Reconciling the understanding of 'hydrophobicity' with physics-based models of proteins

Traversing DNA-Protein Interactions Between Mesophilic and Thermophilic Bacteria: Implications from Their Cold Shock Response

Cold shock proteins (CSPs) are small, acidic proteins which contain a conserved nucleic acid-binding domain. These perform mRNA translation acting as "RNA chaperones" when triggered by low temperatures initiating their cold shock response. CSP- RNA interactions have been predominantly studied. Our focus will be CSP-DNA interaction examination, to analyse the diverse interaction patterns such as electrostatic, hydrogen and hydrophobic bonding in both thermophilic and mesophilic bacteria. The differences in the molecular mechanism of these contrasting bacterial proteins are studied. Computational techniques such as modelling, energy refinement, simulation and docking were operated to obtain data for comparative analysis. The thermostability factors which stabilise a thermophilic bacterium and their effect on their molecular regulation is investigated. Conformational deviation, atomic residual fluctuations, binding affinity, Electrostatic energy and Solvent Accessibility energy were determined during stimulation along with their conformational study. The study revealed that mesophilic bacteria E. coli CSP have higher binding affinity to DNA than thermophilic G. stearothermophilus. This was further evident by low conformation deviation and atomic fluctuations during simulation.

Molecular Dynamics Study of the Antifouling Mechanism of Hydrophilic Polymer Brushes

We perform all-atom molecular dynamics simulations of the adsorption of amino acid side-chain analogues on polymer brushes. The analogues examined are nonpolar isobutane, polar propionamide, negatively charged propionate ion, and positively charged butylammonium ion. The polymer brushes consist of a sheet of graphene and strongly hydrophilic poly(carboxybetaine methacrylate) (PCBMA) or weakly hydrophilic poly(2-hydroxyethyl methacrylate) (PHEMA). The effective interactions between isobutane and polymer chains are repulsive for PCBMA and attractive for PHEMA. Gibbs energy decomposition analysis shows that this is due to the abundance of water in the PCBMA brush, which increases the steric repulsion and decreases the Lennard-Jones attraction. The affinity of the hydrophilic analogues is low for both PCBMA and PHEMA chains, but the balance between the components of the Gibbs energy is different for the two polymers. The simulations are performed at several θ, where θ is the degree of overlap of polymer chains. The antifouling performance against the neutral analogues is better for PCBMA than for PHEMA in the low and high θ regimes. However, in the middle θ regime, the antifouling performance of PHEMA is close to or better than that of PCBMA. This is attributed to the formation of a dense layer of PHEMA on the graphene surface that inhibits direct adsorption of analogue molecules on graphene. The charged analogues do not bind to either the PHEMA or PCBMA brush irrespective of θ.

Sequence determinants and solution conditions underlying liquid to solid phase transition

Life consists of numberless functional biomolecules that exist in various states. Besides well-dissolved phases, biomolecules especially proteins and nucleic acids can form liquid droplets through liquid-liquid phase separation (LLPS). Stronger interactions promote a solid-like state of biomolecular condensates, which are also formerly referred to as detergent-insoluble aggregates. Solid-like condensates exist in vivo physiologically and pathologically, and their formation has not been fully understood. Recently, more and more research has proven that liquid to solid phase transition (LST) is an essential way to form solid condensates. In this review, we summarized the regions in the sequence that have different impacts on phase transition and emphasized that the LST is affected by its sequence characteristics. Moreover, increasing evidence unveiled that LST is affected by various solution conditions. We discussed solution conditions like protein concentration, pH, ATP, ions, and small molecules in a solution. Methods have been established to study these solid phase components. Here, we summarized low-throughput experimental techniques and high-throughput omics methods in the study of the LST.

Affinity of small-molecule solutes to hydrophobic, hydrophilic, and chemically patterned interfaces in aqueous solution

