Integrating bacterial molecular genetics with chemical biology for renewed antibacterial drug discovery.

The application of dyes to understanding the aetiology of infection inspired antimicrobial chemotherapy and the first wave of antibacterial drugs. The second wave of antibacterial drug discovery was driven by rapid discovery of natural products, now making up 69% of current antibacterial drugs. But now with the most prevalent natural products already discovered, ∼107 new soil-dwelling bacterial species must be screened to discover one new class of natural product. Therefore, instead of a third wave of antibacterial drug discovery, there is now a discovery bottleneck. Unlike natural products which are curated by billions of years of microbial antagonism, the vast synthetic chemical space still requires artificial curation through the therapeutics science of antibacterial drugs - a systematic understanding of how small molecules interact with bacterial physiology, effect desired phenotypes, and benefit the host. Bacterial molecular genetics can elucidate pathogen biology relevant to therapeutics development, but it can also be applied directly to understanding mechanisms and liabilities of new chemical agents with new mechanisms of action. Therefore, the next phase of antibacterial drug discovery could be enabled by integrating chemical expertise with systematic dissection of bacterial infection biology. Facing the ambitious endeavour to find new molecules from nature or new-to-nature which cure bacterial infections, the capabilities furnished by modern chemical biology and molecular genetics can be applied to prospecting for chemical modulators of new targets which circumvent prevalent resistance mechanisms.

Boosting the Anti-Helicobacter Efficacy of Azithromycin through Natural Compounds: Insights From In Vitro, In Vivo, Histopathological, and Molecular Docking Investigations.

BACKGROUND: Antimicrobial-resistant Helicobacter pylori (H. pylori) poses a significant public health concern, especially given the limited therapeutic options for azithromycin-resistant strains. Hence, there is a necessity for new studies to reconsider the use of azithromycin, which has diminished in effectiveness against numerous strains. Thus, we aimed to augment azithromycin's anti-Helicobacter properties by combining it with curcumin in different formulations, including curcumin in clove oil, curcumin nano-gold emulsion, and curcumin nanoemulsion. METHODS: The antimicrobial activities of the investigated compounds, both individually and in combination with other anti-Helicobacter drugs, were evaluated. Their antibiofilm and anti-virulence properties were assessed using both phenotypic and genotypic methods, alongside molecular docking studies. Our findings were further validated through mouse protection assays and histopathological analysis. RESULTS: We observed high anti-Helicobacter activities of curcumin, especially curcumin nanoemulsion. A synergistic effect was detected between curcumin nanoemulsion and azithromycin with fraction inhibitory concentration index (FICI) values <0.5. The curcumin nanoemulsion was the most active anti-biofilm and anti-virulence compound among the examined substances. The biofilm-correlated virulence genes (babA and hopQ) and ureA genes were downregulated (fold change <1) post-treatment with curcumin nanoemulsion. On the protein level, the anti-virulence activities of curcumin nanoemulsion were documented based on molecular docking studies. These findings aligned with histopathological scoring of challenge mice, affirming the superior efficacy of curcumin nanoemulsion/azithromycin combination. CONCLUSION: The anti-Helicobacter activities of all curcumin physical forms pose significant challenges due to their higher  minimum inhibitory concentration (MIC) values exceeding the maximum permissible level. However, using curcumin nanoemulsion at sub-MIC levels could enhance the anti-Helicobacter activity of azithromycin and exhibit anti-virulence properties, thereby improving patient outcomes and addressing resistant pathogens. Therefore, more extensive studies are necessary to assess the safety of incorporating curcumin nanoemulsion into H. pylori treatment.

Biological Activity of Natural and Synthetic Peptides as Anticancer Agents.

