Review on natural products databases: where to find data in 2020

Phytochemical analysis and investigation of analgesic, anti-inflammatory, and antispasmodic activities of hydroethanolic extracts of Alternanthera dentata, Ocimum carnosum, and Plectranthus barbatus, three species with vernacular names derived from analgesic drugs

ETHNOPHARMACOLOGICAL RELEVANCE

Plant vernacular names can provide clues about the popular use of a species in different regions and are valuable sources of information about the culture or vocabulary of a population. Several medicinal plants in Brazil have received names of medicines and brand-name products.

AIM OF THE STUDY

The present work aimed to evaluate the chemical composition and pharmacological activity in the central nervous system of three species known popularly by brand names of analgesic, anti-inflammatory, antispasmodic, and digestive drugs.

MATERIALS AND METHODS

Hydroethanolic extracts of Alternanthera dentata (AD), Ocimum carnosum (OC), and Plectranthus barbatus (PB) aerial parts were submitted to phytochemical analysis by HPLC-PAD-ESI-MS/MS and evaluated in animal models at doses of 500 and 1000 mg/kg. Mice were tested on hot plate, acetic acid-induced writing, formalin-induced licking, and intestinal transit tests. Aspirin and morphine were employed as standard drugs.

RESULTS

The three extracts did not change the mice's response on the hot plate. Hydroethanolic extracts of AD and PB reduced the number of writhes and licking time, while OC was only effective on the licking test at dose of 1000 mg/kg. In addition, AD and OC reduced intestinal transit, while PB increased gut motility.

CONCLUSIONS

Pharmacological tests supported some popular uses, suggesting peripheral antinociceptive and anti-inflammatory effects, while the phytochemical analysis showed the presence of several flavonoids in the three hydroethanolic extracts and steroids in PB, with some barbatusterol derivatives described for the first time in the species.

Extracellular production of azurin by reusable magnetic Fe3O4 nanoparticle-immobilized Pseudomonas aeruginosa

Azurin, found in the periplasm of Pseudomonas aeruginosa, has garnered significant attention as a potential anticancer agent in recent years. High-level secretion of proteins into the culture medium, offers a significant advantage over periplasmic or cytoplasmic expression. In this study, for the first time, P. aeruginosa cells were immobilized with magnetic nanoparticles (MNPs) to ensure effective, simple and quick separation of the cells and secretion of periplasmic azurin protein to the culture medium. For this purpose, polyethyleneimine-coated iron oxide (Fe3O4@PEI) MNPs were synthesized and MNPs containing Fe up to 600 ppm were found to be non-toxic to the bacteria. The highest extracellular azurin level was observed in LB medium compared to peptone water. The cells immobilized with 400 ppm Fe-containing MNPs secreted the highest protein. Lastly, the immobilized cells were found suitable for azurin secretion until the sixth use. Thus, the magnetic nanoparticle immobilization method facilitated the release of azurin as well as the simple and rapid separation of cells. This approach, by facilitating protein purification and enabling the reuse of immobilized cells, offers a cost-effective means of protein production, reducing waste cell formation, and thus presents an advantageous method.

Synthetic Biology of Natural Products Engineering: Recent Advances Across the Discover-Design-Build-Test-Learn Cycle

Advances in genome engineering and associated technologies have reinvigorated natural products research. Here we highlight the latest developments in the field across the discover-design-build-test-learn cycle of bioengineering, from recent progress in computational tools for AI-supported genome mining, enzyme and pathway engineering, and compound identification to novel host systems and new techniques for improving production levels, and place these trends in the context of responsible research and innovation, emphasizing the importance of anticipatory analysis at the early stages of process development.

Prioritization before dereplication, an effective strategy to target new metabolites in whole extracts: ghosalin from Murraya paniculata root

Re-discovery of known metabolites is a common challenge in natural product-based drug discovery, and to avoid re-discovery, dereplication has been proposed for identifying known metabolites at the early stage of isolation. A majority of methods use LCMS to profile the extract and ignore the known mass. LC-HRMS profiling may generate a long mass list of metabolites. The identification of a new metabolite is difficult within the mass list. To overcome this, it was hypothesized that identifying a 'new metabolite' in the whole metabolome is more difficult than identifying it within the class of metabolites. A prioritization strategy was proposed to focus on the elimination of unknown and uncommon metabolites first using the designed bias filters and to prioritize the known secondary metabolites. The study employed Murraya paniculata root for the identification of new metabolites. The LC-HRMS-generated mass list of 509 metabolites was subjected to various filters, which resulted in 93 metabolites. Subsequently, it was subjected to regular dereplication, resulting in 10 coumarins, among which 3 were identified as new. Further, chromatographic efforts led to the isolation of a new coumarin, named ghosalin (1). The structure of the new compound was established through 2D NMR and X-ray crystallography. Cytotoxicity studies revealed that ghosalin has significant cytotoxicity against cancer cell lines. The proposed prioritization strategy demonstrates an alternative way for the rapid annotation of a particular set of metabolites to isolate a new metabolite from the whole metabolome of a plant extract.

Current and emerging tools and strategies for the identification of bioactive natural products in complex mixtures

Covering: up to 2024The prompt identification of (bio)active natural products (NPs) from complex mixtures poses a significant challenge due to the presence of numerous compounds with diverse structures and (bio)activities. Thus, this review provides an overview of current and emerging tools and strategies for the identification of (bio)active NPs in complex mixtures. Traditional approaches of bioassay-guided fractionation (BGF), followed by nuclear magnetic resonance (NMR) and mass spectrometry (MS) analysis for compound structure elucidation, continue to play an important role in the identification of active NPs. However, recent advances (2018-2024) have led to the development of novel techniques such as (bio)chemometric analysis, dereplication and combined approaches, which allow efficient prioritization for the elucidation of (bio)active compounds. For researchers involved in the search for bioactive NPs and who want to speed up their discoveries while maintaining accurate identifications, this review highlights the strengths and limitations of each technique and provides up-to-date insights into their combined use to achieve the highest level of confidence in the identification of (bio)active natural products from complex matrices.

Chemoinformatic Characterization of NAPROC-13: A Database for Natural Product 13C NMR Dereplication

Natural products (NPs) are secondary metabolites of natural origin with broad applications across various human activities, particularly the discovery of bioactive compounds. Structural elucidation of new NPs entails significant cost and effort. On the other hand, the dereplication of known compounds is crucial for the early exclusion of irrelevant compounds in contemporary pharmaceutical research. NAPROC-13 stands out as a publicly accessible database, providing structural and 13C NMR spectroscopic information for over 25 000 compounds, rendering it a pivotal resource in natural product (NP) research, favoring open science. This study seeks to quantitatively analyze the chemical content, structural diversity, and chemical space coverage of NPs within NAPROC-13, compared to FDA-approved drugs and a very diverse subset of NPs, UNPD-A. Findings indicated that NPs in NAPROC-13 exhibit properties comparable to those in UNPD-A, albeit showcasing a notably diverse array of structural content, scaffolds, ring systems of pharmaceutical interest, and molecular fragments. NAPROC-13 covers a specific region of the chemical multiverse (a generalization of the chemical space from different chemical representations) regarding physicochemical properties and a region as broad as UNPD-A in terms of the structural features represented by fingerprints.

An Overview on Nocardiopsis Species Originating From North African Biotopes as a Promising Source of Bioactive Compounds and In Silico Genome Mining Analysis of Three Sequenced Genomes

Actinobacteria are renowned for their prolific production of diverse bioactive secondary metabolites. In recent years, there has been an increasing focus on exploring "rare" genera within this phylum for biodiscovery purposes, notably the Nocardiopsis genus, which will be the subject of the present study. Recognizing the absence of articles describing the research process of finding bioactive molecules from the genus Nocardiopsis in North African environments. We, therefore, present a historical overview of the discoveries of bioactive molecules of the genus Nocardiopsis originating from the region, highlighting their biological activities and associated reported molecules, providing a snapshot of the current state of the field, and offering insights into future opportunities and challenges for drug discovery. Additionally, we present a genome mining analysis of three genomes deposited in public databases that have been reported to be bioactive. A total of 36 biosynthetic gene clusters (BGCs) were identified, including those known to encode bioactive molecules. Notably, a substantial portion of the BGCs showed little to no similarity to those previously described, suggesting the possibility that the analyzed strains could be potential producers of new compounds. Further research on these genomes is essential to fully uncovering their biotechnological potential. Moving forward, we discuss the experimental designs adopted in the reported studies, as well as new avenues to guide the exploration of the Nocardiopsis genus in North Africa.

