Multialgorithm-Based Docking Reveals Imidazolidinyl Urea as a Multitargeted Inhibitor for Lung Cancer
Lung cancer is one of the deadliest cancers, responsible for more than 1.80 million deaths annually worldwide, and it is on the priority list of the WHO. In the current scenario, when cancer cells become resistant to drugs, making them less effective and leaving the patient in vulnerable conditions....
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-03-01
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| Series: | Medical Sciences Forum |
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| Online Access: | https://www.mdpi.com/2673-9992/21/1/36 |
| _version_ | 1797379866458324992 |
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| author | Shaban Ahmad Khalid Raza |
| author_facet | Shaban Ahmad Khalid Raza |
| author_sort | Shaban Ahmad |
| collection | DOAJ |
| description | Lung cancer is one of the deadliest cancers, responsible for more than 1.80 million deaths annually worldwide, and it is on the priority list of the WHO. In the current scenario, when cancer cells become resistant to drugs, making them less effective and leaving the patient in vulnerable conditions. To overcome this situation, researchers are constantly working on new drugs and medications that can help fight drug resistance and improve patients’ outcomes. In this study, we have taken five main proteins of lung cancer, namely RSK4 N-terminal kinase, guanylate kinase, cyclin-dependent kinase 2, kinase CK2 holoenzyme, and tumour necrosis factor-alpha, and screened the prepared Drug Bank library with 155,888 compounds against all using three Glide-based docking algorithms, namely HTVS, standard precision and extra precise, with a docking score ranging from −5.422 to −8.432 Kcal/mol. The poses were filtered with the MM\GBSA calculations, which helped to identify Imidazolidinyl urea C11H16N8O8 (DB14075) as a multitargeted inhibitor for lung cancer, validated with advanced computations such as ADMET and interaction pattern fingerprints. Further, it is proposed to optimise the compound with Jaguar and MD Simulation for at least 100 ns with NPT ensemble class to analyse the deviation and fluctuations and possible interactions for stability and experimental validation on the A549 cell line. |
| first_indexed | 2024-03-08T20:29:15Z |
| format | Article |
| id | doaj.art-aca4e3351e5843d89c4019c58d80da1d |
| institution | Directory Open Access Journal |
| issn | 2673-9992 |
| language | English |
| last_indexed | 2024-03-08T20:29:15Z |
| publishDate | 2023-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Medical Sciences Forum |
| spelling | doaj.art-aca4e3351e5843d89c4019c58d80da1d2023-12-22T14:28:45ZengMDPI AGMedical Sciences Forum2673-99922023-03-012113610.3390/ECB2023-14138Multialgorithm-Based Docking Reveals Imidazolidinyl Urea as a Multitargeted Inhibitor for Lung CancerShaban Ahmad0Khalid Raza1Department of Computer Science, Jamia Millia Islamia, New Delhi 110025, IndiaDepartment of Computer Science, Jamia Millia Islamia, New Delhi 110025, IndiaLung cancer is one of the deadliest cancers, responsible for more than 1.80 million deaths annually worldwide, and it is on the priority list of the WHO. In the current scenario, when cancer cells become resistant to drugs, making them less effective and leaving the patient in vulnerable conditions. To overcome this situation, researchers are constantly working on new drugs and medications that can help fight drug resistance and improve patients’ outcomes. In this study, we have taken five main proteins of lung cancer, namely RSK4 N-terminal kinase, guanylate kinase, cyclin-dependent kinase 2, kinase CK2 holoenzyme, and tumour necrosis factor-alpha, and screened the prepared Drug Bank library with 155,888 compounds against all using three Glide-based docking algorithms, namely HTVS, standard precision and extra precise, with a docking score ranging from −5.422 to −8.432 Kcal/mol. The poses were filtered with the MM\GBSA calculations, which helped to identify Imidazolidinyl urea C11H16N8O8 (DB14075) as a multitargeted inhibitor for lung cancer, validated with advanced computations such as ADMET and interaction pattern fingerprints. Further, it is proposed to optimise the compound with Jaguar and MD Simulation for at least 100 ns with NPT ensemble class to analyse the deviation and fluctuations and possible interactions for stability and experimental validation on the A549 cell line.https://www.mdpi.com/2673-9992/21/1/36lung cancermolecular dockingImidazolidinyl ureamolecular fingerprints |
| spellingShingle | Shaban Ahmad Khalid Raza Multialgorithm-Based Docking Reveals Imidazolidinyl Urea as a Multitargeted Inhibitor for Lung Cancer Medical Sciences Forum lung cancer molecular docking Imidazolidinyl urea molecular fingerprints |
| title | Multialgorithm-Based Docking Reveals Imidazolidinyl Urea as a Multitargeted Inhibitor for Lung Cancer |
| title_full | Multialgorithm-Based Docking Reveals Imidazolidinyl Urea as a Multitargeted Inhibitor for Lung Cancer |
| title_fullStr | Multialgorithm-Based Docking Reveals Imidazolidinyl Urea as a Multitargeted Inhibitor for Lung Cancer |
| title_full_unstemmed | Multialgorithm-Based Docking Reveals Imidazolidinyl Urea as a Multitargeted Inhibitor for Lung Cancer |
| title_short | Multialgorithm-Based Docking Reveals Imidazolidinyl Urea as a Multitargeted Inhibitor for Lung Cancer |
| title_sort | multialgorithm based docking reveals imidazolidinyl urea as a multitargeted inhibitor for lung cancer |
| topic | lung cancer molecular docking Imidazolidinyl urea molecular fingerprints |
| url | https://www.mdpi.com/2673-9992/21/1/36 |
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