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DOI 10.1038/s41598-025-23203-8

Медицинская библиотека · Scientific reports · 2025

Structure-based identification of novel FAK1 inhibitors using pharmacophore modeling, molecular dynamics, and MM/PBSA calculations.

Hajipasha Amirhossein, Cherati Nilofar Ghaffari, Darzi Mohammad, Nateghi Seyedeh Sana, Mohsenian Seyed Arshia Sadat, Noorzaei Mahla, Dinaki Fatemeh Kashiri, Halimi Mohammad

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Аннотация

Focal adhesion kinase 1 (FAK1) is a non-receptor tyrosine kinase involved in cancer metastasis and tumor progression. Due to its role in regulating cell migration and survival, FAK1 is considered a promising target for cancer therapy. While large chemical databases such as ZINC offer a wide variety of molecules, many of them have not yet been explored as potential FAK1 inhibitors.In this study, we applied several computational methods to identify new inhibitors of the FAK1 kinase domain. Pharmacophore models were built based on the FAK1-P4N complex (PDB ID: 6YOJ), and the most statistically reliable model was used to screen compounds from the ZINC database. Hits were first docked using AutoDock Vina in PyRx, and seventeen compounds with acceptable pharmacokinetic properties and low predicted toxicity were selected for more precise docking via SwissDock. Four promising candidates-ZINC23845603, ZINC44851809, ZINC266691666, and ZINC20267780-were chosen for molecular dynamics (MD) simulations using GROMACS. The stability and behavior of each protein-ligand complex were examined, and binding free energies were calculated using the MM/PBSA method. Among them, ZINC23845603 showed strong binding and interaction features similar to the known ligand P4N. Given its favorable binding energy and pharmacokinetic profile, ZINC23845603 may be a good candidate for further experimental studies targeting FAK1.

Для цитирования: Hajipasha Amirhossein, Cherati Nilofar Ghaffari, Darzi Mohammad, Nateghi Seyedeh Sana, Mohsenian Seyed Arshia Sadat, Noorzaei Mahla, Dinaki Fatemeh Kashiri, Halimi Mohammad. Structure-based identification of novel FAK1 inhibitors using pharmacophore modeling, molecular dynamics, and MM/PBSA calculations.. Scientific reports. 2025. DOI: 10.1038/s41598-025-23203-8.

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