ZMM

ZMM models molecular systems and performs ligand-protein docking using physics-based force fields and an atom-atom solvent exposure- and distance-dependent dielectric (SEDDD) function to investigate binding interactions in small molecules, peptides, proteins, nucleic acids, and ligand-receptor complexes.

Key Features:

• Physics-Based Force Fields: Utilizes physics-based force fields to model interactions within molecular systems.
• SEDDD Function: Implements an atom-atom solvent exposure- and distance-dependent dielectric (SEDDD) function that combines electrostatic interactions and dehydration energy components to represent dielectric permittivity variation between protein cores and bulk water.
• Docking Methodology: Employs a seeding stage with precomputed libraries of ligand conformers to sample hundreds of thousands of positions and orientations within a rigid protein framework, followed by a refinement stage that subjects the top ten lowest-energy structures to Monte Carlo minimization allowing ligand flexibility and protein adaptability.
• Success Criteria: Defines a successful docking search as when the RMSD of ligand atoms in the apparent global minimum from the X-ray structure is less than 2 Ångströms.

Scientific Applications:

• Molecular interaction studies: Models interactions across small molecules, peptides, proteins, nucleic acids, and ligand-receptor complexes for theoretical investigation.
• Drug discovery and lead optimization: Predicts binding poses and aids in estimating binding affinities to support lead compound optimization.

Methodology:

Seeding uses precomputed ligand-conformer libraries to sample hundreds of thousands of positions and orientations in a rigid protein framework; the top ten lowest-energy structures are refined by Monte Carlo minimization permitting ligand flexibility and protein adaptability; the SEDDD function (electrostatics plus dehydration energy) was validated on 60 ligand-protein complexes against various distance-dependent dielectric (DDD) functions and solvent-exclusion energy models, showing a 20% increase in success rate versus the best traditional DDD, particularly for surface sites (success defined as RMSD < 2 Ångströms).