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1.
Chem Biodivers ; : e202400638, 2024 Jun 04.
Article in English | MEDLINE | ID: mdl-38837284

ABSTRACT

QSAR studies on the number of compounds tested as S. aureus inhibitors were performed using an interactive Online Chemical Database and Modeling Environment (OCHEM) web platform. The predictive ability of the developed consensus QSAR model was q2 = 0.79 ± 0.02. The consensus prediction for the external evaluation set afforded high predictive power (q2 = 0.82 ± 0.03). The models were applied to screen a virtual chemical library with anti-S. aureus activity. Six promising new bicyclic trifluoromethylated pyrroles were identified, synthesized and evaluated in vitro against S. aureus, E. coli, and A. baumannii for their antibacterial activity and against C. albicans, C. krusei and C. glabrata for their antifungal activity. The synthesized compounds were characterized by 1H, 19F, and 13C NMR and elemental analysis. The antimicrobial activity assessment indicated that trifluoromethylated pyrroles 9 and 11 demonstrated the greatest antibacterial and antifungal effects against all the tested pathogens, especially against multidrug-resistant strains. The acute toxicity of the compounds to Daphnia magna ranged from 1.21 to 33.39 mg/L (moderately and slightly toxic). Based on the docking results, it can be suggested that the antibacterial and antifungal effects of the compounds can be explained by the inhibition of bacterial wall component synthesis.

2.
Mol Divers ; 2024 Jan 22.
Article in English | MEDLINE | ID: mdl-38246950

ABSTRACT

Long-chain imidazole-based ionic liquids (compounds 2, 4, 9) and lysosomotropic detergents (compounds 7, 3, 8) with potent anticancer activity were synthesized. Their inhibitory activities against neuroblastoma and leukaemia cell lines were predicted by the new in silico QSAR models. The cytotoxic activities of the synthesized imidazole derivatives were investigated on the SK-N-DZ (human neuroblastoma) and K-562 (human chronic myeloid leukaemia) cell lines. Compounds 2 and 7 showed the highest in vitro cytotoxic effect on both cancer cell lines. The docking procedure of compounds 2 and 7 into the NAD+ coenzyme binding site of deacetylase Sirtuin-1 (SIRT-1) showed the formation of protein-ligand complexes with calculated binding energies of - 8.0 and - 8.1 kcal/mol, respectively. The interaction of SIRT1 with compounds 2, 7 and 9 and the interaction of Bromodomain-containing protein 4 (BRD4) with compounds 7 and 9 were also demonstrated by thermal shift assay. Compounds 2, 4, 7 and 9 inhibited SIRT1 deacetylase activity in the SIRT-Glo assay. Compounds 7 and 9 showed a moderate inhibitory activity against Aurora kinase A. In addition, compounds 3, 4, 8 and 9 inhibited the Janus kinase 2 activity. The results obtained showed that long-chain imidazole derivatives exhibited cytotoxic activities on K562 leukaemia and SK-N-DZ neuroblastoma cell lines. Furthermore, these compounds inhibited a panel of molecular targets involved in leukaemia and neuroblastoma tumorigenesis. All these results suggest that both long-chain imidazole-based ionic liquids and lysosomotropic detergents may be an effective alternative for the treatment of neuroblastoma and chronic myeloid leukemia and merit further investigation.

3.
Chem Biodivers ; 20(12): e202301267, 2023 Dec.
Article in English | MEDLINE | ID: mdl-37943002

ABSTRACT

New substituted imidazolidinone sulfonamides have been developed using a rational drug design strategy. Predictive QSAR models for the search of new antibacterials were created using the OCHEM platform. Regression models were applied to verify a virtual chemical library of new imidazolidinone derivatives designed to have antibacterial activity. A number of substituted imidazolidinone sulfonamides as effective antibacterial agents were identified by QSAR prediction, synthesized and characterized by spectral and elemental, and tested in vitro. Six studied compounds have shown the highest in vitro antibacterial activity against Gram-negative E. coli and Gram-positive S. aureus multidrug-resistant strains. The in vivo acute toxicity of these imidazolidinone sulfonamides based on the LC50 value ranged from 16.01 to 44.35 mg/L (slightly toxic compounds class). The results of molecular docking suggest that the antibacterial mechanism of the compounds can be associated with the inhibition of post-translational modification processes of bacterial peptides and proteins.


