Energy Minimization on Manifolds for Docking Flexible Molecules.

Area of Science:

• Computational chemistry
• Molecular modeling
• Biophysics

Background:

• Minimizing energy in interacting flexible molecules is computationally challenging.
• Existing methods often treat molecules as rigid or have limitations in handling flexibility.
• Integrating ligand positional/orientational changes with internal bond rotations is crucial for accurate modeling.

Purpose of the Study:

• To extend a manifold-based rigid body minimization algorithm for flexible molecular energy minimization.
• To integrate ligand six-dimensional rotational/translational space with internal rotations around rotatable bonds.
• To demonstrate the algorithm's effectiveness in molecular docking problems with varying complexity.

Main Methods:

• Extension of a rigid body minimization algorithm defined on manifolds.
• Incorporation of rotational degrees of freedom for ligands into the optimization search space.
• Application to three docking problems: fragment-ligand to protein mapping, flexible ligand-rigid receptor docking, and flexible ligand-flexible receptor docking.

Main Results:

• The manifold optimization algorithm significantly improves computational efficiency compared to traditional all-atom methods.
• The method achieves comparable solution quality to existing approaches.
• Demonstrated effectiveness across increasing complexities of molecular docking scenarios.

Conclusions:

• The developed manifold optimization approach offers a more efficient way to minimize the energy of interacting flexible molecules.
• The method is general and applicable to a wide range of molecular modeling tasks, including protein-protein interactions.
• Open-source code is available for integration into existing molecular modeling packages.