title: Evaluation of the influence of amino acid composition on the propensity for collision-induced dissociation of model peptides using molecular dynamics simulations.
abstract: The dynamical behavior of model peptides was evaluated with respect to their ability to form internal proton donor-acceptor pairs using molecular dynamics simulations. The proton donor-acceptor pairs are postulated to be prerequisites for peptide bond cleavage resulting in formation of b and y ions during low-energy collision-induced dissociation in tandem mass spectrometry (MS/MS). The simulations for the polyalanine pentamer Ala(5)H(+) were compared with experimental data from energy-resolved surface induced dissociation (SID) studies. The results of the simulation are insightful into the events that likely lead up to the fragmentation of peptides. Nine-mer polyalanine-based model peptides were used to examine the dynamical effect of each of the 20 common amino acids on the probability to form donor-acceptor pairs at labile peptide bonds. A range of probabilities was observed as a function of the substituted amino acid. However, the location of the peptide bond involved in the donor-acceptor pair plays a critical role in the dynamical behavior. This influence of position on the probability of forming a donor-acceptor pair would be hard to predict from statistical analyses on experimental spectra of aggregate, diverse peptides. In addition, the inclusion of basic side chains in the model peptides alters the probability of forming donor-acceptor pairs across the entire backbone. In this case, there are still more ionizing protons than basic residues, but the side chains of the basic amino acids form stable hydrogen bond networks with the peptide carbonyl oxygens and thus act to prevent free access of "mobile protons" to labile peptide bonds. It is clear from the work that the identification of peptides from low-energy CID using automated computational methods should consider the location of the fragmenting bond as well as the amino acid composition.
authors.affiliation: Computational Biology and Bioinformatics Group, Computational and Information Sciences Directorate, Pacific Northwest National Laboratory, Richland, Washington 99352, USA. william.cannon@pnl.gov
authors.forename: William R
authors.initials: WR
authors.lastname: Cannon
authors.forename: Danny
authors.initials: D
authors.lastname: Taasevigen
authors.forename: Douglas J
authors.initials: DJ
authors.lastname: Baxter
authors.forename: Julia
authors.initials: J
authors.lastname: Laskin
mesh_terms: D000595:Amino Acid Sequence; D000596:Amino Acids / Q000737:chemistry*; D003198:Computer Simulation; D008956:Models, Chemical; D008958:Models, Molecular; D008969:Molecular Sequence Data; D010455:Peptides / Q000737:chemistry*; D011487:Protein Conformation; D011489:Protein Denaturation; D017510:Protein Folding; D013329:Structure-Activity Relationship
chemical_list: D000596:Amino Acids; D010455:Peptides; C019529:polyalanine