Molecular modeling provides a structural basis for PERK inhibitor selectivity towards RIPK1

Area of Science:

• Biochemistry
• Pharmacology
• Computational Biology

Background:

• Protein kinases are vital in cancer, but inhibitors often lack specificity due to conserved ATP binding sites.
• PERK (protein regulator of eIF2 alpha kinase) is a promising cancer target, yet existing inhibitors like GSK2606414 and GSK2656157 also inhibit RIPK1.
• AMG44 shows greater PERK specificity, necessitating an understanding of the structural basis for differential targeting.

Purpose of the Study:

• To investigate the structural mechanisms underlying the selectivity of PERK ligands against RIPK1.
• To elucidate the binding interactions of GSK2606414, GSK2656157, and AMG44 with PERK and RIPK1 kinases.
• To provide insights for designing more selective PERK inhibitors for cancer therapy.

Main Methods:

• Utilized molecular docking (rigid and induced fit) to model ligand-protein interactions.
• Employed molecular dynamics simulations to analyze the dynamic behavior of kinase-ligand complexes.
• Performed in silico analysis to explore the selectivity profiles of PERK ligands.

Main Results:

• Identified a common binding mode for GSK2606414 and GSK2656157 in the RIPK1 binding site, mimicking its cognate ligand.
• Observed a distinct binding profile for AMG44 in the RIPK1 binding site across different docking settings.
• Demonstrated that PERK and RIPK1, despite similar binding sites, exhibit differential responses to small molecules.

Conclusions:

• Elucidated the molecular basis for the dual targeting of PERK and RIPK1 by GSK ligands.
• Highlighted the utility of molecular docking in predicting ligand binding across different kinase structures.
• Provided a foundation for the rational design of novel, selective PERK kinase inhibitors.