Preparation of imidazolium ionic liquid functionalized paper membrane for selective extraction of caffeic acid and its structural and functional analogues from Taraxaci Herba

In the search for pharmaceutically active compounds from natural products, it is crucial and challenging to develop separation or purification methods that target not only structurally similar compounds but also those with specific pharmaceutical functions. The adsorption-based method is widely employed in this field and holds potential for this application, given the diverse range of functional monomers that can be chosen based on structural or functional selectivity. In this work, an imidazolium ionic liquid (IL) modified paper membrane was synthesized via microwave reaction. Caffeic acid (CA), with potential interactions with imidazolium IL and a representative component of phenolic acids in Taraxaci Herba, was chosen as a target compound. After optimization of synthesis and extraction parameters, the resulting extraction membrane could be used to quantitatively analyze CA at ng/ml level, and to extract CA's analogues from the sample matrix. Cheminformatics confirmed the presence of structural and functional similarity among these extracted compounds. This study offers a novel approach to preparing a readily synthesized extraction membrane capable of isolating compounds with structural and functional analogies, as well as developing a membrane solid-phase extraction-based analytical method for natural products.

Natural Products from Herbal Medicine Self-Assemble into Advanced Bioactive Materials

Novel biomaterials are becoming more crucial in treating human diseases. However, many materials require complex artificial modifications and synthesis, leading to potential difficulties in preparation, side effects, and clinical translation. Recently, significant progress has been achieved in terms of direct self-assembly of natural products from herbal medicine (NPHM), an important source for novel medications, resulting in a wide range of bioactive supramolecular materials including gels, and nanoparticles. The NPHM-based supramolecular bioactive materials are produced from renewable resources, are simple to prepare, and have demonstrated multi-functionality including slow-release, smart-responsive release, and especially possess powerful biological effects to treat various diseases. In this review, NPHM-based supramolecular bioactive materials have been revealed as an emerging, revolutionary, and promising strategy. The development, advantages, and limitations of NPHM, as well as the advantageous position of NPHM-based materials, are first reviewed. Subsequently, a systematic and comprehensive analysis of the self-assembly strategies specific to seven major classes of NPHM is highlighted. Insights into the influence of NPHM structural features on the formation of supramolecular materials are also provided. Finally, the drivers and preparations are summarized, emphasizing the biomedical applications, future scientific challenges, and opportunities, with the hope of igniting inspiration for future research and applications.

Natural Occurring Terpene Cyclic Anhydrides: Biosynthetic Origin and Biological Activities

Cyclic acid anhydride is a not very widespread structure in nature, but with a determining role in natural products possessing this functionality in their skeleton. To the best of our knowledge, no revision of terpenes containing cyclic anhydrides has been previously reported. The result was that more than 100 terpenic cyclic anhydrides and related compounds were found to be in need of being reported. This review has been systematically organized by terpene skeletons, from the smallest to largest, describing their sources and bioactivities. In addition, different biosynthetic pathways for their final oxidations, namely, routes A, B and C, leading to the formation of these heterocyclic natural products, have been proposed. We have also included the most plausible precursors of these natural products, which mostly happened to be present in the same natural source. Some molecules derived from terpene cyclic anhydrides, such as their natural imide derivatives, have also been described due to their significant biological activity. In this sense, special attention has been paid to cantharidin because of its historical relevance and its broad bioactivity. A plausible biosynthesis of cantharidin has been proposed for the first time. Finally, cyclic anhydride structures that were firstly assigned as anhydrides and later corrected have been also described.

Overview and limitations of database in global traditional medicines: A narrative review

The study of traditional medicine has garnered significant interest, resulting in various research areas including chemical composition analysis, pharmacological research, clinical application, and quality control. The abundance of available data has made databases increasingly essential for researchers to manage the vast amount of information and explore new drugs. In this article we provide a comprehensive overview and summary of 182 databases that are relevant to traditional medicine research, including 73 databases for chemical component analysis, 70 for pharmacology research, and 39 for clinical application and quality control from published literature (2000-2023). The review categorizes the databases by functionality, offering detailed information on websites and capacities to facilitate easier access. Moreover, this article outlines the primary function of each database, supplemented by case studies to aid in database selection. A practical test was conducted on 68 frequently used databases using keywords and functionalities, resulting in the identification of highlighted databases. This review serves as a reference for traditional medicine researchers to choose appropriate databases and also provides insights and considerations for the function and content design of future databases.

Evaluation of Cytotoxicity and Metabolic Profiling of Synechocystis sp. Extract Encapsulated in Nano-Liposomes and Nano-Niosomes Using LC-MS, Complemented by Molecular Docking Studies

Liposomes and niosomes can be considered excellent drug delivery systems due to their ability to load all compounds, whether hydrophobic or hydrophilic. In addition, they can reduce the toxicity of the loaded drug without reducing its effectiveness. Synechocystis sp. is a unicellular, freshwater cyanobacteria strain that contains many bioactive compounds that qualify its use in industrial, pharmaceutical, and many other fields. This study investigated the potential of nano-liposomes (L) and nano-niosomes (N) for delivering Synechocystis sp. extract against cancer cell lines. Four different types of nanoparticles were prepared using a dry powder formulation and ethanol extract of Synechocystis sp. in both nanovesicles (N1 and N2, respectively) and liposomes (L1 and L2, respectively). Analysis of the formed vesicles using zeta analysis, SEM morphological analysis, and visual examination confirmed their stability and efficiency. L1 and L2 in this investigation had effective diameters of 419 and 847 nm, respectively, with PDI values of 0.24 and 0.27. Furthermore, the zeta potentials were found to range from -31.6 mV to -43.7 mV. Regarding N1 and N2, their effective diameters were 541 nm and 1051 nm, respectively, with PDI values of 0.31 and 0.35, and zeta potentials reported from -31.6 mV to -22.2 mV, respectively. Metabolic profiling tentatively identified 22 metabolites (1-22) from the ethanolic extract. Its effect against representative human cancers was studied in vitro, specifically against colon (Caco2), ovarian (OVCAR4), and breast (MCF7) cancer cell lines. The results showed the potential activities of the prepared N1, N2, L1, and L2 against the three cell lines, where L1 had cytotoxicity IC50 values of 19.56, 33.52, and 9.24 µg/mL compared to 26.27, 56.23, and 19.61 µg/mL for L2 against Caco2, OVCAR4, and MCF7, respectively. On the other hand, N1 exhibited IC50 values of 9.09, 11.42, and 2.38 µg/mL, while N2 showed values of 15.57, 18.17, and 35.31 µg/mL against Caco2, OVCAR4, and MCF7, respectively. Meanwhile, the formulations showed little effect on normal cell lines (FHC, OCE1, and MCF10a). All of the compounds were evaluated in silico against the epidermal growth factor receptor tyrosine kinase (EGFR). The molecular docking results showed that compound 21 (1-hexadecanoyl-2-(9Z-hexadecenoyl)-3-(6'-sulfo-alpha-D-quinovosyl)-sn-glycerol), followed by compounds 6 (Sulfoquinovosyl monoacylgycerol), 7 (3-Hydroxymyristic acid), 8 (Glycolipid PF2), 12 (Palmitoleic acid), and 19 (Glyceryl monostearate), showed the highest binding affinities. These compounds formed good hydrogen bond interactions with the key amino acid Lys721 as the co-crystallized ligand. These results suggest that nano-liposomes and nano-niosomes loaded with Synechocystis sp. extract hold promise for future cancer treatment development. Further research should focus on clinical trials, stability assessments, and pharmacological profiles to translate this approach into effective anticancer drugs.

A practical guide to the discovery of biomolecules with biostimulant activity

The growing demand for sustainable solutions in agriculture, which are critical for crop productivity and food quality in the face of climate change and the need to reduce agrochemical usage, has brought biostimulants into the spotlight as valuable tools for regenerative agriculture. With their diverse biological activities, biostimulants can contribute to crop growth, nutrient use efficiency, and abiotic stress resilience, as well as to the restoration of soil health. Biomolecules include humic substances, protein lysates, phenolics, and carbohydrates have undergone thorough investigation because of their demonstrated biostimulant activities. Here, we review the process of the discovery and development of extract-based biostimulants, and propose a practical step-by-step pipeline that starts with initial identification of biomolecules, followed by extraction and isolation, determination of bioactivity, identification of active compound(s), elucidation of mechanisms, formulation, and assessment of effectiveness. The different steps generate a roadmap that aims to expedite the transfer of interdisciplinary knowledge from laboratory-scale studies to pilot-scale production in practical scenarios that are aligned with the prevailing regulatory frameworks.

