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In molecular dynamics (MD) simulation, force field determines the capabilityof an individual model in capturing physical and chemistry properties. Themethod for generating proper parameters of the force field form is the keycomponent for computational research in chemistry, biochemistry, andcondensed-phase physics. Our study showed that the feasibility to predictexperimental condensed phase properties (i.e., density and heat ofvaporization) of methanol through problem specific force field from onlyquantum chemistry information. To acquire the satisfying parameter sets of theforce field, the genetic algorithm (GA) is the main optimization method. Forelectrostatic potential energy, we optimized both the electrostatic parametersof methanol using the GA method, which leads to low deviations of between thequantum mechanics (QM) calculations and the GA optimized parameters. Weoptimized the van der Waals (vdW) parameters both using GA and guided GAmethods by calibrating interaction energy of various methanol homo-clusters,such as nonamers, undecamers, or tridecamers. Excellent agreement between thetraining dataset from QM calculations (i.e., MP2) and GA optimized parameterscan be achieved. However, only the guided GA method, which eliminates theoverestimation of interaction energy from MP2 calculations in the optimizationprocess, provides proper vdW parameters for MD simulation to get the condensedphase properties (i.e., density and heat of vaporization) of methanol.Throughout the whole optimization process, the experimental value were notinvolved in the objective functions, but were only used for the purpose ofjustifying models (i.e., nonamers, undecamers, or tridecamers) and validatingmethods (i.e., GA or guided GA). Our method shows the possibility of developingdescriptive polarizable force field using only QM calculations.

Methodology of Parameterization of Molecular Mechanics Force Field From  Quantum Chemistry Calculations using Genetic Algorithm: A case study of  methanol