Narrow Results

The application of the multicanonical simulation method to small proteins and peptides seems to be feasible and should be undertaken. In this work, the three-dimensional structures of five common tetrapeptide sequences (QPGQ, QSGQ, YPTS, SPQQ and QPGY, in one letter code) in the repetitive central domain of HMW glutenin subunits are investigated by using the multicanonical simulation procedure. Ramachandran plots were prepared and analyzed to predict the relative occurrence probabilities of β-turn and γ-turn structures and helical states. Structural predictions of the five tetrapeptide sequences indicated the presence of high level of β-turns and considerable level of γ-turns. It was also possible to distinguish different type of turns and their occurrence probabilities.

The three-dimensional structures of two hexapeptide repeat motifs (PGQGQQ and SGQGQQ, in one letter code) in the repetitive central domain of HMW glutenin subunits are investigated by using the multicanonical simulation procedure. Ramachandran plots were prepared and analyzed to predict the relative occurrence probabilities of β-turn and γ-turn structures and helical state. Structural predictions of PGQGQQ repeat motif indicated the presence of high level of β-turns and considerable level of γ-turns. Simulations of the repeat motifs in the repetitive central domain of HMW glutenin subunits indicated that these structures take important part in the three-dimensional structures of repeat motifs.

We propose a hybrid algorithm, which combines the features of the energy landscape paving (ELP) and Monte Carlo Minimization (MCM) methods. We have tested its performance in studying the low-energy conformations of the heptapeptide deltorphin.

A combination of replica exchange Monte Carlo sampling techniques and energy landscape paving approach is presented. This hybrid algorithm combines the features of the energy landscape paving (ELP) and replica exchange methods (REM). I have tested its performance in studying the low-energy conformations of the benchmark peptide Met-enkephalin.

Molecular dynamics simulation is performed to investigate self-insertion behaviors of peptides into single-walled carbon nanotubes (SWCNTs) in water environment. Peptides of different hydrophobicities and varied lengths are tested to show that the propensities of peptides to self-insert into SWCNTs differ drastically. Our results indicate that there exists a potential well for the system of SWCNT and peptide that is able to self-insert into the nanotube. Further investigations of energy components demonstrate that electrostatic interactions, combined with van der Waals interactions, play dominant roles in the self-insertion of peptides into nanotubes. In addition, we also observe a significant correlation between the propensity of a peptide to insert into nanotube and its hydrophobicity. Such results provide valuable information on the potential applications of carbon nanotubes in the fields of drug delivery, drug design and protein control, etc.