Identifying hydrophobic protein patches to inform protein interaction interfaces

Cutting Edge: LAG3 Dimerization Is Required for TCR/CD3 Interaction and Inhibition of Antitumor Immunity

Lymphocyte activation gene 3 (LAG3) is an inhibitory receptor that plays a critical role in controlling T cell tolerance and autoimmunity and is a major immunotherapeutic target. LAG3 is expressed on the cell surface as a homodimer but the functional relevance of this is unknown. In this study, we show that the association between the TCR/CD3 complex and a murine LAG3 mutant that cannot dimerize is perturbed in CD8+ T cells. We also show that LAG3 dimerization is required for optimal inhibitory function in a B16-gp100 tumor model. Finally, we demonstrate that a therapeutic LAG3 Ab, C9B7W, which does not block LAG3 interaction with its cognate ligand MHC class II, disrupts LAG3 dimerization and its association with the TCR/CD3 complex. These studies highlight the functional importance of LAG3 dimerization and offer additional approaches to therapeutically target LAG3.

N-terminal truncated phospholipase A1 accessory protein PlaS from Serratia marcescens alleviates inhibitory on host cell growth and enhances PlaA1 enzymatic activity

Phospholipase A1 (PLA1) is a kind of specific phospholipid hydrolase widely used in food, medical, textile. However, limitations in its expression and enzymatic activity have prompted the investigation of the phospholipase-assisting protein PlaS. In this study, we elucidate the role of PlaS in enhancing the expression and activity of PlaA1 through N-terminal truncation. Our research demonstrates that truncating the N-terminal region of PlaS effectively overcomes its inhibitory effect on host cells, resulting in improved cell growth and increased protein solubility of the protein. The yeast two-hybrid assay confirms the interaction between PlaA1 and N-terminal truncated PlaS (∆N27 PlaS), highlighting their binding capabilities. Furthermore, in vitro studies using Biacore analysis reveal a concentration-dependent and specific binding between PlaA1 and ∆N27 PlaS, exhibiting high affinity. Molecular docking analysis provides insights into the hydrogen bond interactions between ∆N27 PlaS and PlaA1, identifying key amino acid residues crucial for their binding. Finally, the enzyme activity of PLA1 was boost to 8.4 U/mL by orthogonal test. Study significantly contributes to the understanding of the interaction mechanism between PlaS and PlaA1, offering potential strategies for enhancing PlaA1 activity through protein engineering approaches.

Computation of Overhauser dynamic nuclear polarization processes reveals fundamental correlation between water dynamics, structure, and solvent restructuring entropy

Hydration water dynamics, structure, and thermodynamics are crucially important to understand and predict water-mediated properties at molecular interfaces. Yet experimentally and directly quantifying water behavior locally near interfaces at the sub-nanometer scale is challenging, especially at interfaces submerged in biological solutions. Overhauser dynamic nuclear polarization (ODNP) experiments measure equilibrium hydration water dynamics within 8-15 angstroms of a nitroxide spin probe on instantaneous timescales (10 picoseconds to nanoseconds), making ODNP a powerful tool for probing local water dynamics in the vicinity of the spin probe. As with other spectroscopic techniques, concurrent computational analysis is necessary to gain access to detailed molecular level information about the dynamic, structural, and thermodynamic properties of water from experimental ODNP data. We chose a model system that can systematically tune the dynamics of water, a water-glycerol mixture with compositions ranging from 0 to 0.3 mole fraction glycerol. We demonstrate the ability of molecular dynamics (MD) simulations to compute ODNP spectroscopic quantities, and show that translational, rotational, and hydrogen bonding dynamics of hydration water align strongly with spectroscopic ODNP parameters. Moreover, MD simulations show tight correlations between the dynamic properties of water that ODNP captures and the structural and thermodynamic behavior of water. Hence, experimental ODNP readouts of varying water dynamics suggest changes in local structural and thermodynamic hydration water properties.

Hotspot site microenvironment in the deubiquitinase OTUB1 drives its stability and aggregation

Lewy bodies (LB) are aberrant protein accumulations observed in the brain cells of individuals affected by Parkinson's disease (PD). A comprehensive analysis of LB proteome identified over a hundred proteins, many co-enriched with α-synuclein, a major constituent of LB. Within this context, OTUB1, a deubiquitinase detected in LB, exhibits amyloidogenic properties, yet the mechanisms underlying its aggregation remain elusive. In this study, we identify two critical sites in OTUB1-namely, positions 133 and 173-that significantly impact its amyloid aggregation. Substituting alanine at position 133 and lysine at position 173 enhances both thermodynamic and kinetic stability, effectively preventing amyloid aggregation. Remarkably, lysine at position 173 demonstrates the highest stability without compromising enzymatic activity. The increased stability and inhibition of amyloid aggregation are attributed mainly to the changes in the specific microenvironment at the hotspot. In our exploration of the in-vivo co-occurrence of α-synuclein and OTUB1 in LB, we observed a synergistic modulation of each other's aggregation. Collectively, our study unveils the molecular determinants influencing OTUB1 aggregation, shedding light on the role of specific residues in modulating aggregation kinetics and structural transition. These findings contribute valuable insights into the complex interplay of amino acid properties and protein aggregation, with potential implications for understanding broader aspects of protein folding and aggregation phenomena.

