S1 SUPPORTING INFORMATION Mechanism of ...

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Tata Institute of Fundamental Research, Center for Interdisciplinary Sciences, Hyderabad, India. 2. UM-DAE Centre for Excellence in Basic Sciences, Mumbai ...
SUPPORTING INFORMATION Mechanism of Initiation, Association and Formation of Amyloid Fibrils Modeled with the N-terminal Peptide Fragment, IKYLEFIS, of Myoglobin G-helix

Sunita Patel1,2*, Yellamraju U. Sasidhar3, Kandala V. R. Chary1,4 1 Tata Institute of Fundamental Research, Center for Interdisciplinary Sciences, Hyderabad, India 2 UM-DAE Centre for Excellence in Basic Sciences, Mumbai University Campus, Mumbai, India 3 Department of Chemistry, Indian Institute of Technology Bombay, Mumbai, India 4 Tata Institute of Fundamental Research, Mumbai, India

*Corresponding address: Dr. Sunita Patel Tata Institute of Fundamental Research, Centre for Interdisciplinary Sciences, Hyderabad, 500075, INDIA Present address: UM-DAE Centre for Excellence in Basic Sciences, Mumbai University Campus, Mumbai 400098, India Email: [email protected] Tel.: 91-22-26524983 Fax: 91-22-26524982

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METHODS Simulation details We used the recent united atom force field GROMOS96 54a7 1-2 to speed up the simulation. This version of the force field has improved ϕ, ψ torsional angle term, a modified N-H, C=O repulsive term and other improvements2. An amyloid β-peptide is studied with this force field and the simulation results in terms of α-helical and β-strand content and calculated NMR chemical shifts etc. compared well with experiments3. All the hydrogen atoms were treated implicitly by united atom approximation except for the polar and aromatic ring hydrogen atoms, which were treated explicitly. The simulations were performed with explicit solvent, using simple point charge (SPC) water model4. The solute was placed initially in the center of the cubic periodic box and the box size was chosen such that the distance between any protein atom and the closest box edge was at least 1 nm. Water molecules were then added to solvate the peptides and fill the box (Table S1). The potential energy of the peptide in water was minimized using steepest descent algorithm with a tolerance of 1000 kJ mol-1 nm-1. Subsequent to energy minimization, position restrained MD simulation was carried out under NVT condition for 100 ps and followed by NPT condition for 100 ps at each of the predefined temperatures. During the position restrained molecular dynamics step, the atomic positions of each of the peptides were restrained and the water molecules were allowed to equilibrate around the peptides. Initial velocities required to start the simulation were generated conforming to Maxwell velocity distribution at each of the predefined temperatures. The temperature thermostat was maintained separately for peptide and the solvent plus ions by velocity rescaling (V-rescale) using a time constant of 0.1 ps5. The isotropic pressure coupling was achieved by Parrinello Rahman method6 using 0.2 ps time constant for coupling with compressibility of 4.5e-5 bar-1. Each MD run was initiated with 2 fs

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time step, which was used for integrating the equations of motion with leap-frog integrator following the equilibration procedures. LINCS algorithm was used to constrain the bonds7. The van der Waals long-range correction was employed using dispersion correction. Coordinates were saved every 1000 steps (or 2 ps). Simulations were run on the high performance computing clusters commissioned at the Tata Institute of Fundamental Research, Center for Interdisciplinary Sciences, Hyderabad.

Data analyses Other conformational parameters used include the following: (i) distance plots (ii) root mean square fluctuation (RMSF), (iii) inter β-sheet distance as measured by taking center of mass of one β-sheet to that of the other, (iv) hydrogen bond (v) Cα contact map, (vi) hydrophobic atomic contacts, (vii) potential energy of the peptides, (viii) Dictionary of Secondary Structure of Protein (DSSP) program8 plot for secondary structures analysis. All these analyses were carried out using GROMACS software, Matlab9 and the tcl scripts implemented in VMD10. VMD was also used for visualizing the trajectories. All the graphs and figures were generated using either Xmgrace11 or Matlab or Pymol12 or VMD.

𝐂𝐨𝐬(𝛉) plot The relative orientation of the strands, whether parallel or anti-parallel was determined by the dot ⃗⃗⃗⃗ . ⃗⃗⃗⃗ product of end-to-end vectors, cos(θ) =(𝐶1 𝐶2)/(|C1||C2|) for a pair of strands C1 and C2. When cos(θ) is 1, strands C1 and C2 are parallel; -1, strands C1 and C2 are anti-parallel and 0, strands C1 and C2 are perpendicular13. The angle between the sheets was thus determined by

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calculating individual cos(θ) and taking its acos(θ) and then averaging over all the angles corresponding to the adjacent β-sheet.