Cancer is one of the leading causes of morbidity and death worldwide, making it a serious global health concern. Chemotherapy, radiotherapy, and surgical treatment are the most used conventional therapeutic approaches, although they show several side effects that limit their effectiveness. For these reasons, the discovery of new effective alternative therapies still represents an enormous challenge for the treatment of tumour diseases. Recently, anticancer peptides (ACPs) have gained attention for cancer diagnosis and treatment. ACPs are small bioactive molecules which selectively induce cancer cell death through a variety of mechanisms such as apoptosis, membrane disruption, DNA damage, immunomodulation, as well as inhibition of angiogenesis, cell survival, and proliferation pathways. ACPs can also be employed for the targeted delivery of drugs into cancer cells. With over 1000 clinical trials using ACPs, their potential for application in cancer therapy seems promising. Peptides can also be utilized in conjunction with imaging agents and molecular imaging methods, such as MRI, PET, CT, and NIR, improving the detection and the classification of cancer, and monitoring the treatment response. In this review we will provide an overview of the biological activity of some natural and synthetic peptides for the treatment of the most common and malignant tumours affecting people around the world.

Chemical language modeling with structured state space sequence models.

Generative deep learning is reshaping drug design. Chemical language models (CLMs) - which generate molecules in the form of molecular strings - bear particular promise for this endeavor. Here, we introduce a recent deep learning architecture, termed Structured State Space Sequence (S4) model, into de novo drug design. In addition to its unprecedented performance in various fields, S4 has shown remarkable capabilities to learn the global properties of sequences. This aspect is intriguing in chemical language modeling, where complex molecular properties like bioactivity can 'emerge' from separated portions in the molecular string. This observation gives rise to the following question: Can S4 advance chemical language modeling for de novo design? To provide an answer, we systematically benchmark S4 with state-of-the-art CLMs on an array of drug discovery tasks, such as the identification of bioactive compounds, and the design of drug-like molecules and natural products. S4 shows a superior capacity to learn complex molecular properties, while at the same time exploring diverse scaffolds. Finally, when applied prospectively to kinase inhibition, S4 designs eight of out ten molecules that are predicted as highly active by molecular dynamics simulations. Taken together, these findings advocate for the introduction of S4 into chemical language modeling - uncovering its untapped potential in the molecular sciences.

[Research progress in targeting DNA G-quadruplexes using natural products].

DNA G-quadruplex(G4) is a guanine-rich single-stranded DNA sequence that spontaneously folds into a spherical four-stranded DNA secondary structure in oncogene promoter sequences and telomeres. G4s are highly associated with the occurrence and development of cancer and have emerged as promising anticancer targets. Natural products have long been important sources of anticancer drug development. In recent years, significant progress has been made in the discovery of natural drugs targeting DNA G4s, with many DNA G4s have been confirmed as promising targets of natural products, including MYC-G4, KRAS-G4, PDGFR-ß-G4, BCL-2-G4, VEGF-G4, and telomeric G4. This review summarizes the research progress in discovering natural small molecules that target DNA G4s and their binding mechanisms. It also discusses the opportunities of and challenges in developing drugs targeting DNA G4s. This review will serve as a valuable reference for the research on natural products, particularly in the development of novel antitumor medications.

Natural Bioactive Compounds in the Management of Periodontal Diseases: A Comprehensive Review.

Periodontal diseases, chronic inflammatory conditions affecting oral health, are primarily driven by microbial plaque biofilm and the body's inflammatory response, leading to tissue damage and potential tooth loss. These diseases have significant physical, psychological, social, and economic impacts, necessitating effective management strategies that include early diagnosis, comprehensive treatment, and innovative therapeutic approaches. Recent advancements in biomanufacturing have facilitated the development of natural bioactive compounds, such as polyphenols, terpenoids, alkaloids, saponins, and peptides, which exhibit antimicrobial, anti-inflammatory, and tissue regenerative properties. This review explores the biomanufacturing processes-microbial fermentation, plant cell cultures, and enzymatic synthesis-and their roles in producing these bioactive compounds for managing periodontal diseases. The integration of these natural compounds into periodontal therapy offers promising alternatives to traditional treatments, potentially overcoming issues like antibiotic resistance and the disruption of the natural microbiota, thereby improving patient outcomes.

Bioactive Compounds from Natural Sources: Discovery, Evaluation, and Applications.

Natural products are of paramount importance due to their extensive range of biological activities, making them indispensable in drug discovery and development [...].