Structure of Human Serum Albumin at a Foam Surface

Proteins can be adsorbed on the air-water interface (AWI), and the structural changes in proteins at the AWI are closely related to the foaming properties of foods and beverages. However, how these structural changes in proteins at the AWI occur is not well understood. We developed a method for the structural assessment of proteins in the foam state using hydrogen/deuterium exchange mass spectrometry. Adsorption sites and structural changes in human serum albumin (HSA) were identified in situ at the peptide-level resolution. The N-terminus and the loop (E492-T506), which contains hydrophobic amino acids, were identified as adsorption sites. Both the structural flexibility and hydrophobicity were considered to be critical factors for the adsorption of HSA at the AWI. Structural changes in HSA were observed after more than one minute of foaming and were spread widely throughout the structure. These structural changes at the foam AWI were reversible.

Exploring preferred binding domains of IgG1 mAbs to multimodal adsorbents using a combined biophysics and simulation approach

In this work, we employ a recently developed biophysical technique that uses diethylpyrocarbonate (DEPC) covalent labeling and mass spectrometry for the identification of mAb binding patches to two multimodal cation exchange resins at different pH. This approach compares the labeling results obtained in the bound and unbound states to identify residues that are sterically shielded and thus located in the mAb binding domains. The results at pH 6 for one mAb (mAb B) indicated that while the complementarity determining region (CDR) had minimal interactions with both resins, the FC domain was actively involved in binding. In contrast, DEPC/MS data with another mAb (mAb C) indicated that both the CDR and FC domains were actively involved in binding. These results corroborated chromatographic retention data with these two mAbs and their fragments and helped to explain the significantly stronger retention of both the intact mAb C and its Fab fragment. In contrast, labeling results with mAb C at pH 7, indicated that only the CDR played a significant role in resin binding, again corroborating chromatographic data. The binding domains identified from the DEPC/MS experiments were also examined using protein surface hydrophobicity maps obtained using a recently developed sparse sampling molecular dynamics (MD) approach in concert with electrostatic potential maps. These results demonstrate that the DEPC covalent labeling/mass spectrometry technique can provide important information about the domain contributions of multidomain proteins such as monoclonal antibodies when interacting with multimodal resins over a range of pH conditions.

An Affordable Topography-Based Protocol for Assigning a Residue's Character on a Hydropathy (PARCH) Scale

The hydropathy of proteins or quantitative assessment of protein-water interactions has been a topic of interest for decades. Most hydropathy scales use a residue-based or atom-based approach to assign fixed numerical values to the 20 amino acids and categorize them as hydrophilic, hydroneutral, or hydrophobic. These scales overlook the protein's nanoscale topography, such as bumps, crevices, cavities, clefts, pockets, and channels, in calculating the hydropathy of the residues. Some recent studies have included protein topography in determining hydrophobic patches on protein surfaces, but these methods do not provide a hydropathy scale. To overcome the limitations in the existing methods, we have developed a Protocol for Assigning a Residue's Character on the Hydropathy (PARCH) scale that adopts a holistic approach to assigning the hydropathy of a residue. The parch scale evaluates the collective response of the water molecules in the protein's first hydration shell to increasing temperatures. We performed the parch analysis of a set of well-studied proteins that include the following─enzymes, immune proteins, and integral membrane proteins, as well as fungal and virus capsid proteins. Since the parch scale evaluates every residue based on its location, a residue may have very different parch values inside a crevice versus a surface bump. Thus, a residue can have a range of parch values (or hydropathies) dictated by the local geometry. The parch scale calculations are computationally inexpensive and can compare hydropathies of different proteins. The parch analysis can affordably and reliably aid in designing nanostructured surfaces, identifying hydrophilic and hydrophobic patches, and drug discovery.

Identifying Potential Ligand Binding Sites on Glycogen Synthase Kinase 3 Using Atomistic Cosolvent Simulations

Glycogen synthase kinase 3 β (GSK3β) is a serine/threonine kinase that phosphorylates several protein substrates in crucial cell signaling pathways. Owing to its therapeutic importance, there is a need to develop GSK3β inhibitors with high specificity and potency. One approach is to find small molecules that can allosterically bind to the GSK3β protein surface. We have employed fully atomistic mixed-solvent molecular dynamics (MixMD) simulations to identify three plausible allosteric sites on GSK3β that can facilitate the search for allosteric inhibitors. Our MixMD simulations narrow down the allosteric sites to precise regions on the GSK3β surface, thereby improving upon the previous predictions of the locations of these sites.

