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Molecular Dynamics (MD) is a powerful computational technique used to understand the physical basis of the structure and function of biological systems.[1] In this context, coarse-grained (CG) models have been successfully applied to a broad range of bio-molecular systems, including the self-assembly of lipids in aqueous solutions. However, many biologically relevant processes occur on timescales that far exceed the timescales of typical MD simulations using CG models. Thanks to an innovative simulation technique, name hybrid particle-field (hPF),[2,3] is possible to study large scale systems beyond what is feasible with traditional MD and CG models.[4] A special class of CG models, developed for the hPF technique, have been successfully used to investigate several problems in biophysics.5–8 The first application of CG hPF models, with parameters for phospholipids only, was published by the Milano group in 2011.[5] Thanks to the speed up of dynamics, due to the hPF approach, the self-diffusion acceleration lead to a fast self-assembly process. The net effect is that the developed CG models can reproduce, via self-assembly, the lamellar and non-lamellar structure phases of many lipids and surfactants.[5–8] Our aim is to highlight recent applications and provide a comprehensive overview of hPF CG models for biological applications.
(1) Karplus, M.; McCammon, J. A. Molecular Dynamics Simulations of Biomolecules. Nat. Struct. Biol. 2002, 9 (9), 646–652. https://doi.org/10.1038/nsb0902-646.
(2) Milano, G.; Kawakatsu, T. Hybrid Particle-Field Molecular Dynamics Simulations for Dense Polymer Systems. J. Chem. Phys. 2009, 130 (21), 214106. https://doi.org/10.1063/1.3142103.
(3) Milano, G.; Kawakatsu, T. Pressure Calculation in Hybrid Particle-Field Simulations. J. Chem. Phys. 2010, 133 (21), 214102. https://doi.org/10.1063/1.3506776.
(4) Milano, G.; Kawakatsu, T.; De Nicola, A. A Hybrid Particle–Field Molecular Dynamics Approach: A Route toward Efficient Coarse-Grained Models for Biomembranes. Phys. Biol. 2013, 10 (4), 045007. https://doi.org/10.1088/1478-3975/10/4/045007.
(5) De Nicola, A.; Zhao, Y.; Kawakatsu, T.; Roccatano, D.; Milano, G. Hybrid Particle Field Coarse Grained Models for Biological Phospholipids. J. Chem. Theory Comput. 2011, 7 (9), 2947–2962. https://doi.org/10.1021/ct200132n.
(6) De Nicola, Antonio; Kawakatsu, T.; Rosano, C.; Celino, M.; Rocco, M.; Milano, G. Self-Assembly of Triton X‑100 in Water Solutions: A Multiscale Simulation Study Linking Mesoscale to Atomistic Models. J Chem Theory Comput 2015, 13. https://doi.org/10.1021/acs.jctc.5b00485.
(7) De Nicola, A.; Kawakatsu, T.; Milano, G. A Hybrid ParticleField CoarseGrained Molecular Model for Pluronics Water Mixtures. Macromol Chem Phys 2013, 11.
(8) De Nicola, A.; Soares, T. A.; Santos, D. E. S.; Bore, S. L.; Sevink, G. J. A.; Cascella, M.; Milano, G. Aggregation of Lipid A Variants: A Hybrid Particle-Field Model. Biochim. Biophys. Acta BBA - Gen. Subj. 2020, 129570. https://doi.org/10.1016/j.bbagen.2020.129570.
| Department | Scuola Superiore Meridionale |
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