Subject(s)
Anti-Bacterial Agents , Staphylococcus aureus , Anti-Bacterial Agents/pharmacology , Anti-Bacterial Agents/chemistry , Molecular Docking Simulation , Sulfonamides/pharmacology , Sulfonamides/chemistry , Escherichia coli , Sulfanilamide , Microbial Sensitivity Tests
4.
Chem Biodivers ; 20(9): e202300839, 2023 Sep.
Article in English | MEDLINE | ID: mdl-37552570

ABSTRACT

To develop novel antimicrobial agents a series of 2(4)-hydrazone derivatives of quinoline were designed, synthesized and tested. QSAR models of the antibacterial activity of quinoline derivatives were developed by the OCHEM web platform using different machine learning methods. A virtual set of quinoline derivatives was verified with a previously published classification model of anti-E. coli activity and screened using the regression model of anti-S. aureus activity. Selected and synthesized 2(4)-hydrazone derivatives of quinoline exhibited antibacterial activity against the standard and antibiotic-resistant S. aureus and E. coli strains in the range from 15 to 30 mm by the diameter of growth inhibition zones. Molecular docking showed the complex formation of the studied compounds into the catalytic domain of dihydrofolate reductase with an estimated binding affinity from -8.4 to -9.4 kcal/mol.


Subject(s)
Methicillin-Resistant Staphylococcus aureus , Quinolines , Hydrazones/pharmacology , Molecular Docking Simulation , Anti-Bacterial Agents/pharmacology , Anti-Bacterial Agents/chemistry , Quinolines/pharmacology , Quinolines/chemistry , Microbial Sensitivity Tests , Structure-Activity Relationship
5.
Chem Biodivers ; 20(8): e202300560, 2023 Aug.
Article in English | MEDLINE | ID: mdl-37477067

ABSTRACT

QSAR analysis of previously synthesized and nature-inspired virtual isoflavone-cytisine hybrids against the HEp-2 laryngeal carcinoma cell lines was performed using the OCHEM web platform. 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 such as 8-cytisinylmethyl derivatives of 5,7- and 6,7-dihydroxyisoflavones. The synthetic procedure for selective aminomethylation of 5,7-dihydroxyisoflavones with cytisine was developed. In vitro testing identified compound 7 f with cisplatin-level cytotoxicity against HEp-2 cell lines and compound 10 which was twice active than cisplatin after 72 h of incubation.


Subject(s)
Alkaloids , Antineoplastic Agents , Carcinoma , Isoflavones , Humans , Cisplatin , Antineoplastic Agents/pharmacology , Isoflavones/pharmacology , Mannich Bases , Structure-Activity Relationship , Alkaloids/pharmacology , Cell Line, Tumor
6.
Antibiotics (Basel) ; 11(4)2022 Apr 06.
Article in English | MEDLINE | ID: mdl-35453241

ABSTRACT

A previously developed model to predict antibacterial activity of ionic liquids against a resistant A. baumannii strain was used to assess activity of phosphonium ionic liquids. Their antioxidant potential was additionally evaluated with newly developed models, which were based on public data. The accuracy of the models was rigorously evaluated using cross-validation as well as test set prediction. Six alkyl triphenylphosphonium and alkyl tributylphosphonium bromides with the C8, C10, and C12 alkyl chain length were synthesized and tested in vitro. Experimental studies confirmed their activity against A. baumannii as well as showed pronounced antioxidant properties. These results suggest that phosphonium ionic liquids could be promising lead structures against A. baumannii.

