ADD Force Field for Sugars and Polyols: Predicting the Additivity of Protein-Osmolyte Interaction

Additivity of Transfer Free Energies Enables the Description of Complex Protein Formulations in Implicit Solvent Molecular Dynamics Simulations

A complex 3D structure and the surrounding environment determine the function and stability of a protein. Various osmolytes can be added to a protein drug formulation to stabilize the native protein structure by preventing unfolding and aggregation. In this context, the concept of transfer free energy, which represents the change in chemical potential of a protein being transferred from water to an osmolyte solution, has emerged as a powerful tool to elucidate the energetics involved in the protein-osmolyte interaction. In the present work, we experimentally determine the transfer free energies for the excipients sodium chloride, arginine hydrochloride, and polysorbate 20, which are frequently used in pharmaceutical protein formulations. We show that these excipients display distinct patterns of exclusion or interaction toward different moieties on the protein surface. Furthermore, we report that the free energy cost for transferring a protein to a formulation composed of multiple components can be calculated by summing up the contributions of the individual components. This finding suggests that additivity applies to the transfer free energies. We demonstrate that this additive behavior can be leveraged to accurately and efficiently model complex protein formulations. Additionally, we discuss how transfer free energies can be incorporated within implicit solvent molecular dynamics calculations, providing a direct link between experiments and simulations. Our molecular dynamics results show good agreement with experimental data for lysozyme, interferon α-2a, and granulocyte colony-stimulating factor, for both single- and multicomponent matrices, demonstrating the validity of our approach.

Assessing the Effect of Deep Eutectic Solvents on α-Chymotrypsin Thermal Stability and Activity

Optimizing the liquid reaction phase holds significant potential for enhancing the efficiency of biocatalytic processes since it determines reaction equilibrium and kinetics. This study investigates the influence of the addition of deep eutectic solvents on the stability and activity of α-chymotrypsin, a proteolytic enzyme with industrial relevance. Deep eutectic solvents, composed of choline chloride or betaine mixed with glycerol or sorbitol, were added in the reaction phase at various concentrations. Experimental techniques, including kinetic and fluorometry, were employed to assess the α-chymotrypsin activity, thermal stability, and unfolding reversibility. Atomistic molecular dynamics simulations were also conducted to assess the interactions and provide molecular-level insights between α-chymotrypsin and the solvent. The results showed that among all studied mixtures, adding choline chloride + sorbitol improved thermal stability up to 18 °C and reaction kinetic efficiency up to two-fold upon adding choline chloride + glycerol. Notably, the choline chloride + sorbitol system exhibited the most substantial stabilization effect, attributed to the surface preferential accumulation of sorbitol, as corroborated by the computational analyses. This work highlights the potential of tailoring liquid reaction phase of α-chymotrypsin catalyzed reaction using neoteric solvents such as deep eutectic solvents to enhance α-chymotrypsin performance and stability in industrial applications.

Solvent accessible surface area-assessed molecular basis of osmolyte-induced protein stability

In solvent-modulated protein folding, under certain physiological conditions, an equilibrium exists between the unfolded and folded states of the protein without any need to break or make a covalent bond. In this process, interactions between various protein groups (peptides) and solvent molecules are known to play a major role in determining the directionality of the chemical reaction. However, an understanding of the mechanism of action of the co(solvent) by a generic theoretical underpinning is lacking. In this study, a generic solvation model is developed based on statistical mechanics and the thermodynamic transfer free energy model by considering the microenvironment polarity of the interacting co(solvent)-protein system. According to this model, polarity and the fractional solvent-accessible surface areas contribute to the interaction energies. The present model includes various orientations of participating interactant solvent surfaces of suitable areas. As model systems, besides the backbone we consider naturally occurring amino acid residues solvated in ten different osmolytes, small organic compounds known to modulate protein stability. The present model is able to predict the correct trend of the osmolyte-peptide interactions ranging from stabilizing to destabilizing not only for the backbone but also for side chains. Our model predicts Asn, Gln, Asp, Glu, Arg and Pro to be highly stable in most of the protecting osmolytes while Ala, Val, Ile, Leu, Thr, Met, Lys, Phe, Trp and Tyr are predicted to be moderately stable, and Ser, Cys and Histidine are predicted to be least stable. However, in denaturing solvents, both backbone and side chain models show similar stabilities in urea and guanidine. One of the important aspects of this model is that it is essentially parameter-free and consistent with the electrostatics of the interaction partners that make this model suitable for estimating any solute-solvent interaction energies.

