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2-Amino Thiazole Derivatives as Prospective Aurora Kinase Inhibitors against Breast Cancer: QSAR, ADMET Prediction, Molecular Docking, and Molecular Dynamic Simulation Studies

[Image: see text] The aurora kinase is a key enzyme that is implicated in tumor growth. Research revealed that small molecules that target aurora kinase have beneficial effects as anticancer agents. In the present study, in order to identify potential antibreast cancer agents with aurora kinase inhi...

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Autores principales: Bathula, Sivakumar, Sankaranarayanan, Murugesan, Malgija, Beutline, Kaliappan, Ilango, Bhandare, Richie R., Shaik, Afzal B.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10666282/
https://www.ncbi.nlm.nih.gov/pubmed/38027360
http://dx.doi.org/10.1021/acsomega.3c07003
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author Bathula, Sivakumar
Sankaranarayanan, Murugesan
Malgija, Beutline
Kaliappan, Ilango
Bhandare, Richie R.
Shaik, Afzal B.
author_facet Bathula, Sivakumar
Sankaranarayanan, Murugesan
Malgija, Beutline
Kaliappan, Ilango
Bhandare, Richie R.
Shaik, Afzal B.
author_sort Bathula, Sivakumar
collection PubMed
description [Image: see text] The aurora kinase is a key enzyme that is implicated in tumor growth. Research revealed that small molecules that target aurora kinase have beneficial effects as anticancer agents. In the present study, in order to identify potential antibreast cancer agents with aurora kinase inhibitory activity, we employed QSARINS software to perform the quantitative structure–activity relationship (QSAR). The statistical values resulted from the study include R(2) = 0.8902, CCC(tr) = 0.7580, Q(2) LOO = 0.7875, Q(2LMO) = 0.7624, CCC(cv) = 0.7535, R(2ext) = 0.8735, and CCC(ext) = 0.8783. Among the four generated models, the two best models encompass five important variables, including PSA, EstateVSA5, MoRSEP3, MATSp5, and RDFC24. The parameters including the atomic volume, atomic charges, and Sanderson’s electronegativity played an important role in designing newer lead compounds. Based on the above data, we have designed six series of compounds including 1a–e, 2a–e, 3a–e, 4a–e, 5a–e, and 6a–e. All these compounds were subjected to molecular docking studies by using AutoDock v4.2.6 against the aurora kinase protein (1MQ4). Among the above 30 compounds, the 2-amino thiazole derivatives 1a, 2a, 3e, 4d, 5d, and 6d have excellent binding interactions with the active site of 1MQ4. Compound 1a had the highest docking score (−9.67) and hence was additionally subjected to molecular dynamic simulation investigations for 100 ns. The stable binding of compound 1a with 1MQ4 was verified by RMSD, RMSF, RoG, H-bond, molecular mechanics-generalized Born surface area (MM-GBSA), free binding energy calculations, and solvent-accessible surface area (SASA) analyses. Furthermore, newly designed compound 1a exhibited excellent ADMET properties. Based on the above findings, we propose that the designed compound 1a may be utilized as the best theoretical lead for future experimental research of selective inhibition of aurora kinase, therefore assisting in the creation of new antibreast cancer drugs.
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spelling pubmed-106662822023-11-07 2-Amino Thiazole Derivatives as Prospective Aurora Kinase Inhibitors against Breast Cancer: QSAR, ADMET Prediction, Molecular Docking, and Molecular Dynamic Simulation Studies Bathula, Sivakumar Sankaranarayanan, Murugesan Malgija, Beutline Kaliappan, Ilango Bhandare, Richie R. Shaik, Afzal B. ACS Omega [Image: see text] The aurora kinase is a key enzyme that is implicated in tumor growth. Research revealed that small molecules that target aurora kinase have beneficial effects as anticancer agents. In the present study, in order to identify potential antibreast cancer agents with aurora kinase inhibitory activity, we employed QSARINS software to perform the quantitative structure–activity relationship (QSAR). The statistical values resulted from the study include R(2) = 0.8902, CCC(tr) = 0.7580, Q(2) LOO = 0.7875, Q(2LMO) = 0.7624, CCC(cv) = 0.7535, R(2ext) = 0.8735, and CCC(ext) = 0.8783. Among the four generated models, the two best models encompass five important variables, including PSA, EstateVSA5, MoRSEP3, MATSp5, and RDFC24. The parameters including the atomic volume, atomic charges, and Sanderson’s electronegativity played an important role in designing newer lead compounds. Based on the above data, we have designed six series of compounds including 1a–e, 2a–e, 3a–e, 4a–e, 5a–e, and 6a–e. All these compounds were subjected to molecular docking studies by using AutoDock v4.2.6 against the aurora kinase protein (1MQ4). Among the above 30 compounds, the 2-amino thiazole derivatives 1a, 2a, 3e, 4d, 5d, and 6d have excellent binding interactions with the active site of 1MQ4. Compound 1a had the highest docking score (−9.67) and hence was additionally subjected to molecular dynamic simulation investigations for 100 ns. The stable binding of compound 1a with 1MQ4 was verified by RMSD, RMSF, RoG, H-bond, molecular mechanics-generalized Born surface area (MM-GBSA), free binding energy calculations, and solvent-accessible surface area (SASA) analyses. Furthermore, newly designed compound 1a exhibited excellent ADMET properties. Based on the above findings, we propose that the designed compound 1a may be utilized as the best theoretical lead for future experimental research of selective inhibition of aurora kinase, therefore assisting in the creation of new antibreast cancer drugs. American Chemical Society 2023-11-07 /pmc/articles/PMC10666282/ /pubmed/38027360 http://dx.doi.org/10.1021/acsomega.3c07003 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Bathula, Sivakumar
Sankaranarayanan, Murugesan
Malgija, Beutline
Kaliappan, Ilango
Bhandare, Richie R.
Shaik, Afzal B.
2-Amino Thiazole Derivatives as Prospective Aurora Kinase Inhibitors against Breast Cancer: QSAR, ADMET Prediction, Molecular Docking, and Molecular Dynamic Simulation Studies
title 2-Amino Thiazole Derivatives as Prospective Aurora Kinase Inhibitors against Breast Cancer: QSAR, ADMET Prediction, Molecular Docking, and Molecular Dynamic Simulation Studies
title_full 2-Amino Thiazole Derivatives as Prospective Aurora Kinase Inhibitors against Breast Cancer: QSAR, ADMET Prediction, Molecular Docking, and Molecular Dynamic Simulation Studies
title_fullStr 2-Amino Thiazole Derivatives as Prospective Aurora Kinase Inhibitors against Breast Cancer: QSAR, ADMET Prediction, Molecular Docking, and Molecular Dynamic Simulation Studies
title_full_unstemmed 2-Amino Thiazole Derivatives as Prospective Aurora Kinase Inhibitors against Breast Cancer: QSAR, ADMET Prediction, Molecular Docking, and Molecular Dynamic Simulation Studies
title_short 2-Amino Thiazole Derivatives as Prospective Aurora Kinase Inhibitors against Breast Cancer: QSAR, ADMET Prediction, Molecular Docking, and Molecular Dynamic Simulation Studies
title_sort 2-amino thiazole derivatives as prospective aurora kinase inhibitors against breast cancer: qsar, admet prediction, molecular docking, and molecular dynamic simulation studies
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10666282/
https://www.ncbi.nlm.nih.gov/pubmed/38027360
http://dx.doi.org/10.1021/acsomega.3c07003
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