Molecular screening of phytocompounds targeting the interface between influenza A NS1 and TRIM25 to enhance host immune responses

BACKGROUND

Influenza A virus causes severe respiratory illnesses, especially in developing nations where most child deaths under 5 occur due to lower respiratory tract infections. The RIG-I protein acts as a sensor for viral dsRNA, triggering interferon production through K63-linked poly-ubiquitin chains synthesized by TRIM25. However, the influenza A virus's NS1 protein hinders this process by binding to TRIM25, disrupting its association with RIG-I and preventing downstream interferon signalling, contributing to the virus's evasion of the immune response.

METHODS

In our study we used structural-based drug designing, molecular simulation, and binding free energy approaches to identify the potent phytocompounds from various natural product databases (>100,000 compounds) able to inhibit the binding of NS1 with the TRIM25.

RESULTS

The molecular screening identified EA-8411902 and EA-19951545 from East African Natural Products Database, NA-390261 and NA-71 from North African Natural Products Database, SA-65230 and SA- 4477104 from South African Natural Compounds Database, NEA- 361 and NEA- 4524784 from North-East African Natural Products Database, TCM-4444713 and TCM-6056 from Traditional Chinese Medicines Database as top hits. The molecular docking and binding free energies results revealed that these compounds have high affinity with the specific active site residues (Leu95, Ser99, and Tyr89) involved in the interaction with TRIM25. Additionally, analysis of structural dynamics, binding free energy, and dissociation constants demonstrates a notably stronger binding affinity of these compounds with the NS1 protein. Moreover, all selected compounds exhibit exceptional ADMET properties, including high water solubility, gastrointestinal absorption, and an absence of hepatotoxicity, while adhering to Lipinski's rule.

CONCLUSION

Our molecular simulation findings highlight that the identified compounds demonstrate high affinity for specific active site residues involved in the NS1-TRIM25 interaction, exhibit exceptional ADMET properties, and adhere to drug-likeness criteria, thus presenting promising candidates for further development as antiviral agents against influenza A virus infections.

Advances, opportunities, and challenges in methods for interrogating the structure activity relationships of natural products

Time span in literature: 1985-early 2024Natural products play a key role in drug discovery, both as a direct source of drugs and as a starting point for the development of synthetic compounds. Most natural products are not suitable to be used as drugs without further modification due to insufficient activity or poor pharmacokinetic properties. Choosing what modifications to make requires an understanding of the compound's structure-activity relationships. Use of structure-activity relationships is commonplace and essential in medicinal chemistry campaigns applied to human-designed synthetic compounds. Structure-activity relationships have also been used to improve the properties of natural products, but several challenges still limit these efforts. Here, we review methods for studying the structure-activity relationships of natural products and their limitations. Specifically, we will discuss how synthesis, including total synthesis, late-stage derivatization, chemoenzymatic synthetic pathways, and engineering and genome mining of biosynthetic pathways can be used to produce natural product analogs and discuss the challenges of each of these approaches. Finally, we will discuss computational methods including machine learning methods for analyzing the relationship between biosynthetic genes and product activity, computer aided drug design techniques, and interpretable artificial intelligence approaches towards elucidating structure-activity relationships from models trained to predict bioactivity from chemical structure. Our focus will be on these latter topics as their applications for natural products have not been extensively reviewed. We suggest that these methods are all complementary to each other, and that only collaborative efforts using a combination of these techniques will result in a full understanding of the structure-activity relationships of natural products.

Synthesis and Cheminformatics-Directed Antibacterial Evaluation of Echinosulfonic Acid-Inspired Bis-Indole Alkaloids

Synthetic efforts toward complex natural product (NP) scaffolds are useful ones, particularly those aimed at expanding their bioactive chemical space. Here, we utilised an orthogonal cheminformatics-based approach to predict the potential biological activities for a series of synthetic bis-indole alkaloids inspired by elusive sponge-derived NPs, echinosulfone A (1) and echinosulfonic acids A-D (2-5). Our work includes the first synthesis of desulfato-echinosulfonic acid C, an α-hydroxy bis(3'-indolyl) alkaloid (17), and its full NMR characterisation. This synthesis provides corroborating evidence for the structure revision of echinosulfonic acids A-C. Additionally, we demonstrate a robust synthetic strategy toward a diverse range of α-methine bis(3'-indolyl) acids and acetates (11-16) without the need for silica-based purification in either one or two steps. By integrating our synthetic library of bis-indoles with bioactivity data for 2048 marine indole alkaloids (reported up to the end of 2021), we analyzed their overlap with marine natural product chemical diversity. Notably, the C-6 dibrominated α-hydroxy bis(3'-indolyl) and α-methine bis(3'-indolyl) analogues (11, 14, and 17) were found to contain significant overlap with antibacterial C-6 dibrominated marine bis-indoles, guiding our biological evaluation. Validating the results of our cheminformatics analyses, the dibrominated α-methine bis(3'-indolyl) alkaloids (11, 12, 14, and 15) were found to exhibit antibacterial activities against methicillin-sensitive and -resistant Staphylococcus aureus. Further, while investigating other synthetic approaches toward bis-indole alkaloids, 16 incorrectly assigned synthetic α-hydroxy bis(3'-indolyl) alkaloids were identified. After careful analysis of their reported NMR data, and comparison with those obtained for the synthetic bis-indoles reported herein, all of the structures have been revised to α-methine bis(3'-indolyl) alkaloids.

BIOMX-DB: A web application for the BIOFACQUIM natural product database

Natural product databases are an integral part of chemoinformatics and computer-aided drug design. Despite their pivotal role, a distinct scarcity of projects in Latin America, particularly in Mexico, provides accessible tools of this nature. Herein, we introduce BIOMX-DB, an open and freely accessible web-based database designed to address this gap. BIOMX-DB enhances the features of the existing Mexican natural product database, BIOFACQUIM, by incorporating advanced search, filtering, and download capabilities. The user-friendly interface of BIOMX-DB aims to provide an intuitive experience for researchers. For seamless access, BIOMX-DB is freely available at www.biomx-db.com.

Plant-Derived Coumarins: A Narrative Review of Their Structural and Biomedical Diversity

Plant-derived coumarin (PDC) is a naturally occurring heterocyclic backbone that belongs to the benzopyrone family. PDC and its based products are characterized by low toxicity and high distribution in a variety of herbal treatments that have numerous therapeutic potentials. These include anticoagulants, antibacterials, anti-inflammatory agents, anticancer agents, antioxidants, and others. So, it may be appropriate to investigate the qualities and potential bioactivities of PDCs. This article provides an overview of the biomedical potentials, availability, and clinical use possibilities of PDCs, with a focus on their important modes of action, using information on various pharmacological qualities discovered. The data used in this study came from published research between 2015 and 2023. We reviewed a selection of databases, including PubMed, Scopus, Web of Science, and Google Scholar, during that period. In conclusion, because of their abundance in medicinal plants, the clinical biochemistry attributes of PDCs are currently of interest. In a variety of medical specialties, PDCs serve a useful role as therapeutic agents.

A critical assessment of bioactive compounds databases

Compound databases (DBs) are essential tools for drug discovery. The number of DBs in public domain is increasing, so it is important to analyze these DBs. In this article, the main characteristics of 64 DBs will be presented. The methodological strategy used was a literature search. To analyze the characteristics obtained in the review, the DBs were categorized into two subsections: Open Access and Commercial DBs. Open access includes generalist DBs (containing compounds of diverse origins), DBs with specific applicability, DBs exclusive to natural products and those containing compounds with specific pharmacological action. The literature review showed that there are challenges to making these repositories available, such as standardizing information curation practices and funding to maintain and sustain them.

plantMASST - Community-driven chemotaxonomic digitization of plants

Understanding the distribution of hundreds of thousands of plant metabolites across the plant kingdom presents a challenge. To address this, we curated publicly available LC-MS/MS data from 19,075 plant extracts and developed the plantMASST reference database encompassing 246 botanical families, 1,469 genera, and 2,793 species. This taxonomically focused database facilitates the exploration of plant-derived molecules using tandem mass spectrometry (MS/MS) spectra. This tool will aid in drug discovery, biosynthesis, (chemo)taxonomy, and the evolutionary ecology of herbivore interactions.

