@article{MTMT:34147665, title = {Medicinal-Chemistry-Driven Approach to 2-Substituted Benzoxazole–Estradiol Chimeras: Synthesis, Anticancer Activity, and Early ADME Profile}, url = {https://m2.mtmt.hu/api/publication/34147665}, author = {Kovács, Ferenc and Huliák, Ildikó and Árva, Hédi and Csontné Kiricsi, Mónika and Erdős, Dóra and Kocsis, Marianna and Takács, Gergely and Balogh, György Tibor and Nagyné Frank, Éva}, doi = {10.1002/cmdc.202300352}, journal-iso = {CHEMMEDCHEM}, journal = {CHEMMEDCHEM}, volume = {18}, unique-id = {34147665}, issn = {1860-7179}, abstract = {The efficient synthesis of novel estradiol‐based A‐ring‐fused oxazole derivatives, which can be considered as benzoxazole‐steroid domain‐integrated hybrids containing a common benzene structural motif, is described. The target compounds were prepared from steroidal 2‐aminophenol precursors by heterocycle formation or functional group interconversion (FGI) strategies. According to 2D projection‐based t‐distributed stochastic neighbor embedding (t‐SNE), the novel molecules were proved to represent a new chemical space among steroid drugs. They were characterized based on critical physicochemical parameters using in silico and experimental data. The performance of the compounds to inhibit cell proliferation was tested on four human cancer cell lines and non‐cancerous cells. Further examinations were performed to reveal IC50 and lipophilic ligand efficiency (LLE) values, cancer cell selectivity, and apoptosis‐triggering features. Pharmacological tests and LLE metric revealed that some derivatives, especially the 2‐(4‐ethylpiperazin‐1‐yl)oxazole derivative exhibit strong anticancer activity and trigger the apoptosis of cancer cells with relatively low promiscuity risk similarly to the structurally most closely‐related and intensively studied anticancer agent, 2‐methoxy‐estradiol.}, year = {2023}, eissn = {1860-7187}, orcid-numbers = {Csontné Kiricsi, Mónika/0000-0002-8416-2052; Balogh, György Tibor/0000-0003-3347-1880; Nagyné Frank, Éva/0000-0002-1332-0551} } @article{MTMT:34119941, title = {DIY Virtual Chemical Libraries - Novel Starting Points for Drug Discovery}, url = {https://m2.mtmt.hu/api/publication/34119941}, author = {Takács, Gergely and Havasi, Dávid and Sándor, Márk and Dohánics, Zsolt and Balogh, György Tibor and Kiss, Róbert}, doi = {10.1021/acsmedchemlett.3c00146}, journal-iso = {ACS MED CHEM LETT}, journal = {ACS MEDICINAL CHEMISTRY LETTERS}, volume = {14}, unique-id = {34119941}, issn = {1948-5875}, year = {2023}, pages = {1188-1197}, orcid-numbers = {Havasi, Dávid/0000-0003-3366-4009; Balogh, György Tibor/0000-0003-3347-1880} } @article{MTMT:33692858, title = {Natural Lipid Extracts as an Artificial Membrane for Drug Permeability Assay: In Vitro and In Silico Characterization}, url = {https://m2.mtmt.hu/api/publication/33692858}, author = {Vincze, Anna and Dékány, Gergely and Bicsak, Richárd and Formanek, András and Moreau, Yves and Koplányi, Gábor and Takács, Gergely and Katona, Gábor and Balogh Weiser, Diána and Arany, Ádám and Balogh, György Tibor}, doi = {10.3390/pharmaceutics15030899}, journal-iso = {PHARMACEUTICS}, journal = {PHARMACEUTICS}, volume = {15}, unique-id = {33692858}, abstract = {In vitro non-cellular permeability models such as the parallel artificial membrane permeability assay (PAMPA) are widely applied tools for early-phase drug candidate screening. In addition to the commonly used porcine brain polar lipid extract for modeling the blood–brain barrier’s permeability, the total and polar fractions of bovine heart and liver lipid extracts were investigated in the PAMPA model