated with the hallmarks of cancer to inhibit growth, angiogenesis, and metastasis of several cancers. Moreover, PGG can enhance the efficacy of chemotherapy and radiotherapy by modulating various cancer-associated pathways. Therefore, PGG can be used for treating different human cancers; nevertheless, the data on the pharmacokinetics and safety profile of PGG are limited, and further studies are essential to define the clinical use of PGG in cancer therapies.

Advanced Methods for Natural Products Discovery: Bioactivity Screening, Dereplication, Metabolomics Profiling, Genomic Sequencing, Databases and Informatic Tools, and Structure Elucidation

Natural Products (NP) are essential for the discovery of novel drugs and products for numerous biotechnological applications. The NP discovery process is expensive and time-consuming, having as major hurdles dereplication (early identification of known compounds) and structure elucidation, particularly the determination of the absolute configuration of metabolites with stereogenic centers. This review comprehensively focuses on recent technological and instrumental advances, highlighting the development of methods that alleviate these obstacles, paving the way for accelerating NP discovery towards biotechnological applications. Herein, we emphasize the most innovative high-throughput tools and methods for advancing bioactivity screening, NP chemical analysis, dereplication, metabolite profiling, metabolomics, genome sequencing and/or genomics approaches, databases, bioinformatics, chemoinformatics, and three-dimensional NP structure elucidation.

Cytochalasans with Inhibitory Activity against NPC1L1 from the Endophytic Fungus Chaetomium nigricolor F5

Mass spectrometry (MS)-based metabolic profiling of the endophytic fungus Chaetomium nigricolor F5 guided the isolation of five novel cytochalasans, chamisides B-F (1-5), and two known ones, chaetoconvosins C and D (6 and 7). Their structures including stereochemistry were unambiguously determined by MS, nuclear magnetic resonance, and single-crystal X-ray diffraction analyses. Compounds 1-3 share a new 5/6/5/5/7-fused pentacyclic skeleton in cytochalasans and are appropriately proposed to be the key biosynthetic precursors of co-isolated cytochalasans with a 6/6/5/7/5, 6/6/5/5/7, or 6/6/5 ring system. Remarkably, compound 5 with a relatively flexible side chain showed promising inhibition activity against the cholesterol transporter protein Niemann-Pick C1-like 1 (NPC1L1), expanding the function of cytochalasans.

Extract of Ficus septica modulates apoptosis and migration in human oral squamous cell carcinoma cells

According to the alarming statistical analysis of global cancer, there are over 19 million new diagnoses and more than 10 million deaths each year. One such cancer is the oral squamous cell carcinoma (OSCC), which requires new therapeutic strategies. Ficus septica extract has been used in traditional medicine to treat infectious diseases. In this study, we examined the anti-proliferative effects of an extract of F. septica bark (FSB) in OSCC cells. Our results showed that FSB caused a concentration-dependent reduction in the viability of SCC2095 OSCC cells, as determined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assays, and was less sensitive to fibroblasts. In addition, FSB induced apoptosis by activating caspases, accompanied by the modulation of Akt/mTOR/NF-κB and mitogen-activated protein kinase signaling. Moreover, FSB increased reactive oxygen species generation in a concentration-dependent manner in SCC2095 cells. Furthermore, FSB inhibited cell migration and modulated the levels of the cell adhesion molecules including E-cadherin, N-cadherin, and Snail in SCC2095 cells. Pinoresinol, a lignan isolated from FSB, showed antitumor effects in SCC2095 cells, implying that this compound might play an important role in FSB-induced OSCC cell death. Taken together, FSB is a potential anti-tumor agent against OSCC cells.

Artificial intelligence in microbial natural product drug discovery: current and emerging role

Covering: up to the end of 2022Microorganisms are exceptional sources of a wide array of unique natural products and play a significant role in drug discovery. During the golden era, several life-saving antibiotics and anticancer agents were isolated from microbes; moreover, they are still widely used. However, difficulties in the isolation methods and repeated discoveries of the same molecules have caused a setback in the past. Artificial intelligence (AI) has had a profound impact on various research fields, and its application allows the effective performance of data analyses and predictions. With the advances in omics, it is possible to obtain a wealth of information for the identification, isolation, and target prediction of secondary metabolites. In this review, we discuss drug discovery based on natural products from microorganisms with the help of AI and machine learning.

