Proteins are a large group of biomolecules present throughout our bodies, functioning as biochemical catalysts, giving structural integrity to our cells or transporting cargo between them. They are built up of a string of amino acid subunits, where the specific sequence along the string defines the 3-dimensional structure and function of the protein. This process of folding from a 1-dimensional amino acid string into a functional protein is referred to as protein "self-assembly". Most of the time the self-assembly process progresses as planned, but sometimes errors occur, either due to alterations in the amino acid sequence or to the surrounding properties of the protein. This happens for example during the formation of plaques in the brains of Alzheimer's and Parkinson's patients. Studying the process of protein self-assembly can improve the understanding why diseases like this occur. Proteins can also be used as molecular building blocks themselves to construct novel bio-compatible materials.
Due to a very high complexity, protein systems are often simplified when subjected to study. Typically one looks at only a short part of the protein chain. These shorter amino acid sequences are called peptides. It is also possible to alter the sequence of the peptide, to see the role of the individual amino acids, or to completely design an amino acid sequence from scratch to analyse its behaviour.
In my research I study the self-assembly behaviour of the model peptide system AnK. A and K are amino acids and n denotes a certain number of the hydrophobic amino acid alanine. Due to the alanine content the peptides show strong water avoiding characteristics, which in turn, leads to self-assembled ribbons structures in aqueous solutions. Through various scattering and microscopy techniques the structure and colloidal behaviour of these peptide ribbons are analysed, trying to understand the underlying thermodynamics behind size and shape in correlation with amino acid sequence. The underlying goal is to improve the fundamental understanding behind hydrophobic self-assembly, and from a given peptide sequence be able to predict a self-assembled structure.