Solvent-mediated Interactions Research Articles

Accurate prediction of dynamic protein-ligand binding using P-score ranking.

Protein-ligand binding prediction typically relies on docking methodologies and associated scoring functions to propose the binding mode of a ligand in a biological target. Significant challenges are associated with this approach, including the flexibility of the protein-ligand system, solvent-mediated interactions, and associated entropy changes. In addition, scoring functions are only weakly accurate due to the short time required for calculating enthalpic and entropic binding interactions. The workflow described here attempts to address these limitations by combining supervised molecular dynamics with dynamical averaging quantum mechanics fragment molecular orbital. This combination significantly increased the ability to predict the experimental binding structure of protein-ligand complexes independent from the starting position of the ligands or the binding site conformation. We found that the predictive power could be enhanced by combining the residence time and interaction energies as descriptors in a novel scoring function named the P-score. This is illustrated using six different protein-ligand targets as case studies.

Abstract 4388: Tumor-associated RhoA mutants interact with effectors in both GDP- and GTP-bound states

Abstract RhoA is the founding member of the Ras-homology (Rho) small GTPase family and is a master regulator for multiple cell functions. Recurrent RhoA mutations have been identified in several human cancers, particularly in leukemia/lymphoma and gastric cancer. Intriguingly, both gain-of-function and loss-of-function mutations of RhoA are present, suggesting that RhoA GTPase may have a more sophisticated role in cancer and requires more rigorous investigations. Here, we have focused on two of the gain-of-function RhoA mutations identified in Adult T cell Leukemia/lymphoma (ATLL) at residue A161 (A161P and A161V) and aim to reveal the underlying mechanistic basis for their function by biochemical and structural analyses. We found that in contrast to conventional gain-of-function RhoA mutants such as RhoAG14V and RhoAQ63L which affect the GTP-hydrolysis activity, RhoAA161P and RhoAA161Vare both fast-cycling with drastically increased nucleotide dissociation and association rates, but only slightly reduced GTP-hydrolysis activity. We solved the crystal structures of GDP-bound RhoAA161P and RhoAA161V and saw that while RhoAA161P displays impaired solvent-mediated interactions to the bound nucleotide, RhoAA161V has a more exposed nucleotide binding pocket compared to RhoAWT and RhoAA161P. Interestingly, RhoAA161P and RhoAA161Vcan interact with effector targets in the GDP-bound states. Further 1H-15N HSQC NMR study provides evidence of the active population in GDP-bound RhoAA161V. Molecule dynamics (MD) simulations show that the dynamic properties of RhoA switch regions are affected differently by the two mutations. Thus, RhoAA161V and RhoAA161P are fast-cycling mutants with distinct mechanisms, and both likely endow their GDP-bound state towards an active conformation. These findings provide a better understanding of the oncogenic role of RhoA mutations in cancer and shine light on how changes in RhoA protein dynamic properties caused by mutations may affect its function. Citation Format: Yuan Lin, Theresa A. Ramelot, Simge Senyuz, Attila Gursoy, Hyunbum Jang, Ruth Nussinov, Ozlem Keskin, Yi Zheng. Tumor-associated RhoA mutants interact with effectors in both GDP- and GTP-bound states [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4388.

Mesoscale simulations of diffusion and sedimentation in shape-anisotropic nanoparticle suspensions.

We determine the long-time self-diffusion coefficient and sedimentation coefficient for suspensions of nanoparticles with anisotropic shapes (octahedra, cubes, tetrahedra, and spherocylinders) as a function of nanoparticle concentration using mesoscale simulations. We use a discrete particle model for the nanoparticles, and we account for solvent-mediated hydrodynamic interactions between nanoparticles using the multiparticle collision dynamics method. Our simulations are compared to theoretical predictions and experimental data from existing literature, demonstrating good agreement in the majority of cases. Further, we find that the self-diffusion coefficient of the regular polyhedral shapes can be estimated from that of a sphere whose diameter is the average of their inscribed and circumscribed sphere diameters.

Quantifying the Relevance of Long-Range Forces for Crystal Nucleation in Water.

Understanding nucleation from aqueous solutions is of fundamental importance in a multitude of fields, ranging from materials science to biophysics. The complex solvent-mediated interactions in aqueous solutions hamper the development of a simple physical picture, elucidating the roles of different interactions in nucleation processes. In this work, we make use of three complementary techniques to disentangle the role played by short- and long-range interactions in solvent-mediated nucleation. Specifically, the first approach we utilize is the local molecular field (LMF) theory to renormalize long-range Coulomb electrostatics. Second, we use well-tempered metadynamics to speed up rare events governed by short-range interactions. Third, the deep learning-based State Predictive Information Bottleneck approach is employed in analyzing the reaction coordinate of the nucleation processes obtained from the LMF treatment coupled with well-tempered metadynamics. We find that the two-step nucleation mechanism can largely be captured by the short-range interactions, while the long-range interactions further contribute to the stability of the primary crystal state under ambient conditions. Furthermore, by analyzing the reaction coordinate obtained from the combined LMF-metadynamics treatment, we discern the fluctuations on different time scales, highlighting the need for long-range interactions when accounting for metastability.

