Structural features of interfacial water predict the hydrophobicity of chemically heterogeneous surfaces

Context Dependency of Hydrophobicity in Intrinsically Disordered Proteins: Insights from a New Dewetting Free Energy-Based Hydrophobicity Scale

The interaction between amino acids (AAs) and hydration water is fundamental to protein folding and protein-protein interactions. Here, we proposed a hydrophobicity scale for AAs based on their computed free energetic cost of dewetting. This metric captures both entropic and enthalpic contributions of AA-water interactions and allows a systematic and intuitive classification of AAs. Using indirect umbrella sampling (INDUS), we rank individual AAs based on the relative magnitude of their dewetting free energies, from lowest (most hydrophobic) to highest (most hydrophilic). This new hydrophobicity scale is a starting point to evaluate different elements of water hydration behavior, and we focus here on the water structure and translational diffusivity of the hydration waters. While the latter is commonly used as a proxy for hydrophobicity, we show that its behavior is in fact nonmonotonic: hydrophobic residues show slow water diffusion due to highly structured hydration water networks, while highly hydrophilic residues have slow water diffusion due to strong hydrogen bonds with water despite less structured hydration networks. We extend our analysis of hydration properties to intrinsically disordered peptides with varied sequence patterning (sequences of proline/leucine and arginine/glutamic acid residues). We find that the hydration behavior of these peptides is highly context-dependent, with hydrophobic (hydrophilic) patches cooperatively enhancing hydrophobicity (hydrophilicity). These molecular insights of sequence-dependent hydration behaviors may be particularly impactful for the study of intrinsically disordered proteins implicated in liquid-liquid phase separation and aggregation, processes where AAs' hydration environments are complex and changing.

Protein-surface interactions in nano-scale biosensors for IL-6 detection using functional monolayers

A multiscale approach is employed to investigate the interaction dynamics between interleukin-6, a key cancer biomarker, and alkyl-functionalized surfaces, with the ultimate goal of guiding biosensor design. The study integrates classical molecular dynamics, Brownian dynamics simulations, and binding experiments to explore the adsorption dynamics and energetics of IL-6 on surfaces modified with self-assembled monolayers (SAMs). The comparative analysis reveals a dramatic effect on the interaction strength of IL-6 with a SAMs comprising a mix of charged and hydrophobic ligands. Solvent accessible surface area analysis shows enhanced exposure of charged terminal groups on the mixed SAM surface. Experimental investigations using surface plasmon resonance reveal that IL-6 interactions enhance with increased charged ligand content in mixed SAMs, retaining high binding affinity even under high ionic strength conditions. Computational studies further highlight hydrophobic and electrostatic interactions as key factors driving the high affinity of IL-6 on the mixed SAMs surface. This research offers insights into optimizing surfaces for enhanced IL-6 recognition, which can be extended to other protein biomarkers, by combining experimental and computational approaches to improve biosensing performance.

Revealing the Solution Conformation and Hydration Structure of Type I Tropocollagen Using X-ray Scattering and Molecular Dynamics Simulation

Hydration plays a crucial role in regulating the dispersion behavior of biomolecules in water, particularly in how pH-sensitive hydration water network forms around proteins. This study explores the conformation and hydration structure of Type-I tropocollagen using small- and wide-angle X-ray scattering (SWAXS) and molecular dynamics (MD) simulations. The results reveal that tropocollagen exhibits a significant softening conformation in solution, transitioning from its rod-like structure in tissues to a worm-like conformation, characterized by a reduced radius of gyration of 50 nm and a persistent length of 34 nm. The SWAXS-supported MD calculations further establish a hydration water network characterized by a 2.8 Å free-water exclusion zone where water molecules are largely hydrogen-bonded to the densely distributed polar groups on the tropocollagen surfaces. These first-layer water molecules are bridged by outer water molecules extending up to 4 Å from the protein surfaces, forming a major hydration shell that encapsulates the protein.

