Computational identification of novel c-MET receptor tyrosine kinase inhibitors in lung cancer through pharmacophore-based screening, docking studies, ADMET evaluation and Molecular dynamic simulations
Published: 22 October 2025| Version 1 | DOI: 10.17632/p8xnpwptm7.1
Contributor:
Azam RoohiDescription
This dataset contains pharmacophore modelling, molecular docking results, binding poses, and MD simulation trajectory files used in the study titled "Computational identification of novel c-MET receptor tyrosine kinase inhibitors in lung cancer through pharmacophore-based screening, docking studies, ADMET evaluation, and Molecular dynamic simulations". The study includes validation of pharmacophore models, Pharmacophore based virtual screening interaction plots, trajectory analysis outputs, and some figures used for validating binding stability. The data was generated using Maestro v. 9. 0 and GROMACS (2020), and supports the findings reported in the manuscript.
Files
Institutions
- Ferdowsi University of Mashhad Faculty of Sciences
Categories
Drug Discovery, Computational Biochemistry