Force Field Improvements

A force field for solid state modeling of fluoropolymers predicted a suitable helical conformation but required further improvement in describing intermole-cular effects. Though victory cannot yet be declared, the derived force fields improve substantially on those previously available. Preliminary molecular dynamics simulations with the interim force field indicate that modeling of PTFE chain behavior can now be done in an all-inclusive manner instead of the piecemeal focus on isolated motions and defects required previously. Further refinement of the force field with a backbone dihedral term capable of reproducing the complex torsional profile of perfluorocarbons has provided a parameterization that promises both qualitative and quantitative modeling of fluoropolymer behavior in the near future. 

There is continuous progress in molecular dynamics and energy minimization. The main topics are force field improvement [26,53-56], incorporation of effective solvation term [57], b Initio modeling of small protein [49—5155.59], the incorporation of real data for x-ray refinement [60] and NMR structure determination [61], However, much work still has to be done to improve the force fields used for ensr"1 calculations before sn,r but trivial errors be detected... 

The first driver for the adoption of modelling software was the ability to provide helpful visualisations even now, a graphics workstation with a stereo display is a must-see for any open day. The appreeiation of the numerieal power of modelling calculations came later, as force fields improved. There is still the issue of the most effective way to represent a moleeule a reeeptor sees a dynamic cloud of electrons, but often we need to represent the same... 

Horta, B. A. C., P. F. J. Fuchs, W. F. van Gunsteren, and P. H. Hunenberger. 2011. New interaction parameters for oxygen compounds in the GROMOS force field Improved pure-liquid and solvation properties for alcohols, ethers, aldehydes, ketones, carboxylic acids, and esters. Journal of Chemical Theory and Computation. 7, 1016. 

The need for high-quality force field parameters is critical to rapidly generate accurate smaU-molecule conformations, which are needed for reliable computational CSP. In this chapter, we presented specific force field improvements that lead to better smaU-molecule conformations for close S O and halogen X - O interactions. We customized the force field by fitting to quantum mechanical data and comparing with conformations from the CSD, which is a general approach that can be extended... 

Although least-squares based parameterization tools have been used for the derivation of the CFF, MM3/MM4, and MMFF force fields, improved methodology and software development is continuing. This will eliminate (or at least reduce) the need for human intervention in the parameterization process, and this will consequently speed the development of force fields for new functional groups and for all of the systems to which new force fields are being applied. Moreover, improvements in the accuracy of experimental measurements and quantum mechanical calculations are likely to continue for a long time, and the use of more fully automated parameterization tools will allow this new data, as well as new functional forms, to be rapidly incorporated into widely used force fields. 

While simulations reach into larger time spans, the inaccuracies of force fields become more apparent on the one hand properties based on free energies, which were never used for parametrization, are computed more accurately and discrepancies show up on the other hand longer simulations, particularly of proteins, show more subtle discrepancies that only appear after nanoseconds. Thus force fields are under constant revision as far as their parameters are concerned, and this process will continue. Unfortunately the form of the potentials is hardly considered and the refinement leads to an increasing number of distinct atom types with a proliferating number of parameters and a severe detoriation of transferability. The increased use of quantum mechanics to derive potentials will not really improve this situation ab initio quantum mechanics is not reliable enough on the level of kT, and on-the-fly use of quantum methods to derive forces, as in the Car-Parrinello method, is not likely to be applicable to very large systems in the foreseeable future. 

Inadequate availability of experimental data can considerably inhibit the development of improved energy functions for more accurate simulations of energetic, structural, and spectroscopic properties. This has led to the development of class II force fields such as CFF and the Merck Molecular Force Field (MMFF), which are both based primarily on quantum mechanical calculations of the energy surface. The purpose of MMFF, which has been developed by Thomas Halgren at Merck and Co., is to be able to handle all functional groups of interest in pharmaceutical design. 

Note All of the force fields provided in HyperChem are built on new irn picm en tatiori s of foree fields developed by various com pii-tational chemistry research groups. How-ever, HyperChem improves on the original force fields and uses new code. 

DREIDING is an all-purpose organic or bio-organic molecule force field. It has been most widely used for large biomolecular systems. It uses five valence terms, one of which is an electrostatic term. The use of DREIDING has been dwindling with the introduction of improved methods. 

Empirical conformational energy program for peptides (ECEPP) is the name of both a computer program and the force field implemented in that program. This is one of the earlier peptide force fields that has seen less use with the introduction of improved methods. It uses three valence terms that are fixed, a van der Waals term, and an electrostatic term. 

MMl, MM2, MM3, and MM4 are general-purpose organic force fields. There have been many variants of the original methods, particularly MM2. MMl is seldom used since the newer versions show measurable improvements. The MM3 method is probably one of the most accurate ways of modeling hydrocarbons. At the time of this book s publication, the MM4 method was still too new to allow any broad generalization about the results. However, the initial published results are encouraging. These are some of the most widely used force fields due to the accuracy of representation of organic molecules. MMX and MM+ are variations on MM2. These force fields use five to six valence terms, one of which is an electrostatic term and one to nine cross terms. 

Tliroughout this chapter and in Table 1 the inclusion of QM results as target data is evident, with the use of such data in the optimization of empirical forces fields leading to many improvements. Use of QM data alone, however, is insufficient for the optimization of parameters for condensed phase simulations. This is due to limitations in the ability to perform QM calculations at an adequate level combined with limitations in empirical force fields. As discussed above, QM data are insufficient for the treatment of dispersion... 

We have presented a simple protocol to run MD simulations for systems of interest. There are, however, some tricks to improve the efficiency and accuracy of molecular dynamics simulations. Some of these techniques, which are discussed later in the book, are today considered standard practice. These methods address diverse issues ranging from efficient force field evaluation to simplified solvent representations. 

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