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Analytical chemistry offers important tools that provide insight and step-by-step understanding. However, natural samples containing many thousands of different compounds are subject to natural variance which makes it complex for artificial intelligence and human understanding. Instead of the prevailing comprehensive separation/detection approach, a prioritization approach is discussed for dereplication that focuses on the most necessary to discover. It is extremely helpful to combine on the same surface two disciplines, i.e. chemistry for separation of mixtures and biology for detection of biological effects, to filter out and prioritize the important compounds that then need to be identified. Complex mixtures are separated in parallel with imaging high-performance thin-layer chromatography, detected non-targeted with planar multiplex bioassays to prioritize compounds and elute the important ones to orthogonal column chromatography−diode array detection−high-resolution mass spectrometry for further characterization. Super-hyphenations reduce thousands of compounds to a manageable number of important active compounds. Its potential lies not only in the prioritization of compounds, but also detection of unknown compounds that were not previously the focus of analysts. An image is worth a thousand words and an effect image even more so. On-surface multiplex bioassays enable the differentiation of opposing signals/effects of compounds in a complex natural sample, which only makes understanding possible. On-surface metabolization enables the study of any changes in the effects through digestion or de-/toxification (S9 liver system). By these new tools applied on the same surface, the mechanisms of action of complex mixtures can be better understood. The latest open-source 2LabsToGo system combines the chemistry and biology laboratory in a miniaturized system developed for wider use of this innovative technique. [ABSTRACT FROM AUTHOR]

Although combinatorial biosynthesis can dramatically expand the chemical structures of bioactive natural products to identify molecules with improved characteristics, progress in this direction has been hampered by the difficulty in isolating and characterizing the numerous produced compounds. This challenge could be overcome with improved designs that enable the analysis of the bioactivity of the produced metabolites ahead of the time‐consuming isolation procedures. Herein, we showcase a structure‐agnostic bioactivity‐driven combinatorial biosynthesis workflow that introduces bioactivity assessment as a selection‐driving force to guide iterative combinatorial biosynthesis rounds towards enzyme combinations with increasing bioactivity. We apply this approach to produce triterpenoids with potent bioactivity against PTP1B, a promising molecular target for diabetes and cancer treatment. We demonstrate that the bioactivity‐guided workflow can expedite the combinatorial process by enabling the narrowing down of more than 1000 possible combinations to only five highly potent candidates. By focusing the isolation and structural elucidation effort on only these five strains, we reveal 20 structurally diverse triterpenoids, including four new compounds and a novel triterpenoid‐anthranilic acid hybrid, as potent PTP1B inhibitors. This workflow expedites hit identification by combinatorial biosynthesis and is applicable to many other types of bioactive natural products, therefore providing a strategy for accelerated drug discovery. [ABSTRACT FROM AUTHOR]

The total synthesis of two new marine natural products, (±)-marinoaziridine B 7 and (±)-N-methyl marinoaziridine A 8, was accomplished. The (±)-marinoaziridine 7 was prepared in a six-step linear sequence with a 2% overall yield. The key steps in our strategy were the preparation of the chiral epoxide (±)-5 using the Johnson Corey Chaykovsky reaction, followed by the ring-opening reaction and the Staudinger reaction. The N,N-dimethylation of compound (±)-7 gives (±)-N-methyl marinoaziridine A 8. The NMR spectra of synthetized (±)-marinoaziridine B 7 and isolated natural product did not match. The compounds are biologically characterized using relevant in silico, in vitro and in vivo methods. In silico ADMET and bioactivity profiling predicted toxic and neuromodulatory effects. In vitro screening by MTT assay on three cell lines (MCF-7, H-460, HEK293T) showed that both compounds exhibited moderate to strong antiproliferative and cytotoxic effects. Antimicrobial tests on bacterial cultures of Escherichia coli and Staphylococcus aureus demonstrated the dose-dependent inhibition of the growth of both bacteria. In vivo toxicological tests were performed on zebrafish Danio rerio and showed a significant reduction of zebrafish mortality due to N-methylation in (±)-8. [ABSTRACT FROM AUTHOR]

The total synthesis of two new marine natural products, (±)-marinoaziridine B 7 and (±)-N-methyl marinoaziridine A 8, was accomplished. The (±)-marinoaziridine 7 was prepared in a six-step linear sequence with a 2% overall yield. The key steps in our strategy were the preparation of the chiral epoxide (±)-5 using the Johnson Corey Chaykovsky reaction, followed by the ring-opening reaction and the Staudinger reaction. The N,N-dimethylation of compound (±)-7 gives (±)-N-methyl marinoaziridine A 8. The NMR spectra of synthetized (±)-marinoaziridine B 7 and isolated natural product did not match. The compounds are biologically characterized using relevant in silico, in vitro and in vivo methods. In silico ADMET and bioactivity profiling predicted toxic and neuromodulatory effects. In vitro screening by MTT assay on three cell lines (MCF-7, H-460, HEK293T) showed that both compounds exhibited moderate to strong antiproliferative and cytotoxic effects. Antimicrobial tests on bacterial cultures of Escherichia coli and Staphylococcus aureus demonstrated the dose-dependent inhibition of the growth of both bacteria. In vivo toxicological tests were performed on zebrafish Danio rerio and showed a significant reduction of zebrafish mortality due to N-methylation in (±)-8.