Performance of membranes for water purification is highly influenced by the interactions of solvated species with membrane surfaces, including surface adsorption of solutes upon fouling. Current efforts toward fouling-resistant membranes often pursue surface hydrophilization, frequently motivated by macroscopic measures of hydrophilicity, because hydrophobicity is thought to increase solute-surface affinity. While this heuristic has driven diverse membrane functionalization strategies, here we build on advances in the theory of hydrophobicity to critically examine the relevance of macroscopic characterizations of solute-surface affinity. Specifically, we use molecular simulations to quantify the affinities to model hydroxyl- and methyl-functionalized surfaces of small, chemically diverse, charge-neutral solutes represented in produced water. We show that surface affinities correlate poorly with two conventional measures of solute hydrophobicity, gas-phase water solubility and oil-water partitioning. Moreover, we find that all solutes show attraction to the hydrophobic surface and most to the hydrophilic one, in contrast to macroscopically based hydrophobicity heuristics. We explain these results by decomposing affinities into direct solute interaction energies (which dominate on hydroxyl surfaces) and water restructuring penalties (which dominate on methyl surfaces). Finally, we use an inverse design algorithm to show how heterogeneous surfaces, with multiple functional groups, can be patterned to manipulate solute affinity and selectivity. These findings, importantly based on a range of solute and surface chemistries, illustrate that conventional macroscopic hydrophobicity metrics can fail to predict solute-surface affinity, and that molecular-scale surface chemical patterning significantly influences affinity-suggesting design opportunities for water purification membranes and other engineered interfaces involving aqueous solute-surface interactions.

Ensembles of Hydrophobicity Scales as Potent Classifiers for Chimeric Virus-Like Particle Solubility - An Amino Acid Sequence-Based Machine Learning Approach

Virus-like particles (VLPs) are protein-based nanoscale structures that show high potential as immunotherapeutics or cargo delivery vehicles. Chimeric VLPs are decorated with foreign peptides resulting in structures that confer immune responses against the displayed epitope. However, insertion of foreign sequences often results in insoluble proteins, calling for methods capable of assessing a VLP candidate's solubility in silico. The prediction of VLP solubility requires a model that can identify critical hydrophobicity-related parameters, distinguishing between VLP-forming aggregation and aggregation leading to insoluble virus protein clusters. Therefore, we developed and implemented a soft ensemble vote classifier (sEVC) framework based on chimeric hepatitis B core antigen (HBcAg) amino acid sequences and 91 publicly available hydrophobicity scales. Based on each hydrophobicity scale, an individual decision tree was induced as classifier in the sEVC. An embedded feature selection algorithm and stratified sampling proved beneficial for model construction. With a learning experiment, model performance in the space of model training set size and number of included classifiers in the sEVC was explored. Additionally, seven models were created from training data of 24-384 chimeric HBcAg constructs, which were validated by 100-fold Monte Carlo cross-validation. The models predicted external test sets of 184-544 chimeric HBcAg constructs. Best models showed a Matthew's correlation coefficient of >0.6 on the validation and the external test set. Feature selection was evaluated for classifiers with best and worst performance in the chimeric HBcAg VLP solubility scenario. Analysis of the associated hydrophobicity scales allowed for retrieval of biological information related to the mechanistic backgrounds of VLP solubility, suggesting a special role of arginine for VLP assembly and solubility. In the future, the developed sEVC could further be applied to hydrophobicity-related problems in other domains, such as monoclonal antibodies.

Hydration-Shell Vibrational Spectroscopy

Hydration-shell vibrational spectroscopy provides an experimental window into solute-induced water structure changes that mediate aqueous folding, binding, and self-assembly. Decomposition of measured Raman and infrared (IR) spectra of aqueous solutions using multivariate curve resolution (MCR) and related methods may be used to obtain solute-correlated spectra revealing solute-induced perturbations of water structure, such as changes in water hydrogen-bond strength, tetrahedral order, and the presence of dangling (non-hydrogen-bonded) OH groups. More generally, vibrational-MCR may be applied to both aqueous and nonaqueous solutions, including multicomponent mixtures, to quantify solvent-mediated interactions between oily, polar, and ionic solutes, in both dilute and crowded fluids. Combining vibrational-MCR with emerging theoretical modeling strategies promises synergetic advances in the predictive understanding of multiscale self-assembly processes of both biological and technological interest.

A local fingerprint for hydrophobicity and hydrophilicity: From methane to peptides

An important characteristic that determines the behavior of a solute in water is whether it is hydrophobic or hydrophilic. The traditional classification is based on chemical experience and heuristics. However, this does not reveal how the local environment modulates this important property. We present a local fingerprint for hydrophobicity and hydrophilicity inspired by the two body contribution to the entropy. This fingerprint is an inexpensive, quantitative, and physically meaningful way of studying hydrophilicity and hydrophobicity that only requires as input the water-solute radial distribution functions. We apply our fingerprint to octanol, benzene, and 20 proteinogenic amino acids. Our measure of hydrophilicity is coherent with chemical experience, and moreover, it also shows how the character of an atom can change as its environment is changed. Finally, we use the fingerprint as a collective variable in a funnel metadynamics simulation of a host-guest system. The fingerprint serves as a desolvation collective variable that enhances transitions between the bound and unbound states.

