Self-assembling peptide biomaterials: Insights from spontaneous and enhanced sampling molecular dynamics simulations

Abstract

Peptide self-assembly is the process by which peptide molecules aggregate into low dimensional (1D, 2D) or 3D ordered materials with potential applications ranging from drug delivery to electronics. Short peptides are particularly good candidates for forming supramolecular assemblies due to the relatively simple structure and ease of modulating their self-assembly process to achieve required material properties. The experimental resolution of fibrous peptide-based nanomaterials as 3D atomic coordinates remains challenging. For surface-mediated peptide assembly in particular, it is typically not feasible to resolve multiple conformationally distinct surface bound peptide structures by experiment. The mechanisms of peptide self-assembly also remain elusive due to the interchange of complex interactions and multiple time and length scales involved in the self-assembly process. Peptide self-assembly in solution, or mediated by surfaces, is driven by specific interactions between the peptides and water, competing interactions within the peptide and/or between peptide aggregate units and, in the latter case, an interplay of the interactions between peptides and solvent molecules for adsorption onto a proximal surface. Computational methodologies have proven beneficial in elucidating the structures formed during peptide self-assembly and the molecular mechanisms driving it, and hence have scope in facilitating the development of functional peptide-based nanomaterials for medical or biotechnological applications. In this perspective, computational methods that have provided molecular insights into the mechanisms of formation of peptide biomaterials, and the all-atom-resolved structures of peptide assemblies are presented. Established and recently emerged molecular simulation approaches are reviewed with a focus on applications relevant to peptide assembly, including all-atom and coarse-grained “brute force” molecular dynamics methods as well as the enhanced sampling methodologies: umbrella sampling, steered and replica exchange molecular dynamics, and variants of metadynamics. These approaches have been shown to contribute all-atom details not yet available experimentally, to advance our understanding of peptide self-assembly processes and biomaterial formation. The scope of this review includes a summary of the current state of the computational methods, in terms of their strengths and limitations for application to self-assembling peptide biomaterials.