Abstract
The molecular dynamics simulation method was used to investigate the structural details for human prion protein (PrPN) and its D178N mutant (PrPM). Root-mean-square fluctuations (RMSFs) and the root-mean-square deviations (RMSDs) showed an increase in the flexibility and high dynamic plasticity of PrPM. Average Total energy for PrPM and PrPN sequentially was -2.975 x105 (kJmol-1) and -3.193 x 105 (kJmol-1). The results showed conformational rearrangement susceptibility for PrPM. For PrPM, highly surface-exposed Glu196 and Arg136 caused hydrogen bond weakening and electrostatic interactions changes in salt bridges. Hydrogen bond weakening under mutation can be mentioned as the leader of conformational changes and disease-related conversions. Contrary to some reports, the contributions of electrostatic interactions of Glu146–Arg208 and Arg156–Glu196 salt bridges for PrPN is less than of these interactions for PrPM. These interactions can pave the way to conformational changes in PrPM. The results showed that the role of the hydrogen bonds in the stability of human prion protein is more important than these salt bridges. The calculation of the solvent accessible surface area showed that the conformational plasticity in PrPM is mainly due to Asn residues that were solvent exposed. Conformational changes in the specific amino acids can affect metal-ion occupancy and function. The secondary structure has also showed that the structural transition arose from D178N mutation and occurs in specific residues. Our studies support the large scale effects of electrostatic forces at key position 178 of prion. As a result, the conformational rearrangements happen by eliminating only a single negative charge because of the mutation induced global forces in the prion structure. These rearrangements can be considered as a molecular switch, which triggers the initial stages of the conformational transition.
Keywords: MD simulations, human prion protein, D178N mutant, salt bridge, solvent accessible surface area, stability, Homology modeling.