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

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.

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Publication Details

Journal
Scientific Reports
Published
2025-11-11
DOI
https://doi.org/10.1038/s41598-025-23203-8
Primary Topic
Cell Adhesion Molecules Research
Type
article
Field-Weighted Citation Impact
0.00

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article

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

Mohammad Halimi, Amirhossein Hajipasha, Mohammad Darzi, Seyed Arshia Sadat Mohsenian et al.
Scientific Reports
Cell Adhesion Molecules Research
article

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

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

Abstract

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.

Scientific ReportsVol. 15(1)
Islamic Azad University, Babol, Babol University of Medical Sciences (IR)
Islamic Azad University
Openalex Percentile: Top 57%
Cell Adhesion Molecules Research
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Structure-based identification of novel FAK1 inhibitors using pharmacophore modeling, molecular dynamics, and MM/PBSA calculations — Mohammad Halimi, Amirhossein Hajipasha, et al. · Scientific Reports (2025) | TGRS Research Map | TGRS