Presented by Shouyong Peng Shouyong Peng May 27, 2005 Journal Club

Why Study Abeta16-22 Peptide Aggregation? Small peptides are well suited as model systems for probing the mechanisms of aggregation and fibril formation.

What do They do? Investigate the formation and properties of Abeta16-22 oligomers by unbiased Monte Carlo simulations of systems with up to SIX chains, using a sequence-based atomic model with an effective potential based on hydrogen bonds and hydrophobic attractions (no explicit water molecules)

Systems Box size: 35 Angstrom for three chains; 44 Angstrom for six chains. corresponding to a constant peptide concentration Periodic boundary condition.

Model and Methods Model contains all atoms of the peptide chains, including hydrogen atoms. Variables for each amino acid: phi psi side-chain torsion angles

Interaction potential Excluded-volume effect Local intrachain potential Hydrogen-bond energy Effective hydrophobic interaction T=300K corresponds to kT~0.447

Excluded-volume Effect

Local intrachain potential q: Partial charge for N, H; +/ for C’,O The inner sum represents the interaction between the partial Charges of the backbone NH and C’O groups in one amino acid

Hydrogen-bond energy r: HO distance; alpha: NHO angle; beta: HOC angle Reduce strength when involving chain ends, Which tend to be exposed to water  hb:

Effective hydrophobic interaction Cij is a measure of the degree of contact between side chains i and j: fraction of atoms in contact with other side chain

Some Tech. details Simulated tempering :Temperature is a dynamical variable Study one- and three-chain systems at 8 diff. Temperatures, ranging from 275 K to 369 K; Study the six-chain system at 9 diff. Temperatures, ranging from 287K to 369K. Two different elementary moves in MC for backbone atoms: 1.Highly nonlocal pivot move for a single backbone torsion angle 2.Semilocal method that works with upto 8 adjacent backbone degrees of freedom Sidechain angles are updated one by one. Rigid body translation and rotation for the whole chain.

Secondary structure determination Torsion angles for inner amin acids Parallel or antiparallel: orientation end-to-end vectors scalar product of vectors

Schematic HB pattern

MC evol.

Helix and Strand contents Nc=1: agree with klimov Nc=3: not agree.

Specific heart

Alpha-helicl intermediates? No sign of an obligatory alpha-helical intermediate in their model

3-chain system

6-chain system

Figure 6.

Other peptides Small peptide with a low overall hydrophobicity: propensity to aggregate is much lower  hydrophobic interaction is the driving force  hydrophobic interaction is the driving force for aggregation Small peptide with a significant hydrophobicity but an uneven distribution of it: KFFAAAE predominantly parallel beta-strand organization  the model is capable of generating stable parallel beta-sheets  the model is capable of generating stable parallel beta-sheets

Examples of low-energy structures No single dominating free-energy minimum, But rather a number of more or less degenerate local minima.

Conclusion In this model, Abeta16-22 peptides have a high propensity to self-assemble into aggregated structures with a high beta-strand content, whereas isolated peptide is mainly a random coil. Both parallel and anti-parallel arrangements of the beta-strands occur in the model, with a definite preference for the anti-parallel arrangement. Anti-parallel preference despite ignoring the Coulomb interactions. Although Coulomb interactions might enhance the tendency for peptides to form beta- sheets with an anti-parallel organization, their results strongly suggest that other factors play a significant role, too. They did not observe an absolute free-energy minimum, but rather several minima corresponding to different supramolecular structures, all consisting of arrangements of beta-strands. Apart from single beta-sheets, laminated multisheet structures were found near free-energy minima for the six-chain system.