Force fields, Molecular Mechanics GROMOS

The kind of energy terms, their functional form, and how carefully (number, quality, and kind of reference data) the parameters were derived determine the quality of a force field. Accurate force fields exist for organic molecules (e.g., MM2, MM3), but more approximate force fields (e.g., with fixed bond distances) optimized for computational speed rather than accuracy [e.g., AMBER (assisted model building with energy refinement), CHARMM (chemistry at Harvard molecular mechanics), GROMOS (Groningen molecular simulation)] are the only practical choice for the treatment of large biomolecules. The type of molecular system to be smdied determines the choice of the force field. 

AMI AMBER A Program for Simulation of Biological and Organic Molecules CHARMM The Energy Function and Its Parameterization Combined Quantum Mechanics and Molecular Mechanics Approaches to Chemical and Biochemical Reactivity Density Functional Theory (DFT), Hartree-Fock (HF), and the Self-consistent Field Divide and Conquer for Semiempirical MO Methods Electrostatic Catalysis Force Fields A General Discussion Force Fields CFF GROMOS Force Field Hybrid Methods Hybrid Quantum Mechanical/Molecular Mechanical (QM/MM) Methods Mixed Quantum-Classical Methods MNDO MNDO/d Molecular Dynamics Techniques and Applications to Proteins OPLS Force Fields Parameterization of Semiempirical MO Methods PM3 Protein Force Fields Quantum Mechanical/Molecular Mechanical (QM/MM) Coupled Potentials Quantum Mecha-nics/Molecular Mechanics (QM/MM) SINDOI Parameterization and Application. 

MD simulations provide a detailed insight in the behavior of molecular systems in both space and time, with ranges of up to nanometers and nanoseconds attainable for a system of the size of a CYP enzyme in solution. However, MD simulations are based on empirical molecular mechanics (MM) force field descriptions of interactions in the system, and therefore depend directly on the quality of the force field parameters (92). Commonly used MD programs for CYPs are AMBER (93), CHARMM (94), GROMOS (95), and GROMACS (96), and results seem to be comparable between methods (also listed in Table 2). For validation, direct comparisons between measured parameters and parameters calculated from MD simulations are possible, e.g., for fluorescence (97) and NMR (cross-relaxation) (98,99). In many applications where previously only energy minimization would be applied, it is now common to perform one or several MD simulations, as Ludemann et al. and Winn et al. (100-102) performed in studies of substrate entrance and product exit. 

Standard molecular mechanics (MM) methods (e.g. the popular force fields developed for AMBER, CHARMM and GROMOS decribed in Section 2 above) provide a good description of protein structure and dynamics, but cannot be used to model chemical reactions. This limitation is due their simple functional forms (e.g. harmonic terms for bond stretching) and inability to model changes in electronic polarization (because of the invariant point partial atomic charge used by these molecular mechanics methods to represent electrostatic interactions). 

Many different force fields are now available from commercial and other sources. Some force fields like the MM series of force fields developed by Allinger and the Merck MM [10] have been parameterized primarily for molecular mechanics and dynamics of small molecules. Due to their limited importance for polymer simulations, they will not be covered in this section however, they have been used to study conformational properties of model compounds for some aromatic polymers. In some cases, force fields primarily developed for biomolecules such as AMBER, CHARMM, and GROMOS have been used in the molecular simulation of polymeric systems. Force fields having particular importance for polymers include simple but versatile... 

As in any molecular level simulation one of the first decisions to make is what inter- and intramolecular force field to use. We have basically two choices. Firstly, we can set about bringing together as much information as possible from experiment and quantum mechanical calculations to develop good force fields and in this way to aim for quantitatively accurate modeling. With this approach there is usually little alternative, but to employ a fully atomic representation with, for instance, the GROMOS force field. ° It must be remembered however that no force field will be completely accurate and all of them have limitations. 

---