7.
Int J Mol Sci ; 23(2)2022 Jan 10.
Article in English | MEDLINE | ID: mdl-35054915

ABSTRACT

The choice of effective biocides used for routine hospital practice should consider the role of disinfectants in the maintenance and development of local resistome and how they might affect antibiotic resistance gene transfer within the hospital microbial population. Currently, there is little understanding of how different biocides contribute to eDNA release that may contribute to gene transfer and subsequent environmental retention. Here, we investigated how different biocides affect the release of eDNA from mature biofilms of two opportunistic model strains Pseudomonas aeruginosa ATCC 27853 (PA) and Staphylococcus aureus ATCC 25923 (SA) and contribute to the hospital resistome in the form of surface and water contaminants and dust particles. The effect of four groups of biocides, alcohols, hydrogen peroxide, quaternary ammonium compounds, and the polymeric biocide polyhexamethylene guanidine hydrochloride (PHMG-Cl), was evaluated using PA and SA biofilms. Most biocides, except for PHMG-Cl and 70% ethanol, caused substantial eDNA release, and PHMG-Cl was found to block biofilm development when used at concentrations of 0.5% and 0.1%. This might be associated with the formation of DNA-PHMG-Cl complexes as PHMG-Cl is predicted to bind to AT base pairs by molecular docking assays. PHMG-Cl was found to bind high-molecular DNA and plasmid DNA and continued to inactivate DNA on surfaces even after 4 weeks. PHMG-Cl also effectively inactivated biofilm-associated antibiotic resistance gene eDNA released by a pan-drug-resistant Klebsiella strain, which demonstrates the potential of a polymeric biocide as a new surface-active agent to combat the spread of antibiotic resistance in hospital settings.


Subject(s)
Anti-Infective Agents/pharmacology , Biofilms/drug effects , DNA, Bacterial/drug effects , Disinfectants/pharmacology , Guanidines/pharmacology , Anti-Infective Agents/chemical synthesis , Anti-Infective Agents/chemistry , DNA, Bacterial/chemistry , Disinfectants/chemistry , Guanidines/chemical synthesis , Guanidines/chemistry , Nucleic Acid Conformation/drug effects , Pseudomonas aeruginosa/drug effects , Pseudomonas aeruginosa/genetics , Staphylococcus aureus/drug effects , Staphylococcus aureus/genetics , Structure-Activity Relationship
8.
Chem Biol Drug Des ; 100(6): 1025-1032, 2022 12.
Article in English | MEDLINE | ID: mdl-34651417

ABSTRACT

Predictive QSAR models for the search of new adenosine A2A receptor antagonists were developed by using OCHEM platform. The predictive ability of the regression models has coefficient of determination q2  = 0.65-0.71 with cross-validation and independent test set. The inhibition activities of novel fused 7-deazaxanthine compounds were predicted by the developed QSAR models. A preparative method for the synthesis of pyrimido[5',4':4,5]pyrrolo[1,2-a][1,4]diazepine derivatives was developed, and 11 new adenosine A2A receptor antagonists were obtained. Preliminary investigations into the toxicology of fused 7-deazaxanthine compounds toward commonly used model organism to assess toxicity invertebrate cladoceran D. magna were also described.


Subject(s)
Quantitative Structure-Activity Relationship , Receptor, Adenosine A2A , Molecular Docking Simulation , Adenosine , Adenosine A2 Receptor Antagonists/pharmacology
9.
Comput Biol Chem ; 90: 107407, 2021 Feb.
Article in English | MEDLINE | ID: mdl-33191110

ABSTRACT

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.


Subject(s)
Alkaloids/pharmacology , Antifungal Agents/pharmacology , Candida/drug effects , Glutathione Reductase/antagonists & inhibitors , Molecular Docking Simulation , Oxazoles/pharmacology , Alkaloids/chemical synthesis , Alkaloids/chemistry , Antifungal Agents/chemical synthesis , Antifungal Agents/chemistry , Azocines/chemical synthesis , Azocines/chemistry , Azocines/pharmacology , Candida/enzymology , Glutathione Reductase/metabolism , Microbial Sensitivity Tests , Molecular Structure , Oxazoles/chemical synthesis , Oxazoles/chemistry , Quantitative Structure-Activity Relationship , Quinolizines/chemical synthesis , Quinolizines/chemistry , Quinolizines/pharmacology
10.
Chem Biol Drug Des ; 95(6): 624-630, 2020 06.
Article in English | MEDLINE | ID: mdl-32168424

ABSTRACT

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.


