GOKNOT · Modelling the formation of a gordian knot in Human Ubiquitin Hydrolase

Modelling the formation of a gordian knot in Human Ubiquitin Hydrolase

Since about two decades the scientific community has discovered proteins that exhibit a self-entangled native structure. The folding of such knotted proteins is a challenging research topic of great interest in biology and biophysics. A complete understanding on how these proteins form topologically complex structures would unveil interesting details on the general paradigm of protein folding and, on top of this, enlighten the rationale behind the folding and misfolding of a class of proteins related to crucial biophysical functions in the human body. In this field, computer simulations have greatly contributed to advance our comprehension of the mechanisms that allow a polypeptide to form a knot during the folding. However, due to limitations in methods and resources, the state-of-the-art picture on the process is still incomplete, and mostly limited to the simplest nontrivial topology, the trefoil knot. The main objective of this action was to computationally investigate the folding of entangled proteins, in particular of human Ubiquitin C-terminal Hydrolase, whose backbone forms a Gordian knot with five crossings. The chosen methods are based on a multi-scale Molecular Dynamics strategy that combines coarse grained and all-atom models with enhanced sampling. The coarse grained model is employed to outline a general picture of the folding, and devise the preferential pathways and intermediate states. Building on this low resolution knowledge, a full-atom representation of the system can be built, targeting these more precise calculations to the most relevant regions of the protein's free energy landscape. To lift the computational time limitations of such an approach, the project proposes to employ enhanced sampling techniques such as Metadynamics and Variationally Enhanced Sampling. These advanced methodologies can drive the molecular dynamics algorithm to generate rare, but extremely relevant configurations for the study of protein folding, thus accelerating the calculations. The output of the project will generalize the current picture on knotted protein folding, introducing important methodological advancements, and contributing to the knowledge on a system of great biomedical interest, connected to diseases such as Parkinson's and Alzheimer's.

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