Protein crystallography plays a critical role in Structure-aided drug design. Because of the low ratio of observed data to refined parameters, macromolecular crystallographic refinement at moderate and low resolution relies heavily on stereochemistry restraints that ensure the correct stereochemistry of the model. This approach inevitably masks fine structural details that are often crucial to the understanding of protein-ligand interactions. To achieve a better description of the geometry, we replaced these stereochemistry restraints with the energy functional derived from quantum-mechanical (QM) treatment. This treatment has been demonstrated with the successful integration of the commercial linear scaling semiempirical QM program DivCon with the Python-based refinement package PHENIX. Based on 5 test structures downloaded from Protein Data Bank (PDB) we report the detailed comparison of the conventional and QM driven refinements. Our preliminary results indicate that incorporation of the QM function not only improves the local geometry but also reduce the R/Rfree factors.

New approach for macromolecular crystallographic refinement: Incorporation of the linear scaling, semiempirical quantum chemical program DivCon into the PHENIX refinement package

242nd National Meeting (2011)

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