Understanding Glucagon Aggregation: In Silico Insights and Experimental Validation

Peptide aggregation poses a significant challenge in biopharmaceutical development and neurodegenerative diseases. This study combines computational simulations and experimental validation to uncover the underlying mechanisms and countermeasures for the aggregation of glucagon, a peptide with a high tendency to aggregate. In silico simulations demonstrate that lactose and 2-hydroxypropyl-β-cyclodextrin (2-HPβCD) influence glucagon aggregation differently: lactose stabilizes glucagon by increasing the α-helical content, while 2-HPβCD disrupts protein-protein interactions. According to the simulations, 2-HPβCD is particularly effective at preserving the monomeric form of glucagon. Experimental validation with microfluidic modulation spectroscopy (MMS) confirms these findings, showing that glucagon in the presence of 2-HPβCD remains structurally stable, supporting the antiaggregation effect of this excipient. This research provides essential insights into glucagon aggregation obtained through a new powerful tool for monitoring the critical properties of peptide aggregation, suggesting new strategies for addressing this challenge in therapeutic peptide development.

Rotational Dynamics of Water near Osmolytes by Molecular Dynamics Simulations

The behavior of water molecules around organic molecules has attracted considerable attention as a crucial factor influencing the properties and functions of soft matter and biomolecules. Recently, it has been suggested that the change in protein stability upon the addition of small organic molecules (osmolytes) is dominated by the change in the water dynamics caused by the osmolyte, where the dynamics of not only the directly interacting water molecules but also the long-range hydration layer affect the protein stability. However, the relation between the long-range structure of hydration water in various solutions and the water dynamics remains unclear at the molecular level. We performed density-functional tight-binding molecular dynamics simulations to elucidate the varying rotational dynamics of water molecules in 15 osmolyte solutions. A positive correlation was observed between the rotational relaxation time and our proposed normalized parameter obtained by dividing the number of hydrogen bonds between water molecules by the number of nearest-neighbor water molecules. For the 15 osmolyte solutions, an increase or a decrease in the value of the normalized parameter for the second hydration shell tended to result in water molecules with slow and fast rotational dynamics, respectively, thus illustrating the importance of the second hydration shell for the rotational dynamics of water molecules. Our simulation results are anticipated to advance the current understanding of water dynamics around organic molecules and the long-range structure of water molecules.

Mechanistic Investigation of tert-Butanol's Impact on Biopharmaceutical Formulations: When Experiments Meet Molecular Dynamics

The use of tert-butyl alcohol for the lyophilization of pharmaceuticals has seen an uptick over the past years. Its advantages include increased solubility of hydrophobic drugs, enhanced product stability, shorter reconstitution time, and decreased processing time. While the mechanisms of protein stabilization exerted by cryo- and lyo-protectants are well known when water is the solvent of choice, little is known for organic solvents. This work investigates the interactions between two model proteins, namely, lactate dehydrogenase and myoglobin, and various excipients (mannitol, sucrose, 2-hydroxypropyl-β-cyclodextrin and Tween 80) in the presence of tert-butyl alcohol. We thermally characterized mixtures of these components by differential scanning calorimetry and freeze-drying microscopy. We also spectroscopically evaluated the protein recovery after freezing and freeze-drying. We additionally performed molecular dynamics simulations to elucidate the interactions in ternary mixtures of the herein-investigated excipients, tert-butyl alcohol and the proteins. Both experiments and simulations revealed that tert-butyl alcohol had a detrimental impact on the recovery of the two investigated proteins, and no combination of excipients yielded a satisfactory recovery when the organic solvent was present within the formulation. Simulations suggested that the denaturing effect of tert-butyl alcohol was related to its propensity to accumulate in the proximity of the peptide surface, especially near positively charged residues.

Thermodynamic Modeling and Experimental Data Reveal That Sugars Stabilize Proteins According to an Excluded Volume Mechanism

We present a new thermodynamic model to investigate the relative effects of excluded volume and soft interaction contributions in determining whether a cosolute will either destabilize or stabilize a protein in solution. This model is unique in considering an atomistically detailed model of the protein and accounting for the preferential accumulation/exclusion of the osmolyte molecules from the protein surface. Importantly, we use molecular dynamics simulations and experiments to validate the model. The experimental approach presents a unique means of decoupling excluded volume and soft interaction contributions using a linear polymeric series of cosolutes with different numbers of glucose subunits, from 1 (glucose) to 8 (maltooctaose), as well as an 8-mer of glucose units in the closed form (γ-CD). By studying the stabilizing effect of cosolutes along this polymeric series using lysozyme as a model protein, we validate the thermodynamic model and show that sugars stabilize proteins according to an excluded volume mechanism.

Effect of Cosolutes on the Aggregation of a Tau Fragment: A Combined Experimental and Simulation Approach

The intrinsically disordered protein Tau represents the main component of neurofibrillary tangles that are a hallmark of Alzheimer's disease. A small fragment of Tau, known as paired helical filament 6 (PHF6), is considered to be important for the formation of the β-structure core of the fibrils. Here we study the aggregation of this fragment in the presence of different cosolutes, including urea, TMAO, sucrose and 2-hydroxypropyl-β-cyclodextrin (2-HPβCD), using both experiments and molecular dynamics simulations. A novel implicit solvation approach (MIST - Model with Implicit Solvation Thermodynamics) is used, where an energetic contribution based on the concept of transfer free energies describes the effect of the cosolutes. The simulation predictions are compared to thioflavin-T and atomic force microscopy results, and the good agreement observed confirms the predictive ability of the computational approach herein proposed. Both simulations and experiments indicate that PHF6 aggregation is inhibited in the presence of urea and 2-HPβCD, while TMAO and sucrose stabilize associated conformations. The remarkable ability of HPβCD to inhibit aggregation represents an extremely promising result for future applications, especially considering the widespread use of this molecule as a drug carrier to the brain and as a solubilizer/excipient in pharmaceutical formulations.

