Understanding proteins folding mechanism : precursors and fingerprints. - Chua, Khi Pin. (2013)
This thesis aims to understand the mechanism of protein folding from the statistical viewpoint by using the measure of Pearson's correlation coefficient(PCC). Protein folding is one of the most actively researched field, yet its mechanism is still a mystery to scientists. Understanding the mechanism is vital to the medical field as protein misfolding is known to be the cause of various diseases like Parkinson and Alzheimer disease. Besides, being able to pinpoint the protein folding pathway will provide a significant breakthrough in the field of medical drug design. The correlations between angles of residues (which is defined later) are calculated to study the dynamics between the residues. Three simulated polyalanine peptides that folded into fi-helices are studied, namely Q, K and D that only differ among themselves in two substituted residues in each amino acid sequence. D has the lowest fi- helical content among the three peptides and is considered to be only partially folded. We look for precursors preceding the folding process and fingerprints in the correlation time series. It is found that there are a number of common precursors between the three pep- tides. One important precursor involving the substituted residue is present in both protein Q and K, but notably absent in D. The precursor could be the key to the partial folding attempt in D. PCC method also captures the fingerprints characterizing the folded states of the peptides. Cross checking the time where the fingerprints start appearing with the pictures of molecules drawn in VMD(Visual Molecular Dynamics) confirms our finding. We can also see interesting patterns in the trajectory and fluctuation of the cosine of angles between residues involved in the important precursor mentioned above. The patterns imply phase transitions surrounding the period of the precursors.