Development of computational methods for the analysis of protein structure using data from chemical cross-linking mass spectrometry

Sinnott, Matthew James (2021) Development of computational methods for the analysis of protein structure using data from chemical cross-linking mass spectrometry. PhD thesis, Birkbeck, University of London.

Abstract

Chemical Crosslinking Mass Spectrometry (XLMS) is a method which is gaining in popularity for the modelling of protein structures. The distance and residue exposure restraints generated from an XLMS experiment provide useful information for positioning of residues in a protein structure. Previous work in the Topf and Thalassinos labs has produced computational tools to utilise the distance and residue exposure information contained in crosslinks through the Matched and Non- Accessible Crosslink (MNXL) and Complex MNXL (cMNXL) scores. These scores leverage both of these properties through the use of Solvent Accessible Surface Distances (SASDs), calculated using Jwalk (also developed in the Topf and Thalassinos labs). In this thesis I extend our suite of tools to use information from monolinks, a by-product of an XLMS experiment which acts as a chemical label indicating that a residue is exposed to solvent. I describe the Monolink Depth Score (MoDS) for scoring model protein structures using chemical labelling information using the residue depth of the modified residues. I benchmark this score on two separate targetdecoy protein structure datasets, a large dataset onto which crosslinks and monolinks are simulated and a smaller one containing experimentally derived XLMS data. Through this analysis I show that MoDS can provide comparable model scoring performance with MNXL, and that combining MNXL and MoDS can lead to greater model scoring performance. Further to this, I also describe my efforts to integrate our model scoring tools through the Crosslink Modelling Tools (XLM-Tools) package and accompanying webserver. In the final results chapter we employ tools from our lab and other labs to the modelling of the Nucleotide Free state of the Human Kinesin V motor domain using Quantitative XLMS (qXLMS) data. With this information we show the flexibility of the Neck Linker region responsible for initiating the power stroke driving the movement of the motor domain upon ATP hydrolysis.

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