De novo design of a protein binder against Staphylococcus enterotoxin B

Staphylococcus enterotoxin B (SEB) interacts with MHC-II molecules to overactivate immune cells and thereby to produce excessive pro-inflammatory cytokines. Disrupting the interactions between SEB and MHC-II helps eliminate the lethal threat posed by SEB. In this study, a de novo computational approach was used to design protein binders targeting SEB. The MHC-II binding domain of SEB was selected as the target, and the possible promising binding mode was broadly explored. The obtained original binder was folded into triple-helix bundles and contained 56 amino acids with molecular weight 5.9 kDa. The interface of SEB and the binder was highly hydrophobic. ProteinMPNN optimization further enlarged the hydrophobic region of the binder and improved the stability of the binder-SEB complex. In vitro study demonstrated that the optimized binder significantly inhibited the inflammatory response induced by SEB. Overall, our research demonstrated the applicability of this approach in de novo designing protein binders against SEB, and thereby providing potential therapeutics for SEB induced diseases.

Comparative Analysis of Protein Surface Hydrophobicity Maps Determined by Sparse Sampling INDUS and Spatial Aggregation Propensity

Protein surface hydrophobicity plays a central role in various biological processes such as protein folding and aggregation, as well as in the design and manufacturing of biotherapeutics. While the hydrophobicity of protein surface patches has been linked to their constituent residue hydropathies, recent research has shown that protein surface hydrophobicity is more complex and characterized by the response of water to these surfaces. In this work, we employ water density perturbations to map the surface hydrophobicity of a set of model proteins using sparse indirect umbrella sampling simulations (SSI). This technique is used to identify hydrophobic surface patches for the set of model proteins, and the results are compared to those obtained from the widely adopted spatial aggregation propensity (SAP) technique. While SAP-based calculations show agreement with SSI in some cases, there are several examples of disagreement. We identify four general classes of difference in behavior and study factors that contribute to these differences. We find that the SAP method can sometimes mask the effect of weakly nonpolar or isolated nonpolar residues that can lead to strong hydrophobic patches on the protein surface. In addition, hydrophobic patches identified by SAP can exhibit shifts in both position and strength on the SSI map. Our results demonstrate that the combination of topography and chemical context controls the hydrophobicity of a given patch above and beyond the intrinsic polarity of the residues present on the patch surface. The availability of more accurate protein hydrophobicity maps in concert with new classes of hydrophobic molecular descriptors may create significant opportunities for in silico prediction of protein behavior for a range of applications, such as protein design, biomanufacturability, and downstream bioprocessing.

Radical-Mediated Covalent Azidylation of Hydrophobic Microdomains in Water-Soluble Proteins

Hydrophobic microdomains, also known as hydrophobic patches, are essential for many important biological functions of water-soluble proteins. These include ligand or substrate binding, protein-protein interactions, proper folding after translation, and aggregation during denaturation. Unlike transmembrane domains, which are easily recognized from stretches of contiguous hydrophobic sidechains in amino acids via primary protein sequence, these three-dimensional hydrophobic patches cannot be easily predicted. The lack of experimental strategies for directly determining their locations hinders further understanding of their structure and function. Here, we posit that the small triatomic anion N3- (azide) is attracted to these patches and, in the presence of an oxidant, forms a radical that covalently modifies C-H bonds of nearby amino acids. Using two model proteins (BSA and lysozyme) and a cell-free lysate from the model higher plant Arabidopsis thaliana, we find that radical-mediated covalent azidylation occurs within buried catalytic active sites and ligand binding sites and exhibits similar behavior to established hydrophobic probes. The results herein suggest a model in which the azido radical is acting as an "affinity reagent" for nonaqueous three-dimensional protein microenvironments and is consistent with both the nonlocalized electron density of the azide moiety and the known high reactivity of azido radicals widely used in organic chemistry syntheses. We propose that the azido radical is a facile means of identifying hydrophobic microenvironments in soluble proteins and, in addition, provides a simple new method for attaching chemical handles to proteins without the need for genetic manipulation or specialized reagents.

Using Implicit-Solvent Potentials to Extract Water Contributions to Enthalpy-Entropy Compensation in Biomolecular Associations

Biomolecular assembly typically exhibits enthalpy-entropy compensation (EEC) behavior whose molecular origin remains a long-standing puzzle. While water restructuring is believed to play an important role in EEC, its contribution to the entropy and enthalpy changes, and how these changes relate to EEC, remains poorly understood. Here, we show that water reorganization entropy/enthalpy can be obtained by exploiting the temperature dependence in effective, implicit-solvent potentials. We find that the different temperature dependencies in the hydrophobic interaction, rooted in water reorganization, result in substantial variations in the entropy/enthalpy change, which are responsible for EEC. For lower-critical-solution-temperature association, water reorganization entropy dominates the free-energy change at the expense of enthalpy; for upper-critical-solution-temperature association, water reorganization enthalpy drives the process at the cost of entropy. Other effects, such as electrostatic interaction and conformation change of the macromolecules, contribute much less to the variations in entropy/enthalpy.

