Project Description
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The relationship between the structure of a protein and its function is vital to understanding how molecules give rise to biological effects. There is an emerging realization that the flexibility and dynamics of proteins in many cases drives their functional activity. McManus, a student of Walker, ABW, cosupervised by Van Den Elsen, JVdE, Crennell, SJC, and Stephen Wells, SAW, Chemical Engineering at Bath, has developed a user friendly implementation of the computationally-efficient Framework Rigidity Optimised Algorithm, FRODA, that explores the flexibility of protein structures, based on codes written by SAW. This code is initiated by experimental structures from the Protein Data Bank, PDB, accessed by the open source software Rosetta. It gives protein structures that retain atomic level resolution in regions of the protein critical for its functionality, without the need for computer resource intensive molecular dynamics, MD, methods and has been used to study commercially available antiviral drugs which target HIV-1 protease. Our FRODA code has an improved treatment of non-covalent interactions. Salt bridges are now included, and have been shown to affect connectivity measures such as rigidity fractions in a study of thermostability of citrate synthase enzymes in temperate environments (publication in progress).
The student in this proposal will develop McManus’ code to create a virtual tool for modelling antibody structures. Therapeutic interventions based on antibodies require understanding of the antibody-antigen interactions at a molecular level. Experimental structure determination is time-consuming and costly so is not practical for the many variants of an antibody under optimization, nor is ab initio modelling of protein structure yet tractable. Modelling of antibody structures is feasible since the antigen recognition area, the Complementarity-Determining Regions (CDR), comprises 6 loops attached to an Fv scaffold, a stable recognizable antibody fragment. The student will identify suitable scaffolds from the PDB, and add flexible CDR loops allowing for known constraints. We will investigate alterations of structure at the macro level, such as rotations between scaffold domains, which may be vital for recognition by affecting how the antibody interacts with antigens.
Enhanced sampling MD simulation will identify precise bonding sites and predict antibody-antigen interactions. Other immune system proteins, such as Major Histocompatibility Complexes and T cell receptors whose structures follow a similar pattern of conserved framework and small interaction area, will be addressed. The student will work with Van der Kamp, MvdK, on development of enhanced sampling MD protocols to ascertain antibody-antigen binding, starting from the FRODA structures with the antigen docked in. The aim is to find realistic, low-energy conformations of the antibody loops interacting with the antigen. Techniques will be explored to establish best-practice and develop a computationally efficient protocol. Global structural changes will be informed by the FRODA results, e.g. using targeted molecular dynamics to drive the conformational transition in a physically accurate manner. Locally enhanced sampling, combined with accelerated molecular dynamics and simulated annealing, will be used for loop position optimization around the antigen. Protocols will be automated for use as part of the virtual tool.
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