High-Throughput Mining of Novel Compounds from Known Microbes: A Boost to Natural Product Screening.

Advanced techniques can accelerate the pace of natural product discovery from microbes, which has been lagging behind the drug discovery era. Therefore, the present review article discusses the various interdisciplinary and cutting-edge techniques to present a concrete strategy that enables the high-throughput screening of novel natural compounds (NCs) from known microbes. Recent bioinformatics methods revealed that the microbial genome contains a huge untapped reservoir of silent biosynthetic gene clusters (BGC). This article describes several methods to identify the microbial strains with hidden mines of silent BGCs. Moreover, antiSMASH 5.0 is a free, accurate, and highly reliable bioinformatics tool discussed in detail to identify silent BGCs in the microbial genome. Further, the latest microbial culture technique, HiTES (high-throughput elicitor screening), has been detailed for the expression of silent BGCs using 500-1000 different growth conditions at a time. Following the expression of silent BGCs, the latest mass spectrometry methods are highlighted to identify the NCs. The recently emerged LAESI-IMS (laser ablation electrospray ionization-imaging mass spectrometry) technique, which enables the rapid identification of novel NCs directly from microtiter plates, is presented in detail. Finally, various trending 'dereplication' strategies are emphasized to increase the effectiveness of NC screening.

Integrating In Silico and In Vitro Approaches to Identify Natural Peptides with Selective Cytotoxicity against Cancer Cells.

Anticancer peptides (ACPs) are bioactive compounds known for their selective cytotoxicity against tumor cells via various mechanisms. Recent studies have demonstrated that in silico machine learning methods are effective in predicting peptides with anticancer activity. In this study, we collected and analyzed over a thousand experimentally verified ACPs, specifically targeting peptides derived from natural sources. We developed a precise prediction model based on their sequence and structural features, and the model's evaluation results suggest its strong predictive ability for anticancer activity. To enhance reliability, we integrated the results of this model with those from other available methods. In total, we identified 176 potential ACPs, some of which were synthesized and further evaluated using the MTT colorimetric assay. All of these putative ACPs exhibited significant anticancer effects and selective cytotoxicity against specific tumor cells. In summary, we present a strategy for identifying and characterizing natural peptides with selective cytotoxicity against cancer cells, which could serve as novel therapeutic agents. Our prediction model can effectively screen new molecules for potential anticancer activity, and the results from in vitro experiments provide compelling evidence of the candidates' anticancer effects and selective cytotoxicity.

Iron-sulphur protein catalysed [4+2] cycloadditions in natural product biosynthesis.

To the best of our knowledge, enzymes that catalyse intramolecular Diels-Alder ([4+2] cycloaddition) reactions are frequently reported in natural product biosynthesis; however, no native enzymes utilising Lewis acid catalysis have been reported. Verticilactam is a representative member of polycyclic macrolactams, presumably produced by spontaneous cycloaddition. We report that the intramolecular [4+2] cycloadditions can be significantly accelerated by ferredoxins (Fds), a class of small iron-sulphur (Fe-S) proteins. Through iron atom substitution by Lewis acidic gallium (Ga) iron and computational calculations, we confirm that the ubiquitous Fe-S cluster efficiently functions as Lewis acid to accelerate the tandem [4+2] cycloaddition and Michael addition reactions by lowering free energy barriers. Our work highlights Nature's ingenious strategy to generate complex molecule structures using the ubiquitous Fe-S protein. Furthermore, our study sheds light on the future design of Fd as a versatile Lewis acid catalyst for [4+2] cycloaddition reactions.

Role of Charge Heterogeneity on Physical Stability of Monoclonal Antibody Biotherapeutic Products.

