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Vukomanović P, Stefanović M, Stevanović JM, Petrić A, Trenkić M, Andrejević L, Lazarević M, Sokolović D, Veselinović AM. Monte Carlo Optimization Method Based QSAR Modeling of Placental Barrier Permeability. Pharm Res 2024; 41:493-500. [PMID: 38337105 DOI: 10.1007/s11095-024-03675-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2023] [Accepted: 01/30/2024] [Indexed: 02/12/2024]
Abstract
PURPOSE In order to ensure that drug administration is safe during pregnancy, it is crucial to have the possibility to predict the placental permeability of drugs in humans. The experimental method which is most widely used for the said purpose is in vitro human placental perfusion, though the approach is highly expensive and time consuming. Quantitative structure-activity relationship (QSAR) modeling represents a powerful tool for the assessment of the drug placental transfer, and can be successfully employed to be an alternative in in vitro experiments. METHODS The conformation-independent QSAR models covered in the present study were developed through the use of the SMILES notation descriptors and local molecular graph invariants. What is more, the Monte Carlo optimization method, was used in the test sets and the training sets as the model developer with three independent molecular splits. RESULTS A range of different statistical parameters was used to validate the developed QSAR model, including the standard error of estimation, mean absolute error, root-mean-square error (RMSE), correlation coefficient, cross-validated correlation coefficient, Fisher ratio, MAE-based metrics and the correlation ideality index. Once the mentioned statistical methods were employed, an excellent predictive potential and robustness of the developed QSAR model was demonstrated. In addition, the molecular fragments, which are derived from the SMILES notation descriptors accounting for the decrease or increase in the investigated activity, were revealed. CONCLUSION The presented QSAR modeling can be an invaluable tool for the high-throughput screening of the placental permeability of drugs.
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Affiliation(s)
- Predrag Vukomanović
- Faculty of Medicine, University of Niš, Niš, Serbia
- Clinic for Gynecology and Obstetrics, University Clinical Centre of Niš, Niš, Serbia
| | - Milan Stefanović
- Faculty of Medicine, University of Niš, Niš, Serbia
- Clinic for Gynecology and Obstetrics, University Clinical Centre of Niš, Niš, Serbia
| | - Jelena Milošević Stevanović
- Faculty of Medicine, University of Niš, Niš, Serbia
- Clinic for Gynecology and Obstetrics, University Clinical Centre of Niš, Niš, Serbia
| | - Aleksandra Petrić
- Faculty of Medicine, University of Niš, Niš, Serbia
- Clinic for Gynecology and Obstetrics, University Clinical Centre of Niš, Niš, Serbia
| | - Milan Trenkić
- Faculty of Medicine, University of Niš, Niš, Serbia
- Clinic for Gynecology and Obstetrics, University Clinical Centre of Niš, Niš, Serbia
| | - Lazar Andrejević
- COVID Hospital, University Clinical Centre of Niš, Kruševac, Serbia
| | - Milan Lazarević
- Faculty of Medicine, University of Niš, Niš, Serbia
- Clinic for Cardiovascular and Transplant Surgery, University Clinical Centre of Niš, Niš, Serbia
| | | | - Aleksandar M Veselinović
- Faculty of Medicine, Department of Chemistry, University of Niš, Bulevar Dr Zorana Đinđića 81, 18000, Niš, Serbia.
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Tabti K, Abdessadak O, Sbai A, Maghat H, Bouachrine M, Lakhlifi T. Design and development of novel spiro-oxindoles as potent antiproliferative agents using quantitative structure activity based Monte Carlo method, docking molecular, molecular dynamics, free energy calculations, and pharmacokinetics /toxicity studies. J Mol Struct 2023. [DOI: 10.1016/j.molstruc.2023.135404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/28/2023]
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Methodology for the projection of population pyramids based on Monte Carlo simulation and genetic algorithms. APPL INTELL 2023. [DOI: 10.1007/s10489-023-04492-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
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Köse E, Erkan Köse M, Güneşdoğdu Sağdınç S. Principal component analysis of quantum mechanical descriptors data to reveal the pharmacological activities of oxindole derivatives. RESULTS IN CHEMISTRY 2023. [DOI: 10.1016/j.rechem.2023.100905] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/29/2023] Open
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QSAR modelling, molecular docking studies and ADMET predictions of polysubstituted pyridinylimidazoles as dual inhibitors of JNK3 and p38α MAPK. J Mol Struct 2022. [DOI: 10.1016/j.molstruc.2022.133504] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
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Shayanfar S, Shayanfar A. Comparison of various methods for validity evaluation of QSAR models. BMC Chem 2022; 16:63. [PMID: 35999611 PMCID: PMC9396839 DOI: 10.1186/s13065-022-00856-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2022] [Accepted: 08/09/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Quantitative structure-activity relationship (QSAR) modeling is one of the most important computational tools employed in drug discovery and development. The external validation of QSAR models is the main point to check the reliability of developed models for the prediction activity of not yet synthesized compounds. It was performed by different criteria in the literature. METHODS In this study, 44 reported QSAR models for biologically active compounds reported in scientific papers were collected. Various statistical parameters of external validation of a QSAR model were calculated, and the results were discussed. RESULTS The findings revealed that employing the coefficient of determination (r2) alone could not indicate the validity of a QSAR model. The established criteria for external validation have some advantages and disadvantages which should be considered in QSAR studies. CONCLUSION This study showed that these methods alone are not only enough to indicate the validity/invalidity of a QSAR model.
