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1.
Int J Mol Sci ; 22(2)2021 Jan 08.
Artículo en Inglés | MEDLINE | ID: mdl-33429999

RESUMEN

Online Chemical Modeling Environment (OCHEM) was used for QSAR analysis of a set of ionic liquids (ILs) tested against multi-drug resistant (MDR) clinical isolate Acinetobacter baumannii and Staphylococcus aureus strains. The predictive accuracy of regression models has coefficient of determination q2 = 0.66 - 0.79 with cross-validation and independent test sets. The models were used to screen a virtual chemical library of ILs, which was designed with targeted activity against MDR Acinetobacter baumannii and Staphylococcus aureus strains. Seven most promising ILs were selected, synthesized, and tested. Three ILs showed high activity against both these MDR clinical isolates.


Asunto(s)
Acinetobacter baumannii/efectos de los fármacos , Infecciones Bacterianas/tratamiento farmacológico , Imidazoles/química , Piridinas/química , Acinetobacter baumannii/patogenicidad , Infecciones Bacterianas/microbiología , Resistencia a Múltiples Medicamentos , Humanos , Imidazoles/síntesis química , Líquidos Iónicos/síntesis química , Líquidos Iónicos/química , Piridinas/síntesis química , Staphylococcus aureus/efectos de los fármacos , Staphylococcus aureus/patogenicidad , Relación Estructura-Actividad
2.
Comput Biol Chem ; 90: 107407, 2021 Feb.
Artículo en Inglés | MEDLINE | ID: mdl-33191110

RESUMEN

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.


Asunto(s)
Alcaloides/farmacología , Antifúngicos/farmacología , Candida/efectos de los fármacos , Glutatión Reductasa/antagonistas & inhibidores , Simulación del Acoplamiento Molecular , Oxazoles/farmacología , Alcaloides/síntesis química , Alcaloides/química , Antifúngicos/síntesis química , Antifúngicos/química , Azocinas/síntesis química , Azocinas/química , Azocinas/farmacología , Candida/enzimología , Glutatión Reductasa/metabolismo , Pruebas de Sensibilidad Microbiana , Estructura Molecular , Oxazoles/síntesis química , Oxazoles/química , Relación Estructura-Actividad Cuantitativa , Quinolizinas/síntesis química , Quinolizinas/química , Quinolizinas/farmacología
3.
Chem Biol Drug Des ; 95(6): 624-630, 2020 06.
Artículo en Inglés | MEDLINE | ID: mdl-32168424

RESUMEN

QSAR analysis of a set of previously synthesized phosphonium ionic liquids (PILs) tested against Gram-negative multidrug-resistant clinical isolate Acinetobacter baumannii was done using the Online Chemical Modeling Environment (OCHEM). To overcome the problem of overfitting due to descriptor selection, fivefold cross-validation with variable selection in each step of the model development was applied. The predictive ability of the classification models was tested by cross-validation, giving balanced accuracies (BA) of 76%-82%. The validation of the models using an external test set proved that the models can be used to predict the activity of newly designed compounds with a reasonable accuracy within the applicability domain (BA = 83%-89%). The models were applied to screen a virtual chemical library with expected activity of compounds against MDR Acinetobacter baumannii. The eighteen most promising compounds were identified, synthesized, and tested. Biological testing of compounds was performed using the disk diffusion method in Mueller-Hinton agar. All tested molecules demonstrated high anti-A. baumannii activity and different toxicity levels. The developed classification SAR models are freely available online at http://ochem.eu/article/113921 and could be used by scientists for design of new more effective antibiotics.


Asunto(s)
Acinetobacter baumannii/efectos de los fármacos , Antibacterianos/química , Líquidos Iónicos/química , Compuestos Organofosforados/química , Animales , Antibacterianos/farmacología , Simulación por Computador , Crustáceos/efectos de los fármacos , Bases de Datos de Compuestos Químicos , Evaluación Preclínica de Medicamentos , Farmacorresistencia Bacteriana Múltiple , Humanos , Líquidos Iónicos/farmacología , Aprendizaje Automático , Pruebas de Sensibilidad Microbiana , Relación Estructura-Actividad Cuantitativa
4.
Curr Drug Discov Technol ; 16(2): 204-209, 2019.
Artículo en Inglés | MEDLINE | ID: mdl-29669499

RESUMEN

BACKGROUND: The incidence of invasive fungal infections caused by Candida spp. has increased continuously in recent decades, especially in populations of immunocompromised patients or individuals hospitalized with serious underlying diseases. Therefore, the goal of our study was the search for new potent Candida albicans inhibitors via the development of QSAR models that could speed up this search process. A number of the most promising 1,3-oxazol-4-yltriphenylphosphonium derivatives with predicted activities were synthesized and experimentally tested. Furthermore, the toxicity of the studied compounds was determined in vitro using acetylcholinesterase enzyme as a biological marker. METHODS: The classification QSAR models were created using Random Forests (WEKA-RF), k-Nearest Neighbors and Associative Neural Networks methods and different combinations of descriptors on the Online Chemical Modeling Environment (OCHEM) platform. Аntifungal properties of the investigated compounds were performed using standard disk diffusion method. The enzyme inhibitory action of the compounds was determined by modified Ellman's method using acetylcholinesterase from the electric organ of Electrophorus electricus. RESULTS: Three classification QSAR models were developed by the WEKA-RF, k-NN and ASNN methods using the ALogPS, E-State indices and Dragon v.7 descriptors. The predictive ability of the models was tested through cross-validation, giving a balanced accuracy BA = 80-91%. All compounds demonstrated good antifungal properties against Candida spp. and slight inhibition of the acetylcholinesterase activity. CONCLUSION: The high percentage of coincidence between the QSAR predictions and the experimental results confirmed the high predictive power of the developed QSAR models that can be applied as tools for finding new potential inhibitors against Candida spp. Furthermore, 1,3-oxazol-4- yl(triphenyl)phosphonium salts could be considered as promising candidates for the treatment of candidiasis and the disinfection of medical equipment.


Asunto(s)
Antifúngicos/química , Antifúngicos/farmacología , Candida albicans/efectos de los fármacos , Compuestos Organofosforados/química , Compuestos Organofosforados/farmacología , Oxazoles/química , Oxazoles/farmacología , Acetilcolinesterasa/metabolismo , Antifúngicos/toxicidad , Candida albicans/crecimiento & desarrollo , Compuestos Organofosforados/toxicidad , Oxazoles/toxicidad , Relación Estructura-Actividad Cuantitativa
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