Mapping the Glycan Recognition Landscape of Galectin-3 through Enhanced Sampling Simulations

Area of Science:

• Biochemistry
• Molecular Biology
• Computational Chemistry

Background:

• Galectin-3 is a key protein in cell processes and a cancer therapeutic target.
• Understanding galectin-3's interaction with carbohydrate ligands is vital for drug discovery.
• Atomistic simulations of rare ligand-binding events are computationally intensive.

Purpose of the Study:

• To investigate galectin-3's intricate binding mechanisms with glycans of varying lengths.
• To utilize Gaussian accelerated molecular dynamics (GaMD) for efficient simulation of these interactions.
• To provide insights for designing targeted galectin-3 therapeutics.

Main Methods:

• Employed Gaussian accelerated molecular dynamics (GaMD) simulations.
• Studied the binding of galectin-3 with glycans of different chain lengths.
• Analyzed ligand interaction modes and binding pocket occupancy.

Main Results:

• Longer glycans (pentasaccharides, ortho-fluoro derivatives) bind strongly and stably to galectin-3's native pocket.
• Shorter glycans (beta-lactose, TF-antigen) exhibit conformational flexibility, exploring allosteric pockets before native binding.
• Glycan chain length significantly influences the mode of galectin-3 interaction.

Conclusions:

• Glycan length is a critical determinant of galectin-3 binding modes.
• GaMD simulations effectively capture complex ligand-binding mechanisms.
• Findings inform the rational design of galectin-3-targeting cancer therapies.