Protein adsorption on blood-contacting surfaces: A thermodynamic perspective to guide the design of antithrombogenic polymer coatings

Blood-contacting medical devices often succumb to thrombosis, limiting their durability and safety in clinical applications. Thrombosis is fundamentally initiated by the nonspecific adsorption of proteins to the material surface, which is strongly governed by thermodynamic factors established by the nature of the interaction between the material surface, surrounding water molecules, and the protein itself. Along these lines, different surface materials (such as polymeric, metallic, ceramic, or composite) induce different entropic and enthalpic changes at the surface-protein interface, with material wettability significantly impacting this behavior. Consequently, protein adsorption on medical devices can be modulated by altering their wettability and surface energy. A plethora of polymeric coating modifications have been utilized for this purpose; hydrophobic modifications may promote or inhibit protein adsorption determined by van der Waals forces, while hydrophilic materials achieve this by mainly relying on hydrogen bonding, or unbalanced/balanced electrostatic interactions. This review offers a cohesive understanding of the thermodynamics governing these phenomena, to specifically aid in the design and selection of hemocompatible polymeric coatings for biomedical applications. STATEMENT OF SIGNIFICANCE: Blood-contacting medical devices often succumb to thrombosis, limiting their durability and safety in clinical applications. A plethora of polymeric coating modifications have been utilized for addressing this issue. This review offers a cohesive understanding of the thermodynamics governing these phenomena, to specifically aid in the design and selection of hemocompatible polymeric coatings for biomedical applications.

Relationships between Water's Structure and Solute Affinity at Polypeptoid Brush Surfaces

Excellent antifouling surfaces are generally thought to create a tightly bound layer of water that resists solute adsorption, and highly hydrophilic surfaces such as those with zwitterionic functionalities are of significant current interest as antifoulant strategies. However, despite significant proofs-of-concept, we still lack a fundamental understanding of how the nanoscopic structure of this hydration layer translates to reduced fouling, how surface chemistry can be tuned to achieve antifouling through hydration water, and why, in particular, zwitterionic surfaces seem so promising. Here, we use molecular dynamics simulations and free energy calculations to investigate the molecular relationships among surface chemistry, hydration water structure, and surface-solute affinity across a variety of surface-decorated chemistries. Specifically, we consider polypeptoid-decorated surfaces that display well-known experimental antifouling capabilities and that can be synthesized sequence specifically, with precise backbone positioning of, e.g., charged groups. Through simulations, we calculate the affinities of a range of small solutes to polypeptoid brush surfaces of varied side-chain chemistries. We then demonstrate that measures of the structure of surface hydration water in response to a particular surface chemistry signal solute-surface affinity; specifically, we find that zwitterionic chemistries produce solute-surface repulsion through highly coordinated hydration water while suppressing tetrahedral structuring around the solute, in contrast to uncharged surfaces that show solute-surface affinity. Based on the relationship of this structural perturbation to the affinity of small-molecule solutes, we propose a molecular mechanism by which zwitterionic surface chemistries enhance solute repulsion, with broader implications for the design of antifouling surfaces.