PURPOSE: Chemical modifications in monoclonal antibodies can change hydrophobicity, charge heterogeneity as well as conformation, which eventually can impact their physical stability. In this study, the effect of the individual charge variants on physical stability and aggregation propensity in two different buffer conditions used during downstream purification was investigated. METHODS: The charge variants were separated using semi-preparative cation exchange chromatography and buffer exchanged in the two buffers with pH 6.0 and 3.8. Subsequently each variant was analysed for size heterogeneity using size exclusion chromatography and dynamic light scattering, conformational stability, colloidal stability, and aggregation behaviour under accelerated stability conditions. RESULTS: Size variants in each charge variant were similar in both pH conditions when analyzed without extended storage. However, conformational stability was lower at pH 3.8 than pH 6.0. All charge variants showed similar apparent melting temperature at pH 6.0. In contrast, at pH 3.8 variants A3, A5, B2, B3 and B4 display lower Tm, suggesting reduced conformational stability. Further, A2, A3 and A5 exhibit reduced colloidal stability at pH 3.8. In general, acidic variants are more prone to aggregation than basic variants. CONCLUSION: Typical industry practice today is to examine in-process intermediate stability with acidic species and basic species taken as a single category each. We suggest that perhaps stability evaluation needs to be performed at specie level as different acidic or basic species have different stability and this knowledge can be used for clever designing of the downstream process to achieve a stable product.

High-Throughput Fluorometric Assay For Quantifying Polysorbate In Biopharmaceutical Products Using Micelle Activated Fluorescence Probe N-Phenyl-1-Naphthylamine.

PURPOSE: Polysorbates are among the most used surfactants in biopharmaceutical products containing proteins. Our work aims to develop a high-throughput fluorometric assay to further diversify the analytical toolbox for quantification of PSs. METHOD: The assay leverages the micelle activated fluorescence signal from N-Phenyl-1-Naphthylamine (NPN). The development and optimization of assay parameters were guided by the pre-defined analytical target profile. Furthermore, NMR was used to probe the interaction between protein, PS80 and NPN in the measurement system and understand protein interference. RESULTS: All assay parameters including excitation and emission wavelengths, standard curve, NPN concentration, and incubation time have been optimized and adapted to a microplate format, making it compatible with automated solutions that will be pursued in the near future to drive consistency and efficiency in our workflows. The specificity, accuracy, and precision of the assay have been demonstrated through a case study. Furthermore, NMR results provided additional insight into the change of the interaction dynamics between PS80 and NPN as the protein concentration increases. The results indicate minimal interaction between the protein and PS80 at lower concentration. However, when the concentration exceeds 75 mg/mL, there is a significant interaction between the protein and PS-80 micelle and monomer. CONCLUSION: A high-throughput fluorometric assay has been developed for quantification of polysorbates in biopharmaceutical samples including in-process samples, drug substance and drug product. The assay reported herein could serve as a powerful analytical tool for polysorbate quantification and control, complementing the widely used liquid chromatography with charged aerosol detection method.

Recent Progress in Synthetic and Biological Application of Diorganyl Diselenides.

Diorganyl diselenides have emerged as privileged structures because they are easy to prepare, have distinct reactivity, and have broad biological activity. They have also been used in the synthesis of natural products as an electrophile in the organoselenylation of aromatic systems and peptides, reductions of alkenes, and nucleophilic substitution. This review summarizes the advancements in methods for the transformations promoted by diorganyl diselenides in the main functions of organic chemistry. Parallel, it will also describe the main findings on pharmacology and toxicology of diorganyl diselenides, emphasizing anti-inflammatory, hypoglycemic, chemotherapeutic, and antimicrobial activities. Therefore, an examination detailing the reactivity and biological characteristics of diorganyl diselenides provides valuable insights for academic researchers and industrial professionals.

Natural Products of Licorice for Uranium Decorporation with Low Toxicity and High Efficiency.

The development and exploration of uranium decorporation agents with straightforward synthesis, high removal ability, and low toxicity are crucial guarantees for the safety of workers in the nuclear industry and the public. Herein, we report the use of traditional Chinese medicine licorice for uranium decorporation. Licorice has good adsorption performance and excellent selectivity for uranium in the simulated human environment. Glycyrrhizic acid (GL) has a high affinity for uranium (p(UO2) = 13.67) and will complex with uranium at the carbonyl site. Both licorice and GL exhibit lower cytotoxicity compared to the commercial clinical decorporation agent diethylenetriamine pentaacetate sodium salts (CaNa3-DTPA). Notably, at the cellular level, the uranium removal efficiency of GL is eight times higher than that of CaNa3-DTPA. Administration of GL by prophylactic intraperitoneal injection demonstrates that its uranium removal efficiency from kidneys and bones is 55.2 and 23.9%, while CaNa3-DTPA shows an insignificant effect. The density functional theory calculation of the bonding energy between GL and uranium demonstrates that GL exhibits a higher binding affinity (-2.01 vs -1.15 eV) to uranium compared to DTPA. These findings support the potential of licorice and its active ingredient, GL, as promising candidates for uranium decorporation agents.