Antibacterial, Trichomonacidal, and Cytotoxic Activities of Pleopeltis crassinervata Extracts

Pleopeltis crassinervata is a fern documented in ethnobotanical records for its use in Mexican traditional medicine to treat gastric disorders and mouth ulcers. Consequently, conducting biological and pharmacological assays is crucial to validate the therapeutic efficacy of this plant within the context of traditional medicine. In the present study, we investigated the biological activity of extracts and fractions obtained from P. crassinervata organs against bacteria (Salmonella typhimurium, Salmonella typhi, Staphylococcus aureus, Proteus mirabilis, Shigella flexneri, Bacillus subtilis, Escherichia coli) and Trichomonas vaginalis using in vitro models. The precipitate fraction obtained from the frond methanolic extract showed significant antibacterial activity (minimal inhibitory concentration [MIC] 120 µg/mL) against the Staphylococcus aureus strain and was effective against both Gram-positive and Gram-negative bacteria. The hexane fraction also obtained from frond methanolic extract, showed a trichomonacidal effect with an IC50 of 82.8 μg/mL and a low cytotoxic effect. Hsf6 exhibited the highest activity against T. vaginalis, and the GC-MS analysis revealed that the predominant compound was 16-pregnenolone. The remaining identified compounds were primarily terpene-type compounds.

Unveiling the Potential of Ent-Kaurane Diterpenoids: Multifaceted Natural Products for Drug Discovery

Natural products hold immense potential for drug discovery, yet many remain unexplored in vast libraries and databases. In an attempt to fill this gap and meet the growing demand for effective drugs, this study delves into the promising world of ent-kaurane diterpenoids, a class of natural products with huge therapeutic potential. With a dataset of 570 ent-kaurane diterpenoids obtained from the literature, we conducted an in silico analysis, evaluating their physicochemical, pharmacokinetic, and toxicological properties with a focus on their therapeutic implications. Notably, these natural compounds exhibit drug-like properties, aligning closely with those of FDA-approved drugs, indicating a high potential for drug development. The ranges of the physicochemical parameters were as follows: molecular weights-288.47 to 626.82 g/mol; number of heavy atoms-21 to 44; the number of hydrogen bond donors and acceptors-0 to 8 and 1 to 11, respectively; the number of rotatable bonds-0 to 11; fraction Csp3-0.65 to 1; and TPSA-20.23 to 189.53 Ų. Additionally, the majority of these molecules display favorable safety profiles, with only 0.70%, 1.40%, 0.70%, and 46.49% exhibiting mutagenic, tumorigenic, reproduction-enhancing, and irritant properties, respectively. Importantly, ent-kaurane diterpenoids exhibit promising biopharmaceutical properties. Their average lipophilicity is optimal for drug absorption, while over 99% are water-soluble, facilitating delivery. Further, 96.5% and 28.20% of these molecules exhibited intestinal and brain bioavailability, expanding their therapeutic reach. The predicted pharmacological activities of these compounds encompass a diverse range, including anticancer, immunosuppressant, chemoprotective, anti-hepatic, hepatoprotectant, anti-inflammation, antihyperthyroidism, and anti-hepatitis activities. This multi-targeted profile highlights ent-kaurane diterpenoids as highly promising candidates for further drug discovery endeavors.

Essentials in the acquisition, interpretation, and reporting of plant metabolite profiles

Plant metabolite profiling reveals the diversity of secondary or specialized metabolites in the plant kingdom with its hundreds of thousands of species. Specialized plant metabolites constitute a vast class of chemicals posing significant challenges in analytical chemistry. In order to be of maximum scientific relevance, reports dealing with these compounds and their source species must be transparent, make use of standards and reference materials, and be based on correctly and traceably identified plant material. Essential aspects in qualitative plant metabolite profiling include: (i) critical review of previous literature and a reasoned sampling strategy; (ii) transparent plant sampling with wild material documented by vouchers in public herbaria and, optimally, seed banks; (iii) if possible, inclusion of generally available reference plant material; (iv) transparent, documented state-of-the art chemical analysis, ideally including chemical reference standards; (v) testing for artefacts during preparative extraction and isolation, using gentle analytical methods; (vi) careful chemical data interpretation, avoiding over- and misinterpretation and taking into account phytochemical complexity when assigning identification confidence levels, and (vii) taking all previous scientific knowledge into account in reporting the scientific data. From the current stage of the phytochemical literature, selected comments and suggestions are given. In the past, proposed revisions of botanical taxonomy were sometimes based on metabolite profiles, but this approach ("chemosystematics" or "chemotaxonomy") is outdated due to the advent of DNA sequence-based phylogenies. In contrast, systematic comparisons of plant metabolite profiles in a known phylogenetic framework remain relevant. This approach, known as chemophenetics, allows characterizing species and clades based on their array of specialized metabolites, aids in deducing the evolution of biosynthetic pathways and coevolution, and can serve in identifying new sources of rare and economically interesting natural products.

A comprehensive computational study to explore promising natural bioactive compounds targeting glycosyltransferase MurG in Escherichia coli for potential drug development

Peptidoglycan is a carbohydrate with a cross-linked structure that protects the cytoplasmic membrane of bacterial cells from damage. The mechanism of peptidoglycan biosynthesis involves the main synthesizing enzyme glycosyltransferase MurG, which is known as a potential target for antibiotic therapy. Many MurG inhibitors have been recognized as MurG targets, but high toxicity and drug-resistant Escherichia coli strains remain the most important problems for further development. In addition, the discovery of selective MurG inhibitors has been limited to the synthesis of peptidoglycan-mimicking compounds. The present study employed drug discovery, such as virtual screening using molecular docking, drug likeness ADMET proprieties predictions, and molecular dynamics (MD) simulation, to identify potential natural products (NPs) for Escherichia coli. We conducted a screening of 30,926 NPs from the NPASS database. Subsequently, 20 of these compounds successfully passed the potency, pharmacokinetic, ADMET screening assays, and their validation was further confirmed through molecular docking. The best three hits and the standard were chosen for further MD simulations up to 400 ns and energy calculations to investigate the stability of the NPs-MurG complexes. The analyses of MD simulations and total binding energies suggested the higher stability of NPC272174. The potential compounds can be further explored in vivo and in vitro for promising novel antibacterial drug discovery.

Effectiveness of molecular fingerprints for exploring the chemical space of natural products

Natural products are a diverse class of compounds with promising biological properties, such as high potency and excellent selectivity. However, they have different structural motifs than typical drug-like compounds, e.g., a wider range of molecular weight, multiple stereocenters and higher fraction of sp3-hybridized carbons. This makes the encoding of natural products via molecular fingerprints difficult, thus restricting their use in cheminformatics studies. To tackle this issue, we explored over 30 years of research to systematically evaluate which molecular fingerprint provides the best performance on the natural product chemical space. We considered 20 molecular fingerprints from four different sources, which we then benchmarked on over 100,000 unique natural products from the COCONUT (COlleCtion of Open Natural prodUcTs) and CMNPD (Comprehensive Marine Natural Products Database) databases. Our analysis focused on the correlation between different fingerprints and their classification performance on 12 bioactivity prediction datasets. Our results show that different encodings can provide fundamentally different views of the natural product chemical space, leading to substantial differences in pairwise similarity and performance. While Extended Connectivity Fingerprints are the de-facto option to encoding drug-like compounds, other fingerprints resulted to match or outperform them for bioactivity prediction of natural products. These results highlight the need to evaluate multiple fingerprinting algorithms for optimal performance and suggest new areas of research. Finally, we provide an open-source Python package for computing all molecular fingerprints considered in the study, as well as data and scripts necessary to reproduce the results, at https://github.com/dahvida/NP_Fingerprints .