Metabolic Profiling for the Discovery of Structurally Diverse Gibberellins and Their Precursors from the Endophytic Fungus Fusarium sp. NJ-F5

Gibberellins (GAs) are well-known tetracyclic diterpenoid phytohormones since the 1950s. In this work, eight skeletally diverse GAs (1-8) including four new compounds (1-4), and three known ent-kaurene diterpenoids (9-11), were isolated from the endophytic fungus Fusarium sp. NJ-F5 by integrating mass spectrometry (MS)- and nuclear magnetic resonance (NMR)-based metabolic profiling. Their planar structures and stereochemistry were determined by extensive spectroscopic analyses including MS, NMR, as well as electronic circular dichroism and their calculations, together with single-crystal X-ray diffraction studies. As far as we know, this is a rare report of naturally occurring GAs and their detailed spectroscopic data including MS and NMR in recent decades. Compound 1, as a new member of GAs family, showed an obvious promoting effect on the seedling's growth ofArabidopsis thaliana.

Emerging Strategies in Stimuli-Responsive Prodrug Nanosystems for Cancer Therapy

Prodrugs are chemically modified drug molecules that are inactive before administration. After administration, they are converted in situ to parent drugs and induce the mechanism of action. The development of prodrugs has upgraded conventional drug treatments in terms of bioavailability, targeting, and reduced side effects. Especially in cancer therapy, the application of prodrugs has achieved substantial therapeutic effects. From serendipitous discovery in the early stage to functional design with pertinence nowadays, the importance of prodrugs in drug design is self-evident. At present, studying stimuli-responsive activation mechanisms, regulating the stimuli intensity in vivo, and designing nanoscale prodrug formulations are the major strategies to promote the development of prodrugs. In this review, we provide an outlook of recent cutting-edge studies on stimuli-responsive prodrug nanosystems from these three aspects. We also discuss prospects and challenges in the future development of such prodrugs.

Isolation, biosynthesis, and biological activity of rubromycins derived from actinomycetes

Natural occurring aromatic polyketides from actinomycetes indicate a structurally and functionally diverse family of polycyclic polyphenols. Some of them are consequently suggested as lead structures for drug development. Among them, rubromycins are derived from a single C26 polyketide chain and exhibit an unusual bisbenzannulated [5,6]-spiroketal system that connects a highly oxygenated naphthazarin motif to an isocoumarin unit. This type of biosynthetically elusive polycyclic polyketides has shown promising pharmacological activities, including antimicrobial, anticancer, and enzyme inhibition activity. The unique structures, intriguing biosynthesis, and marked bioactivities of rubromycins have drawn considerable attention from several chemists and biologists. This review covers the isolation, characterization, biosynthesis, and biological studies of these structurally diverse and complex rubromycins.

Coumarins as Fungal Metabolites with Potential Medicinal Properties

Coumarins are a structurally varied set of 2H-chromen-2-one compounds categorized also as members of the benzopyrone group of secondary metabolites. Coumarin derivatives attract interest owing to their wide practical application and the unique reactivity of fused benzene and pyrone ring systems in molecular structure. Coumarins have their own specific fingerprints as antiviral, antimicrobial, antioxidant, anti-inflammatory, antiadipogenic, cytotoxic, apoptosis, antitumor, antitubercular, and cytotoxicity agents. Natural products have played an essential role in filling the pharmaceutical pipeline for thousands of years. Biological effects of natural coumarins have laid the basis of low-toxic and highly effective drugs. Presently, more than 1300 coumarins have been identified in plants, bacteria, and fungi. Fungi as cultivated microbes have provided many of the nature-inspired syntheses of chemically diverse drugs. Endophytic fungi bioactivities attract interest, with applications in fields as diverse as cancer and neuronal injury or degeneration, microbial and parasitic infections, and others. Fungal mycelia produce several classes of bioactive molecules, including a wide group of coumarins. Of promise are further studies of conditions and products of the natural and synthetic coumarins' biotransformation by the fungal cultures, aimed at solving the urgent problem of searching for materials for biomedical engineering. The present review evaluates the fungal coumarins, their structure-related peculiarities, and their future therapeutic potential. Special emphasis has been placed on the coumarins successfully bioprospected from fungi, whereas an industry demand for the same coumarins earlier found in plants has faced hurdles. Considerable attention has also been paid to some aspects of the molecular mechanisms underlying the coumarins' biological activity. The compounds are selected and grouped according to their cytotoxic, anticancer, antibacterial, antifungal, and miscellaneous effects.

Isolation, Biosynthesis, and Biological Activity of Polycyclic Xanthones From Actinomycetes

Natural products from actinomycetes serve as a crucial source of clinical pharmaceuticals, especially antibiotics and anticancer agents. Among them, polycyclic xanthones belong to a growing group of highly oxygenated aromatic polyketides with a xanthone-containing angular hexacyclic framework. These biosynthetically unique small molecules are of great interest due to their wide spectrum of biological activities, especially the remarkable antibacterial activity against gram-positive bacteria and the significant antineoplastic effects toward various cancer cells at nanomolar concentrations. Their complex structures and significant bioactivities have aroused considerable attention in the chemical and biological communities in recent decades. This review covers the isolation, the biosynthesis, and the biological studies toward these structurally complex and biologically active molecules.