Houston, TX 77005
12:45 p.m. Monday, Oct. 7, 2013
On Campus | Alumni,
As volumes of macromolecular complexes increase, methods that deal with X-ray crystallography at low resolution are of particular interest. With limited diffraction data in hand, experimentalists rely on advanced theoretical and computational tools to extract and utilize as much useful information as possible, in order to determinate a three dimensional model that best fits the experiment data. Success of further technical analysis on the function of a specific macromolecule – the key to practical applications – is therefore heavily dependent on the validity and accuracy of the solved structures. In this thesis we introduce the Deformable Complex Network (DCN) and Normal Mode Analysis (NMA), which are designed to model the average coordinates of atoms and associated fluctuations. Their applications on structure determination target two major branches – the positional refinement and temperature factor refinement, respectively. We demonstrate their performance in structure improvements based on several criteria, such as the free R value, overfitting effect and Ramachandran Statistics, with tests carried out across a range of real systems for generality and consistency purpose.