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Peptide Folding Simulations for Protein Structure Prediction

Explore molecular simulations of peptide folding for protein structure prediction and lipid aggregation analysis. Research conducted at the SMMS Chemistry Building, University of Queensland, and Lab of Biophysical Chemistry, University of Groningen. Simulation results showcase reversible folding transitions, folding pathways, and secondary structures. Investigate beta-peptides, heptapeptide folding, and peptide assemblies. Study lipid bilayer and vesicle formation, phase transitions, and fusion processes.

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Peptide Folding Simulations for Protein Structure Prediction

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  1. Simulations of the folding and aggregation of peptides, proteins and lipids. BRISBANE School of Molecular and Microbial Sciences (SMMS)Chemistry Building (#68)University of QueenslandBrisbane, QLD 4072,AustraliaEmail a.mark@uq.edu.auPhone: +61-7-33469922 FAX: +61-7-33654623Centre Secr: +61-7-33653975GRONINGEN Lab. of Biophysical Chemistry University of Groningen Nijenborgh 4 email 9747 AG GRONINGEN The Netherlands tel +31.50.3634457fax: +31.50.3634800 tel secr: +31.50.3634323email:a.e.mark@rug.nl secr: mdsecr@fmns.rug.nl http://md.chem.rug.nl Alan E. Mark Herman Berendsen Siewert-Jan Marrink

  2. Peptide folding and assembly: • Our best example of peptide folding to date is a the beta-hexapeptide shown • on the following slides (solvent Methanol). • This system is fully reversible. • We have simulations of this and other systems to > 200ns at temperatures • from 180 -> to 450K. • We have replica exchange simulations of a slightly modified system • showing 1000’s of individual folding events. • As far as we can determine our modified system approaches full • convergence in 200-400 ns. • 5. Trajectories are available.

  3. -Peptides • -amino-acids (additional backbone carbon) • Stable 2nd structure. • Non-degradable peptide mimetics • (e.g. highly selective somatastatin analogue) -Heptapeptide (M) 31-helix in MeOH at 298 K (left-handed) D. Seebach, B. Jaun + coworkers organic chem ETH-Zurich Daura, X., Bernhard, J., Seebach, D., van Gunsteren, W. F. and Mark, A. E. (1998) J. Mol. Biol. 280, 925-932.

  4. -Heptapeptide, 340 K unfold fold unfold fold unfold fold unfold

  5. Starting structure -Heptapeptide, 360 K Gfolding = -RT ln (folded/unfolded)

  6. Predict Probability of Individual Microstates in Solution G=0 kJ/mol G=~6 kJ/mol G=~8 kJ/mol G=~9 kJ/mol G=~9 kJ/mol Daura, X., van Gunsteren, W. F. and Mark, A. E. (1999) Proteins: Struct. Funct. Genet. 34, 269-280.

  7. Folding Pathways

  8. Simulations of peptide folding As part of our program we are looking a range of larger peptides. So far getting reversible folding from random starting structures has proved difficult for systems > 20 a.a. In particular we are investigating a series of related helical peptides (~20 a.a.) with fast folding kinetics AP A5(A3RA)3A YGA Ac-YG(AKA3)2AG-NH2 YGG Ac-YGG(KA4)3K-NH2 So far results are limited but we have seen reversible transitions. An example is given below.

  9. AP A5(A3RA)3A Ref: Lednev I. K. et al. J. Am. Chem. Soc. 1999, 121, 8074-8086. • A 21 amino acid, mainly alanine, α-helical peptide (AP). • The folding/unfolding activating barriers based on an nanosecond UV resonance Raman study. • ~8 kcal/mol activation barrier; reciprocal rate constant ~240±60 ns at 37 °C (310 K). MD simulation start from the α-helix structure The GROMOS 45A3 force field was adopted

  10. β-Sheet β-Bridge Bend Turn α-helix 5-Helix 3-Helix Coil The secondary structure as a function of time shows one refolding transition in 100ns. Secondary structure Residue Time (ps)

  11. C-ter N-ter N-ter N-ter C-ter N-ter C-ter 30 ns 50 ns C-ter 10 ns 0 ns (starting structure) N-ter C-ter N-ter N-ter C-ter C-ter C-ter N-ter N-ter C-ter 85 ns 75 ns 70 ns 80 ns 100 ns

  12. Other peptide systems on which we have simulations showing partial • folding or assemble include: • Various amyloid forming peptides on surfaces. • Betanova (a designed triple stranded peptide) • A series of coiled-coils. • WW domain peptide (~20 a.a. peptide studied by replica exchange) • Several proteins showing recovery from mild denaturing conditions.

  13. Spontaneous Aggregation of Lipids and Surfactants I believe this is one area where complexity analysis should be able to perform well as the systems show spontaneous generation of order. • We have multiple simulations of: • Bilayer formation (course grained and in atomic detail) • Vesicle formation (course grained and in atomic detail) • Phase transitions (course grained and in atomic detail) • Membrane and vesicle fusion. Note: these are highly reproducible collective processes involving 100’s to 1000’s of lipids. A few examples are given below.

  14. Spontaneous assembly of phospholipds into a bilayer A B C 0 ns 0.2 ns 3 ns Ceq C* Deq 25 ns 20 ns 10 ns S.J. Marrink

  15. Density Evolution Showing the Generation of Order density water head groups lipid tails S.J. Marrink

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