[en] Self-assembly of peptides into supramolecular structures represents an active field of research with potential applications ranging from material science to medicine. Their study typically involves the application of a large toolbox of spectroscopic and imaging techniques. However, quite often the structural aspects remain underexposed. Besides, molecular modeling of the self-assembly process is usually difficult to handle since a vast conformational space has to be sampled. Here, we have used an approach that combines short molecular dynamics simulations for peptide dimerization and NMR restraints to build a model of the supramolecular structure from the dimeric units. Experimental NMR data notably provide crucial information about the conformation of the monomeric units, the supramolecular assembly dimensions and the orientation of the individual peptides within the assembly. This in silico/in vitro mixed approach enables us to define accurate atomistic models of supramolecular structures of the bacterial cyclic lipodepsipeptide Pseudodesmin A.
Colombo, G.; Soto, P.; Gazit, E. Peptide Self-Assembly at the Nanoscale: A Challenging Target for Computational and Experimental Biotechnology. Trends Biotechnol. 2007, 25 (5), 211-218, 10.1016/j.tibtech.2007.03.004
Frederix, P. W. J. M.; Patmanidis, I.; Marrink, S. J. Molecular Simulations of Self-Assembling Bio-Inspired Supramolecular Systems and Their Connection to Experiments. Chem. Soc. Rev. 2018, 47 (10), 3470-3489, 10.1039/C8CS00040A
Tuttle, T. Computational Approaches to Understanding the Self-Assembly of Peptide-Based Nanostructures. Isr. J. Chem. 2015, 55 (6-7), 724-734, 10.1002/ijch.201400188
Mandal, D.; Nasrolahi Shirazi, A.; Parang, K. Self-Assembly of Peptides to Nanostructures. Org. Biomol. Chem. 2014, 12 (22), 3544-3561, 10.1039/C4OB00447G
Qiu, F.; Chen, Y.; Tang, C.; Zhao, X. Amphiphilic Peptides as Novel Nanomaterials: Design, Self-Assembly and Application. Int. J. Nanomed. 2018, 13, 5003-5022, 10.2147/IJN.S166403
Eskandari, S.; Guerin, T.; Toth, I.; Stephenson, R. J. Recent Advances in Self-Assembled Peptides: Implications for Targeted Drug Delivery and Vaccine Engineering. Adv. Drug Delivery Rev. 2017, 110-111, 169-187, 10.1016/j.addr.2016.06.013
Nieuwland, M.; Ruizendaal, L.; Brinkmann, A.; Kroon-Batenburg, L.; van Hest, J. C. M.; Löwik, D. W. P. M. A Structural Study of the Self-Assembly of a Palmitoyl Peptide Amphiphile. Faraday Discuss. 2013, 166 (0), 361, 10.1039/c3fd00055a
Hollamby, M. J.; Karny, M.; Bomans, P. H. H.; Sommerdjik, N. A. J. M.; Saeki, A.; Seki, S.; Minamikawa, H.; Grillo, I.; Pauw, B. R.; Brown, P. et al. Directed Assembly of Optoelectronically Active Alkyl-Ï-Conjugated Molecules by Adding n-Alkanes or Ï-Conjugated Species. Nat. Chem. 2014, 6 (8), 690-696, 10.1038/nchem.1977
Rad-Malekshahi, M.; Visscher, K. M.; Rodrigues, J. P. G. L. M.; de Vries, R.; Hennink, W. E.; Baldus, M.; Bonvin, A. M. J. J.; Mastrobattista, E.; Weingarth, M. The Supramolecular Organization of a Peptide-Based Nanocarrier at High Molecular Detail. J. Am. Chem. Soc. 2015, 137 (24), 7775-7784, 10.1021/jacs.5b02919