by measuring the permeability of 32 diverse drugs. The zeta potential of the lipid extracts and the net charge of their glycerophospholipid components were also determined. Physicochemical parameters of the 32 compounds were calculated using three independent forms of software (Marvin Sketch, RDKit, and ACD/Percepta). The relationship between the lipid-specific permeabilities and the physicochemical descriptors of the compounds was investigated using linear correlation, Spearman correlation, and PCA analysis. While the results showed only subtle differences between total and polar lipids, permeability through liver lipids highly differed from that of the heart or brain lipid-based models. Correlations between the in silico descriptors (e.g., number of amide bonds, heteroatoms, and aromatic heterocycles, accessible surface area, and H-bond acceptor–donor balance) of drug molecules and permeability values were also found, which provides support for understanding tissue-specific permeability.}, year = {2023}, eissn = {1999-4923}, orcid-numbers = {Vincze, Anna/0000-0002-9756-574X; Formanek, András/0000-0003-0734-1417; Koplányi, Gábor/0000-0002-3791-1057; Katona, Gábor/0000-0003-1564-4813; Balogh Weiser, Diána/0000-0002-9957-1203; Balogh, György Tibor/0000-0003-3347-1880} } @article{MTMT:33645504, title = {CoPriNet: graph neural networks provide accurate and rapid compound price prediction for molecule prioritisation}, url = {https://m2.mtmt.hu/api/publication/33645504}, author = {Sanchez-Garcia, Ruben and Havasi, Dávid and Takács, Gergely and Robinson, Matthew C. and Lee, Alpha and von Delft, Frank and Deane, Charlotte M.}, doi = {10.1039/D2DD00071G}, journal-iso = {Digital Discovery}, journal = {Digital Discovery}, volume = {2}, unique-id = {33645504}, abstract = {CoPriNet can predict compound prices after being trained on 6M pairs of compounds and prices collected from the Mcule catalogue.}, year = {2023}, eissn = {2635-098X}, pages = {103-111}, orcid-numbers = {Sanchez-Garcia, Ruben/0000-0001-6156-3542; Havasi, Dávid/0000-0003-3366-4009; Takács, Gergely/0000-0002-8090-0732; Lee, Alpha/0000-0002-9616-3108; von Delft, Frank/0000-0003-0378-0017; Deane, Charlotte M./0000-0003-1388-2252} } @{MTMT:33282190, title = {Scavengome of an antioxidant}, url = {https://m2.mtmt.hu/api/publication/33282190}, author = {Hunyadi, Attila and Agbadua, Orinamhe Godwin and Takács, Gergely and Balogh, György Tibor}, booktitle = {Antioxidants}, doi = {10.1016/bs.vh.2022.09.003}, unique-id = {33282190}, year = {2023}, pages = {81-108}, orcid-numbers = {Hunyadi, Attila/0000-0003-0074-3472; Balogh, György Tibor/0000-0003-3347-1880} } @misc{MTMT:32740866, title = {CoPriNet: Deep learning compound price prediction for use in de novo molecule generation and prioritization.}, url = {https://m2.mtmt.hu/api/publication/32740866}, author = {Sanchez-Garcia, Ruben and Havasi, Dávid and Takács, Gergely and Robinson, Matthew C and Lee, Alpha and von Delft, Frank and Deane, Charlotte M}, unique-id = {32740866}, year = {2022}, orcid-numbers = {Havasi, Dávid/0000-0003-3366-4009} } @article{MTMT:32470850, title = {Analysis of the uncharted, druglike property space by self-organizing maps}, url = {https://m2.mtmt.hu/api/publication/32470850}, author = {Takács, Gergely and Sándor, Márk and Szalai, Zoltán and Kiss, Róbert and Balogh, György Tibor}, doi = {10.1007/s11030-021-10343-y}, journal-iso = {MOL DIVERS}, journal = {MOLECULAR DIVERSITY}, volume = {26}, unique-id = {32470850}, issn = {1381-1991}, year = {2022}, eissn = {1573-501X}, pages = {2427-2441}, orcid-numbers = {Balogh, György Tibor/0000-0003-3347-1880} }