V.P. Kukhar Institute of Bioorganic Chemistry and Petrochemistry, National Academy of Sciences of Ukraine, 02094, Kyiv-94, Murmanska Str,1, Kyiv, Ukraine.
Nizhyn Mykola Gogol State University, 16600, Grafska Str. 2, Nizhyn, Chernihivska Oblast, Ukraine.
Comput Biol Chem. 2021 Feb;90:107407. doi: 10.1016/j.compbiolchem.2020.107407. Epub 2020 Nov 5.
Natural products as well as their derivatives play a significant role in the discovery of new biologically active compounds in the different areas of our life especially in the field of medicine. The synthesis of compounds produced from natural products including cytisine is one approach for the wider use of natural substances in the development of new drugs. QSAR modeling was used to predict and select of biologically active cytisine-containing 1,3-oxazoles. The eleven most promising compounds were identified, synthesized and tested. The activity of the synthesized compounds was evaluated using the disc diffusion method against C. albicans M 885 (ATCC 10,231) strain and clinical fluconazole-resistant Candida krusei strain. Molecular docking of the most active compounds as potential inhibitors of the Candida spp. glutathione reductase was performed using the AutoDock Vina. The built classification models demonstrated good stability, robustness and predictive power. The eleven cytisine-containing 1,3-oxazoles were synthesized and their activity against Candida spp. was evaluated. Compounds 10, 11 as potential inhibitors of the Candida spp. glutathione reductase demonstrated the high activity against C. albicans M 885 (ATCC 10,231) strain and clinical fluconazole-resistant Candida krusei strain. The studied compounds 10, 11 present the interesting scaffold for further investigation as potential inhibitors of the Candida spp. glutathione reductase with the promising antifungal properties. The developed models are publicly available online at http://ochem.eu/article/120720 and could be used by scientists for design of new more effective drugs.
天然产物及其衍生物在发现新的生物活性化合物方面发挥着重要作用,特别是在医学领域。从天然产物中合成化合物,包括 cytisine,是更广泛地利用天然物质开发新药的一种方法。QSAR 建模用于预测和选择具有生物活性的含 cytisine 的 1,3-噁唑。确定了十一种最有前途的化合物,对其进行了合成和测试。使用圆盘扩散法评估合成化合物对 C. albicans M 885(ATCC 10,231)菌株和临床氟康唑耐药念珠菌 krusei 菌株的活性。使用 AutoDock Vina 对最活跃的化合物作为潜在的 Candida spp.谷胱甘肽还原酶抑制剂进行分子对接。所建立的分类模型表现出良好的稳定性、鲁棒性和预测能力。合成了十一种含 cytisine 的 1,3-噁唑,并评估了它们对 Candida spp.的活性。化合物 10、11 作为 Candida spp.谷胱甘肽还原酶的潜在抑制剂,对 C. albicans M 885(ATCC 10,231)菌株和临床氟康唑耐药 Candida krusei 菌株表现出高活性。研究的化合物 10、11 作为 Candida spp.谷胱甘肽还原酶的潜在抑制剂,具有有前途的抗真菌特性,呈现出有趣的骨架,可进一步研究。开发的模型可在 http://ochem.eu/article/120720 上公开获取,可供科学家用于设计新的更有效的药物。