%0 Journal Article %1 duaber.signal.processcing.1996 %A Dauber-Osguthorpe, Pnina %A Maunder, Colette M. %A Osguthorpe, David J. %D 1996 %J J Comput Aided Mol Des. %K frequency method processing signaling %P 177-85 %T Molecular dynamics: deciphering the data. %V 10 %X The dynamic behaviour of molecules is important in determining their activity. Molecular dynamics (MD) simulations give a detailed description of motion, from small fluctuations to conformational transitions, and can include solvent effects. However, extracting useful information about conformational motion from a trajectory is not trivial. We have used digital signal-processing techniques to characterise the motion in MD simulations, including: calculating the frequency distribution, applying filtering functions, and extraction of vectors defining the characteristic motion for each frequency in an MD simulation. We describe here some typical results obtained for peptides and proteins. The nature of the low-frequency modes of motion, as obtained from MD and normal mode (NM) analysis, of Ace-(Ala)31-Nma and of a proline mutant is discussed. Low-frequency modes extracted from the MD trajectories of Rop protein and phospholipase A2 reveal characteristic motions of secondary structure elements, as well as concerted motions that are of significance to the protein's biological activity. MD simulations are also used frequently as a tool for conformational searches and for investigating protein folding/unfolding. We have developed a novel method that uses time-domain filtering to channel energy into conformational motion and thus enhance conformational transitions. The selectively enhanced molecular dynamics method is tested on the small molecule hexane.

@article{duaber.signal.processcing.1996, abstract = {The dynamic behaviour of molecules is important in determining their activity. Molecular dynamics (MD) simulations give a detailed description of motion, from small fluctuations to conformational transitions, and can include solvent effects. However, extracting useful information about conformational motion from a trajectory is not trivial. We have used digital signal-processing techniques to characterise the motion in MD simulations, including: calculating the frequency distribution, applying filtering functions, and extraction of vectors defining the characteristic motion for each frequency in an MD simulation. We describe here some typical results obtained for peptides and proteins. The nature of the low-frequency modes of motion, as obtained from MD and normal mode (NM) analysis, of Ace-(Ala)31-Nma and of a proline mutant is discussed. Low-frequency modes extracted from the MD trajectories of Rop protein and phospholipase A2 reveal characteristic motions of secondary structure elements, as well as concerted motions that are of significance to the protein's biological activity. MD simulations are also used frequently as a tool for conformational searches and for investigating protein folding/unfolding. We have developed a novel method that uses time-domain filtering to channel energy into conformational motion and thus enhance conformational transitions. The selectively enhanced molecular dynamics method is tested on the small molecule hexane.}, added-at = {2009-01-15T03:42:35.000+0100}, author = {Dauber-Osguthorpe, Pnina and Maunder, Colette M. and Osguthorpe, David J.}, biburl = {https://www.bibsonomy.org/bibtex/252a89fe31178154ac81da335114645d7/huiyangsfsu}, description = {folding.bib}, interhash = {275150c9daca1574a722bc06364daa34}, intrahash = {52a89fe31178154ac81da335114645d7}, issue = {3}, journal = {J Comput Aided Mol Des.}, keywords = {frequency method processing signaling}, month = Jun, pages = {177-85}, timestamp = {2009-01-15T03:42:35.000+0100}, title = {Molecular dynamics: deciphering the data.}, volume = 10, year = { 1996} }