Yu, Z.; Erbas, A.; Tantakitti, F.; Palmer, L. C.; Jackman, J. A.; Olvera de la Cruz, M.; Cho, N.-J.; Stupp, S. I. Co-Assembly of Peptide Amphiphiles and Lipids into Supramolecular Nanostructures Driven by Anion-πInteractions. J. Am. Chem. Soc. 2017, 139 (23), 7823-7830, 10.1021/jacs.7b02058
Yuan, C.; Li, S.; Zou, Q.; Ren, Y.; Yan, X. Multiscale Simulations for Understanding the Evolution and Mechanism of Hierarchical Peptide Self-Assembly. Phys. Chem. Chem. Phys. 2017, 19 (35), 23614-23631, 10.1039/C7CP01923H
Nasica-Labouze, J.; Meli, M.; Derreumaux, P.; Colombo, G.; Mousseau, N. A Multiscale Approach to Characterize the Early Aggregation Steps of the Amyloid-Forming Peptide GNNQQNY from the Yeast Prion Sup-35. PLoS Comput. Biol. 2011, 7 (5), e1002051 10.1371/journal.pcbi.1002051
Sinnaeve, D.; Michaux, C.; Van hemel, J.; Vandenkerckhove, J.; Peys, E.; Borremans, F. a. M.; Sas, B.; Wouters, J.; Martins, J. C. Structure and X-Ray Conformation of Pseudodesmins A and B, Two New Cyclic Lipodepsipeptides from Pseudomonas Bacteria. Tetrahedron 2009, 65 (21), 4173-4181, 10.1016/j.tet.2009.03.045
Raaijmakers, J. M.; de Bruijn, I.; de Kock, M. J. D. Cyclic Lipopeptide Production by Plant-Associated Pseudomonas Spp.: Diversity, Activity, Biosynthesis, and Regulation. Mol. Plant-Microbe Interact. 2006, 19 (7), 699-710, 10.1094/MPMI-19-0699
Gross, H.; Loper, J. E. Genomics of Secondary Metabolite Production by Pseudomonas Spp. Nat. Prod. Rep. 2009, 26 (11), 1408, 10.1039/b817075b
Sinnaeve, D.; Hendrickx, P. M. S.; Van Hemel, J.; Peys, E.; Kieffer, B.; Martins, J. C. The Solution Structure and Self-Association Properties of the Cyclic Lipodepsipeptide Pseudodesmin A Support Its Pore-Forming Potential. Chem.-Eur. J. 2009, 15 (46), 12653-12662, 10.1002/chem.200901885
Sinnaeve, D.; Delsuc, M.-A.; Martins, J. C.; Kieffer, B. Insight into Peptide Self-Assembly from Anisotropic Rotational Diffusion Derived from 13C NMR Relaxation. Chem. Sci. 2012, 3 (4), 1284, 10.1039/c2sc01088g
De Vleeschouwer, M.; Sinnaeve, D.; Van den Begin, J.; Coenye, T.; Martins, J. C.; Madder, A. Rapid Total Synthesis of Cyclic Lipodepsipeptides as a Premise to Investigate Their Self-Assembly and Biological Activity. Chem.-Eur. J. 2014, 20 (25), 7766-7775, 10.1002/chem.201402066
Geudens, N.; De Vleeschouwer, M.; Fehér, K.; Rokni-Zadeh, H.; Ghequire, M. G. K.; Madder, A.; De Mot, R.; Martins, J. C.; Sinnaeve, D. Impact of a Stereocentre Inversion in Cyclic Lipodepsipeptides from the Viscosin Group: A Comparative Study of the Viscosinamide and Pseudodesmin Conformation and Self-Assembly. ChemBioChem 2014, 15 (18), 2736-2746, 10.1002/cbic.201402389
Geudens, N.; Nasir, M. N.; Crowet, J.-M.; Raaijmakers, J. M.; Fehér, K.; Coenye, T.; Martins, J. C.; Lins, L.; Sinnaeve, D.; Deleu, M. Membrane Interactions of Natural Cyclic Lipodepsipeptides of the Viscosin Group. Biochim. Biophys. Acta, Biomembr. 2017, 1859 (3), 331-339, 10.1016/j.bbamem.2016.12.013