Subject(s)
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
11.
Comput Biol Chem ; 85: 107224, 2020 Apr.
Article in English | MEDLINE | ID: mdl-32018168

ABSTRACT

Spread of multidrug-resistant Escherichia coli clinical isolates is a main problem in the treatment of infectious diseases. Therefore, the modern scientific approaches in decision this problem require not only a prevention strategy, but also the development of new effective inhibitory compounds with selective molecular mechanism of action and low toxicity. The goal of this work is to identify more potent molecules active against E. coli strains by using machine learning, docking studies, synthesis and biological evaluation. A set of predictive QSAR models was built with two publicly available structurally diverse data sets, including recent data deposited in PubChem. The predictive ability of these models tested by a 5-fold cross-validation, resulted in balanced accuracies (BA) of 59-98% for the binary classifiers. Test sets validation showed that the models could be instrumental in predicting the antimicrobial activity with an accuracy (with BA = 60-99 %) within the applicability domain. The models were applied to screen a virtual chemical library, which was designed to have activity against resistant E. coli strains. The eight most promising compounds were identified, synthesized and tested. All of them showed the different levels of anti-E. coli activity and acute toxicity. The docking results have shown that all studied compounds are potential DNA gyrase inhibitors through the estimated interactions with amino acid residues and magnesium ion in the enzyme active center The synthesized compounds could be used as an interesting starting point for further development of drugs with low toxicity and selective molecular action mechanism against resistant E. coli strains. The developed QSAR models are freely available online at OCHEM http://ochem.eu/article/112525 and can be used to virtual screening of potential compounds with anti-E. coli activity.


Subject(s)
Anti-Bacterial Agents/pharmacology , DNA Gyrase/metabolism , Drug Design , Escherichia coli/drug effects , Machine Learning , Molecular Docking Simulation , Quinolines/pharmacology , Topoisomerase II Inhibitors/pharmacology , Anti-Bacterial Agents/chemical synthesis , Anti-Bacterial Agents/chemistry , Computational Biology , Escherichia coli/enzymology , Microbial Sensitivity Tests , Molecular Structure , Quantitative Structure-Activity Relationship , Quinolines/chemical synthesis , Quinolines/chemistry , Topoisomerase II Inhibitors/chemical synthesis , Topoisomerase II Inhibitors/chemistry
12.
Curr Drug Discov Technol ; 17(3): 365-375, 2020.
Article in English | MEDLINE | ID: mdl-30973110

ABSTRACT

BACKGROUND: Tuberculosis (TB) is an infection disease caused by Mycobacterium tuberculosis (Mtb) bacteria. One of the main causes of mortality from TB is the problem of Mtb resistance to known drugs. OBJECTIVE: The goal of this work is to identify potent small molecule anti-TB agents by machine learning, synthesis and biological evaluation. METHODS: The On-line Chemical Database and Modeling Environment (OCHEM) was used to build predictive machine learning models. Seven compounds were synthesized and tested in vitro for their antitubercular activity against H37Rv and resistant Mtb strains. RESULTS: A set of predictive models was built with OCHEM based on a set of previously synthesized isoniazid (INH) derivatives containing a thiazole core and tested against Mtb. The predictive ability of the models was tested by a 5-fold cross-validation, and resulted in balanced accuracies (BA) of 61-78% for the binary classifiers. Test set validation showed that the models could be instrumental in predicting anti- TB activity with a reasonable accuracy (with BA = 67-79 %) within the applicability domain. Seven designed compounds were synthesized and demonstrated activity against both the H37Rv and multidrugresistant (MDR) Mtb strains resistant to rifampicin and isoniazid. According to the acute toxicity evaluation in Daphnia magna neonates, six compounds were classified as moderately toxic (LD50 in the range of 10-100 mg/L) and one as practically harmless (LD50 in the range of 100-1000 mg/L). CONCLUSION: The newly identified compounds may represent a starting point for further development of therapies against Mtb. The developed models are available online at OCHEM http://ochem.eu/article/11 1066 and can be used to virtually screen for potential compounds with anti-TB activity.