Nematic order (P2) In this work nematic order (P2) is used to characterize the order/disorder nature of the β-sheet14 and is defined as 1 3 ̂ 2 1 𝑃2 = 𝑁 ∑𝑁 𝑖=1 2 (𝑧̂𝑖 ∙ 𝑑 ) − 2

(1)

where 𝑑̂ is a unit vector used as a reference director which in our case is the vector pointing from N- to C-termini of the chain 1. The molecular vectors, 𝑧̂𝑖 are defined as unit vector linking N- to C-terminus of all chains, N is the number of monomers in the simulation box. For ordered systems, P2 is greater than 0.5 whereas for disordered system it is less than 0.5.

Clustering and network layout The network clustering method is based on the pairwise RMSD (Cα) matrix. The network layout is essentially made up of nodes and links of a graph. Each node represents a structure sampled in the conformational space and links between them are established by the pairwise RMSD cutoff. The potential energy of the graph undergoes minimization as a virtual physical system, during which the links act as springs with attractive forces to connect the repulsive nodes. This process is achieved by employing force directed layout algorithm15 implemented in Cytoscape software16. The RMSD cutoff value is a critical parameter. If it is too large then all the structures would fall into one cluster and if it is too small then most nodes are disconnected from one another resulting in fragmented clusters. Ahlstrom et al.17 find that choosing a cutoff value one standard deviation less than the mean of pairwise RMSD distribution generates well segregated S4

network layout. The RMSD pairwise cutoff used in the respective network layout is mentioned in the caption of each network diagram. A Matlab based average linkage algorithm18 was used for clustering the structures and to generate centroid structure for each of the resulting clusters. The centroid structures thus generated represent the central configuration of a given cluster. The graphical network representation of the nodes and links was constructed using Cytoscape software16.

Overall summary of the Results The Ac-IKYLEFIS-NMe peptide displayed conformational preference for β-hairpin and extended structures. We have used these conformational preferences to investigate the feasibility of formation of oligomeric structures. In 4DEP simulation, the double-layered dimer where all the strands were parallel, gave rise to a stable single-layered tetrameric β-sheet of the type C1C2C3C4 (Figure 17). In 4SEPa simulation, wherein all the four β-strands were separated by 15 Å from one another also resulted in a single-layered tetrameric β-sheet (C2C4C1C3). In the third category of simulation 4DEA, where each strand is anti-parallel with respect to other gives rise to a tetrameric β-sheet of the type C1C2C4C3 where again three strands are parallel and one strand is anti-parallel. The fourth category, where each layer containing two hairpins (4DHP), gives rise to a single-layer tetrameric β-sheet where the outer two β-stands were anti-parallel while middle two β-strands were in parallel orientation (C1C2C4C3, Figure 17). Thus, irrespective of many different starting configurations, we ended up arriving at a similar aggregated ordered structure, which we believe could act as a potential seed in amyloid propagation. Further, we performed MD simulations on two and four layered oligomers having six, eight and sixteen monomeric units. The double-layered trimer 6DEP and tetramer 8DEP resulted in an angular orientation

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between two β-sheets with larger inter-β-sheet distance whereas 8DEAm simulation gave rise to a stable structure with proper β-sheet stacking, with minimal angular orientation and smaller inter β-sheet distance. Further, the four-layered structure (16FEP) resulted into a collapsed and highly disorganized structure whereas

16

FTEAm gave rise to an ordered and highly stable

oligomer (Figure 8). We believe that potentially such oligomeric structure can lead to fibrilar aggregate.