Khavani, M.; Izadyar, M.; Housaindokht, M. R. Theoretical Design of the Cyclic Lipopeptide Nanotube as a Molecular Channel in the Lipid Bilayer, Molecular Dynamics and Quantum Mechanics Approach. Phys. Chem. Chem. Phys. 2015, 17 (38), 25536-25549, 10.1039/C5CP03136B
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 (7), 843-856, 10.1007/s00249-011-0700-9
Malde, A. K.; Zuo, L.; Breeze, M.; Stroet, M.; Poger, D.; Nair, P. C.; Oostenbrink, C.; Mark, A. E. An Automated Force Field Topology Builder (ATB) and Repository: Version 1.0. J. Chem. Theory Comput. 2011, 7 (12), 4026-4037, 10.1021/ct200196m
Hermans, J.; Berendsen, H. J. C.; Van Gunsteren, W. F.; Postma, J. P. M. A Consistent Empirical Potential for Water-Protein Interactions. Biopolymers 1984, 23 (8), 1513-1518, 10.1002/bip.360230807
Bussi, G.; Donadio, D.; Parrinello, M. Canonical Sampling through Velocity Rescaling. J. Chem. Phys. 2007, 126 (1), 014101, 10.1063/1.2408420
Parrinello, M. Polymorphic Transitions in Single Crystals: A New Molecular Dynamics Method. J. Appl. Phys. 1981, 52 (12), 7182, 10.1063/1.328693
Essmann, U.; Perera, L.; Berkowitz, M. L.; Darden, T.; Lee, H.; Pedersen, L. G. A Smooth Particle Mesh Ewald Method. J. Chem. Phys. 1995, 103 (19), 8577, 10.1063/1.470117
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 (12), 1463-1472, 10.1002/(SICI)1096-987X(199709)18:12<1463::AID-JCC4>3.0.CO;2-H
Schrödinger, L. L. C. The PyMOL Molecular Graphics System, Version 1.3. Methods Enzymol. 2010, 266, 540-553
Humphrey, W.; Dalke, A.; Schulten, K. VMD: Visual Molecular Dynamics. J. Mol. Graphics 1996, 14 (1), 33-38, 10.1016/0263-7855(96)00018-5
Ekiz, M. S.; Cinar, G.; Khalily, M. A.; Guler, M. O. Self-Assembled Peptide Nanostructures for Functional Materials. Nanotechnology 2016, 27 (40), 402002, 10.1088/0957-4484/27/40/402002
Morriss-Andrews, A.; Shea, J.-E. Simulations of Protein Aggregation: Insights from Atomistic and Coarse-Grained Models. J. Phys. Chem. Lett. 2014, 5 (11), 1899-1908, 10.1021/jz5006847
Manandhar, A.; Kang, M.; Chakraborty, K.; Tang, P. K.; Loverde, S. M. Molecular Simulations of Peptide Amphiphiles. Org. Biomol. Chem. 2017, 15 (38), 7993-8005, 10.1039/C7OB01290J
Moore, S.; Sonar, K.; Bharadwaj, P.; Deplazes, E.; Mancera, R. Characterisation of the Structure and Oligomerisation of Islet Amyloid Polypeptides (IAPP): A Review of Molecular Dynamics Simulation Studies. Molecules 2018, 23 (9), 2142, 10.3390/molecules23092142
Shea, J.-E.; Urbanc, B. Insights into Aβ Aggregation: A Molecular Dynamics Perspective. Curr. Top. Med. Chem. 2013, 12 (22), 2596-2610, 10.2174/1568026611212220012
Redler, R. L.; Shirvanyants, D.; Dagliyan, O.; Ding, F.; Kim, D. N.; Kota, P.; Proctor, E. a.; Ramachandran, S.; Tandon, A.; Dokholyan, N. V. Computational Approaches to Understanding Protein Aggregation in Neurodegeneration. J. Mol. Cell Biol. 2014, 6 (2), 104-115, 10.1093/jmcb/mju007
Ning, L.; Guo, J.; Bai, Q.; Jin, N.; Liu, H.; Yao, X. Structural Diversity and Initial Oligomerization of PrP106-126 Studied by Replica-Exchange and Conventional Molecular Dynamics Simulations. PLoS One 2014, 9 (2), e87266 10.1371/journal.pone.0087266
