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1.
Chem Biol Drug Des ; 95(6): 624-630, 2020 06.
Article En | MEDLINE | ID: mdl-32168424

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.


Acinetobacter baumannii/drug effects , Anti-Bacterial Agents/chemistry , Ionic Liquids/chemistry , Organophosphorus Compounds/chemistry , Animals , Anti-Bacterial Agents/pharmacology , Computer Simulation , Crustacea/drug effects , Databases, Chemical , Drug Evaluation, Preclinical , Drug Resistance, Multiple, Bacterial , Humans , Ionic Liquids/pharmacology , Machine Learning , Microbial Sensitivity Tests , Quantitative Structure-Activity Relationship
2.
Chem Biodivers ; 16(10): e1900391, 2019 Oct.
Article En | MEDLINE | ID: mdl-31479201

A series of novel 2-oxoimidazolidine derivatives were synthesized and their antiviral activities against BK human polyomavirus type 1 (BKPyV) were evaluated in vitro. Bioassays showed that the synthesized compounds 1-{[(4E)-5-(dichloromethylidene)-2-oxoimidazolidin-4-ylidene]sulfamoyl}piperidine-4-carboxylic acid (5) and N-Cyclobutyl-N'-[(4E)-5-(dichloromethylidene)-2-oxoimidazolidin-4-ylidene]sulfuric diamide (4) exhibited moderate activities against BKPyV (EC50 =5.4 and 5.5 µm, respectively) that are comparable to the standard drug Cidofovir. Compound 5 exhibited the same cytotoxicity in HFF cells and selectivity index (SI50 ) as Cidofovir. The selectivity index of compound 4 is three times less than that of Cidofovir due to the higher toxicity of this compound. Hence, these compounds may be taken as lead compound for further development of novel ant-BKPyV agents.


Antiviral Agents/pharmacology , BK Virus/drug effects , Cidofovir/pharmacology , Drug Design , Imidazolidines/pharmacology , Antiviral Agents/chemical synthesis , Antiviral Agents/chemistry , Cell Survival/drug effects , Cells, Cultured , Cidofovir/chemistry , Dose-Response Relationship, Drug , Humans , Imidazolidines/chemical synthesis , Imidazolidines/chemistry , Microbial Sensitivity Tests , Structure-Activity Relationship , Virus Replication/drug effects
3.
Curr Drug Discov Technol ; 14(1): 25-38, 2017.
Article En | MEDLINE | ID: mdl-27829331

BACKGROUND: The increasing rate of appearance of multidrug-resistant strains of Mycobacterium tuberculosis (MDR-TB) is a serious problem at the present time. MDR-TB forms do not respond to the standard treatment with the commonly used drugs and can take some years or more to treat with drugs that are less potent, more toxic and much more expensive. OBJECTIVE: The goal of this work is to identify the novel effective drug candidates active against MDR-TB strains through the use of methods of cheminformatics and computeraided drug design. METHODS: This paper describes Quantitative Structure-Activity Relationships (QSAR) studies using Artificial Neural Networks, synthesis and in vitro antitubercular activity of several potent compounds against H37Rv and resistant Mycobacterium tuberculosis (Mtb) strains. RESULTS: Eight QSAR models were built using various types of descriptors with four publicly available structurally diverse datasets, including recent data from PubChem and ChEMBL. The predictive power of the obtained QSAR models was evaluated with a cross-validation procedure, giving a q2=0.74-0.78 for regression models and overall accuracy 78.9-94.4% for classification models. The external test sets were predicted with accuracies in the range of 84.1-95.0% (for the active/inactive classifications) and q2=0.80- 0.83 for regressions. The 15 synthesized compounds showed inhibitory activity against H37Rv strain whereas the compounds 1-7 were also active against resistant Mtb strain (resistant to isoniazid and rifampicin). CONCLUSION: The results indicated that compounds 1-7 could serve as promising leads for further optimization as novel antibacterial inhibitors, in particular, for the treatment of drug resistance of Mtb forms.


Antitubercular Agents/chemistry , Antitubercular Agents/pharmacology , Mycobacterium tuberculosis/drug effects , Quantitative Structure-Activity Relationship , Models, Molecular , Mycobacterium tuberculosis/growth & development , Neural Networks, Computer , Tuberculosis, Multidrug-Resistant/drug therapy
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