Computer simulations can provide valuable insights into the structure, dynamics, and function of proteins and chemical reactions in solution. Undoubtedly, the key to success underlying these studies is to accurately describe their intramolecular and intermolecular interactions in solution. Empirical molecular mechanics potential functions have traditionally been used for the simulation of such large systems and much effort has been devoted to the parameterization of empirical potentials by studying small, model compounds that mimic the chemical groups in proteins and nucleic acids.
However, there are several well-known deficiencies in the molecular mechanics force fields in use today. First, empirical potential functions are not appropriate for studying chemical processes involving bond formation and breaking, which consist of electronic structural reorganizations. Secondly, electronic polarization effects are typically not treated explicitly in empirical potentials, which severely limit their reliability for describing processes such as substrate-enzyme binding and molecular recognition in aqueous solution. Although polarization terms may be included in the force field, there is no direct experimental data applicable for such a parameterization. Finally, empirical potential functions are not uniquely defined and are difficult to generalize for the application to new systems.
To overcome these difficulties, combined quantum mechanical and molecular mechanical (QM/MM) approaches have been proposed. In these methods, part of the system (for example, a solute molecule in solution or the active site region of an enzyme), is treated quantum mechanically. At the same time, the energy and forces for the remainder of the system (for example, the solvent molecules or rest of the enzyme) are calculated using a molecular mechanics force field. The use of a quantum mechanical method for the central part of the system means that the parameterization of a force field for that part is no longer necessary and, furthermore, means that electronic properties including bond formation/breaking and polarization effects are naturally determined by the molecular wave function. It is likely that advances in the methodology of hybrid QM/MM potentials shall greatly increase our ability to understand and to accurately predict intermolecular interactions in systems of biological interest.
The use of the hybrid QM/MM potential in condensed phase simulations has only become possible very recently, thanks to advances in computer technology, statistical simulation methods, and quantum mechanical computational techniques. The hybrid QM/MM method has great potential in molecular modeling and in simulation to provide a consistent and an accurate description of intermolecular interactions in solution. To date, effort towards development of hybrid QM/MM methods has been largely centered on individual investigators and there has been a lack of meetings at which they can discuss problems specific to the area.
The aim of the minitrack on hybrid quantum and classical mechanical methods at the PSB is to assess the state-of-the-art in the field and to highlight areas for future research by bringing together researchers who develop hybrid simulation algorithms and apply them to biological systems. We are accepting proposals for presentations of papers in any area that is relevant to the development or application of hybrid techniques to biological systems. Paper submission should be made as soon as possible and, in any case, not later than the end of July. All papers will be peer-reviewed and all accepted papers will be published.
For more information, contact the session chairs:
Dr. Martin Field
Institut de Biologie Structurale - Jean-Pierre Ebel
41 Avenue des Martyrs
38027 Grenoble Cedex 1
Telephone: (33) 76 88 95 94
Fax: (33) 76 88 54 94
Dr. Jiali Gao
Department of Chemistry
State University of New York
Buffalo, New York 14214
Telephone: (716) 645-6800 x2102
Fax: (716) 645-6963
Bernard R. Brooks
National Institutes of Health
Bldg 12A, Rm 2007
9000 Rockville Pike
Bethesda, MD 20892
Mark A. Thompson
Environmental Molecular Science Laboratory
Pacific Northwest Laboratory
Richland, WA 99352-0999