Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 6 de 6
Filter
Add more filters










Database
Language
Publication year range
1.
Int J Mol Sci ; 22(2)2021 Jan 08.
Article in English | MEDLINE | ID: mdl-33429999

ABSTRACT

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.


Subject(s)
Acinetobacter baumannii/drug effects , Bacterial Infections/drug therapy , Imidazoles/chemistry , Pyridines/chemistry , Acinetobacter baumannii/pathogenicity , Bacterial Infections/microbiology , Drug Resistance, Multiple , Humans , Imidazoles/chemical synthesis , Ionic Liquids/chemical synthesis , Ionic Liquids/chemistry , Pyridines/chemical synthesis , Staphylococcus aureus/drug effects , Staphylococcus aureus/pathogenicity , Structure-Activity Relationship
2.
Curr Drug Discov Technol ; 16(2): 204-209, 2019.
Article in English | MEDLINE | ID: mdl-29669499

ABSTRACT

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.


Subject(s)
Antifungal Agents/chemistry , Antifungal Agents/pharmacology , Candida albicans/drug effects , Organophosphorus Compounds/chemistry , Organophosphorus Compounds/pharmacology , Oxazoles/chemistry , Oxazoles/pharmacology , Acetylcholinesterase/metabolism , Antifungal Agents/toxicity , Candida albicans/growth & development , Organophosphorus Compounds/toxicity , Oxazoles/toxicity , Quantitative Structure-Activity Relationship
3.
Comput Biol Chem ; 73: 127-138, 2018 Apr.
Article in English | MEDLINE | ID: mdl-29494924

ABSTRACT

This paper describes Quantitative Structure-Activity Relationships (QSAR) studies, molecular docking and in vitro antibacterial activity of several potent imidazolium-based ionic liquids (ILs) against S. aureus ATCC 25923 and its clinical isolate. Small set of 131 ILs was collected from the literature and uploaded in the OCHEM database. QSAR methodologies used Associative Neural Networks and Random Forests (WEKA-RF) methods. The predictive ability of the models was tested through cross-validation, giving cross-validated coefficients q2 = 0.82-0.87 for regression models and overall prediction accuracies of 80-82.1% for classification models. The proposed QSAR models are freely available online on OCHEM server at https://ochem.eu/article/107364 and can be used for estimation of antibacterial activity of new imidazolium-based ILs. A series of synthesized 1,3-dialkylimidazolium ILs with predicted activity were evaluated in vitro. The high activity of 7 ILs against S. aureus strain and its clinical isolate was measured and thereafter analyzed by the molecular docking to prokaryotic homologue of a eukaryotic tubulin FtsZ.


Subject(s)
Anti-Infective Agents, Local/pharmacology , Disinfectants/pharmacology , Imidazoles/pharmacology , Ionic Liquids/pharmacology , Machine Learning , Methicillin-Resistant Staphylococcus aureus/drug effects , Anti-Infective Agents, Local/chemistry , Disinfectants/chemistry , Imidazoles/chemistry , Ionic Liquids/chemistry , Neural Networks, Computer , Quantitative Structure-Activity Relationship
4.
Environ Toxicol Chem ; 36(9): 2543-2551, 2017 09.
Article in English | MEDLINE | ID: mdl-28262978

ABSTRACT

A new polymeric biocide polyhexamethylene guanidine (PHMG) molybdate has been synthesized. The obtained cationic polymer has limited water solubility of 0.015 g/100 mL and is insoluble in paint solvents. The results of acute toxicity studies indicate moderate toxicity of PHMG molybdate, which has a median lethal dose at 48 h of 0.7 mg/L for Daphnia magna and at 96 h of 17 mg/L for Danio rerio (zebrafish) freshwater model organisms. Commercial ship paint was then modified by the addition of a low concentration of polymeric biocide 5% (w/w). The painted steel panels were kept in Dnipro River water for the evaluation of the dynamics of fouling biomass. After 129-d exposure, Bryozoa dominated in biofouling of tested substrates, forming 86% (649 g/m2 ) of the total biomass on control panel surfaces. However, considerably lower Bryozoa fouling biomass (15 g/m2 ) was detected for coatings containing PHMG molybdate. Dreissenidae mollusks were found to form 88% (2182 g/m2 ) of the fouling biomass on the control substrates after 228 d of exposure, whereas coatings containing PHMG molybdate showed a much lower biomass value of 23.6 g/m2 . The leaching rate of PHMG molybdate in water was found to be similar to rates for conventional booster biocides ranging from 5.7 µg/cm2 /d at the initial stage to 2.2 µg/cm2 /d at steady state. Environ Toxicol Chem 2017;36:2543-2551. © 2017 SETAC.