Quantification of binding capacity of natural products to target proteins by sensors integrating SERS labeling and photocrosslinked molecular probes.

Natural products-based screening of active ingredients and their interactions with target proteins is an important ways to discover new drugs. Assessing the binding capacity of target proteins, particularly when multiple components are involved, presents a significant challenge for sensors. As far as we know, there is currently no sensor that can accomplish high-throughput quantitative analysis of natural product-target protein binding capacity based on Raman spectroscopy. In this study, a novel sensor model has been developed for the quantitative analysis of binding capacity based on Surface-Enhanced Raman Spectroscopy (SERS) and Photocrosslinked Molecular Probe (PCMP) technology. This sensor, named SERS-PCMP, leverages the high throughput of molecular probe technology to investigate the active ingredients in natural products, along with the application of SERS labelling technology for target proteins. Thus it significantly improves the efficiency and accuracy of target protein identification. Based on the novel strategy, quantitative analysis of the binding capacity of 20 components from Shenqi Jiangtang Granules (SJG) to α-Glucosidase were completed. Ultimately, the binding capacity of these active ingredients was ranked based on the detected Raman Intensity. The compounds with higher binding capacity were Astragaloside IV (Intensity, 138.17), Ginsenoside Rh2 (Intensity, 87.46), Ginsenoside Rg3 (Intensity, 73.92) and Ginsenoside Rh1 (Intensity, 64.37), which all exceeded the binding capacity of the positive drug Acarbose (Intensity, 28.75). Furthermore, this strategy also performed a high detection sensitivity. The limit of detection for the enzyme using 0.1 mg of molecular probe magnetic nanoparticles (MP MNPs) was determined to be no less than 0.375 µg/mL. SERS-PCMP sensor integrating SERS labeling and photocrosslinked molecular probes which offers a fresh perspective for future drug discovery studies. Such as high-throughput drug screening and the exploration of small molecule-target protein interactions in vitro.

Updating and profiling the natural product-likeness of Latin American compound libraries.

Compound databases of natural products play a crucial role in drug discovery and development projects and have implications in other areas, such as food chemical research, ecology and metabolomics. Recently, we put together the first version of the Latin American Natural Product database (LANaPDB) as a collective effort of researchers from six countries to ensemble a public and representative library of natural products in a geographical region with a large biodiversity. The present work aims to conduct a comparative and extensive profiling of the natural product-likeness of an updated version of LANaPDB and the individual ten compound databases that form part of LANaPDB. The natural product-likeness profile of the Latin American compound databases is contrasted with the profile of other major natural product databases in the public domain and a set of small-molecule drugs approved for clinical use. As part of the extensive characterization, we employed several chemoinformatics metrics of natural product likeness. The results of this study will capture the attention of the global community engaged in natural product databases, not only in Latin America but across the world.

Total syntheses of (-)-macrocalyxoformins A and B and (-)-ludongnin C.

The complex and diverse molecular architectures along with broad biological activities of ent-kauranoids natural products make them an excellent testing ground for the invention of synthetic methods and strategies. Recent efforts notwithstanding, synthetic access to the highly oxidized enmein-type ent-kauranoids still presents considerable challenges to synthetic chemists. Here, we report the enantioselective total syntheses of C-19 oxygenated enmein-type ent-kauranoids, including (-)-macrocalyxoformins A and B and (-)-ludongnin C, along with discussion and study of synthetic strategies. The enabling feature in our synthesis is a devised Ni-catalyzed decarboxylative cyclization/radical-polar crossover/C-acylation cascade that forges a THF ring concomitantly with the ß-keto ester group. Mechanistic studies reveal that the C-acylation process in this cascade reaction is achieved through a carboxylation followed by an in situ esterification. Biological evaluation of these synthetic natural products reveals the indispensable role of the ketone on the D ring in their anti-tumor efficacy.

