Multisampling-based docking reveals Imidazolidinyl urea as a multitargeted inhibitor for lung cancer: an optimisation
Shaban Ahmad1, Vijay Singh2, Hemant K Gautam2
1Department of Computer Science, Jamia Millia Islamia, New Delhi, India.
Abstract:
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 WHO. In the current scenario, when cancer cells become resistant to the drug, making it less effective leaves 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, tumour necrosis factor-alpha and screened the prepared Drug Bank library with 1,55,888 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 like ADMET, interaction pattern fingerprints, and optimised the compound with Jaguar, producing satisfied relative energy. All five complexes were performed with MD Simulation for 100 ns with NPT ensemble class, producing cumulative deviation and fluctuations < 2 Å and a web of intermolecular interaction, making the complexes stable. Further, the in-vitro analysis for morphological imaging, Annexin V/PI FACS assay, ROS and MMP analysis caspase3//7 activity were performed on the A549 cell line producing promising results and can be an option to treat lung cancer at a significantly cheaper state.Communicated by Ramaswamy H. Sarma.
Insights
Researchers identified Imidazolidinyl urea as a potential multi-target drug for lung cancer, showing promise in vitro. This new compound may offer a cheaper treatment option for drug-resistant lung cancer.
Area of Science:
- Oncology
- Computational Chemistry
- Drug Discovery
Background:
- Lung cancer remains a leading cause of cancer-related deaths globally, with drug resistance posing a significant challenge.
- Developing novel therapeutic agents is crucial to overcome treatment resistance and improve patient outcomes in lung cancer.
Purpose of the Study:
- To identify novel multi-targeted inhibitors for key lung cancer proteins using computational screening.
- To validate the efficacy and safety of a lead compound through advanced computational and in vitro analyses.
Main Methods:
- Virtual screening of 155,888 compounds against five lung cancer proteins using Glide docking algorithms.
- Molecular mechanics with generalized Born surface area (MM/GBSA) for pose filtering, ADMET prediction, and molecular dynamics (MD) simulations.
- In vitro assays including morphological imaging, Annexin V/PI FACS, ROS, MMP, and caspase activity on A549 cell lines.
Main Results:
- Imidazolidinyl urea (DB14075) was identified as a potent multi-targeted inhibitor with significant docking scores (-5.422 to -8.432 Kcal/mol).
- MD simulations confirmed the stability of the protein-ligand complexes, with deviations < 2 Å.
- In vitro studies demonstrated promising results in inducing apoptosis and inhibiting proliferation in A549 lung cancer cells.
Conclusions:
- Imidazolidinyl urea is a promising candidate for a multi-targeted lung cancer therapy, effectively addressing drug resistance.
- The identified compound shows potential for development into a cost-effective treatment option for lung cancer.
- This study highlights the synergy between computational drug design and experimental validation in advancing oncology therapeutics.
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