Subject(s)
Antitubercular Agents/pharmacology , Drug Design , Machine Learning , Mycobacterium tuberculosis/drug effects , Tuberculosis, Multidrug-Resistant/drug therapy , Animals , Antitubercular Agents/chemistry , Antitubercular Agents/therapeutic use , Daphnia , Datasets as Topic , Humans , Isoniazid/pharmacology , Isoniazid/therapeutic use , Microbial Sensitivity Tests , Models, Chemical , Rifampin/pharmacology , Rifampin/therapeutic use , Toxicity Tests, Acute , Tuberculosis, Multidrug-Resistant/microbiology
14.
Heliyon ; 5(4): e01462, 2019 Apr.
Article in English | MEDLINE | ID: mdl-31011642

ABSTRACT

In this study, the synthesis, in vitro anti-Candida activity and molecular modeling of 4-phosphorylated derivatives of 1,3-oxazole as inhibitors of Candida albicans fructose-1,6-bisphosphate aldolase (FBA-II) are demonstrated and discussed. Significant similarity of the primary and secondary structure, binding sites and active sites of FBA-II C. albicans and Mycobacterium tuberculosis are established. FBA-II C. albicans inhibitors contained 1,3-oxazole-4-phosphonates moiety are created by analogy to inhibitors FBA-II M. tuberculosis. The experimental studies of the anti-Candida activity of the designed and synthesized compounds have shown their high activity against standard strain and its C. albicans fluconazole resistant clinical isolate. It was hypothesized that the growth suppression of fluconazole-resistant С. albicans strain may be due to the inhibition of aldolase fructose-1,6-bisphosphate. A qualitative homology 3D model of the C. albicans FBA-II was created using SWISS-MODEL server. The probable mechanism of FBA-II inhibition by studied 4-phosphorylated derivatives was shown using molecular docking. The main role of amino acid residues His110, His226, Gly227, Leu248, Val238, Asp144, Lys230, Glu147, Gly227, Ala112, Leu145 and catalytic zinc atom in the formation of stable ligand-protein complexes with ΔG = -6.89, -7.2, -7.16, -7.5, -8.0, -7.9 kcal/mol was shown. Thus, the positive results obtained in the work were demonstrated the promise of using the proposed homology 3D model of the C. albicans FBA-II as the target for the search and development of new anti-Candida agents against azole-resistant fungal pathogens. Designed and studied 4-phosphorylated derivatives of 1,3-oxazole having a direct inhibiting FBA-II molecular mechanism of action can be used as perspective drug-candidates against resistant C. albicans strains.

15.
Environ Sci Pollut Res Int ; 26(5): 4878-4889, 2019 Feb.
Article in English | MEDLINE | ID: mdl-30569361

ABSTRACT

Ester-functionalized pyridinium ionic liquids (ILs), 1-decyloxycarbonylmethylpyridinium chloride (PyrСOOC10-Cl), and 1-dodecyloxycarbonylmethylpyridinium chloride (PyrСOOC12-Cl) have been synthesized and studied for their environmental toxicity. Simple long-chain pyridinium ILs, 1-dodecylpyridinium chloride (PyrC12-Cl), and commercial disinfectant cetylpyridinium chloride (CPC) were used as reference compounds. Both ester-functionalized ILs and CPC showed significantly reduced antibacterial activity compared to PyrC12-Cl. However, ester-functionalized ILs were found to have excellent antifungal activity towards Candida albicans fungus strains, similar to PyrC12-Cl and much higher than for CPC. The molecular docking of ILs in the active site of the known antifungal target N-myristoyltransferase (Nmt) C. albicans has been conducted. The obtained results indicate the possibility of ILs binding into the Nmt pocket. The high stability of the complexes, especially for PyrCOOC10-Cl, is ensured by hydrogen bonding, electrostatic anion-pi interactions, as well as hydrophobic pi-alkyl and alkyl interactions that was confirmed by calculated binding energy values. The acute toxicity studies of ester-functionalized ILs on D. rerio (zebrafish) hydrobiont have shown their dramatically reduced ecotoxicity compared to PyrC12-Cl and CPC. Thus, LD50 values of 15.2 mg/L and 16.8 mg/L were obtained for PyrCOOC10-Cl and PyrCOOC12-Cl, respectively, whereas CPC had LD50 value of 0.018 mg/L. The primary biodegradation test CEC L-33-A93 of ILs indicated an improved biodegradability of ester-functionalized compounds compared to simple long-chain ILs. Based on the obtained results, PyrCOOC10-Cl may be considered as very promising cationic biocide due to the combination of soft antimicrobial activity and reduced ecotoxicity, as well as improved biodegradability.