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Affiliation(s)
- Shadi Shayanfar
- Student Research Committee, Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Ali Shayanfar
- Pharmaceutical Analysis Research Center, Tabriz University of Medical Sciences, Tabriz, Iran. .,Editorial Office of Pharmaceutical Sciences Journal, Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran.
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Đorđević V, Petković M, Živković J, Nikolić GM, Veselinović AM. Development of Novel Therapeutics for Schizophrenia Treatment Based on a Selective Positive Allosteric Modulation of α1-Containing GABAARs-In Silico Approach. Curr Issues Mol Biol 2022; 44:3398-3412. [PMID: 36005130 PMCID: PMC9406691 DOI: 10.3390/cimb44080234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Revised: 07/22/2022] [Accepted: 07/26/2022] [Indexed: 11/25/2022] Open
Abstract
For the development of atypical antipsychotics, the selective positive allosteric modulation of the ionotropic GABAA receptor (GABAAR) has emerged as a promising approach. In the presented research, two unrelated methods were used for the development of QSAR models for selective positive allosteric modulation of 1-containing GABAARs with derivatives of imidazo [1,2-a]-pyridine. The development of conformation-independent QSAR models, based on descriptors derived from local molecular graph invariants and SMILES notation, was achieved with the Monte Carlo optimization method. From the vast pool of 0D, 1D, and 2D molecule descriptors, the GA-MLR method developed additional QSAR models. Various statistical methods were utilised for the determination of the developed models’ robustness, predictability, and overall quality, and according to the obtained results, all QSAR models are considered good. The molecular fragments that have a positive or negative impact on the studied activity were obtained from the studied molecules’ SMILES notations, and according to the obtained results, nine novel compounds were designed. The binding affinities to GABAAR of designed compounds were assessed with the application of molecular docking studies and the obtained results showed a high correlation with results obtained from QSAR modeling. To assess all designed molecules’ “drug-likeness”, their physicochemical descriptors were computed and utilised for the prediction of medicinal chemistry friendliness, pharmacokinetic properties, ADME parameters, and druglike nature.
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Affiliation(s)
- Vladimir Đorđević
- Department of Psychiatry with Medical Psychology, Faculty of Medicine, University of Niš, 18000 Niš, Serbia;
| | - Milan Petković
- Department of Physiology, Faculty of Medicine, University of Niš, 18000 Niš, Serbia;
| | - Jelena Živković
- Department of Chemistry, Faculty of Medicine, University of Niš, 18000 Niš, Serbia; (J.Ž.); (G.M.N.)
| | - Goran M. Nikolić
- Department of Chemistry, Faculty of Medicine, University of Niš, 18000 Niš, Serbia; (J.Ž.); (G.M.N.)
| | - Aleksandar M. Veselinović
- Department of Chemistry, Faculty of Medicine, University of Niš, 18000 Niš, Serbia; (J.Ž.); (G.M.N.)
- Correspondence:
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Ničkčović VP, Nikolić GR, Nedeljković BM, Mitić N, Danić SF, Mitić J, Marčetić Z, Sokolović D, Veselinović AM. In silico approach for the development of novel antiviral compounds based on SARS-COV-2 protease inhibition. CHEMICAL PAPERS 2022; 76:4393-4404. [PMID: 35400796 PMCID: PMC8977062 DOI: 10.1007/s11696-022-02170-8] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/29/2021] [Accepted: 03/05/2022] [Indexed: 11/03/2022]
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9
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Đorđević V, Pešić S, Živković J, Nikolić GM, Veselinović AM. Development of novel antipsychotic agents by inhibiting dopamine transporter – in silico approach. NEW J CHEM 2022. [DOI: 10.1039/d1nj04759k] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
Abstract
Various in silico methods were employed for the development of antipsychotic agents by dopamine transporter inhibition.
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Affiliation(s)
- Vladimir Đorđević
- Faculty of Medicine, University of Niš, Department of Psychiatry with Medical Psychology, Niš, Serbia
| | - Srđan Pešić
- Faculty of Medicine, University of Niš, Department of Pharmacology, Niš, Serbia
| | - Jelena Živković
- Faculty of Medicine, University of Niš, Department of Chemistry, Bulevar Dr Zorana Đinđića 81, 18000 Niš, Serbia
| | - Goran M. Nikolić
- Faculty of Medicine, University of Niš, Department of Chemistry, Bulevar Dr Zorana Đinđića 81, 18000 Niš, Serbia
| | - Aleksandar M. Veselinović
- Faculty of Medicine, University of Niš, Department of Chemistry, Bulevar Dr Zorana Đinđića 81, 18000 Niš, Serbia
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Antović AR, Karadžić R, Veselinović AM. Monte Carlo optimization method based QSAR modeling of postmortem redistribution of structurally diverse drugs. NEW J CHEM 2022. [DOI: 10.1039/d2nj01944b] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The Monte Carlo optimization method was employed for the development of the QSAR model for the prediction for postmortem redistribution of structurally diverse drugs.
