These changes were incorporated into the program MOPAC2007. Minor changes to the basic MOZYME approach were made in an attempt to reduce the computational requirements. In this work, the entire protein is modeled using semiempirical QM methods in which the self-consistent field (SCF) equations are solved using the localized molecular orbital method MOZYME instead of the more conventional matrix algebra methods. This approach, QM/MM, although complicated because of problems associated with the boundary between the QM and MM regions, has enjoyed considerable success. Īnother, hybrid, approach has been to model the interesting parts of a protein using quantum mechanics (QM), and to model the rest of the system using molecular mechanics (MM). This approach has been applied extensively to biochemical systems. One such technique is the divide-and-conquer method, in which a large molecule is divided into fragments, each of which is relatively easy to manipulate using quantum chemistry methods. Several successful approaches have been developed to reduce the computational effort required for modeling proteins using semiempirical quantum chemical methods. It is only when secondary, tertiary, and quaternary structures are involved that the wide range of properties of proteins becomes apparent, among the more important of which is the ability to catalyze reactions. As such, the primary structure is easily and accurately reproduced by NDDO methods, in particular PM6. At the primary structural level, therefore, proteins can be described in terms of simple covalent bonds and weak hydrogen bonds. But with the exception of photoactive sites of the type that occur in chlorophyll and in retinal-containing proteins, most of the subtle electronic phenomena frequently encountered in transition metal chemistry is absent. Some, for example, cytochrome-P450 and hemoglobin, are more complicated, in that they contain organometallic structures, e.g., the metalloporphyrin heme ring system, while others, such as the structural protein collagen, contain modified residues. Because of these encouraging results, determining the applicability of PM6 to modeling larger biochemical molecules, particularly proteins, was of obvious interest.ĭespite their large size, proteins can be regarded as simple organic compounds, being composed mainly or even entirely of residues of the 20 common amino acids. The recently developed semiempirical method PM6 has been shown to reproduce the heats of formation and geometries of small molecules, simple organic and inorganic crystals, and a hormone-the nonapeptide oxytocin -with good accuracy. They have not, however, enjoyed much success when used for modeling proteins, primarily due to the poor accuracy in reproducing the geometries of large organic systems such as oligopeptides, and to the large computational effort involved. Semiempirical methods, such as MNDO, AM1, and PM3, have been used for a long time for modeling small organic and inorganic systems. A proposed technique for generating accurate protein geometries, starting with X-ray structures, was examined. The applicability of PM6 to model transition states was investigated by simulating a hypothetical reaction step in the chymotrypsin-catalyzed hydrolysis of a peptide bond. Some derived properties, such as pKa and bulk elastic modulus, were also calculated. For most systems, PM6 gave structures in good agreement with the reported X-ray structures. The resulting method was used in the unconstrained geometry optimization of 45 proteins ranging in size from a simple nonapeptide of 244 atoms to an importin consisting of 14,566 atoms. In order to allow the geometries of such large systems to be optimized rapidly, three modifications were made to the conventional semiempirical procedure: the matrix algebra method for solving the self-consistent field (SCF) equations was replaced with a localized molecular orbital method (MOZYME), Baker’s Eigenfollowing technique for geometry optimization was replaced with the L-BFGS function minimizer, and some of the integrals used in the NDDO set of approximations were replaced with point-charge and polarization functions. The applicability of the newly developed PM6 method for modeling proteins is investigated.
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