Protein structure determination using a database of interatomic distance probabilities |
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Authors: | Wall M E Subramaniam S Phillips G N |
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Affiliation: | Department of Biochemistry and Cell Biology and Keck Center for Computational Biology, Rice University, Houston, Texas 77005-1892, USA. mewall@lanl.gov |
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Abstract: | The accelerated pace of genomic sequencing has increased the demand for structural models of gene products. Improved quantitative methods are needed to study the many systems (e.g., macromolecular assemblies) for which data are scarce. Here, we describe a new molecular dynamics method for protein structure determination and molecular modeling. An energy function, or database potential, is derived from distributions of interatomic distances obtained from a database of known structures. X-ray crystal structures are refined by molecular dynamics with the new energy function replacing the Van der Waals potential. Compared to standard methods, this method improved the atomic positions, interatomic distances, and side-chain dihedral angles of structures randomized to mimic the early stages of refinement. The greatest enhancement in side-chain placement was observed for groups that are characteristically buried. More accurate calculated model phases will follow from improved interatomic distances. Details usually seen only in high-resolution refinements were improved, as is shown by an R-factor analysis. The improvements were greatest when refinements were carried out using X-ray data truncated at 3.5 A. The database potential should therefore be a valuable tool for determining X-ray structures, especially when only low-resolution data are available. |
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Keywords: | knowledge-based modeling low-resolution molecular dynamics structure refinement X-ray crystallography |
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