References (1) Huang, W.; Lin, Z.; van Gunsteren, W. F., Validation of the gromos 54a7 force field with respect to β-peptide folding. J. Chem. Theory. Comput. 2011, 7, 1237-1243. (2) Schmid, N.; Eichenberger, A. P.; Choutko, A.; Riniker, S.; Winger, M.; Mark, A. E.; van Gunsteren, W. F., Definition and testing of the gromos force-field versions 54a7 and 54b7. Eur. Biophys. J. 2011, 40, 843-856. (3) Gerben, S. R.; Lemkul, J. A.; Brown, A. M.; Bevan, D. R., Comparing atomistic molecular mechanics force fields for a difficult target: A case study on the Alzheimer's amyloid β-peptide. J. Biomol. Struct. Dyn. 2014, 32, 1817-1832. (4) Berendsen, H. J. C.; Postma, J. P. M.; van Gunsteren, W. F.; Hermans, J., Interaction models for water in relation to protein hydration. In Intermolecular forces, In: Pullman, B., Ed. Reidel Publishing Company 1981; pp 331-342. (5) Bussi, G.; Donadio, D.; Parrinello, M., Canonical sampling through velocity rescaling. J. Chem. Phys. 2007, 126, 014101. (6) Parrinello, M.; Rahman, A., Polymorphic transitions in single crystals: A new molecular dynamics method. J. Appl. Phys. 1981, 52, 7182. (7) Hess, B.; Bekker, H.; Berendsen, H. J. C.; Fraaije, J. G. E. M., Lincs: A linear constraint solver for molecular simulations. J. Comput. Chem. 1997, 18, 1463-1472. (8) Kabsch, W.; Sander, C., Dictionary of protein secondary structure: Pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 1983, 22, 2577-2637.

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(9) MATLAB, Matlab and statistics toolbox release 2017a, the mathworks, inc., natick, massachusetts, united states. Home page. http://www.Mathworks.Com/. (10) Humphrey, W.; Dalke, A.; Schulten, K., Vmd - visual molecular dynamics. J. Mol. Graphics. 1996, 14, 33-38. (11) Grace, Home page. http://plasma-gate.Weizmann.Ac.Il/grace/ (accessed june 15, 2013). (12) DeLano, W. L., The pymol molecular graphics system, version 1.8 schrödinger, llc. Home page. http://www.Pymol.Org/ (accessed june 15, 2013). (13) Klimov, D. K.; Thirumalai, D., Dissecting the assembly of Abeta16-22 amyloid peptides into antiparallel beta sheets. Structure 2003, 11, 295-307. (14) Cecchini, M.; Rao, F.; Seeber, M.; Caflisch, A., Replica exchange molecular dynamics simulations of amyloid peptide aggregation. J. Chem. Phys. 2004, 121, 10748-10756. (15) Kobourov, S. G. Spring embedders and force-directed graph drawing algorithms arXiv:1201.3011 [Online], 2012, p. 1-23. (16) Shannon, P.; Markiel, A.; Ozier, O.; Baliga, N. S.; Wang, J. T.; Ramage, D.; Amin, N.; Schwikowski, B.; Ideker, T., Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Res. 2003, 13, 2498-2504. (17) Ahlstrom, L. S.; Baker, J. L.; Ehrlich, K.; Campbell, Z. T.; Patel, S.; Vorontsov, I. I.; Tama, F.; Miyashita, O., Network visualization of conformational sampling during molecular dynamics simulation. J. Mol. Graph. Model. 2014, 46, 140-149. (18) Shao, J.; Tanner, S. W.; Thompson, N.; Cheatham, T. E., Clustering molecular dynamics trajectories: 1. Characterizing the performance of different clustering algorithms. J. Chem. Theory. Comput. 2007, 3, 2312-2334. (19) Hao, S.; Ting, H.; Jing, W.; Rong-Ri, T.; Feng-Shou, Z., Properties of pure water and sodium chloride solutions at high temperatures and pressures: A simulation study. Mol. Simul. 2015, 41, 1-7. (20) Soper, A. K., The radial distribution functions of water and ice from 220 to 673 k and at pressures up to 400 mpa. Chem. Phys. 2000, 258, 121-137.

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Table S1. Details of various simulations carried out on the N-terminal eight-residue segment (Ac-IKYLEFIS-NMe) of myoglobin G-helix.