PLATO (Polypharmacology pLATform predictiOn) is an easy-to-use drug discovery web platform, which has been designed with a two-fold objective: to fish putative protein drug targets and to compute bioactivity values of small molecules. Predictions are based on the similarity principle, through a reverse ligand-based screening, based on a collection of 632,119 compounds known to be experimentally active on 6004 protein targets. An efficient backend implementation allows to speed-up the process that returns results for query in less than 20 s. The graphical user interface is intuitive to give practitioners easy input and transparent output, which is available as a standard report in portable document format. PLATO has been validated on thousands of external data, with performances better than those of other parallel approaches. PLATO is available free of charge (http://plato.uniba.it/ accessed on 13 April 2022). [ABSTRACT FROM AUTHOR]

• A chemical profiling method was developed for six baobab (Adansonia digitata) fruit pulp extracts. • The obtained high-performance thin-layer chromatography profiles differed only slightly. • Effect-directed screening was done via enzyme inhibition assays and antibacterial bioassays. • A multiple bioactive compound zone was detected in all six baobab extracts. • HRMS recording tentatively assigned the bioactive compound zone to coeluting fatty acids. Baobab (Adansonia digitata) fruit pulp has a high nutrient content and has been traditionally used for medicinal purposes (e.g. , as an anti-inflammatory and antioxidant agent) that may help protect against chronic diseases. Six different baobab fruit pulp powders were investigated using three different extractants and analyzed by high-performance thin-layer chromatography (HPTLC) hyphenated with antibacterial bioassays and enzyme inhibition assays. The developed non-target effect-directed screening was performed after extraction with pentyl acetate – ethanol 1:1 (V / V) on the HPTLC plate silica gel 60 using toluene – ethyl acetate – methanol 6:3:1 (V / V / V) as mobile phase system and derivatization via the anisaldehyde sulfuric acid reagent for detection. The physico-chemical profiles of the six baobab fruit pulp powder extracts were comparable, although the intensity of some zones was moderately different. The following effect-directed profiling via tyrosinase, α-glucosidase, and acetylcholinesterase inhibition assays as well as antibacterial Aliivibrio fischeri and Bacillus subtilis bioassays revealed one prominent multipotent bioactive compound zone in common, more or less active in all five studied (bio)assays. Via the recording of high-resolution mass spectra, this compound zone was tentatively assigned to coeluting saturated (palmitic acid 16:0 and stearic acid 18:0), monounsaturated (oleic acid 18:1), and polyunsaturated (linoleic acid 18:2 and linolenic acid 18:3) fatty acids. This finding was confirmed by other studies, which already proved individual activities of fatty acids. The first (bio)activity profiling of baobab fruit pulp powders via HPTLC-effect-directed analysis revealed that the baobab fruit could be considered as a functional food, however, further research is needed to study the impact on health and the influences on the bioactivity arising from different climates, years and soils or regions. [ABSTRACT FROM AUTHOR]

The complexity of human biology has made prediction of health effects as a consequence of exposure to environmental chemicals especially challenging. Complex cell systems, such as the Biologically Multiplexed Activity Profiling (BioMAP) primary, human, cell-based disease models, leverage cellular regulatory networks to detect and distinguish chemicals with a broad range of target mechanisms and biological processes relevant to human toxicity. Here the authors use the BioMAP human cell systems to characterize effects relevant to human tissue and inflammatory disease biology following exposure to the 320 environmental chemicals in the Environmental Protection Agency's (EPA's) ToxCast phase I library. The ToxCast chemicals were assayed at 4 concentrations in 8 BioMAP cell systems, with a total of 87 assay endpoints resulting in more than 100,000 data points. Within the context of the BioMAP database, ToxCast compounds could be classified based on their ability to cause overt cytotoxicity in primary human cell types or according to toxicity mechanism class derived from comparisons to activity profiles of BioMAP reference compounds. ToxCast chemicals with similarity to inducers of mitochondrial dysfunction, cAMP elevators, inhibitors of tubulin function, inducers of endoplasmic reticulum stress, or NFκB pathway inhibitors were identified based on this BioMAP analysis. This data set is being combined with additional ToxCast data sets for development of predictive toxicity models at the EPA. [ABSTRACT FROM AUTHOR]

In order to assess bioactivity profiles for small organic molecules we propose to use parallel pharmacophore-based virtual screening. Our aim is to provide a fast, reliable and scalable system that allows for rapid in silico activity profile prediction of virtual molecules. In this proof of principle study, carried out with the new structure-based pharmacophore modelling tool LigandScout and the high-performance database mining platform Catalyst, we present a model work for the application of parallel pharmacophore-based virtual screening on a set of 50 structure-based pharmacophore models built for various viral targets and 100 antiviral compounds. The latter were screened against all pharmacophore models in order to determine if their known biological targets could be correctly predicted via an enrichment of corresponding pharmacophores matching these ligands. The results demonstrate that the desired enrichment, i.e. a successful activity profiling, was achieved for approximately 90% of all input molecules. Additionally, we discuss descriptors for output validation, as well as various aspects influencing the analysis of the obtained activity profiles, and the effect of the searching mode utilized for screening. The results of the study presented here clearly indicate that pharmacophore-based parallel screening comprises a reliable in silico method to predict the potential biological activities of a compound or a compound library by screening it against a series of pharmacophore queries. [ABSTRACT FROM AUTHOR]