D3Rings: A Fast and Accurate Method for Ring System Identification and Deep Generation of Drug-Like Cyclic Compounds

Continuous exploration of the chemical space of molecules to find ligands with high affinity and specificity for specific targets is an important topic in drug discovery. A focus on cyclic compounds, particularly natural compounds with diverse scaffolds, provides important insights into novel molecular structures for drug design. However, the complexity of their ring structures has hindered the applicability of widely accepted methods and software for the systematic identification and classification of cyclic compounds. Herein, we successfully developed a new method, D3Rings, to identify acyclic, monocyclic, spiro ring, fused and bridged ring, and cage ring compounds, as well as macrocyclic compounds. By using D3Rings, we completed the statistics of cyclic compounds in three different databases, e.g., ChEMBL, DrugBank, and COCONUT. The results demonstrated the richness of ring structures in natural products, especially spiro, macrocycles, and fused and bridged rings. Based on this, three deep generative models, namely, VAE, AAE, and CharRNN, were trained and used to construct two data sets similar to DrugBank and COCONUT but 10 times larger than them. The enlarged data sets were then used to explore the molecular chemical space, focusing on complex ring structures, for novel drug discovery and development. Docking experiments with the newly generated COCONUT-like data set against three SARS-CoV-2 target proteins revealed that an expanded compound database improves molecular docking results. Cyclic structures exhibited the best docking scores among the top-ranked docking molecules. These results suggest the importance of exploring the chemical space of structurally novel cyclic compounds and continuous expansion of the library of drug-like compounds to facilitate the discovery of potent ligands with high binding affinity to specific targets. D3Rings is now freely available at http://www.d3pharma.com/D3Rings/.

An organic extract from ascidian Ciona robusta induces cytotoxic autophagy in human malignant cell lines

The last decades have seen an increase in the isolation and characterization of anticancer compounds derived from marine organisms, especially invertebrates, and their use in clinical trials. In this regard, ascidians, which are included in the subphylum Tunicata, represent successful examples with two drugs, Aplidine© and Yondelis© that reached the market as orphan drugs against several malignancies. Here, we report that an organic extract prepared from homogenized tissues of the Mediterranean ascidian Ciona robusta inhibited cell proliferation in HT-29, HepG2, and U2OS human cells with the former being the most sensitive to the extract (EC50 = 250 μg/mL). We demonstrated that the ascidian organic extract was not cytotoxic on HT-29 cells that were induced to differentiate with sodium butyrate, suggesting a preference for the mixture for the malignant phenotype. Finally, we report that cell death induced by the organic extract was mediated by the activation of a process of cytotoxic autophagy as a result of the increased expression of the LC3-II marker and number of autophagic vacuoles, which almost doubled in the treated HT-29 cells. In summary, although the detailed chemical composition of the Ciona robusta extract is still undetermined, our data suggest the presence of bioactive compounds possessing anticancer activity.

Identification of terpenoids as dihydropteroate synthase and dihydrofolate reductase inhibitors through structure-based virtual screening and molecular dynamic simulations

Bacterial infections are rising, and antimicrobial resistance (AMR) in bacteria has worsened the scenario, requiring extensive research to find alternative therapeutic agents. Terpenoids play an essential role in protecting plants from herbivores and pathogens. The present study was designed to focus on in silico evaluation of terpenoids for their affinity towards two necessary enzymes, i.e. DHFR and DHPS, which are involved in forming 5, 6, 7, 8-tetrahydrofolate, a key component in bacterial DNA synthesis proteins. Additionally, to account for activity against resistant bacteria, their affinity towards the L28R mutant of DHFR was also assessed in the study. The structure-based drug design approach was used to screen the compound library of terpenes for their interaction with active sites of DHFR and DHPS. Further, compounds were screened based on their dock score, pharmacokinetic properties, and binding affinities. A total of five compounds for each target protein were screened, having dock scores better than their respective standard drug molecules. CNP0169378 (-8.4 kcal/mol) and CNP0309455 (-6.5 kcal/mol) have been identified as molecules with a higher affinity toward the targets of DHFR and DHPS, respectively. At the same time, one molecule CNP0298407 (-5.8 kcal/mol for DHPS, -7.6 kcal/mol for DHFR, -6.1 kcal/mol for the L28R variant), has affinity for both proteins (6XG5 and 6XG4). All the molecules have good pharmacokinetic properties. We further validated the docking study by binding free energy calculations using the MM/GBSA approach and molecular dynamics simulations.Communicated by Ramaswamy H. Sarma.

Integrative Oncology Approaches to Reduce Recurrence of Disease and Improve Survival

PURPOSE OF REVIEW

After a cancer diagnosis, patients ask what they can do in addition to the recommended treatments to increase their survival. Many turn to integrative medicine modalities and lifestyle changes to improve their chances of survival. Numerous studies have demonstrated that lifestyle changes can significantly improve survival rates for cancer patients. Less support exists for the use of natural products or supplements to improve cancer survival. In this manuscript, we review key findings and evidence in the areas of healthy eating habits, physical activity, stress management and social support, and sleep quality, as well as natural products and supplements as they relate to the cancer recurrence and survival.

RECENT FINDINGS

While more research is needed to fully understand the mechanisms underlying the associations between lifestyle changes and cancer survival, findings suggest that lifestyle modifications in the areas of diet, physical activity, stress management and social support, and sleep quality improve clinical cancer outcomes. This is especially true for programs that modify more than one lifestyle habit. To date, outside of supplementing with vitamin D to maintain adequate levels, conflicting conclusion within the research remain regarding the efficacy of using natural products or supplement to improve cancer recurrence of disease or cancer survival. A call for further research is warranted. Lifestyle screening and counseling should be incorporated into cancer treatment plans to help improve patient outcomes. While the scientific community strives for the pursuit of high-quality research on natural products to enhance cancer survival, transparency, dialogue, and psychological safety between patients and clinicians must continue to be emphasized. Proactive inquiry by clinicians regarding patients' supplement use will allow for an informed discussion of the benefits and risks of natural products and supplements, as well as a re-emphasis of the evidence supporting diet and other lifestyle habits to increase survival.

Rumen fermentation and microbiota in Shami goats fed on condensed tannins or herbal mixture

BACKGROUND

Phytochemical compounds can modify the rumen microbiome and improve rumen fermentation. This study evaluated the impact of supplementation with tannin and an herbal mixture containing ginger (Zingiber officinale), garlic (Allium sativum), Artemisia (Artemisia vulgaris), and turmeric (Curcuma longa) on the rumen fermentation and microbiota, and histology of rumen tissue of goats. Eighteen Shami male goats were divided into three groups (n = 6): non-supplemented animals fed the basal diet (C, control); animals fed basal diet and supplemented with condensed tannin (T); and animals fed basal diet and supplemented with herbal mixture (HM). Each animal received a basal diet composed of Alfalfa hay and a concentrate feed mixture.

RESULTS

Group HM revealed higher (P < 0.05) rumen pH, total volatile fatty acids (VFA), acetic, propionic, isobutyric, butyric, isovaleric, and valeric. Principal Co-ordinate analysis (PCoA) showed that rumen microbial communities in the control group and supplemented groups were distinct. The supplementation increased (P < 0.05) the relative abundances of phylum Bacteroidota and Proteobacteria and declined (P < 0.05) Firmicutes and Fibrobacterota. Additionally, the dominant genus Prevotella and Rikenellaceae RC9 gut group were increased (P < 0.05) and the family Ruminococcaceae was declined (P < 0.05) due to the supplementation. The supplementation decreased (P < 0.05) the archaeal genus Methanobrevibacter and increased (P < 0.05) Candidatus Methanomethylophilus. Tannin supplementation in T group shortened the rumen papillae.

CONCLUSIONS

The results revealed that the herbal mixture might be used to alter the rumen microbiota to improve rumen fermentation.

Discovery of Streptomyces species CS-62, a novel producer of the Acinetobacter baumannii selective antibiotic factumycin

Narrow-spectrum antibiotics are of great interest given their ability to spare the microbiome and decrease widespread antibiotic resistance compared to broad-spectrum antibiotics. Herein, we screened an in-house library of Actinobacteria strains for selective activity against Acinetobacter baumannii and successfully identified Streptomyces sp. CS-62 as a producer of a natural product with this valuable activity. Analysis of the cultures via high-resolution mass spectrometry and tandem mass spectrometry, followed by comparison with molecules in the Natural Product Atlas and the Global Natural Products Social Molecular Networking platform, suggested a novel natural product. Genome mining analysis initially supported the production of a novel kirromycin derivative. Isolation and structure elucidation via mass spectrometry and Nuclear Magnetic Resonance (NMR) analyses revealed that the active natural product was the known natural product factumycin, exposing omissions and errors in the consulted databases. While public databases are generally very useful for avoiding rediscovery of known molecules, rediscovery remains a problem due to public databases either being incomplete or having errors that result in failed dereplication. Overall, the work describes the ongoing problem of dereplication and the continued need for public database curation.