Uncovering potential CDK9 inhibitors from natural compound databases through docking-based virtual screening and MD simulations.

CONTEXT: Cyclin-dependent kinase 9 (CDK9) plays a significant role in gene regulation and RNA polymerase II transcription under basal and stimulated conditions. The upregulation of transcriptional homeostasis by CDK9 leads to various malignant tumors and therefore acts as a valuable drug target in addressing cancer incidences. Ongoing drug development endeavors targeting CDK9 have yielded numerous clinical candidate molecules currently undergoing investigation as potential CDK9 modulators, though none have yet received Food and Drug Administration (FDA) approval. METHODS: In this study, we employ in silico approaches including the molecular docking and molecular dynamics simulations for the virtual screening over the natural compounds library to identify novel promising selective CDK9 inhibitors. The compounds derived from the initial virtual screening were subsequently employed for molecular dynamics simulations and binding free energy calculations to study the compound's stability under virtual physiological conditions. The first-generation CDK inhibitor Flavopiridol was used as a reference to compare with our novel hit compound as a CDK9 antagonist. The 500-ns molecular dynamics simulation and binding free energy calculation showed that two natural compounds showed better binding affinity and interaction mode with CDK9 receptors over the reference Flavopiridol. They also showed reasonable figures in the predicted absorption, distribution, metabolism, excretion, and toxicity (ADMET) calculations as well as in computational cytotoxicity predictions. Therefore, we anticipate that the proposed scaffolds could contribute to developing potential and selective CDK9 inhibitors subjected to further validations.

Occurrence of "Natural Selection" in Successful Small Molecule Drug Discovery.

Published compounds from ChEMBL version 32 are used to seek evidence for the occurrence of "natural selection" in drug discovery. Three measures of natural product (NP) character were applied, to compare time- and target-matched compounds reaching the clinic (clinical compounds in phase 1-3 development and approved drugs) with background compounds (reference compounds). Pseudo-NPs (PNPs), containing NP fragments combined in ways inaccessible by nature, are increasing over time, reaching 67% of clinical compounds first disclosed since 2010. PNPs are 54% more likely to be found in post-2008 clinical versus reference compounds. The majority of target classes show increased clinical compound NP character versus their reference compounds. Only 176 NP fragments appear in >1000 clinical compounds published since 2008, yet these make up on average 63% of the clinical compound's core scaffolds. There is untapped potential awaiting exploitation, by applying nature's building blocks─"natural intelligence"─to drug design.

Persistent and Bioaccumulative Halogenated Natural Products in Various Tropical Reef Fish Species from the Seychelles, Western Indian Ocean.

Gas chromatography with electron capture negative ion mass spectrometry (GC/ECNI-MS) was used to quantify and compare halogenated natural products (HNPs) and selected anthropogenic persistent organic pollutants (POPs) in individual samples of 17 fish species from the Seychelles (Western Indian Ocean). The sum-HNP amounts (9.5-1100 ng/g lipid mass (lm)) were between 1 and 2 orders of magnitude higher than those of the sum of seven abundant polychlorinated biphenyl (PCB) congeners (0.2-15 ng/g lm) and dichlorodiphenyltrichloroethane-related compounds (DDTs) (<1.1-43 ng/g lm). Within the group of HNPs, the two tetrabrominated phenoxyanisoles (aka methoxylated diphenyl ethers, MeO-BDEs), 2'-MeO-BDE 68 ≫ 6-MeO-BDE 47, were predominant in most cases. Pearson correlation analysis showed that MeO-BDE levels were positively correlated with less abundant HNPs (2,2'-diMeO-BB 80, 2',6-diMeO-BDE 68, and Br6-DBP) (p < 0.01). Accordingly, HNPs, rather than PCBs and DDTs, were the predominant polyhalogenated contaminants in the current species.