Precision Proteoform Design for 4R Tau Isoform Selective Templated Aggregation

Prion-like spread of disease-specific tau conformers is a hallmark of all tauopathies. A 19-residue probe peptide containing a P301L mutation and spanning the R2/R3 splice junction of tau, folds and stacks into seeding-competent fibrils and induces aggregation of 4R, but not 3R tau. These tau peptide fibrils propagate aggregated intracellular tau over multiple generations, have a high β-sheet content, a colocalized lipid signal, and adopt a well-defined U-shaped fold found in 4R tauopathy brain-derived fibrils. Fully atomistic replica exchange molecular dynamics (MD) simulations were used to compute the free energy landscapes of the conformational ensemble of the peptide monomers. These identified an aggregation-prohibiting β-hairpin structure and an aggregation-competent U-fold unique to 4R tauopathy fibrils. Guided by MD simulations, we identified that the N-terminal-flanking residues to PHF6, which slightly vary between 4R and 3R isoforms, modulate seeding. Strikingly, when a single amino acid switch at position 305 replaced the serine of 4R tau with a lysine from the corresponding position in the first repeat of 3R tau, the seeding induced by the 19-residue peptide was markedly reduced. Conversely, a 4R tau mimic with three repeats, prepared by replacing those amino acids in the first repeat with those amino acids uniquely present in the second repeat, recovered aggregation when exposed to the 19-residue peptide. These peptide fibrils function as partial prions to recruit naïve 4R tau-ten times the length of the peptide-and serve as a critical template for 4R tauopathy propagation. These results hint at opportunities for tau isoform-specific therapeutic interventions.

Local solvation structures govern the mixing thermodynamics of glycerol-water solutions

Glycerol is a major cryoprotective agent and is widely used to promote protein stabilization. By a combined experimental and theoretical study, we show that global thermodynamic mixing properties of glycerol and water are dictated by local solvation motifs. We identify three hydration water populations, i.e., bulk water, bound water (water hydrogen bonded to the hydrophilic groups of glycerol) and cavity wrap water (water hydrating the hydrophobic moieties). Here, we show that for glycerol experimental observables in the THz regime allow quantification of the abundance of bound water and its partial contribution to the mixing thermodynamics. Specifically, we uncover a 1 : 1 connection between the population of bound waters and the mixing enthalpy, which is further corroborated by the simulation results. Therefore, the changes in global thermodynamic quantity - mixing enthalpy - are rationalized at the molecular level in terms of changes in the local hydrophilic hydration population as a function of glycerol mole fraction in the full miscibility range. This offers opportunities to rationally design polyol water, as well as other aqueous mixtures to optimize technological applications by tuning mixing enthalpy and entropy based on spectroscopic screening.

Relationships between Molecular Structural Order Parameters and Equilibrium Water Dynamics in Aqueous Mixtures

Water's unique thermophysical properties and how it mediates aqueous interactions between solutes have long been interpreted in terms of its collective molecular structure. The seminal work of Errington and Debenedetti [Nature 2001, 409, 318-321] revealed a striking hierarchy of relationships among the thermodynamic, dynamic, and structural properties of water, motivating many efforts to understand (1) what measures of water structure are connected to different experimentally accessible macroscopic responses and (2) how many such structural metrics are adequate to describe the collective structural behavior of water. Diffusivity constitutes a particularly interesting experimentally accessible equilibrium property to investigate such relationships because advanced NMR techniques allow the measurement of bulk and local water dynamics in nanometer proximity to molecules and interfaces, suggesting the enticing possibility of measuring local diffusivities that report on water structure. Here, we apply statistical learning methods to discover persistent structure-dynamic correlations across a variety of simulated aqueous mixtures, from alcohol-water to polypeptoid-water systems. We investigate a variety of molecular water structure metrics and find that an unsupervised statistical learning algorithm (namely, sequential feature selection) identifies only two or three independent structural metrics that are sufficient to predict water self-diffusivity accurately. Surprisingly, the translational diffusivity of water across all mixed systems studied here is strongly correlated with a measure of tetrahedral order given by water's triplet angle distribution. We also identify a separate small number of structural metrics that well predict an important thermodynamic property, the excess chemical potential of an idealized methane-sized hydrophobe in water. Ultimately, we offer a Bayesian method of inferring water structure by using only structure-dynamics linear regression models with experimental Overhauser dynamic nuclear polarization (ODNP) measurements of water self-diffusivity. This study thus quantifies the relationships among several distinct structural order parameters in water and, through statistical learning, reveals the potential to leverage molecular structure to predict fundamental thermophysical properties. In turn, these findings suggest a framework for solving the inverse problem of inferring water's molecular structure using experimental measurements such as ODNP studies that probe local water properties.