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Improved Biomolecular Crystallography at Low Resolution with the Deformable Complex Network Approach

Posted on:2013-09-09Degree:M.SType:Thesis
University:Rice UniversityCandidate:Zhang, ChongFull Text:PDF
GTID:2450390008475170Subject:Theoretical Physics
Abstract/Summary:
It is often a challenge to atomically determine the structure of large macromolecular assemblies, even if successfully crystallized, due to their weak diffraction of X-rays. Refinement algorithms that work with low-resolution diffraction data are necessary for researchers to obtain a picture of the structure from limited experimental information. Relationship between the structure and function of proteins implies that a refinement approach delivering accurate structures could considerably facilitate further research on their function and other related applications such as drug design.;Here a refinement algorithm called the Deformable Complex Network is presented. Computation results revealed that, significant improvement was observed over the conventional refinement and DEN refinement, across a wide range of test systems from the Protein Data Bank, indicated by multiple criteria, including the free R value, the Ramachandran Statistics, the GDT (<1A) score, TM-score as well as associated electron density map.
Keywords/Search Tags:Deformable complex network
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