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…
Results of scientific work in chemistry can usually be obtained in the form of materials and data. A big step towards transparency and reproducibility of the scientific work can be gained if scientists publish their data in research data repositories in a FAIR manner. Nevertheless, in order to make chemistry a sustainable discipline, obtaining FAIR data is insufficient and a comprehensive concept that includes preservation of materials is needed. In order to offer a comprehensive infrastructure to find and access data and materials that were generated in chemistry projects, we combined the infrastructure Chemotion repository with an archive for chemical compounds. Samples play a key role in this concept: we describe how FAIR metadata of a virtual sample representation can be used to refer to a physically available sample in a materials’ archive and to link it with the FAIR research data gained using the said sample. We further describe the measures to make the physically available samples not only FAIR through their metadata but also findable, accessible and reusable.
Preprints
Balcke, G.; 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.;Machine learning-based metabolic pattern recognition predicts mode of action for anti-cancer drug candidatesResearch Square(2024)DOI: 10.21203/rs.3.rs-3494185/v1
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
Hmedat, A.; Morejón, M.; Rivera, D.; Pantelić, N.; Wessjohann, L.; Kaluđerović, G. N.;In vitro anticancer studies of a small library of cyclic lipopeptides against the human cervix adenocarcinoma HeLa cellsJ. Serb. Chem. Soc.89471-484(2024)DOI: 10.2298/jsc240109018h
Various cyclic lipopeptides (CLPs, 23 compounds) were tested for their antitumor potential against human cervix adenocarcinoma HeLa cells. From the fast screening (tested concentrations: 0.01 and 10 μM) compound 10 ((12S,6S,10S,13S)-6-((R)-sec-butyl)-7-(2-(dodecylamino)-2-oxoethyl)-13-isopropyl- 82-nitro-2,5,12,15-tetraoxo-4,7,11,14-tetraaza-1(1,2)-pyrrolidina-8(1,4)-benzenacyclopentadecaphane- 10-carboxamide) was identified as active against HeLa cell line. The MTT 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide and CV (crystal violet) assays revealed at least five times higher cytotoxic potential of 10 (IC50 = 12.3±1.8 μM, MTT; 9.4±1.5 μM; CV) in comparison to control drug natural occurring CLP surfactin (IC50 = 64.9±0.8 μM, MTT; 76.2±1.6 μM; CV). The cell cycle analysis performed by DAPI (4\',6-diamidino- 2-phenylindole) assay indicated the involvement of apoptosis in HeLa cell death upon treatment with 10, which was confirmed by apoptosis assay (annexin V/PI). Furthermore, during this process caspase activation could be detected (ApoStat assay, immunocytochemistry caspase-3 analysis). The flow cytometry analysis did not display induction of autophagy as a possible death mechanism in HeLa cells upon 10 treatment. The current findings could be used to design more effective CLPs based on 10 structure as potential anticancer agents.
Publikation
Klein, J.; Lam, H.; Mak, T. D.; Bittremieux, W.; Perez-Riverol, Y.; Gabriels, R.; Shofstahl, J.; Hecht, H.; Binz, P.-A.; Kawano, S.; Van Den Bossche, T.; Carver, J.; Neely, B. A.; Mendoza, L.; Suomi, T.; Claeys, T.; Payne, T.; Schulte, D.; Sun, Z.; Hoffmann, N.; Zhu, Y.; Neumann, S.; Jones, A. R.; Bandeira, N.; Vizcaíno, J. A.; Deutsch, E. W.;The Proteomics Standards Initiative Standardized Formats for Spectral Libraries and Fragment Ion Peak Annotations: mzSpecLib and mzPAFAnal. Chem.9618491-18501(2024)DOI: 10.1021/acs.analchem.4c04091
Mass spectral libraries are collections of reference spectra, usually associated with specific analytes from which the spectra were generated, that are used for further downstream analysis of new spectra. There are many different formats used for encoding spectral libraries, but none have undergone a standardization process to ensure broad applicability to many applications. As part of the Human Proteome Organization Proteomics Standards Initiative (PSI), we have developed a standardized format for encoding spectral libraries, called mzSpecLib (https://psidev.info/mzSpecLib). It is primarily a data model that flexibly encodes metadata about the library entries using the extensible PSI-MS controlled vocabulary and can be encoded in and converted between different serialization formats. We have also developed a standardized data model and serialization for fragment ion peak annotations, called mzPAF (https://psidev.info/mzPAF). It is defined as a separate standard, since it may be used for other applications besides spectral libraries. The mzSpecLib and mzPAF standards are compatible with existing PSI standards such as ProForma 2.0 and the Universal Spectrum Identifier. The mzSpecLib and mzPAF standards have been primarily defined for peptides in proteomics applications with basic small molecule support. They could be extended in the future to other fields that need to encode spectral libraries for nonpeptidic analytes.