DICE

DICE performs configurational bias Monte Carlo (CBMC) simulations of flexible, fragment-based molecules to sample solute–solvent systems across liquid, gas, and interfacial phases and to generate configurations for sequential QM/MM (S-QM/MM) calculations.

Key Features:

• Configurational Bias Monte Carlo (CBMC): Implements enhanced CBMC methodologies for sampling flexible molecules using molecular fragments and a simplified acceptance criterion.
• Fragment-Based Modeling: Represents flexible molecules as molecular fragments to enable efficient conformational sampling.
• Phase and Interface Coverage: Simulates solute–solvent systems in liquid and gas phases and at gas–liquid and solid–liquid interfaces.
• S-QM/MM Configuration Generation: Produces configurations intended for sequential quantum mechanics/molecular mechanics (S-QM/MM) calculations.
• Validation Against Reference Data: Validates simulations by comparison with molecular dynamics (MD) simulations, experimental data, and other theoretical results.
• Efficiency Analysis: Evaluates conformational sampling efficiency using acceptance rates for alkanes including n-octane, neopentane, and 4-ethylheptane.
• Complex Molecule Handling: Simulates moderately sized molecules (up to ~150 atoms) such as boron subphthalocyanine while enforcing Boltzmann thermodynamic equilibrium sampling.

Scientific Applications:

• Solute–Solvent Interaction Studies: Theoretical investigation of how solvent interactions modify solute properties across phases and interfaces.
• S-QM/MM Preparatory Sampling: Generation of ensemble configurations for sequential QM/MM calculations.
• Interfacial Phenomena: Study of molecular behavior at gas–liquid and solid–liquid interfaces.
• Conformational Sampling Assessment: Analysis of sampling efficiency and acceptance rates for alkanes and related molecules.
• Method Validation: Comparative validation of Monte Carlo results against MD, experimental measurements, and other theoretical approaches.

Methodology:

Uses configurational bias Monte Carlo with molecular fragments and a simplified CBMC acceptance criterion to sample conformations, generates configurations for S-QM/MM, evaluates acceptance rates for conformational efficiency, and validates results against MD simulations, experimental data, and other theoretical results while enforcing Boltzmann equilibrium sampling.