Subject(s)
Disinfectants/toxicity , Ionic Liquids/toxicity , Pyridinium Compounds/toxicity , Acyltransferases/metabolism , Animals , Biodegradation, Environmental , Candida albicans/drug effects , Candida albicans/enzymology , Cations , Disinfectants/chemistry , Ecotoxicology , Esters , Hydrophobic and Hydrophilic Interactions , Ionic Liquids/chemistry , Lethal Dose 50 , Molecular Docking Simulation , Pyridinium Compounds/chemistry , Zebrafish/growth & development
16.
Comput Biol Chem ; 74: 294-303, 2018 Jun.
Article in English | MEDLINE | ID: mdl-29698921

ABSTRACT

Based on modern literature data about biological activity of E7010 derivatives, a series of new sulfonamides as potential anticancer drugs were rationally designed by QSAR modeling methods Сlassification learning QSAR models to predict the tubulin polymerization inhibition activity of novel sulfonamides as potential anticancer agents were created using the Online Chemical Modeling Environment (OCHEM) and are freely available online on OCHEM server at https://ochem.eu/article/107790. A series of sulfonamides with predicted activity were synthesized and tested against 60 human cancer cell lines with growth inhibition percent values. The highest antiproliferative activity against leukemia (cell lines K-562 and MOLT-4), non-small cell lung cancer (cell line NCI-H522), colon cancer (cell lines NT29 and SW-620), melanoma (cell lines MALME-3M and UACC-257), ovarian cancer (cell lines IGROV1 and OVCAR-3), renal cancer (cell lines ACHN and UO-31), breast cancer (cell line T-47D) was found for compounds 4-9. According to the docking results the compounds 4-9 induce cytotoxicity by the disruption of the microtubule dynamics by inhibiting tubulin polymerization via effective binding into colchicine domain, similar the E7010.


Subject(s)
Antineoplastic Agents/pharmacology , Drug Design , Sulfonamides/pharmacology , Antineoplastic Agents/chemical synthesis , Antineoplastic Agents/chemistry , Cell Line, Tumor , Cell Proliferation/drug effects , Drug Screening Assays, Antitumor , Humans , Machine Learning , Models, Molecular , Molecular Structure , Quantitative Structure-Activity Relationship , Sulfonamides/chemical synthesis , Sulfonamides/chemistry
17.
Chem Biol Drug Des ; 92(1): 1272-1278, 2018 07.
Article in English | MEDLINE | ID: mdl-29536635

ABSTRACT

The problem of designing new antitubercular drugs against multiple drug-resistant tuberculosis (MDR-TB) was addressed using advanced machine learning methods. As there are only few published measurements against MDR-TB, we collected a large literature data set and developed models against the non-resistant H37Rv strain. The predictive accuracy of these models had a coefficient of determination q2  = .7-.8 (regression models) and balanced accuracies of about 80% (classification models) with cross-validation and independent test sets. The models were applied to screen a virtual chemical library, which was designed to have MDR-TB activity. The seven most promising compounds were identified, synthesized and tested. All of them showed activity against the H37Rv strain, and three molecules demonstrated activity against the MDR-TB strain. The docking analysis indicated that the discovered molecules could bind enoyl reductase, InhA, which is required in mycobacterial cell wall development. The models are freely available online (http://ochem.eu/article/103868) and can be used to predict potential anti-TB activity of new chemicals.


