Molecular Docking and MD Modeling Techniques for the Development of Novel ROS1 Kinase Inhibitors
Mohammad Jahoor Alam1, Arshad Jamal1, Shaik Daria Hussain2
1Department of Biology, College of Science, University of Ha'il, Ha'il 2440, Saudi Arabia.
Abstract:
Background: Chemotherapy is a cornerstone of cancer treatment; however, resistance to first-line chemotherapeutic agents remains a major challenge. ROS1, one of fifty-eight receptor tyrosine kinases, has been implicated in various cancer subtypes, including glioblastoma, non-small-cell lung cancer, and cholangiocarcinoma. Notably, the Gly2032Arg mutation in the ROS1 protein has been linked to resistance against the kinase inhibitor crizotinib. Objectives: Given the challenge, we conducted a comprehensive in silico study to identify new drug candidates. Methods: The study starts with modeling the Gly2032Arg-mutated ROS1 protein, followed by structure-based screening of the PubChem database. Results: Out of 1760 molecules screened, we selected the top 4 molecules (PubChem CID: 67463531, 72544946, 139431449, and 139431487) with structural features similar to crizotinib, a high docking score, and drug likeness. To further validate the effectiveness of the identified compounds, we assessed their binding affinity using the Molecular Mechanics with Generalized Born Surface Area (MM-GBSA) scoring method. To underpin the behavior and stability of protein-ligand complexes, 500 ns molecular dynamics (MD) simulations were conducted, and parameters including RMSD, RMSF, and H-bond dynamics were studied and compared. Density functional theory (DFT) at the B3LYP/6-31G* level was performed to elucidate molecular features of the identified compounds. Conclusions: Overall, this study sheds light on a new series of compounds effective against mutated targets, thereby offering a new horizon in this area.
Insights
This study identifies four novel drug candidates effective against mutated ROS1, a key factor in chemotherapy resistance. These compounds show promise for overcoming resistance to kinase inhibitors like crizotinib in cancer treatment.
Area of Science:
- Oncology
- Computational Chemistry
- Drug Discovery
Background:
- Chemotherapy resistance is a major obstacle in cancer treatment.
- The Gly2032Arg mutation in ROS1 (a receptor tyrosine kinase) confers resistance to crizotinib.
- Targeting mutated ROS1 is crucial for developing new anti-cancer therapies.
Purpose of the Study:
- To identify novel drug candidates targeting the Gly2032Arg-mutated ROS1 protein.
- To computationally screen for molecules effective against crizotinib-resistant ROS1.
- To provide new therapeutic strategies for cancers with ROS1 mutations.
Main Methods:
- In silico modeling of the Gly2032Arg-mutated ROS1 protein.
- Structure-based virtual screening of the PubChem database.
- Molecular docking, MM-GBSA, molecular dynamics (MD) simulations, and DFT calculations.
Main Results:
- Identified four promising drug candidates (PubChem CID: 67463531, 72544946, 139431449, 139431487) with high docking scores and drug-likeness.
- Validated binding affinity and stability of protein-ligand complexes through MM-GBSA and MD simulations.
- Elucidated molecular features of identified compounds using DFT.
Conclusions:
- The identified compounds demonstrate potential efficacy against mutated ROS1 targets.
- This research offers a new avenue for developing drugs to overcome chemotherapy resistance.
- The findings contribute to the development of targeted cancer therapies.