Main Factors Shaping Amino Acid Usage Across Evolution

The standard genetic code determines that in most species, including viruses, there are 20 amino acids that are coded by 61 codons, while the other three codons are stop triplets. Considering the whole proteome each species features its own amino acid frequencies, given the slow rate of change, closely related species display similar GC content and amino acids usage. In contrast, distantly related species display different amino acid frequencies. Furthermore, within certain multicellular species, as mammals, intragenomic differences in the usage of amino acids are evident. In this communication, we shall summarize some of the most prominent and well-established factors that determine the differences found in the amino acid usage, both across evolution and intragenomically.

Second-Shell Residues Contribute to Catalysis by Predominately Preorganizing the Apo State in PafA

Residues beyond the first coordination shell are often observed to make considerable cumulative contributions in enzymes. Due to typically indirect perturbations of multiple physicochemical properties of the active site, however, their individual and specific roles in enzyme catalysis and disease-causing mutations remain difficult to predict and understand at the molecular level. Here we analyze the contributions of several second-shell residues in phosphate-irrepressible alkaline phosphatase of flavobacterium (PafA), a representative system as one of the most efficient enzymes. By adopting a multifaceted approach that integrates quantum-mechanical/molecular-mechanical free energy computations, molecular-mechanical molecular dynamics simulations, and density functional theory cluster model calculations, we probe the rate-limiting phosphoryl transfer step and structural properties of all relevant enzyme states. In combination with available experimental data, our computational results show that mutations of the studied second-shell residues impact catalytic efficiency mainly by perturbation of the apo state and therefore substrate binding, while they do not affect the ground state or alter the nature of phosphoryl transfer transition state significantly. Several second-shell mutations also modulate the active site hydration level, which in turn influences the energetics of phosphoryl transfer. These mechanistic insights also help inform strategies that may improve the efficiency of enzyme design and engineering by going beyond the current focus on the first coordination shell.

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.

Molecular Dynamics Investigation of Nanoscale Hydrophobicity of Polymer Surfaces: What Makes Water Wet?

The wettability of a polymer surface─related to its hydrophobicity or tendency to repel water─can be crucial for determining its utility, such as for a coating or a purification membrane. While wettability is commonly associated with the macroscopic measurement of a contact angle between surface, water, and air, the molecular physics that underlie these macroscopic observations are not fully known, and anticipating the relative behavior of different polymers is challenging. To address this gap in molecular-level understanding, we use molecular dynamics simulations to investigate and contrast interactions of water with six chemically distinct polymers: polytetrafluoroethylene, polyethylene, polyvinyl chloride, poly(methyl methacrylate), Nylon-66, and poly(vinyl alcohol). We show that several prospective quantitative metrics for hydrophobicity agree well with experimental contact angles. Moreover, the behavior of water in proximity to these polymer surfaces can be distinguished with analysis of interfacial water dynamics, extent of hydrogen bonding, and molecular orientation─even when macroscopic measures of hydrophobicity are similar. The predominant factor dictating wettability is found to be the extent of hydrogen bonding between polymer and water, but the precise manifestation of hydrogen bonding and its impact on surface water structure varies. In the absence of hydrogen bonding, other molecular interactions and polymer mechanics control hydrophobic ordering. These results provide new insights into how polymer chemistry specifically impacts water-polymer interactions and translates to surface hydrophobicity. Such factors may facilitate the design or processing of polymer surfaces to achieve targeted wetting behavior, and presented analyses can be useful in studying the interfacial physics of other systems.

Triggered Polymersome Fusion

The contents of biological cells are retained within compartments formed of phospholipid membranes. The movement of material within and between cells is often mediated by the fusion of phospholipid membranes, which allows mixing of contents or excretion of material into the surrounding environment. Biological membrane fusion is a highly regulated process that is catalyzed by proteins and often triggered by cellular signaling. In contrast, the controlled fusion of polymer-based membranes is largely unexplored, despite the potential application of this process in nanomedicine, smart materials, and reagent trafficking. Here, we demonstrate triggered polymersome fusion. Out-of-equilibrium polymersomes were formed by ring-opening metathesis polymerization-induced self-assembly and persist until a specific chemical signal (pH change) triggers their fusion. Characterization of polymersomes was performed by a variety of techniques, including dynamic light scattering, dry-state/cryogenic-transmission electron microscopy, and small-angle X-ray scattering (SAXS). The fusion process was followed by time-resolved SAXS analysis. Developing elementary methods of communication between polymersomes, such as fusion, will prove essential for emulating life-like behaviors in synthetic nanotechnology.

Lipidation Alters the Structure and Hydration of Myristoylated Intrinsically Disordered Proteins

Lipidated proteins are an emerging class of hybrid biomaterials that can integrate the functional capabilities of proteins into precisely engineered nano-biomaterials with potential applications in biotechnology, nanoscience, and biomedical engineering. For instance, fatty-acid-modified elastin-like polypeptides (FAMEs) combine the hierarchical assembly of lipids with the thermoresponsive character of elastin-like polypeptides (ELPs) to form nanocarriers with emergent temperature-dependent structural (shape or size) characteristics. Here, we report the biophysical underpinnings of thermoresponsive behavior of FAMEs using computational nanoscopy, spectroscopy, scattering, and microscopy. This integrated approach revealed that temperature and molecular syntax alter the structure, contact, and hydration of lipid, lipidation site, and protein, aligning with the changes in the nanomorphology of FAMEs. These findings enable a better understanding of the biophysical consequence of lipidation in biology and the rational design of the biomaterials and therapeutics that rival the exquisite hierarchy and capabilities of biological systems.

