Closing the Gap Between Modeling and Experiments in the Self-Assembly of Biomolecules at Interfaces and in Solution

Abstract

Molecular self-assembly is a powerful tool in materials design, wherein noncovalent interactions like electrostatic, hydrophobic, hydrogen bonding, and van der Waals can be exploited to produce supramolecular nanostructures that are functional and highly tunable. Biomolecules are attractive building blocks, as they are biocompatible, biodegradable, and adopt a wide array of higher order structures. Moreover, naturally occurring protein systems display a manifold of structures and interactions that can be replicated in synthetic biomolecules. In this perspective, we highlight advances in multiscale simulation techniques across broad spatiotemporal scales that can aid in characterizing selfassembly of hybrid and hierarchical bionanomaterial systems, with an emphasis on physicsbased simulation approaches currently employed to study biomolecules at mineral interfaces. The power of these approaches is highlighted across a few recent areas where molecular simulations have advanced our understanding of self-assembly spanning peptides to protein self-assembly. Looking forward, we discuss how in the near future emerging methods in statistical and machine learning will advance this research field in all areas from expanding the capabilities of physics-based simulation methods to enabling new analyses of high throughput experiments. These advances will pave the way for understanding the molecular recognition patterns in systems that are dictated by self-assemblybiomineralizing peptides, hierarchical peptoids, and large protein assembliesand will aid in the development of a new synthesis science for achieving precise molecular control in materials design.

Biomass‐Derived Carbon for High‐Performance Batteries: From Structure to Properties

“…Extracting biomolecules from natural to modify nanostructures has become an important research method to detect highperformance batteries. [208,209] The sustainability and renewability of the ecosystem provide economic benefits for the large-scale extraction of biomolecules. [210,211] However, complex preparation methods still restrict the application of biomolecules in highly stable batteries.…”

Hierarchical Materials from High Information Content Macromolecular Building Blocks: Construction, Dynamic Interventions, and Prediction

“…An alternative to enhanced sampling techniques is generalized-ensemble strategies such as parallel tempering, a multireplicate variant of simulated tempering in which high temperatures are used to induce disorder in a chemical system and then gradually lowered to reach ordered assembled states . Other thermodynamic quantities like pressure can be used in place of temperature. , The increased availability of high-performance computing resources has made parallel tempering especially popular ,− because the method runs several simulations in parallel and exchanges information between them via Monte Carlo moves. Many hierarchical assembly processes take place at room temperature and ambient pressure.…”

Ion-dependent protein–surface interactions from intrinsic solvent response

“…Biasing ion z coordinates in this way expedites the exploration of phase space and can reveal hidden energetic basins. PBMetaD-PF used Gaussian width sigma 0.01, with bias factor 5, initial hill height 1.25 kJ/mol, and pace 500 steps, at a target temperature of 300 K in accordance with previous ion-binding potential of mean force (PMF) studies (65). Production runs were on the time scale of 200 ns in the NVT ensemble.…”