Sequence-Structure-Binding Relationships Reveal Adhesion Behavior of the Car9 Solid-Binding Peptide: An Integrated Experimental and Simulation Study.

Solid-binding peptides (SBPs) recognizing inorganic and synthetic interfaces have enabled a broad range of materials science applications and hold promise as adhesive or morphogenetic control units that can be genetically encoded within desirable or designed protein frameworks. To date, the underlying relationships governing both SBP-surface and SBP-SBP interactions and how they give rise to different adsorption mechanisms remain unclear. Here, we combine protein engineering, surface plasmon resonance characterization, and molecular dynamics (MD) simulations initiated from Rosetta predictions to gain insights on the interplay of amino acid composition, structure, self-association, and adhesion modality in a panel of variants of the Car9 silica-binding peptide (DSARGFKKPGKR) fused to the C-terminus of superfolder green fluorescent protein (sfGFP).

Solid-State NMR and MD Study of the Structure of the Statherin Mutant SNa15 on Mineral Surfaces.

Elucidation of the structure and interactions of proteins at native mineral interfaces is key to understanding how biological systems regulate the formation of hard tissue structures. In addition, understanding how these same proteins interact with non-native mineral surfaces has important implications for the design of medical and dental implants, chromatographic supports, diagnostic tools, and a host of other applications. Here, we combine solid-state NMR spectroscopy, isotherm measurements, and molecular dynamics simulations to study how SNa15, a peptide derived from the hydroxyapatite (HAP) recognition domain of the biomineralization protein statherin, interacts with HAP, silica (SiO), and titania (TiO) mineral surfaces.

Biasing Smarter, Not Harder, by Partitioning Collective Variables into Families in Parallel Bias Metadynamics.

Molecular simulations of systems with multiple copies of identical atoms or molecules may require the biasing of numerous, degenerate collective variables (CVs) to accelerate sampling. Recently, a variation of metadynamics (MetaD) named parallel bias metadynamics (PBMetaD) has been shown to make biasing of many CVs more tractable. We extended the PBMetaD scheme so that it partitions degenerate CVs into families that share the same bias potential, consequently expediting convergence of the free-energy landscape.

Peptoid Backbone Flexibilility Dictates Its Interaction with Water and Surfaces: A Molecular Dynamics Investigation.

Peptoids are peptide-mimetic biopolymers that are easy to synthesize and adaptable for use in drugs, chemical scaffolds, and coatings. However, there is insufficient information about their structural preferences and interactions with the environment in various applications. We conducted a study to understand the fundamental differences between peptides and peptoids using molecular dynamics simulations with semiempirical (PM6) and empirical (AMBER) potentials, in conjunction with metadynamics enhanced sampling.

Investigating the Role of Phosphorylation in the Binding of Silaffin Peptide R5 to Silica with Molecular Dynamics Simulations.

Biomimetic silica formation, a process that is largely driven by proteins, has garnered considerable interest in recent years due to its role in the development of new biotechnologies. However, much remains unknown of the molecular-scale mechanisms underlying the binding of proteins to biomineral surfaces such as silica, or even of the key residue-level interactions between such proteins and surfaces. In this study, we employ molecular dynamics (MD) simulations to study the binding of R5-a 19-residue segment of a native silaffin peptide used for in vitro silica formation-to a silica surface.

Essential slow degrees of freedom in protein-surface simulations: A metadynamics investigation.

Many proteins exhibit strong binding affinities to surfaces, with binding energies much greater than thermal fluctuations. When modelling these protein-surface systems with classical molecular dynamics (MD) simulations, the large forces that exist at the protein/surface interface generally confine the system to a single free energy minimum. Exploring the full conformational space of the protein, especially finding other stable structures, becomes prohibitively expensive.

Tuning crystallization pathways through sequence engineering of biomimetic polymers.

Two-step nucleation pathways in which disordered, amorphous, or dense liquid states precede the appearance of crystalline phases have been reported for a wide range of materials, but the dynamics of such pathways are poorly understood. Moreover, whether these pathways are general features of crystallizing systems or a consequence of system-specific structural details that select for direct versus two-step processes is unknown. Using atomic force microscopy to directly observe crystallization of sequence-defined polymers, we show that crystallization pathways are indeed sequence dependent.