Natural Products Dereplication: Databases and Analytical Methods

The development of efficient methods for dereplication has been critical in the re-emergence of the research in natural products as a source of drug leads. Current dereplication workflows rapidly identify already known bioactive secondary metabolites in the early stages of any drug discovery screening campaign based on natural extracts or enriched fractions. Two main factors have driven the evolution of natural products dereplication over the last decades. First, the availability of both commercial and public large databases of natural products containing the key annotations against which the biological and chemical data derived from the studied sample are searched for. Second, the considerable improvement achieved in analytical technologies (including instrumentation and software tools) employed to obtain robust and precise chemical information (particularly spectroscopic signatures) on the compounds present in the bioactive natural product samples. This chapter describes the main methods of dereplication, which rely on the combined use of large natural product databases and spectral libraries, alongside the information obtained from chromatographic, UV-Vis, MS, and NMR spectroscopic analyses of the samples of interest.

Extracts of Jamun seeds inhibited the growth of human (Hep-2) cancer cells

INTRODUCTION

In the last century, the human laryngeal epithelioma has become a life-threatening disease leading to a high rate of mortality worldwide. The current investigation is focusing on the antiproliferative effect of Eugenia jambolana seed extracts against Hep-2 cancer cells.

METHODS

The active compounds from the seeds of E. jambolana were extracted by the decoction extraction method using acetone, ethanol, and methanol. The filtrates from the different solvents were subjected to liquid-liquid separation before drying by a rotary evaporator. In various doses, the crude extracts and carcinoma were subjected to a methylthiazolyl diphenyl tetrazolium bromide assay. Cell viability was determined under ultraviolet visualization at an absorbance of 540 nm. The data of the viable cells were subjected to analysis of variance at P ≤ .01.

RESULTS

Crude compounds of E. jambolana seeds extracted by acetone, methanol, and methanol extract had an anticarcinoma effect. Among the extracts, methanol extract possessed a recommendable anti-carcinoma effect compared to acetone and ethanol crude extracts. At a concentration of 125 µg/mL, the crude extracts of methanol, acetone, and ethanol destroyed 49.57, 35.01, and 27.67 carcinomas, respectively. The concentration of 31.25 µg/mL of acetone extract and 125 µg/mL of ethanolic extract affected 28.11 and 27.67 carcinomas, respectively.

CONCLUSIONS

E.jambolana seeds possess anticarcinoma potency and thus can be administered in the reduction of proliferative carcinoma. The study recommended further studies which will involve the elution of pure compounds from the methanol extract of E. jambolana that possess antitumour and antiproliferative activity against Hep-2 cell lines.

Carbazole derivatives as promising competitive and allosteric inhibitors of human serotonin transporter: computational pharmacology

The human serotonin transporters (hSERTs) are neurotransmitter sodium symporters of the aminergic G protein-coupled receptors, regulating the synaptic serotonin and neuropharmacological processes related to neuropsychiatric disorders, notably, depression. Selective serotonin reuptake inhibitors (SSRIs) such as fluoxetine and (S)-citalopram are competitive inhibitors of hSERTs and are commonly the first-line medications for major depressive disorder (MDD). However, treatment-resistance and unpleasant aftereffects constitute their clinical drawbacks. Interestingly, vilazodone emerged with polypharmacological (competitive and allosteric) inhibitions on hSERTs, amenable to improved efficacy. However, its application usually warrants adjuvant/combination therapy, another subject of critical adverse events. Thus, the discovery of alternatives with polypharmacological potentials (one-drug-multiple-target) and improved safety remains essential. In this study, carbazole analogues from chemical libraries were explored using docking and molecular dynamics (MD) simulation. Selectively, two IBScreen ligands, STOCK3S-30866 and STOCK1N-37454 predictively bound to the active pockets and expanded boundaries (extracellular vestibules) of the hSERTs more potently than vilazodone and (S)-citalopram. For instance, the two ligands showed docking scores of -9.52 and -9.59 kcal/mol and MM-GBSA scores of -92.96 and -65.66 kcal/mol respectively compared to vilazodone's respective scores of -7.828 and -59.27 against the central active site of the hSERT (PDB 7LWD). Similarly, the two ligands also docked to the allosteric pocket (PDB 5I73) with scores of -8.15 and -8.40 kcal/mol and MM-GBSA of -96.14 and -68.46 kcal/mol whereas (S)-citalopram has -6.90 and -69.39 kcal/mol respectively. The ligands also conferred conformational stability on the receptors during 100 ns MD simulations and displayed interesting ADMET profiles, representing promising hSERT modulators for MDD upon experimental validation.Communicated by Ramaswamy H. Sarma.

PhyloSophos: a high-throughput scientific name mapping algorithm augmented with explicit consideration of taxonomic science, and its application on natural product (NP) occurrence database processing

BACKGROUND

The standardization of biological data using unique identifiers is vital for seamless data integration, comprehensive interpretation, and reproducibility of research findings, contributing to advancements in bioinformatics and systems biology. Despite being widely accepted as a universal identifier, scientific names for biological species have inherent limitations, including lack of stability, uniqueness, and convertibility, hindering their effective use as identifiers in databases, particularly in natural product (NP) occurrence databases, posing a substantial obstacle to utilizing this valuable data for large-scale research applications.

RESULT

To address these challenges and facilitate high-throughput analysis of biological data involving scientific names, we developed PhyloSophos, a Python package that considers the properties of scientific names and taxonomic systems to accurately map name inputs to entries within a chosen reference database. We illustrate the importance of assessing multiple taxonomic databases and considering taxonomic syntax-based pre-processing using NP occurrence databases as an example, with the ultimate goal of integrating heterogeneous information into a single, unified dataset.

CONCLUSIONS

We anticipate PhyloSophos to significantly aid in the systematic processing of poorly digitized and curated biological data, such as biodiversity information and ethnopharmacological resources, enabling full-scale bioinformatics analysis using these valuable data resources.

Model nematodes as a practical innovation to promote high throughput screening of natural products for anthelmintics discovery in South Asia: Current challenges, proposed practical and conceptual solutions

With the increasing prevalence of anthelmintic resistance in animals recorded globally, and the threat of resistance in human helminths, the need for novel anthelmintic drugs is greater than ever. Most research aimed at discovering novel anthelmintic leads relies on high throughput screening (HTS) of large libraries of synthetic small molecules in industrial and academic settings in developed countries, even though it is the tropical countries that are most plagued by helminth infections. Tropical countries, however, have the advantage of possessing a rich flora that may yield natural products (NP) with promising anthelmintic activity. Focusing on South Asia, which produces one of the world's highest research outputs in NP and NP-based anthelmintic discovery, we find that limited basic research and funding, a lack of awareness of the utility of model organisms, poor industry-academia partnerships and lack of technological innovations greatly limit anthelmintics research in the region. Here we propose that utilizing model organisms including the free-living nematode Caenorhabditis elegans, that can potentially allow rapid target identification of novel anthelmintics, and Oscheius tipulae, a closely related, free-living nematode which is found abundantly in soil in hotter temperatures, could be a much-needed innovation that can enable cost-effective and efficient HTS of NPs for discovering compounds with anthelmintic/antiparasitic potential in South Asia and other tropical regions that historically have devoted limited funding for such research. Additionally, increased collaborations at the national, regional and international level between parasitologists and pharmacologists/ethnobotanists, setting up government-industry-academia partnerships to fund academic research, creating a centralized, regional collection of plant extracts or purified NPs as a dereplication strategy and HTS library, and holding regional C. elegans/O. tipulae-based anthelmintics workshops and conferences to share knowledge and resources regarding model organisms may collectively promote and foster a NP-based anthelmintics landscape in South Asia and beyond.