A Transfer Free Energy Based Implicit Solvent Model for Protein Simulations in Solvent Mixtures: Urea-Induced Denaturation as a Case Study

We developed a method for implicit solvent molecular dynamics simulations of proteins in solvent mixtures (model with implicit solvation thermodynamics, MIST). The MIST method introduces experimental group transfer free energies to the generalized Born formulation for generating molecular trajectories without the need for developing rigorous explicit-solvent force fields for multicomponent solutions. As a test case, we studied the urea-induced denaturation of the Trp-cage miniprotein in water. We demonstrate that our method allows efficient exploration of the conformational space of the protein in only a few hundreds of nanoseconds of all-atom unbiased simulations. Furthermore, selective implementation of the transfer free energies of specific peptide groups, backbone, and side chains enables us to decouple their specific energetic contributions to the conformational changes of the protein. The approach herein developed can readily be extended to the investigation of complex matrices as well as to the characterization of protein aggregation. The MIST method is implemented in Plumed (ver. 2.8) as a separate module called SASA.

A fast-slow method to treat solute dynamics in explicit solvent

Aiming to reduce the computational cost in the current explicit solvent molecular dynamics (MD) simulation, this paper proposes a fast-slow method for the fast MD simulation of biomolecules in explicit solvent. This fast-slow method divides the entire system into two parts: a core layer (typically solute or biomolecule) and a peripheral layer (typically solvent molecules). The core layer is treated using standard MD method but the peripheral layer is treated by a slower dynamics method to reduce the computational cost. We compared four different simulation models in testing calculations for several small proteins. These include gas-phase, implicit solvent, fast-slow explicit solvent and standard explicit solvent MD simulations. Our study shows that gas-phase and implicit solvent models do not provide a realistic solvent environment and fail to correctly produce reliable dynamic structures of proteins. On the other hand, the fast-slow method can essentially reproduce the same solvent effect as the standard explicit solvent model while gaining an order of magnitude in efficiency. This fast-slow method thus provides an efficient approach for accelerating the MD simulation of biomolecules in explicit solvent.

The Study of Protein-Cyclitol Interactions

Investigation of interactions between the target protein molecule and ligand allows for an understanding of the nature of the molecular recognition, functions, and biological activity of protein-ligand complexation. In the present work, non-specific interactions between a model protein (Bovine Serum Albumin) and four cyclitols were investigated. D-sorbitol and adonitol represent the group of linear-structure cyclitols, while shikimic acid and D-(-)-quinic acid have cyclic-structure molecules. Various analytical methods, including chromatographic analysis (HPLC-MS/MS), electrophoretic analysis (SDS-PAGE), spectroscopic analysis (spectrofluorimetry, Fourier transform infrared spectroscopy, and Raman spectroscopy), and isothermal titration calorimetry (ITC), were applied for the description of protein-cyclitol interactions. Additionally, computational calculations were performed to predict the possible binding places. Kinetic studies allowed us to clarify interaction mechanisms that may take place during BSA and cyclitol interaction. The results allow us, among other things, to evaluate the impact of the cyclitol's structure on the character of its interactions with the protein.

Force Field Parameterization for the Description of the Interactions between Hydroxypropyl-β-Cyclodextrin and Proteins

Cyclodextrins are cyclic oligosaccharides, widely used as drug carriers, solubilizers, and excipients. Among cyclodextrins, the functionalized derivative known as hydroxypropyl-β-cyclodextrin (HPβCD) offers several advantages due to its unique structural features. Its optimal use in pharmaceutical and medical applications would benefit from a molecular-level understanding of its behavior, as can be offered by molecular dynamics simulations. Here, we propose a set of parameters for all-atom simulations of HPβCD, based on the ADD force field for sugars developed in our group, and compare it to the original CHARMM36 description. Using Kirkwood-Buff integrals of binary HPβCD-water mixtures as target experimental data, we show that the ADD-based description results in a considerably improved prediction of HPβCD self-association and interaction with water. We then use the new set of parameters to characterize the behavior of HPβCD toward the different amino acids. We observe pronounced interactions of HPβCD with both polar and nonpolar moieties, with a special preference for the aromatic rings of tyrosine, phenylalanine, and tryptophan. Interestingly, our simulations further highlight a preferential orientation of HPβCD's hydrophobic cavity toward the backbone atoms of amino acids, which, coupled with a favorable interaction of HPβCD with the peptide backbone, suggest a propensity for HPβCD to denature proteins.