Solvation free energy arithmetic for small organic molecules

Solvent-mediated interactions contribute to ligand binding affinities in computational drug design and provide a challenge for theoretical predictions. In this study, we analyze the solvation free energy of benzene derivatives in water to guide the development of predictive models for solvation free energies and solvent-mediated interactions. We use a spatially resolved analysis of local solvation free energy contributions and define solvation free energy arithmetic, which enable us to construct additive models to describe the solvation of complex compounds. The substituents analyzed in this study are carboxyl and nitro-groups due to their similar sterical requirements but distinct interactions with water. We find that nonadditive solvation free energy contributions are primarily attributed to electrostatics, which are qualitatively reproduced with computationally efficient continuum models. This suggests a promising route for the development of efficient and accurate models for the solvation of complex molecules with varying substitution patterns using solvation arithmetic.

Liquid-Liquid Phase Separation? Ask the Water!

Water is more than an inert spectator during liquid-liquid phase separation (LLPS), the reversible compartmentalization of protein solutions into a protein-rich and a dilute phase. We show that LLPS is driven by changes in hydration entropy and enthalpy. Tuning LLPS by adjusting experimental parameters, e.g., addition of co-solutes, is a major goal for biological and medical applications. This requires a general model to quantify thermodynamic driving forces. Here, we develop such a model based on the measured amplitudes of characteristic THz-features of two hydration populations: "Cavity-wrap" water hydrating hydrophobic patches is released during LLPS leading to an increase in entropy. "Bound" water hydrating hydrophilic patches is retained since it is enthalpically favorable. We introduce a THz-phase diagram mapping these spectroscopic/thermodynamic changes. This provides not only a precise understanding of hydrophobic and hydrophilic hydration driving forces as a function of temperature and concentration but also a rational means to tune LLPS.

On the Trail of Molecular Hydrophilicity and Hydrophobicity at Aqueous Interfaces

Uncovering microscopic hydrophilicity and hydrophobicity at heterogeneous aqueous interfaces is essential as it dictates physico/chemical properties such as wetting, the electrical double layer, and reactivity. Several molecular and spectroscopic descriptors were proposed, but a major limitation is the lack of connections between them. Here, we combine density functional theory-based MD simulations (DFT-MD) and SFG spectroscopy to explore how interfacial water responds in contact with self-assembled monolayers (SAM) of tunable hydrophilicity. We introduce a microscopic metric to track the transition from hydrophobic to hydrophilic interfaces. This metric combines the H/V descriptor, a structural descriptor based on the preferential orientation within the water network in the topmost binding interfacial layer (BIL) and spectroscopic fingerprints of H-bonded and dangling OH groups of water carried by BIL-resolved SFG spectra. This metric builds a bridge between molecular descriptors of hydrophilicity/hydrophobicity and spectroscopically measured quantities and provides a recipe to quantitatively or qualitatively interpret experimental SFG signals.

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

The hydrophobicity of an interface determines the magnitude of hydrophobic interactions that drive numerous biological and industrial processes. Chemically heterogeneous interfaces are abundant in these contexts; examples include the surfaces of proteins, functionalized nanomaterials, and polymeric materials. While the hydrophobicity of nonpolar solutes can be predicted and related to the structure of interfacial water molecules, predicting the hydrophobicity of chemically heterogeneous interfaces remains a challenge because of the complex, non-additive contributions to hydrophobicity that depend on the chemical identity and nanoscale spatial arrangements of polar and nonpolar groups. In this work, we utilize atomistic molecular dynamics simulations in conjunction with enhanced sampling and data-centric analysis techniques to quantitatively relate changes in interfacial water structure to the hydration free energy (a thermodynamically well-defined descriptor of hydrophobicity) of chemically heterogeneous interfaces. We analyze a large data set of 58 self-assembled monolayers (SAMs) composed of ligands with nonpolar and polar end groups of different chemical identity (amine, amide, and hydroxyl) in five mole fractions, two spatial patterns, and with scaled partial charges. We find that only five features of interfacial water structure are required to accurately predict hydration free energies. Examination of these features reveals mechanistic insights into the interfacial hydrogen bonding behaviors that distinguish different surface compositions and patterns. This analysis also identifies the probability of highly coordinated water structures as a unique signature of hydrophobicity. These insights provide a physical basis to understand the hydrophobicity of chemically heterogeneous interfaces and connect hydrophobicity to experimentally accessible perturbations of interfacial water structure.

