1. Molecular simulations of self-assembling bio-inspired supramolecular systems and their connection to experiments
- Author
-
Pim W. J. M. Frederix, Siewert J. Marrink, and Ilias Patmanidis
- Subjects
PEPTIDE-BASED NANOSTRUCTURES ,Nanostructure ,Field (physics) ,Computer science ,Supramolecular chemistry ,Nanotechnology ,ACID SIDE-CHAINS ,Degrees of freedom (mechanics) ,010402 general chemistry ,01 natural sciences ,GENERAL FORCE-FIELD ,CIRCULAR-DICHROISM ,Software ,2D IR SPECTROSCOPY ,0103 physical sciences ,Nanobiotechnology ,COARSE-GRAINED SIMULATIONS ,Quantum ,010304 chemical physics ,DYNAMICS SIMULATIONS ,business.industry ,SHORT AMPHIPHILIC PEPTIDES ,SMALL ORGANIC-MOLECULES ,Observable ,FREE-ENERGY ,General Chemistry ,0104 chemical sciences ,Chemistry ,business - Abstract
The self-assembly of bio-inspired supramolecular polymers can be unravelled using molecular dynamics simulations combined with experiments., In bionanotechnology, the field of creating functional materials consisting of bio-inspired molecules, the function and shape of a nanostructure only appear through the assembly of many small molecules together. The large number of building blocks required to define a nanostructure combined with the many degrees of freedom in packing small molecules has long precluded molecular simulations, but recent advances in computational hardware as well as software have made classical simulations available to this strongly expanding field. Here, we review the state of the art in simulations of self-assembling bio-inspired supramolecular systems. We will first discuss progress in force fields, simulation protocols and enhanced sampling techniques using recent examples. Secondly, we will focus on efforts to enable the comparison of experimentally accessible observables and computational results. Experimental quantities that can be measured by microscopy, spectroscopy and scattering can be linked to simulation output either directly or indirectly, via quantum mechanical or semi-empirical techniques. Overall, we aim to provide an overview of the various computational approaches to understand not only the molecular architecture of nanostructures, but also the mechanism of their formation.
- Published
- 2018