Simulation abbreviation 1

4

Hx (Monomer in Helix)

DEP (4 monomers in Doublelayers Extended Parallel) *

Simulation box size (in nm3), number of water molecules and total number of atoms

Simulation length (μs)

(3.7×3.7×3.7), 1613, 4938

2; 1

(5.5×5.5×5.5), 5112, 15732

2, 1; 2, 1, 1; 2, 1

333 K

(6.0×6.0×6.0), 6699, 20493

1, 1

333 K

(5.6×5.6×5.6), 5586, 17154

2, 1

333 K

(4.8×4.8×4.8), 3483, 10845

1, 1

333 K

(7.0×7.0×7.0), 9925, 31359

1, 1

333 K

(5.6×5.6×5.6), 5447, 17133

1, 1

333 K

(6.5×6.5×6.5), 8503, 26301

1

333 K

(7.0×7.0×7.0), 9925, 31359

1

333 K

(8.9×8.9×8.9), 21350, 65634

1

Temperature 300 K 333 K 300 K 333 K 353 K

4

SEPa (4 monomers in square Extended Parallel Apart) * 4 DEA (4 monomers in Doublelayers Extended Anti-parallel) * 4 DHP (4 monomers in Doublelayers Hairpin Parallel) * 6 DEP (6 monomers in Doublelayers Extended Parallel) 8 DEP (8 monomers in Doublelayers Extended Parallel) 8 DEAm (8 monomers in Doublelayers Extended Anti-parallel in Middle two strands) 16 FEP (16 monomers in Fourlayers Extended Parallel) 16 FEAm (16 monomers in Fourlayers Extended Anti-parallel in Middle two strands) *4

DEP 300 K Simulation was repeated twice for 2 μs and 1 μs simulation length, while 4DEP 333 K was repeated trice (2 μs, 1 μs and 1 μs) and 4DEP 353 K was repeated twice (2 μs and 1 μs) with different initial velocities. 4SEPa, 4 DEA, 4DHP, 6DEP and 8DEP simulations were also repeated twice and their corresponding length indicated in the table.

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Table S2. The average angle between the two β-strands, corresponding to the upper and lower βsheets in various simulations.

Simulations

Average angle

6

DEP

70.7±8.0

8

DEP

42.3±12.0

8

DEAm

145.7±5.8

16

FEAm

149.4±6.1

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Figure S1. Conformational propensities of the isolated peptide Ac-IKYLEFIS-NMe from the Ghelix of myoglobin, starting from its native α-helical structure at 300 and 333 K. The conformational states at select times are shown on the top panel, DSSP plot in the middle panel, Cα RMSD with respect to the end structure of 1Hx 300 K trajectory and backbone Rg as a function of simulation time in the bottom panel. The secondary structures taken up by the peptide are indicated in the DSSP plot by different color codes. The extended or coil conformations in the DSSP plot are indicated in white while the compact conformations representing β-hairpins are indicated in red-yellow-red strips. The observed β-hairpin is symmetrical with two β-strands (1Ac-IKY4 and 7FIS-NMe10) of equal length and a tight type II β-turn formed by L5 and E6. It is stabilized by 2 to 3 main-chain hydrogen bonds. Running averages over 100 data points were considered for clarity of RMSD and Rg plots (black). The normalized probability distributions of RMSD and Rg are shown in panels right-hand-side of the RMSD and Rg plots. Structures are shown in stick representation while side-chains are shown in lines.

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Figure S2. Radial distribution function g(r) of O-O, O-H and H-H of water were determined for 4

DEP simulations performed at 300, 333 and 353 K temperatures. It does not show any

significant change with an increase in temperature, thus suggesting that the characteristic structure of liquid water is preserved even at higher temperature19-20. Further, there is no broadening of the first g(r)O-O peak as well as no disappearance of second peak indicating that the liquid structure of the water is intact. However, there is decrease in peak heights with increase in temperature indicating lowering of water density due to weaker hydrogen bonded network.

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Figure S3. Centroid structure of 4DEP 300 K simulation, showing hydrophobic association from all four chains. The hydrophobic side chains are shown in stick (light blue) while chain 1 (red), chain 2 (green), chain 3 (blue) and chain 4 (pink) are shown in cartoon representation.

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Figure S4. Residue contact maps for various oligomers of Ac-IKYLEFIS-NMe peptides in different simulations. The average smallest distances between the residues are determined for an equilibrium stretch corresponding to a given simulation. The same time stretch used for potential energy calculation (Table 1) are used here except for 4DEP 353 K simulation in which 500-750 ns time stretch is used. The β-sheet observed during this time is C2C1C4C3. The distance greater than or equal to 1 nm are shaded in black while the distance between 0 to 1 nm are shown in gradient of shades from white to black as indicated in the picture. The maps are symmetric across the diagonal. The x-axis and y-axis show the chain identity. The off diagonal regions indicate the closest contacting chains.