Gee, J.; Shell, M. S. Two-Dimensional Replica Exchange Approach for Peptide-Peptide Interactions. J. Chem. Phys. 2011, 134 (6), 064112, 10.1063/1.3551576
Mousseau, N.; Derreumaux, P. Exploring the Early Steps of Amyloid Peptide Aggregation by Computers. Acc. Chem. Res. 2005, 38 (11), 885-891, 10.1021/ar050045a
Liu, D.; Liu, F.; Zhou, W.; Chen, F.; Wei, J. Molecular Dynamics Simulation of Self-Assembly and Viscosity Behavior of PAM and CTAC in Salt-Added Solutions. J. Mol. Liq. 2018, 268, 131-139, 10.1016/j.molliq.2018.07.053
Sasselli, I. R.; Moreira, I. P.; Ulijn, R. V.; Tuttle, T. Molecular Dynamics Simulations Reveal Disruptive Self-Assembly in Dynamic Peptide Libraries. Org. Biomol. Chem. 2017, 15 (31), 6541-6547, 10.1039/C7OB01268C
Lee, O.-S.; Cho, V.; Schatz, G. C. Modeling the Self-Assembly of Peptide Amphiphiles into Fibers Using Coarse-Grained Molecular Dynamics. Nano Lett. 2012, 12 (9), 4907-4913, 10.1021/nl302487m
Marrink, S. J.; Tieleman, D. P. Perspective on the Martini Model. Chem. Soc. Rev. 2013, 42 (16), 6801-6822, 10.1039/c3cs60093a
Gautieri, A.; Milani, A.; Pizzi, A.; Rigoldi, F.; Redaelli, A.; Metrangolo, P. Molecular Dynamics Investigation of Halogenated Amyloidogenic Peptides. J. Mol. Model. 2019, 25 (5), 124, 10.1007/s00894-019-4012-9
Rigoldi, F.; Metrangolo, P.; Redaelli, A.; Gautieri, A. Nanostructure and Stability of Calcitonin Amyloids. J. Biol. Chem. 2017, 292 (18), 7348-7357, 10.1074/jbc.M116.770271
Bertran, O.; Curcó, D.; Zanuy, D.; Alemán, C. Atomistic Organization and Characterization of Tube-like Assemblies Comprising Peptide-Polymer Conjugates: Computer Simulation Studies. Faraday Discuss. 2013, 166, 59, 10.1039/c3fd00079f
Vijayaraj, R.; Van Damme, S.; Bultinck, P.; Subramanian, V. Structure and Stability of Cyclic Peptide Based Nanotubes: A Molecular Dynamics Study of the Influence of Amino Acid Composition. Phys. Chem. Chem. Phys. 2012, 14 (43), 15135, 10.1039/c2cp42030a
Lee, O.-S.; Stupp, S. I.; Schatz, G. C. Atomistic Molecular Dynamics Simulations of Peptide Amphiphile Self-Assembly into Cylindrical Nanofibers. J. Am. Chem. Soc. 2011, 133 (10), 3677-3683, 10.1021/ja110966y
Kang, M.; Chakraborty, K.; Loverde, S. M. Molecular Dynamics Simulations of Supramolecular Anticancer Nanotubes. J. Chem. Inf. Model. 2018, 58 (6), 1164-1168, 10.1021/acs.jcim.8b00193
Lee, O.-S.; Stupp, S. I.; Schatz, G. C. Atomistic Molecular Dynamics Simulations of Peptide Amphiphile Self-Assembly into Cylindrical Nanofibers. J. Am. Chem. Soc. 2011, 133 (10), 3677-3683, 10.1021/ja110966y
Cormier, A. R.; Pang, X.; Zimmerman, M. I.; Zhou, H.-X.; Paravastu, A. K. Molecular Structure of RADA16-I Designer Self-Assembling Peptide Nanofibers. ACS Nano 2013, 7 (9), 7562-7572, 10.1021/nn401562f
Nagy-Smith, K.; Moore, E.; Schneider, J.; Tycko, R. Molecular Structure of Monomorphic Peptide Fibrils within a Kinetically Trapped Hydrogel Network. Proc. Natl. Acad. Sci. U. S. A. 2015, 112 (32), 9816-9821, 10.1073/pnas.1509313112