Ligand Design Using Unique Conformations to Preferentially Dock a Specific Site on Collagen-Bound MMP1

Area of Science:

• Biochemistry
• Computational Biology
• Drug Discovery

Background:

• Structure-based drug discovery often uses static protein models, neglecting protein dynamics and substrate-specific states.
• Ligand screening is incomplete without considering binding competition and dynamic conformational changes.
• Matrix metalloprotease-1 (MMP1) dynamics are altered by collagen, with residue R405 showing allosteric effects.

Purpose of the Study:

• To develop a computational framework for substrate-specific allosteric ligand design.
• To identify and exploit collagen-bound MMP1 conformations for selective ligand targeting.
• To establish a generalizable workflow for identifying ligands that preferentially bind to specific allosteric states.

Main Methods:

• All-atom molecular dynamics simulations to characterize MMP1 conformational dynamics.
• Clustering of conformational ensembles to identify substrate-specific states.
• Machine-learning-based ligand generation and docking against identified pockets and allosteric sites.

Main Results:

• Identified unique conformations of collagen-bound MMP1.
• Generated ~150,000 candidate ligands using these conformations.
• Predicted several ligands preferentially docking to the R405 allosteric region over other surface pockets.

Conclusions:

• Established a computational workflow for designing ligands targeting substrate-specific allosteric conformations.
• Demonstrated potential for selective allosteric modulation of MMP1.
• Provided a foundation for experimental validation of novel allosteric modulators.