Learning the relationship between nanoscale chemical patterning and hydrophobicity

The hydrophobicity of proteins and similar surfaces, which display chemical heterogeneity at the nanoscale, drives countless aqueous interactions and assemblies. However, predicting how surface chemical patterning influences hydrophobicity remains a challenge. Here, we address this challenge by using molecular simulations and machine learning to characterize and model the hydrophobicity of a diverse library of patterned surfaces, spanning a wide range of sizes, shapes, and chemical compositions. We find that simple models, based only on polar content, are inaccurate, whereas complex neural network models are accurate but challenging to interpret. However, by systematically incorporating chemical correlations between surface groups into our models, we are able to construct a series of minimal models of hydrophobicity, which are both accurate and interpretable. Our models highlight that the number of proximal polar groups is a key determinant of hydrophobicity and that polar neighbors enhance hydrophobicity. Although our minimal models are trained on particular patch size and shape, their interpretability enables us to generalize them to rectangular patches of all shapes and sizes. We also demonstrate how our models can be used to predict hot-spot locations with the largest marginal contributions to hydrophobicity and to design chemical patterns that have a fixed polar content but vary widely in their hydrophobicity. Our data-driven models and the principles they furnish for modulating hydrophobicity could facilitate the design of novel materials and engineered proteins with stronger interactions or enhanced solubilities.

Oxidation of active cysteines mediates protein aggregation of S10R, the cataract-associated mutant of mouse GammaB-crystallin

The Ser10 to Arg mutation in mouse γB-crystallin (MGB) has been associated with protein aggregation, dense nuclear opacity, and the degeneration of fiber cells in the lens core. Overexpression of the gap junction protein, connexin 46 (Cx46), was found to suppress the nuclear opacity and restore normal cell-cell contact. However, the molecular basis for the protein aggregation and related downstream effects were not evident from these studies. Here, we provide a comparison of the structures and solution properties of wild type MGB and the S10R mutant in vitro and show that, even though the mutation does not directly involve cysteine residues, some cysteines in the mutant protein are activated, leading to the enhanced formation of intermolecular disulfide-crosslinked protein aggregates relative to the wild-type. This occurs even as the protein structure is essentially unaltered. Thus, the primary event is enhanced protein aggregation due to the disulfide crosslinking of the mutant protein. We suggest that these aggregates eventually get deposited on fiber cell membranes. Since the gap junction protein, Cx46 is involved in the transport of reduced glutathione, we posit that these deposits interfere in Cx46-mediated glutathione transport and facilitate the oxidative stress-mediated downstream changes. Overexpression of Cx46 suppresses such oxidative aggregation. These studies provide a plausible explanation for the protein aggregation and other changes that accompany this mutation. If indeed cysteine oxidation is the primary event for protein aggregation also in vivo, then the S10R mutant mouse, which is currently available, could serve as a viable animal model for human age-onset cataract.

Understanding Supramolecular Assembly of Supercharged Proteins

Ordered supramolecular assemblies have recently been created using electrostatic interactions between oppositely charged proteins. Despite recent progress, the fundamental mechanisms governing the assembly of oppositely supercharged proteins are not fully understood. Here, we use a combination of experiments and computational modeling to systematically study the supramolecular assembly process for a series of oppositely supercharged green fluorescent protein variants. We show that net charge is a sufficient molecular descriptor to predict the interaction fate of oppositely charged proteins under a given set of solution conditions (e.g., ionic strength), but the assembled supramolecular structures critically depend on surface charge distributions. Interestingly, our results show that a large excess of charge is necessary to nucleate assembly and that charged residues not directly involved in interprotein interactions contribute to a substantial fraction (∼30%) of the interaction energy between oppositely charged proteins via long-range electrostatic interactions. Dynamic subunit exchange experiments further show that relatively small, 16-subunit assemblies of oppositely charged proteins have kinetic lifetimes on the order of ∼10-40 min, which is governed by protein composition and solution conditions. Broadly, our results inform how protein supercharging can be used to create different ordered supramolecular assemblies from a single parent protein building block.

Spectroscopic Fingerprints of Cavity Formation and Solute Insertion as a Measure of Hydration Entropic Loss and Enthalpic Gain

Hydration free energies are dictated by a subtle balance of hydrophobic and hydrophilic interactions. We present here a spectroscopic approach, which gives direct access to the two main contributions: Using THz-spectroscopy to probe the frequency range of the intermolecular stretch (150-200 cm^-1 ) and the hindered rotations (450-600 cm^-1 ), the local contributions due to cavity formation and hydrophilic interactions can be traced back. We show that via THz calorimetry these fingerprints can be correlated 1 : 1 with the group specific solvation entropy and enthalpy. This allows to deduce separately the hydrophobic (i.e. cavity formation) and hydrophilic contributions to thermodynamics, as shown for hydrated alcohols as a case study. Accompanying molecular dynamics simulations quantitatively support our experimental results. In the future our approach will allow to dissect hydration contributions in inhomogeneous mixtures and under non-equilibrium conditions.