Anti-cancer bioprospecting on medicinal plants from Indonesia: A review

The Indonesian archipelago is home to the second largest biodiversity in the world and is inhabited by more than 300 ethnic groups with a total population of more than 270 million. The indigenous population still rely on traditional medicine practices, especially the use of plant-based remedies. Although modern science-based exploration on Indonesian medicinal plants started with the European settlement in the archipelago in the 16th century, it was not until the 1970's that the phytochemistry of Indonesian medicinal plants was recognized for its potency. The need for new cancer cures to increase the quality of human life has led to the bioprospecting of medicinal plants including those of Indonesian origin. Despite published reports on the anticancer potency of Indonesian medicinal plants, to date there has been no comprehensive review on this topic. In this manuscript, we review the phytochemical and pharmacological studies on medicinal plants from Indonesia related to cancer therapy. Established databases (GARUDA, SciFinder, and PubMed) were used to collate data from 1990 to 2022, resulting in the description of 134 medicinal plants and their phytochemical and pharmacological properties including examples containing potent agents against breast, leukaemia, cervix, lung, and colon cancer cell lines based on in vitro bioassays and in vivo evaluation. These findings provide valuable insights into the bioprospecting of Indonesian medicinal plant providing directions for future studies, including the development of new therapeutics, both as botanicals or by using conventional dosage.

Multi-level advances in databases related to systems pharmacology in traditional Chinese medicine: a 60-year review

The therapeutic effects of traditional Chinese medicine (TCM) involve intricate interactions among multiple components and targets. Currently, computational approaches play a pivotal role in simulating various pharmacological processes of TCM. The application of network analysis in TCM research has provided an effective means to explain the pharmacological mechanisms underlying the actions of herbs or formulas through the lens of biological network analysis. Along with the advances of network analysis, computational science has coalesced around the core chain of TCM research: formula-herb-component-target-phenotype-ZHENG, facilitating the accumulation and organization of the extensive TCM-related data and the establishment of relevant databases. Nonetheless, recent years have witnessed a tendency toward homogeneity in the development and application of these databases. Advancements in computational technologies, including deep learning and foundation model, have propelled the exploration and modeling of intricate systems into a new phase, potentially heralding a new era. This review aims to delves into the progress made in databases related to six key entities: formula, herb, component, target, phenotype, and ZHENG. Systematically discussions on the commonalities and disparities among various database types were presented. In addition, the review raised the issue of research bottleneck in TCM computational pharmacology and envisions the forthcoming directions of computational research within the realm of TCM.

Use of carbon-13 NMR to identify known natural products by querying a nuclear magnetic resonance database-An assessment

The quick identification of known organic low molecular weight compounds, also known as structural dereplication, is a highly important task in the chemical profiling of natural resource extracts. To that end, a method that relies on carbon-13 nuclear magnetic resonance (NMR) spectroscopy, elaborated in earlier works of the author's research group, requires the availability of a dedicated database that establishes relationships between chemical structures, biological and chemical taxonomy, and spectroscopy. The construction of such a database, called acd_lotus, was reported earlier, and its usefulness was illustrated by only three examples. This article presents the results of structure searches carried out starting from 58 carbon-13 NMR data sets recorded on compounds selected in the metabolomics section of the biological magnetic resonance bank (BMRB). Two compound retrieval methods were employed. The first one involves searching in the acd_lotus database using commercial software. The second one operates through the freely accessible web interface of the nmrshiftdb2 database, which includes the compounds present in acd_lotus and many others. The two structural dereplication methods have proved to be efficient and can be used together in a complementary way.

Artificial intelligence for natural product drug discovery

Developments in computational omics technologies have provided new means to access the hidden diversity of natural products, unearthing new potential for drug discovery. In parallel, artificial intelligence approaches such as machine learning have led to exciting developments in the computational drug design field, facilitating biological activity prediction and de novo drug design for molecular targets of interest. Here, we describe current and future synergies between these developments to effectively identify drug candidates from the plethora of molecules produced by nature. We also discuss how to address key challenges in realizing the potential of these synergies, such as the need for high-quality datasets to train deep learning algorithms and appropriate strategies for algorithm validation.

Discovery of novel HDAC8 inhibitors from natural compounds by in silico high throughput screening

A class I histone deacetylase HDAC8 is associated with several diseases, including cancer, intellectual impairment and parasite infection. Most of the HDAC inhibitors that have so far been found to inhibit HDAC8 limit their efficacy in the clinic by producing toxicities. It is therefore very desirable to develop specific HDAC8 inhibitors. The emergence of HDAC inhibitors derived from natural sources has become quite popular. In recent decades, it has been shown that naturally occurring HDAC inhibitors have strong anticancer properties. A total of 0.2 million natural compounds were screened against HDAC8 from the Universal Natural Product Database (UNPD). Molecular docking was performed for these natural compounds and the top six hits were obtained. In addition, molecular dynamics (MD) simulations were used to evaluate the structural stability and binding affinity of the inhibitors, which showed that the protein-ligand complexes remained stable throughout the 100 ns simulation. MM-PBSA method demonstrated that the selected compounds have high affinity towards HDAC8. We infer from our findings that Hit-1 (-29.35 kcal mol-1), Hit-2 (-29.15 kcal mol-1) and Hit-6 (-30.28 kcal mol-1) have better binding affinity and adhesion to ADMET (absorption, distribution, metabolism, excretion and toxicity) characteristics against HDAC8. To compare our discussions and result in an effective way. We performed molecular docking, MD and MM-PBSA analysis for the FDA-approved drug romidepsin. The above results show that our hits show better binding affinity than the compound romidepsin (-12.03 ± 4.66 kcal mol-1). The important hotspot residues Asp29, Ile34, Trp141, Phe152, Asp267, Met274 and Tyr306 have significantly contributed to the protein-ligand interaction. These findings suggest that in vitro testing and additional optimization may lead to the development of HDAC8 inhibitors.Communicated by Ramaswamy H. Sarma.

Structure-Based In Silico Screening of Marine Phlorotannins for Potential Walrus Calicivirus Inhibitor

A new calicivirus isolated from a walrus was reported in 2004. Since unknown marine mammalian zoonotic viruses could pose great risks to human health, this study aimed to develop therapeutic countermeasures to quell any potential outbreak of a pandemic caused by this virus. We first generated a 3D model of the walrus calicivirus capsid protein and identified compounds from marine natural products, especially phlorotannins, as potential walrus calicivirus inhibitors. A 3D model of the target protein was generated using homology modeling based on two publicly available template sequences. The sequence of the capsid protein exhibited 31.3% identity and 42.7% similarity with the reference templates. The accuracy and reliability of the predicted residues were validated via Ramachandran plotting. Molecular docking simulations were performed between the capsid protein 3D model and 17 phlorotannins. Among them, five phlorotannins demonstrated markedly stable docking profiles; in particular, 2,7-phloroglucinol-6,6-bieckol showed favorable structural integrity and stability during molecular dynamics simulations. The results indicate that the phlorotannins are promising walrus calicivirus inhibitors. Overall, the study findings showcase the rapid turnaround of in silico-based drug discovery approaches, providing useful insights for developing potential therapies against novel pathogenic viruses, especially when the 3D structures of the viruses remain experimentally unknown.

Challenges in natural product-based drug discovery assisted with in silico-based methods

The application of traditional medicine by humans for the treatment of ailments as well as improving the quality of life far outdates recorded history. To date, a significant percentage of humans, especially those living in developing/underprivileged communities still rely on traditional medicine for primary healthcare needs. In silico-based methods have been shown to play a pivotal role in modern pharmaceutical drug discovery processes. The application of these methods in identifying natural product (NP)-based hits has been successful. This is very much observed in many research set-ups that use rationally in silico-based methods in combination with experimental validation techniques. The combination has rendered the use of in silico-based approaches even more popular and successful in the investigation of NPs. However, identifying and proposing novel NP-based hits for experimental validation comes with several challenges such as the availability of compounds by suppliers, the huge task of separating pure compounds from complex mixtures, the quantity of samples available from the natural source to be tested, not to mention the potential ecological impact if the natural source is exhausted. Because most peer-reviewed publications are biased towards "positive results", these challenges are generally not discussed in publications. In this review, we highlight and discuss these challenges. The idea is to give interested scientists in this field of research an idea of what they can come across or should be expecting as well as prompting them on how to avoid or fix these issues.