Subject(s)
Biofouling , Disinfectants/chemical synthesis , Guanidines/chemical synthesis , Polyamines/chemical synthesis , Aquatic Organisms , Disinfectants/toxicity , Guanidines/toxicity , Paint , Polyamines/toxicity , Ships , Solubility , Steel
5.
Curr Drug Discov Technol ; 13(2): 109-19, 2016.
Article in English | MEDLINE | ID: mdl-27160290

ABSTRACT

Quantitative structure-activity relationships (QSAR) of imidazolium ionic liquids (ILs) as inhibitors of C. albicans collection strains (IOA-109, KCTC 1940, ATCC 10231) have been studied. Predictive QSAR models were built using different descriptor sets for a set of 88 ionic liquids with known minimum inhibitory concentrations (MIC) against C. albicans. We applied the state-of-the-art QSAR methodologies such as WEKA Random Forest (RF) as a binary classifier, Associative Neural Networks (ASNN) and k-Nearest Neighbors (k-NN) to build continuum non-linear regression models. The obtained models were validated using a 5-fold cross-validation approach and resulted in the prediction accuracies of 80% ± 5.0 for the classification models and q2 = 0.73-0.87 for the non-linear regression models. Biological testing of newly synthesized 1,3-dialkylimidazolium ionic liquids with predicted activity was performed by disco-diffusion method against C. albicans ATCC 10231 M885 strain and clinical isolates C. albicans, C. krusei and C. glabrata strains. The high percentage of coincidence between the QSAR predictions and the experimental results confirmed the high predictive power of the developed QSAR models within the applicability domain of new imidazolium ionic liquids.


Subject(s)
Antifungal Agents/pharmacology , Candida albicans/drug effects , Imidazoles/pharmacology , Ionic Liquids/pharmacology , Models, Molecular , Antifungal Agents/chemistry , Candida albicans/growth & development , Imidazoles/chemistry , Ionic Liquids/chemistry , Machine Learning , Neural Networks, Computer , Quantitative Structure-Activity Relationship , Regression Analysis , Reproducibility of Results
6.
Chem Biol Drug Des ; 88(3): 422-33, 2016 Sep.
Article in English | MEDLINE | ID: mdl-27086199

ABSTRACT

Predictive QSAR models for the inhibitors of B. subtilis and Ps. aeruginosa among imidazolium-based ionic liquids were developed using literary data. The regression QSAR models were created through Artificial Neural Network and k-nearest neighbor procedures. The classification QSAR models were constructed using WEKA-RF (random forest) method. The predictive ability of the models was tested by fivefold cross-validation; giving q(2) = 0.77-0.92 for regression models and accuracy 83-88% for classification models. Twenty synthesized samples of 1,3-dialkylimidazolium ionic liquids with predictive value of activity level of antimicrobial potential were evaluated. For all asymmetric 1,3-dialkylimidazolium ionic liquids, only compounds containing at least one radical with alkyl chain length of 12 carbon atoms showed high antibacterial activity. However, the activity of symmetric 1,3-dialkylimidazolium salts was found to have opposite relationship with the length of aliphatic radical being maximum for compounds based on 1,3-dioctylimidazolium cation. The obtained experimental results suggested that the application of classification QSAR models is more accurate for the prediction of activity of new imidazolium-based ILs as potential antibacterials.


Subject(s)
Anti-Bacterial Agents/pharmacology , Imidazoles/pharmacology , Ionic Liquids , Quantitative Structure-Activity Relationship , Models, Theoretical , Neural Networks, Computer
SELECTION OF CITATIONS
SEARCH DETAIL
...