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Figure S5. Nematic order parameter (P2) is plotted as a function of time for all simulations. For the ordered β-sheet, the P2 value is greater than 0.5 and for the disordered oligomer, the P2 value is less than 0.5. A red dotted line in each plot indicates the nematic order value 0.5.

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Figure S6. The Cα RMSD and backbone Rg plots of various simulations performed with different initial velocities. The top panel shows snapshots at select times during the simulation. The Cα RMSD was calculated with respect to end structure of the trajectory. The peptide chains are indicated as C1 (red), C2 (green), C3 (blue) and C4 (pink). The third simulation of 4DEP 333 K is not shown here.

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Figure S7. Salt bridges and Cα-Cα distance plots between various hydrophobic residues across the 4DEP simulation at 333 K. Most of the distances are constant indicating their existences throughout the simulation.

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Figure S8. (A) Hydrophobic clusters observed in 4SEPa and 4DEA simulations, (B) cos(θ) angle between two strands as a function of time for 4SEPa, 4DEA and 4DHP simulations. If the value of cos(θ) is equal to 1 then the corresponding β-strands are parallel, if it is -1 then β-strands are anti-parallel and if it is 0 then strands are perpendicular.

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Figure S9. Number of hydrogen bonds between the peptide main-chain with water and peptide’s main-chain to main-chain as a function of time during 4SEPa and 4DEA simulations.

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Figure S10. The secondary structures adopted by the residues (C1 for chain 1, C2 for chain 2 and C3 for chain 3 and C4 for chain 4) are shown for the 4DHP simulation at 333 K. The secondary structures are indicated in the different color codes as mentioned on top of the DSSP plot. A peptide chain showing red-yellow-red strip indicates a β-hairpin conformation.

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Figure S11. Network cluster layouts of 6DEP, 8DEP, 8DEAm,

16

FEP and

16

FEAm simulations.

For network cluster layouts, a pairwise RMSD cutoffs of 2.5 Å was used for 6DEP, 8DEP, 8

DEAm simulations and 4.5 Å for

16

FEP and

16

FEAm simulations respectively. The cluster

percentages are shown along the side and the centroid structure of the cluster is indicated by an arrow. Structures are shown in cartoon representation (green) while side-chains are shown in lines (yellow).

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Figure S12. The Tyr side-chain is bridging to Glu and Lys residues by hydrogen bonding was observed in 6DEP and 8DEAm simulations.

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Figure S13. The distance (in Å) between the centre-of-mass of one β-sheet to the adjacent βsheet is plotted as a function of time for 6DEP, 8DEP, 8DEAm and

16

FEAm simulations. The

running averages over 100 data points were shown for all the distances in black except for 16

FEAm simulation where the distances for first, second and third pairs are shown in orange,

green and pink lines and the corresponding running averages in blue, red and black respectively.

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Figure S14. Number of peptide solvent hydrogen bonds between a given β-sheet and the surrounding water in

16

FEAm simulation. Running averages over 1000 points were taken for

clarity. The β-sheet 1 and β-sheet 4 are the outer layers while β-sheet 2 and β-sheet 3 are the inner layers.

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Figure S15. The centroid structures of 8DEAm and

16

FEAm simulations.

16

FEAm is showing

alternating inter β-sheet saltbridges and hydrophobic associations. The inter β-sheet saltbridges are indicated in the red square and the inter β-sheet hydrophobic associations are shown in grey square.

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Figure S16. The 2D frequency plots of number of hydrogen bonds versus number of hydrophobic atomic contacts in various oligomeric simulations. The same time stretch used for potential energy calculation (Table 1) is used here except for 4DEP 353 K simulation in which 500-750 ns time stretch is used. When distance between any two atoms of the hydrophobic residues corresponding to different chains is less than or equal to 6 Å then there is a hydrophobic contact. These plots indicate that in spite of all of them forming similar single-layered tetrameric β-sheets, they show differences in terms of the number hydrogen bonds and the number of hydrophobic contacts.

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Figure S17. Overall summary of amyloidogenesis in the N-terminal eight residues segment (AcIKYLEFIS-NMe) of myoglobin G-helix. The starting structures are labeled as A (4DHP), B (4DEP), C (4SEPa), D (4DEA), E (8DEAm), F (16FEAm), G (6DEP), H (8DEP) and I (16FEP) to indicate distinct simulation.

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Figure S18. Cα root mean square fluctuations (RMSF) of the peptides in various simulations.

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Figure S19. The β-sheet percentage (%) as a function of time for all the simulations.

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