TCMBank: bridges between the largest herbal medicines, chemical ingredients, target proteins, and associated diseases with intelligence text mining

Traditional Chinese Medicine (TCM) has long been viewed as a precious source of modern drug discovery. AI-assisted drug discovery (AIDD) has been investigated extensively. However, there are still two challenges in applying AIDD to guide TCM drug discovery: the lack of a large amount of standardized TCM-related information and AIDD is prone to pathological failures in out-of-domain data. We have released TCM Database@Taiwan in 2011, and it has been widely disseminated and used. Now, we developed TCMBank, the largest systematic free TCM database, which is an extension of TCM Database@Taiwan. TCMBank contains 9192 herbs, 61 966 ingredients (unduplicated), 15 179 targets, 32 529 diseases, and their pairwise relationships. By integrating multiple data sources, TCMBank provides 3D structure information of ingredients and provides a standard list and detailed information on herbs, ingredients, targets and diseases. TCMBank has an intelligent document identification module that continuously adds TCM-related information retrieved from the literature in PubChem. In addition, driven by TCMBank big data, we developed an ensemble learning-based drug discovery protocol for identifying potential leads and drug repurposing. We take colorectal cancer and Alzheimer's disease as examples to demonstrate how to accelerate drug discovery by artificial intelligence. Using TCMBank, researchers can view literature-driven relationship mapping between herbs/ingredients and genes/diseases, allowing the understanding of molecular action mechanisms for ingredients and identification of new potentially effective treatments. TCMBank is available at https://TCMBank.CN/.

Navigating the Chemical Space and Chemical Multiverse of a Unified Latin American Natural Product Database: LANaPDB

The number of databases of natural products (NPs) has increased substantially. Latin America is extraordinarily rich in biodiversity, enabling the identification of novel NPs, which has encouraged both the development of databases and the implementation of those that are being created or are under development. In a collective effort from several Latin American countries, herein we introduce the first version of the Latin American Natural Products Database (LANaPDB), a public compound collection that gathers the chemical information of NPs contained in diverse databases from this geographical region. The current version of LANaPDB unifies the information from six countries and contains 12,959 chemical structures. The structural classification showed that the most abundant compounds are the terpenoids (63.2%), phenylpropanoids (18%) and alkaloids (11.8%). From the analysis of the distribution of properties of pharmaceutical interest, it was observed that many LANaPDB compounds satisfy some drug-like rules of thumb for physicochemical properties. The concept of the chemical multiverse was employed to generate multiple chemical spaces from two different fingerprints and two dimensionality reduction techniques. Comparing LANaPDB with FDA-approved drugs and the major open-access repository of NPs, COCONUT, it was concluded that the chemical space covered by LANaPDB completely overlaps with COCONUT and, in some regions, with FDA-approved drugs. LANaPDB will be updated, adding more compounds from each database, plus the addition of databases from other Latin American countries.

Animal models of silicosis: fishing for new therapeutic targets and treatments

Silicosis as an occupational lung disease has been present in our lives for centuries. Research studies have already developed and implemented many animal models to study the pathogenesis and molecular basis of the disease and enabled the search for treatments. As all experimental animal models used to date have their advantages and disadvantages, there is a continuous search for a better model, which will not only accelerate basic research, but also contribute to clinical aspects and drug development. We review here, for the first time, the main animal models developed to date to study silicosis and the unique advantages of the zebrafish model that make it an optimal complement to other models. Among the main advantages of zebrafish for modelling human diseases are its ease of husbandry, low maintenance cost, external fertilisation and development, its transparency from early life, and its amenability to chemical and genetic screening. We discuss the use of zebrafish as a model of silicosis, its similarities to other animal models and the characteristics of patients at molecular and clinical levels, and show the current state of the art of inflammatory and fibrotic zebrafish models that could be used in silicosis research.

Degradation of benzo [a] pyrene in the soil enhanced by soapwort: The role of soapwort and functional microbial community

The limited bioavailability of polycyclic aromatic hydrocarbons (PAHs) in soils poses a challenge for their biodegradation. We hypotheses soapwort (Saponaria officinalis L.) as a factory in-situ providing biosurfactant, which could effectively promote the BaP removal by exogenous or native functional microbes. Rhizo-box and microcosm experiments were conducted to analyze the phyto-microbial remediation mechanism of soapwort, a plant that excretes biosurfactants known as saponins, and combined with two exogenous strains (P. chrysosporium and/or B. subtilis) for benzo[a]pyrene (BaP)-contaminated soils. The results revealed that the natural attenuation treatment (CK) BaP achieved only a 15.90% BaP removal rate after 100 days. In contrast, soapwort (SP), soapwort-bacteria (SPB), soapwort-fungus (SPF), soapwort- bacteria - fungus (SPM) mediated rhizosphere soils treatments yielded removal rates of 40.48%, 42.42%, 52.37%, and 62.57%, respectively. The analysis of the microbial community structure suggested that soapwort stimulated the introduction and native functional microorganisms, such as Rhizobiales, Micrococcales, and Clostridiales, which contributed to BaP removal via metabolic pathways. Furthermore, the efficient BaP removal was attributed to saponins, amino acids, and carbohydrates, which facilitated mobilization, solubilization of BaP, and microbial activity. In conclusion, our study highlights the potential of soapwort and specific microbial strains to effectively remediate PAH-contaminated soils.

Emerging pharmaceutical therapies of Ascidian-derived natural products and derivatives

In a growing multidrug-resistant environment, the identification of potential new drug candidates with an acceptable safety profile is a substantial crux in pharmaceutical discovery. This review discusses several aspects and properties of approved marine natural products derived from ascidian sources (phylum Chordata, subphylum Tunicata) and/or their deduced analogues including their biosynthetic origin, (bio)chemical preclinical assessments and known efficacy-safety profiles, clinical status in trials, but also translational developments, opportunities and final conclusions. The review also describes the preclinical assessments of a large number of other ascidian compounds that have not been involved in clinical trials yet. Finally, the emerging research on the connectivity of the ascidian hosts and their independent or obligate symbiotic guests is discussed. The review covers the latest information on the topic of ascidian-derived marine natural products over the last two decades including 2022, with the majority of publications published in the last decade.

Phytochemical Profiling and Pharmacological Evaluation of Leaf Extracts of Ruellia tuberosa L.: An In Vitro and In Silico Approach

The present study was designed to appraise the photoprotective, antioxidant, and antibacterial bioactivities of Ruellia tuberosa leaves extracts (RtPE, RtChl, RtEA, RtAc, RtMe, and RtHMe). The results showed that, RtHMe extracts of R. tuberosa was rich in total phenolic content, i. e., 1.60 mgGAE/g dry extract, while highest total flavonoid content was found in RtAc extract, i. e., 0.40 mgQE/g. RtMe showed effective antioxidant activity (%RSA: 58.16) at the concentration of 120 μL. RtMe, RtEA and RtHMe exhibited effective in vitro antibacterial activity against Gram-negative bacteria (E. coli). In silico docking studies revealed that paucifloside (-11.743 kcal/mol), indole-3-carboxaldehyde (-7.519 kcal/mol), nuomioside (-7.275 kcal/mol), isocassifolioside (-6.992 kcal/mol) showed best docking score against PDB ID 2EX8 [penicillin binding protein 4 (dacB) from Escherichia coli, complexed with penicillin-G], PDB ID 6CQA (E. coli dihydrofolate reductase protein complexed with inhibitor AMPQD), PDB ID 2Y2I [Penicillin-binding protein 1B in complex with an alkyl boronate (ZA3)] and PDB ID 2OLV (from S. aureus), respectively. Docked phytochemicals also showed good drug likeness properties.

Combining the Peptide RWQWRWQWR and an Ethanolic Extract of Bidens pilosa Enhances the Activity against Sensitive and Resistant Candida albicans and C. auris Strains

The antifungal activity of palindromic peptide RWQWRWQWR and its derivatives was evaluated against clinical isolates of Candida albicans and C. auris. Also, Bidens pilosa ethanolic extracts of leaves and stem were evaluated. Furthermore, combinations of peptide, extract, and/or fluconazole (FLC) were evaluated. The cytotoxicity of peptides and extracts in erythrocytes and fibroblasts was determined. The original palindromic peptide, some derivative peptides, and the ethanolic extract of leaves of B. pilosa exhibited the highest activity in some of the strains evaluated. Synergy was obtained between the peptide and the FLC against C. auris 435. The combination of the extract and the original palindromic peptide against C. albicans SC5314, C. auris 435, and C. auris 537 decreased the minimal inhibitory concentrations (MICs) by a factor of between 4 and 16. These mixtures induced changes in cell morphology, such as deformations on the cell surface. The results suggest that the combination of RWQWRWQWR and B. pilosa extract is an alternative for enhancing antifungal activity and decreasing cytotoxicity and costs and should be considered to be a promising strategy for treating diseases caused by Candida spp.