Different Temperature- and Pressure-Effects on the Water-Mediated Interactions between Hydrophobic, Hydrophilic, and Hydrophobic-Hydrophilic Nanoscale Surfaces

Water-mediated interactions (WMI) are responsible for diverse processes in aqueous solutions, including protein folding and nanoparticle aggregation. WMI may be affected by changes in temperature and pressure and hence, they can alter chemical/physical processes that occur in aqueous environments. Traditionally, attention has been focused on hydrophobic interactions while, in comparison, the role of hydrophilic and hybrid (hydrophobic-hydrophilic) interactions have been mostly overlooked. Here we study the role of T and P of the WMI between nanoscale (i) hydrophobic-hydrophobic, (ii) hydrophilic-hydrophilic, and (iii) hydrophilic-hydrophobic pairs of (hydroxylated/non-hydroxylated) graphene-based surfaces. We find that hydrophobic, hydrophilic and hybrid interactions are all sensitive to P. However, while hydrophobic interactions [case (i)] are sensitive to T-variations, hydrophilic [case (ii)] and hybrid interactions [case (iii)] are practically T-independent. An analysis of the entropic and enthalpic contributions to the PMF for cases (i)-(iii) is also presented. Our results are important in understanding T- and P-induced protein denaturation, and the interactions of biomolecules in solution, including protein aggregation andphase separation processes. From the computational point of view, the results presented here are relevant in the design of implicit water models for the study of molecular and colloidal/nanoparticle systems at different thermodynamic conditions.

Spatially Resolved Hydration Thermodynamics in Biomolecular Systems

Water is essential for the structure, dynamics, energetics, and thus the function of biomolecules. It is a formidable challenge to elicit, in microscopic detail, the role of the solvation-related driving forces of biomolecular processes, such as the enthalpy and entropy contributions to the underlying free-energy landscape. In this Perspective, we discuss recent developments and applications of computational methods that provide a spatially resolved map of hydration thermodynamics in biomolecular systems and thus yield atomic-level insights to guide the interpretation of experimental observations. An emphasis is on the challenge of quantifying the hydration entropy, which requires characterization of both the motions of the biomolecules and of the water molecules in their surrounding.

Computational models for studying physical instabilities in high concentration biotherapeutic formulations

Computational prediction of the behavior of concentrated protein solutions is particularly advantageous in early development stages of biotherapeutics when material availability is limited and a large set of formulation conditions needs to be explored. This review provides an overview of the different computational paradigms that have been successfully used in modeling undesirable physical behaviors of protein solutions with a particular emphasis on high-concentration drug formulations. This includes models ranging from all-atom simulations, coarse-grained representations to macro-scale mathematical descriptions used to study physical instability phenomena of protein solutions such as aggregation, elevated viscosity, and phase separation. These models are compared and summarized in the context of the physical processes and their underlying assumptions and limitations. A detailed analysis is also given for identifying protein interaction processes that are explicitly or implicitly considered in the different modeling approaches and particularly their relations to various formulation parameters. Lastly, many of the shortcomings of existing computational models are discussed, providing perspectives and possible directions toward an efficient computational framework for designing effective protein formulations.

Sequence Modulates Polypeptoid Hydration Water Structure and Dynamics

We use molecular dynamics simulations to investigate the effect of polypeptoid sequence on the structure and dynamics of its hydration waters. Polypeptoids provide an excellent platform to study small-molecule hydration in disordered polymers, as they can be precisely synthesized with a variety of sidechain chemistries. We examine water behavior near a set of peptoid oligomers in which the number and placement of nonpolar versus polar sidechains are systematically varied. To do this, we leverage a new computational workflow enabling accurate sampling of polypeptoid conformations. We find that the hydration waters are less dense, are more tetrahedral, and have slower dynamics compared to bulk water. The magnitude of these shifts increases with the number of nonpolar groups. We also find that shifts in the water structure and dynamics are strongly correlated, suggesting that experimental insight into the dynamics of hydration water obtained by Overhauser dynamic nuclear polarization (ODNP) also contains information about water structural properties. We then demonstrate the ability of ODNP to probe site-specific dynamics of hydration water near these model peptoid systems.

How Far Is "Bulk Water" from Interfaces? Depends on the Nature of the Surface and What We Measure

Using systematic molecular dynamics (MD) simulations, we revisit the question: At what distance from an interface do the properties of "bulk water" get recovered? We have considered three different kinds of interfaces: nonpolar (hydrophobic; isooctane-water interface), charged (negative; AOT bilayer), and polar (zwitterionic; POPC bilayer). In order to interrogate the extent of perturbation of the interfacial water molecules as a function of the distance from the interface, we utilize a diverse range of structural and dynamical parameters. To capture the structural perturbations, we look into local density (translational order), local tetrahedral order parameter, and dipolar orientation of the water molecules. We also explore the anisotropic diffusion of the water molecules in the direction perpendicular to the interface as well as the planar diffusion parallel to the interface in a distance dependent manner. In addition, the orientational time correlation functions have been computed to understand the extent of slowdown in the rotational dynamics. As expected, the electrostatic field emanating from the charged AOT interface seems to have the highest long-range effect on the orientational order and dynamics of the water molecules, whereas specific interactions like hydrogen bonding and electrostatic interaction lead to significant trapping and kinetic slowdown for both AOT and POPC (zwitterionic) very close to the interface. Our analysis highlights that not only the length-scale of perturbation depends on the nature of the interfaces and specific interactions but also the type of water property that we measure/calculate. Different water properties seem to have widely different length-scale of perturbation. Orientational order parameters seem to be perturbed to a much longer length-scale as compared to translational order parameters. The global orientational order of water can be perturbed even up to ∼4-5 nm near the negatively charged AOT surface in the absence of any extra electrolyte. This observation has significant implication toward the interpretation of experimental measurements as well since different spectroscopic techniques would probe different parameters or water properties with possible mutual disagreement and inconsistency between different types of measurements. Thus, our study provides a broader and unifying perspective toward the aspect of "context dependent" structural and dynamical perturbation of "interfacial water".

