Klein, Kevin; (2025) Structural analysis and self-assembly simulations of collagen I fibrils. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Collagens are ubiquitous proteins found throughout the animal kingdom, playing critical roles in a variety of tissues including the dermis, bone, tendon, and extracel- lular matrix. Their evolutionary significance is underscored by evidence suggesting collagens may have been pivotal for the emergence of multicellular life. An iconic hallmark of collagen type I, the most studied type in the collagen superfamily, is its ability to self-assemble into fibrils with a distinct striped pattern. Despite being discovered almost a century ago, both the mechanisms driving the self-assembly into fibrils featuring this pattern as well as its detailed microscopic origins remain incompletely understood. This thesis addresses these gaps through computational and theoretical ap- proaches. First, we develop coarse-grained molecular dynamics simulations to model fibrillar self-assembly, complemented by an automated toolset for simula- tion analysis. We demonstrate the utility of this framework in three collaborative experimental studies in chapters 3–5, where our insights help to increase the broader understanding of both collagen and collagen-like peptides. In the last chapter, we develop a statistical model to explore collagen fibril microstructure. By sampling a vast configuration space, we find that fibril mor- phology may be much more heterogeneous and variable than previously assumed. We combine our model with experimental data to deliver arguments supporting the hypothesis that collagen fibrils are dynamic assemblies governed by a probability distribution of microscopic configurations, challenging the classic assumption of a quasi-crystalline structure. This structural adaptability may underlie their functional versatility in diverse tissues. Collectively, our work advances the understanding of collagen self-assembly and microstructure, offering tools and paradigms for future research. The method- ologies developed here could further inspire broader applications in biomaterials and tissue engineering.

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