Repeat proteins represent an important class of proteins which, in nature, have been used for a variety of functions including scaffolds and high affinity binders. Many repeat proteins in nature are used as dynamic protein scaffolds. Repeat proteins display unique folding properties whereby, each repeat domain folds largely independently of the overall protein, only interacting with its nearest neighbours. Accordingly, each repeat domain adopts different conformations depending on the context it is found in. Recently improvements in methods targeted at rapidly designing de novo repeat proteins have been developed, however, incorporating the dynamic aspects of these proteins into the design has largely been ignored. Here we simulated and analysed a series of repeat protein domains to assess their dynamics and classify the resulting ensemble of structures into a small representative set of conformations. To accomplish this, we utilised metrics such as RMSD and developed Dynamatch, a python tool which maps structural perturbations to rigid body transforms, to extract dynamic information from each domain. Analysing structural conformations from each domain we demonstrate that they were most commonly found in conformations deviating little from the reference structure. Comparison of the behaviours of modules in different contexts was shown to have an impact on the conformational set they were able to sample. We aim to use information gained on the dynamic properties of these repeat domains to better guide the design of repeat proteins with an emphasis on enabling design towards more functional proteins.
|Date of Award||24 Mar 2020|
- The University of Bristol
|Supervisor||Fabio Parmeggiani (Supervisor) & J L R Anderson (Supervisor)|