Size-Dependent Order-Disorder Crossover in Hydrophobic Hydration: Comparison between Spherical Solutes and Linear Alcohols

Theory and computer simulation studies have predicted that water molecules around hydrophobic molecules should undergo an order-disorder transition with increasing solute size around a 1 nm length scale. Some theories predict the formation of a clathrate-like ordered structure around smaller hydrophobic solutes (<1 nm) and the formation of disordered vapor-liquid interfaces around larger solutes (>1 nm) and surfaces. Experimental validation of these predictions has often been elusive and contradictory. High-resolution Raman spectroscopy has detected that water around small hydrophobic solutes shows a signature similar to that of bulk water at lower temperature (increased ordering and a stronger hydrogen-bonded network). Similarly, water around larger solutes shows an increasing population of dangling OH bonds very similar to higher temperature bulk water. Thus, the solute size dependence of the structure and dynamics of water around hydrophobic molecules seems to have an analogy with the temperature dependence in bulk water. In this work, using atomistic classical molecular dynamics (MD) simulations, we have systematically investigated this aspect and characterized this interesting analogy. Structural order parameters including the tetrahedral order parameter (Q), hydrogen bond distribution, and vibrational power spectrum highlight this similarity. However, in contrast to the experimental observations, we do not observe any length-dependent crossover for linear hydrophobic alcohols (n-alkanols) using classical MD simulations. This is in agreement with earlier findings that linear alkane chains do not demonstrate the length-dependent order-disorder transition due to the presence of a sub-nanometer length scale along the cross section of the chain. Moreover, the collapsed state of linear hydrocarbon chains is not significantly populated for smaller chains (number of carbons below 20). In the context of our computational results, we raise several pertinent questions related to the sensitivity of various structural and dynamical parameters toward capturing these complex phenomena of hydrophobic hydration.

Membrane hydrophobicity determines the activation free energy of passive lipid transport

The collective behavior of lipids with diverse chemical and physical features determines a membrane's thermodynamic properties. Yet, the influence of lipid physicochemical properties on lipid dynamics, in particular interbilayer transport, remains underexplored. Here, we systematically investigate how the activation free energy of passive lipid transport depends on lipid chemistry and membrane phase. Through all-atom molecular dynamics simulations of 11 chemically distinct glycerophospholipids, we determine how lipid acyl chain length, unsaturation, and headgroup influence the free energy barriers for two elementary steps of lipid transport: lipid desorption, which is rate limiting, and lipid insertion into a membrane. Consistent with previous experimental measurements, we find that lipids with longer, saturated acyl chains have increased activation free energies compared to lipids with shorter, unsaturated chains. Lipids with different headgroups exhibit a range of activation free energies; however, no clear trend based solely on chemical structure can be identified, mirroring difficulties in the interpretation of previous experimental results. Compared to liquid-crystalline phase membranes, gel phase membranes exhibit substantially increased free energy barriers. Overall, we find that the activation free energy depends on a lipid's local hydrophobic environment in a membrane and that the free energy barrier for lipid insertion depends on a membrane's interfacial hydrophobicity. Both of these properties can be altered through changes in lipid acyl chain length, lipid headgroup, and membrane phase. Thus, the rate of lipid transport can be tuned through subtle changes in local membrane composition and order, suggesting an unappreciated role for nanoscale membrane domains in regulating cellular lipid dynamics.

Characterizing the Interplay between Polymer Solvation and Conformation

Conformational transitions of flexible molecules, especially those driven by hydrophobic effects, tend to be hindered by desolvation barriers. For such transitions, it is thus important to characterize and understand the interplay between solvation and conformation. Using specialized molecular simulations, here we perform such a characterization for a hydrophobic polymer solvated in water. We find that an external potential, which unfavorably perturbs the polymer hydration waters, can trigger a coil-to-globule or collapse transition, and that the relative stabilities of the collapsed and extended states can be quantified by the strength of the requisite potential. Our results also provide mechanistic insights into the collapse transition, highlighting that the bottleneck to polymer collapse is the formation of a sufficiently large cluster, and the collective dewetting of such a cluster. We also study the collapse of the hydrophobic polymer in octane, a nonpolar solvent, and interestingly, we find that the mechanistic details of the transition are qualitatively similar to that in water.