Subject(s)
Antitubercular Agents/chemical synthesis , Drug Design , Isoniazid/chemistry , Antitubercular Agents/pharmacology , Antitubercular Agents/therapeutic use , Bacterial Proteins/chemistry , Bacterial Proteins/metabolism , Binding Sites , Catalytic Domain , Humans , Isoniazid/pharmacology , Isoniazid/therapeutic use , Machine Learning , Microbial Sensitivity Tests , Molecular Docking Simulation , Mycobacterium tuberculosis/drug effects , Mycobacterium tuberculosis/metabolism , Oxidoreductases/chemistry , Oxidoreductases/metabolism , Tuberculosis, Multidrug-Resistant/drug therapy , Tuberculosis, Multidrug-Resistant/pathology
18.
Food Chem Toxicol ; 112: 507-517, 2018 Feb.
Article in English | MEDLINE | ID: mdl-28802948

ABSTRACT

Inorganic nanomaterials have become one of the new areas of modern knowledge and technology and have already found an increasing number of applications. However, some nanoparticles show toxicity to living organisms, and can potentially have a negative influence on environmental ecosystems. While toxicity can be determined experimentally, such studies are time consuming and costly. Computational toxicology can provide an alternative approach and there is a need to develop methods to reliably assess Quantitative Structure-Property Relationships for nanomaterials (nano-QSPRs). Importantly, development of such models requires careful collection and curation of data. This article overviews freely available nano-QSPR models, which were developed using the Online Chemical Modeling Environment (OCHEM). Multiple data on toxicity of nanoparticles to different living organisms were collected from the literature and uploaded in the OCHEM database. The main characteristics of nanoparticles such as chemical composition of nanoparticles, average particle size, shape, surface charge and information about the biological test species were used as descriptors for developing QSPR models. QSPR methodologies used Random Forests (WEKA-RF), k-Nearest Neighbors and Associative Neural Networks. The predictive ability of the models was tested through cross-validation, giving cross-validated coefficients q2 = 0.58-0.80 for regression models and balanced accuracies of 65-88% for classification models. These results matched the predictions for the test sets used to develop the models. The proposed nano-QSPR models and uploaded data are freely available online at http://ochem.eu/article/103451 and can be used for estimation of toxicity of new and emerging nanoparticles at the early stages of nanomaterial development.


Subject(s)
Metal Nanoparticles/toxicity , Models, Chemical , Computational Biology , Machine Learning , Metal Nanoparticles/chemistry , Neural Networks, Computer , Oxides/chemistry , Quantitative Structure-Activity Relationship , Reproducibility of Results , Toxicity Tests
19.
Curr Drug Discov Technol ; 14(1): 25-38, 2017.
Article in English | MEDLINE | ID: mdl-27829331

ABSTRACT

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.


Subject(s)
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
20.
Comput Biol Chem ; 65: 8-15, 2016 Dec.
Article in English | MEDLINE | ID: mdl-27684433

ABSTRACT

Microtubules play a significant role in cell growth and functioning. Therefore inhibition of the microtubule assemblies has emerged as one of the most promising cancer treatment strategies. Predictive QSAR models were built on a series of selective inhibitors of the tubulin were performed by using Associative Neural Networks (ANN). To overcome the problem of data overfitting due to the descriptor selection, a 5-fold cross-validation with variable selection in each step of the analysis was used. All developed QSAR models showed excellent statistics on the training (total accuracy: 0.96-0.97) and test sets (total accuracy: 0.95-97). The models were further validated by 11 synthesized 1,3-oxazole derivatives and all of them showed inhibitory effect on the Hep-2 cancer cell line. The most promising compound showed inhibitory activity IC50=60.2µM. In order to hypothesize their mechanism of action the top three compounds were docked in the colchicine binding site of tubulin and showed reasonable docking scores as well as favorable interactions with the protein.


Subject(s)
Antineoplastic Agents/pharmacology , Computer Simulation , Oxazoles/pharmacology , Antineoplastic Agents/chemistry , Cell Line, Tumor , Humans , Molecular Docking Simulation , Oxazoles/chemistry , Quantitative Structure-Activity Relationship
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