AUTOMATED FORCE FIELD PARAMETERIZATION FOR NON-POLARIZABLE AND POLARIZABLE ATOMIC MODELS BASED ON AB INITIO TARGET
1Department of Biochemistry and Molecular Biology University of Chicago 929 East 57th Street, Chicago, IL 60637.
Journal of Chemical Theory and Computation
|November 14, 2013
Summary
General Automated Atomic Model Parameterization (GAAMP) creates accurate molecular models for simulations. This method uses quantum mechanics to generate force field parameters, improving biological system studies.
Area of Science:
- Computational Chemistry
- Biophysics
- Molecular Modeling
Background:
- Molecular dynamics (MD) simulations are crucial for studying biological systems.
- Accurate molecular mechanical force fields are essential for reliable MD simulation results.
- Current force fields (e.g., AMBER, CHARMM) have limited coverage for non-standard molecules, necessitating parameterization by analogy, which can reduce accuracy.
Purpose of the Study:
- To introduce a novel automated method, General Automated Atomic Model Parameterization (GAAMP), for generating accurate atomic model parameters for small molecules.
- To leverage *ab initio* quantum mechanical (QM) calculations as target data for parameterization.
- To improve the accuracy and applicability of force fields for diverse chemical compounds in biomolecular simulations.
Main Methods:
- GAAMP automatically generates force field parameters using QM data.
- Electrostatic parameters (partial charges, polarizabilities, shielding) are optimized against QM electrostatic potential (ESP) and interaction energies with water.
- Soft dihedrals are identified and parameterized by targeting QM dihedral scans and stable conformer energies.
- Previously developed force fields serve as an initial guess, with options for optimizing final parameters.
Main Results:
- The GAAMP method was validated by calculating solvation free energies for over 200 small molecules.
- MD simulations were performed on three different proteins using parameters generated by GAAMP.
- The results demonstrate the method's capability to produce accurate parameters for diverse molecules.
Conclusions:
- GAAMP provides an automated and accurate approach for generating molecular mechanical force field parameters.
- The method enhances the reliability of MD simulations for a wider range of biological and chemical systems.
- This work facilitates more precise atomistic modeling of complex biological molecules.
