Geschmack ist vorhersagbar: Mit FlavorMiner. FlavorMiner heißt das Tool, das IPB-Chemiker und Partner aus Kolumbien jüngst entwickelt haben. Das Programm kann, basierend auf maschinellem Lernen (KI), anhand der…
Seit Februar 2021 bietet Wolfgang Brandt, ehemaliger Leiter der Arbeitsgruppe Computerchemie am IPB, sein Citizen Science-Projekt zur Pilzbestimmung an. Dafür hat er in regelmäßigen Abständen öffentliche Vorträge zur Vielfalt…
A bottleneck in the development of new anti-cancer drugs is the recognition of their mode of action (MoA). We combined metabolomics and machine learning to predict MoAs of novel anti-proliferative drug candidates, focusing on human prostate cancer cells (PC-3). As proof of concept, we studied 38 drugs with known effects on 16 key processes of cancer metabolism, profiling low molecular weight intermediates of the central carbon and cellular energy metabolism (CCEM) by LC-MS/MS. These metabolic patterns unveiled distinct MoAs, enabling accurate MoA predictions for novel agents by machine learning. We validate the transferability of MoA predictions from PC-3 to two other cancer cell models and show that correct predictions are still possible, but at the expense of prediction quality. Furthermore, metabolic profiles of treated cells yield insights into intracellular processes, exemplified for drugs inducing different types of mitochondrial dysfunction. Specifically, we predict that pentacyclic triterpenes inhibit oxidative phosphorylation and affect phospholipid biosynthesis, as supported by respiration parameters, lipidomics, and molecular docking. Using biochemical insights from individual drug treatments, our approach offers new opportunities, including the optimization of combinatorial drug applications.
Publikation
Saoud, M.; Grau, J.; Rennert, R.; Mueller, T.; Yousefi, M.; Davari, M. D.; Hause, B.; Csuk, R.; Rashan, L.; Grosse, I.; Tissier, A.; Wessjohann, L. A.; Balcke, G. U.;Advancing anticancer drug discovery: leveraging metabolomics and machine learning for mode of action prediction by pattern recognitionAdvanced Science112404085(2024)DOI: 10.1002/advs.202404085
A bottleneck in the development of new anti‐cancer drugs is the recognition of their mode of action (MoA). Metabolomics combined with machine learning allowed to predict MoAs of novel anti‐proliferative drug candidates, focusing on human prostate cancer cells (PC‐3). As proof of concept, 38 drugs are studied with known effects on 16 key processes of cancer metabolism, profiling low molecular weight intermediates of the central carbon and cellular energy metabolism (CCEM) by LC‐MS/MS. These metabolic patterns unveiled distinct MoAs, enabling accurate MoA predictions for novel agents by machine learning. The transferability of MoA predictions based on PC‐3 cell treatments is validated with two other cancer cell models, i.e., breast cancer and Ewing\'s sarcoma, and show that correct MoA predictions for alternative cancer cells are possible, but still at some expense of prediction quality. Furthermore, metabolic profiles of treated cells yield insights into intracellular processes, exemplified for drugs inducing different types of mitochondrial dysfunction. Specifically, it is predicted that pentacyclic triterpenes inhibit oxidative phosphorylation and affect phospholipid biosynthesis, as confirmed by respiration parameters, lipidomics, and molecular docking. Using biochemical insights from individual drug treatments, this approach offers new opportunities, including the optimization of combinatorial drug applications.
Publikation
Hussain, H.; Xiao, J.; Ali, A.; Green, I. R.; Westermann, B.;Unusually cyclized triterpenoids: occurrence, biosynthesis and chemical synthesisNat. Prod. Rep.40412-451(2023)DOI: 10.1039/d2np00033d
Covering: 2009 to 2021Biosynthetically, most of the syntheses of triterpenes follow the cascade cyclization and rearrangement of the acyclic precursors viz., squalene (S) and 2,3-oxidosqualene (OS), which lead to the very well known tetra- and pentacyclic triterpene skeletons. Aside from these, numerous other triterpenoid molecules are also reported from various natural sources and their structures are derived from \"S\" and \"OS\" via some unusual cyclization operations which are different from the usual tetra- and pentacyclic frameworks. Numerous compelling advances have been made and reported in the identification of these unusual cyclized mono-, di-, tri- and tetracyclic triterpenes between 2009 and 2021. Besides a dramatic increase in the newly isolated uncommon cyclized triterpenoids, substantial progress in the (bio)-synthesis of these triterpenes has been published along with significant progress in their biological effects. In this review, 180 new unusual cyclized triterpenoids together with their demonstrated biogenetic pathways, syntheses and biological effects will be categorized and discussed.
Publikation
Hussain, H.; Rashan, L.; Hassan, U.; Abbas, M.; Hakkim, F. L.; Green, I. R.;Frankincense diterpenes as a bio-source for drug discoveryExpert Opinion on Drug Discovery17513-529(2022)DOI: 10.1080/17460441.2022.2044782
Introduction
Frankincense (Boswellia sp.) gum resins have been employed as an incense in cultural and religious ceremonies for many years. Frankincense resin has over the years been employed to treat depression, inflammation, and cancer in traditional medicines.
Areas coveredThis inclusive review focuses on the significance of frankincense diterpenoids, and in particular, incensole derivatives for establishment future treatments of depression, neurological disorders, and cancer. The authors survey the available literature and furnish an overview of future perspectives of these intriguing molecules.
Expert opinion
Numerous diterpenoids including cembrane, prenylaromadendrane, and the verticillane-type have been isolated from various Boswellia resins. Cembrane-type diterpenoids occupy a crucial position in pharmaceutical chemistry and related industries because of their intriguing biological and encouraging pharmacological potentials. Several cembranes have been reported to possess anti-Alzheimer, anti-inflammatory, hepatoprotective, and antimalarial effects along with a good possibility to treat anxiety and depression. Although some slight drawbacks of these compounds have been noted, including the selectivity of these diterpenoids, there is a great need to address these in future research endeavors. Moreover, it is vitally important for medicinal chemists to prepare libraries of incensole-heterocyclic analogs as well as hybrid compounds between incensole or its acetate and anti-depressant or anti-inflammatory drugs.