Implicit Solvation Using the Superposition Approximation (IS-SPA): An Implicit Treatment of the Nonpolar Component to Solvation for Simulating Molecular Aggregation

Nonpolar solute-solvent interactions are the driving force for aggregation in important chemical and biological phenomena including protein folding, peptide self-assembly, and oil-water emulsion formation. Currently, the most accurate and computationally efficient description of these processes requires an explicit treatment of all solvent and solute atoms. Previous computationally feasible implicit solvent models, such as solute surface area approaches, are unsuccessful at capturing aggregation features including both structural and energetic trends while more theoretically rigorous approaches, such as Reference Interaction Site Model (RISM), are accurate but extremely computationally demanding. Our approach, denoted Implicit Solvation using the Superposition Approximation (IS-SPA), builds on previous theory utilizing the Kirkwood superposition approximation to approximate the mean force of the solvent from solute parameters. We introduce and verify a parabolic first solvation shell truncation of atomic solvation, fitting water distributions around a molecule, and a Monte Carlo integration of the mean solvent force. These extensions allow this method to be implemented as an efficient nonpolar implicit solvent model for molecular simulation. The approximations in IS-SPA are first explored and justified for the homodimerization of an array of different sized Lennard-Jones spheres. The accuracy and transferability of the approach are demonstrated by its ability to capture the position and relative energies of the desolvation barrier and free energy minimum of alkane homodimers. The model is then shown to reproduce the phase separation and solubility of cyclohexane and water. These promising results, coupled with 2 orders of magnitude speed-up for dilute systems as compared to explicit solvent simulations, demonstrate that IS-SPA is an appealing approach to boost the time- and length-scale of molecular aggregation simulations.

Solvation Thermodynamics of Oligoglycine with Respect to Chain Length and Flexibility

Oligoglycine is a backbone mimic for all proteins and is prevalent in the sequences of intrinsically disordered proteins. We have computed the absolute chemical potential of glycine oligomers at infinite dilution by simulation with the CHARMM36 and Amber ff12SB force fields. We performed a thermodynamic decomposition of the solvation free energy (ΔG(sol)) of Gly2-5 into enthalpic (ΔH(sol)) and entropic (ΔS(sol)) components as well as their van der Waals and electrostatic contributions. Gly2-5 was either constrained to a rigid/extended conformation or allowed to be completely flexible during simulations to assess the effects of flexibility on these thermodynamic quantities. For both rigid and flexible oligoglycine models, the decrease in ΔG(sol) with chain length is enthalpically driven with only weak entropic compensation. However, the apparent rates of decrease of ΔG(sol), ΔH(sol), ΔS(sol), and their elec and vdw components differ for the rigid and flexible models. Thus, we find solvation entropy does not drive aggregation for this system and may not explain the collapse of long oligoglycines. Additionally, both force fields yield very similar thermodynamic scaling relationships with respect to chain length despite both force fields generating different conformational ensembles of various oligoglycine chains.

Real-time monitoring of hydrophobic aggregation reveals a critical role of cooperativity in hydrophobic effect

The hydrophobic interaction drives nonpolar solutes to aggregate in aqueous solution, and hence plays a critical role in many fundamental processes in nature. An important property intrinsic to hydrophobic interaction is its cooperative nature, which is originated from the collective motions of water hydrogen bond networks surrounding hydrophobic solutes. This property is widely believed to enhance the formation of hydrophobic core in proteins. However, cooperativity in hydrophobic interactions has not been successfully characterized by experiments. Here, we quantify cooperativity in hydrophobic interactions by real-time monitoring the aggregation of hydrophobic solute (hexaphenylsilole, HPS) in a microfluidic mixer. We show that association of a HPS molecule to its aggregate in water occurs at sub-microsecond, and the free energy change is −5.8 to −13.6 kcal mol⁻¹. Most strikingly, we discover that cooperativity constitutes up to 40% of this free energy. Our results provide quantitative evidence for the critical role of cooperativity in hydrophobic interactions.

Hydrophobic interactions occur between nonpolar molecules in water and their experimental quantification can help the understanding of biological self-assembly. Here Jiang et al. examine the kinetics and thermodynamics of hydrophobic aggregation in a bulk environment and characterize its cooperativity.