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Affiliation(s)
| | - Radovan Karadžić
- Institute of Forensic Medicine, Faculty of Medicine, University of Niš, Niš, Serbia
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In silico development of potential therapeutic for the pain treatment by inhibiting voltage-gated sodium channel 1.7. Comput Biol Med 2021; 132:104346. [PMID: 33774271 DOI: 10.1016/j.compbiomed.2021.104346] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2020] [Revised: 03/13/2021] [Accepted: 03/13/2021] [Indexed: 01/27/2023]
Abstract
The voltage-gated sodium channel Nav1.7 can be considered as a promising target for the treatment of pain. This research presents conformational-independent and 3D field-based QSAR modeling for a series of aryl sulfonamide acting as Nav1.7 inhibitors. As descriptors used for building conformation-independent QSAR models, SMILES notation and local invariants of the molecular graph were used with the Monte Carlo optimization method as a model developer. Different statistical methods, including the index of ideality of correlation, were used to test the quality of the developed models, robustness and predictability and obtained results were good. Obtained results indicate that there is a very good correlation between 3D QSAR and conformation-independent models. Molecular fragments that account for the increase/decrease of a studied activity were defined and used for the computer-aided design of new compounds as potential analgesics. The final evaluation of the developed QSAR models and designed inhibitors were carried out using molecular docking studies, bringing to light an excellent correlation with the QSAR modeling results.
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Perić V, Golubović M, Lazarević M, Marjanović V, Kostić T, Đorđević M, Milić D, Veselinović AM. Development of potential therapeutics for pain treatment by inducing Sigma 1 receptor antagonism – in silico approach. NEW J CHEM 2021. [DOI: 10.1039/d1nj00883h] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
QSAR modeling with computer-aided drug design were used for the in silico development of novel therapeutics for pain treatment.
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Affiliation(s)
- Velimir Perić
- Department for Cardiac Surgery
- Clinic for Anaesthesiology and Intensive Therapy
- Clinical Center Niš
- Niš
- Serbia
| | - Mladjan Golubović
- Department for Cardiac Surgery
- Clinic for Anaesthesiology and Intensive Therapy
- Clinical Center Niš
- Niš
- Serbia
| | - Milan Lazarević
- Faculty of Medicine
- Department of Chemistry
- Medical School of Niš
- University of Niš
- 18000 Niš
| | - Vesna Marjanović
- Faculty of Medicine
- Department of Chemistry
- Medical School of Niš
- University of Niš
- 18000 Niš
| | - Tomislav Kostić
- Faculty of Medicine
- Department of Chemistry
- Medical School of Niš
- University of Niš
- 18000 Niš
| | - Miodrag Đorđević
- Faculty of Medicine
- Department of Chemistry
- Medical School of Niš
- University of Niš
- 18000 Niš
| | - Dragan Milić
- Faculty of Medicine
- Department of Chemistry
- Medical School of Niš
- University of Niš
- 18000 Niš
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Toropov AA, Toropova AP, Veselinović AM, Leszczynska D, Leszczynski J. SARS-CoV M pro inhibitory activity of aromatic disulfide compounds: QSAR model. J Biomol Struct Dyn 2020; 40:780-786. [PMID: 32907512 PMCID: PMC7544941 DOI: 10.1080/07391102.2020.1818627] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
The main protease (Mpro) of SARS-associated coronavirus (SARS-CoV) had caused a high rate of mortality in 2003. Current events (2019-2020) substantiate important challenges for society due to coronaviruses. Consequently, advancing models for the antiviral activity of therapeutic agents is a necessary component of the fast development of treatment for the virus. An analogy between anti-SARS agents suggested in 2017 and anti-coronavirus COVID-19 agents are quite probable. Quantitative structure-activity relationships for SARS-CoV are developed and proposed in this study. The statistical quality of these models is quite good. Mechanistic interpretation of developed models is based on the statistical and probability quality of molecular alerts extracted from SMILES. The novel, designed structures of molecules able to possess anti-SARS activities are suggested. For the final assessment of the designed molecules inhibitory potential, developed from the obtained QSAR model, molecular docking studies were applied. Results obtained from molecular docking studies were in a good correlation with the results obtained from QSAR modeling.
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Affiliation(s)
- Andrey A Toropov
- Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Science, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy
| | - Alla P Toropova
- Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Science, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milano, Italy
| | | | - Danuta Leszczynska
- Departments of Civil and Environmental Engineering, Jackson State University, Jackson, MS, USA
| | - Jerzy Leszczynski
- Interdisciplinary Center for Nanotoxicity, Jackson State University, Jackson, MS, USA
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