Electrosteric, van der Waals and elastic interaction of polyelectrolyte hydrogels

The electrosteric interaction energy for a charged hydrogel and hard plane, and between two charged hydrogels is derived in the Debye–Hückel approximation. This is combined with a van der Waals potential that explicitly addresses the Hamaker constant for the solvent-mediated hydrogel interactions. Then, in the Derjaguin approximation, DLVO-type interaction potentials are provided for hydrogel and hard/rigid spheres, accounting for elastic deformation that accompanies adhesion. As examples, this furnishes the energy for cohesion of soft polyelectrolyte microspheres, and provides a quantitative interpretation for the adhesion of rigid latex spheres to a soft deformable hydrogel, as reported by Sato et al. (Sato et al. 2017 Sci. Rep. 7 , 1–10 ( doi:10.1038/s41598-017-06257-1 )). The theory demonstrates that weak van der Waals attraction of hydrogels is readily balanced by electrosteric interactions, e.g. making colloidal hydrogel dispersions less stable than their rigid-particulate counterparts.

Thermal titration molecular dynamics (TTMD): shedding light on the stability of RNA-small molecule complexes.

Ribonucleic acids are gradually becoming relevant players among putative drug targets, thanks to the increasing amount of structural data exploitable for the rational design of selective and potent binders that can modulate their activity. Mainly, this information allows employing different computational techniques for predicting how well would a ribonucleic-targeting agent fit within the active site of its target macromolecule. Due to some intrinsic peculiarities of complexes involving nucleic acids, such as structural plasticity, surface charge distribution, and solvent-mediated interactions, the application of routinely adopted methodologies like molecular docking is challenged by scoring inaccuracies, while more physically rigorous methods such as molecular dynamics require long simulation times which hamper their conformational sampling capabilities. In the present work, we present the first application of Thermal Titration Molecular Dynamics (TTMD), a recently developed method for the qualitative estimation of unbinding kinetics, to characterize RNA-ligand complexes. In this article, we explored its applicability as a post-docking refinement tool on RNA in complex with small molecules, highlighting the capability of this method to identify the native binding mode among a set of decoys across various pharmaceutically relevant test cases.

Dynamic Stereochemistry of M8 Pd6 Supramolecular Cages Based on Metal-Center Lability for Differential Chiral Induction, Resolution, and Recognition.

A series of isostructural supramolecular cages with a rhombic dodecahedron shape have been assembled with distinct metal-coordination lability (M8 Pd6 -MOC-16, M=Ru2+ , Fe2+ , Ni2+ , Zn2+ ). The chirality transfer between metal centers generally imposes homochirality on individual cages to enable solvent-dependent spontaneous resolution of Δ8 /Λ8 -M8 Pd6 enantiomers; however, their distinguishable stereochemical dynamics manifests differential chiral phenomena governed by the cage stability following the order Ru8 Pd6 >Ni8 Pd6 >Fe8 Pd6 >Zn8 Pd6 . The highly labile Zn centers endow the Zn8 Pd6 cage with conformational flexibility and deformation, enabling intrigue chiral-Δ8 /Λ8 -Zn8 Pd6 to meso-Δ4 Λ4 -Zn8 Pd6 transition induced by anions. The cage stabilization effect differs from inert Ru2+ , metastable Fe2+ /Ni2+ , and labile Zn2+ , resulting in different chiral-guest induction. Strikingly, solvent-mediated host-guest interactions have been revealed for Δ8 /Λ8 -(Ru/Ni/Fe)8 Pd6 cages to discriminate the chiral recognition of the guests with opposite chirality. These results demonstrate a versatile procedure to control the stereochemistry of metal-organic cages based on the dynamic metal centers, thus providing guidance to maneuver cage chirality at a supramolecular level by virtue of the solvent, anion, and guest to benefit practical applications.

Dewatering and consolidation of clay slurries

Dewatering, which is the process of separating (colloidal) suspended particles from a solvent (usually water), is used in many engineering applications (sanitary engineering, dredging engineering…). Key questions associated with dewatering in the context of the reuse of dredged sediment are (1) what is the process kinetics, (2) how can these processes be optimized and (3) can the dewatered sludge be reused and for which application? Dewatering and consolidation are functions of the suspended particles’ size and type, and their solvent-mediated interaction. In this presentation, some examples will be given about the dewatering of suspensions and slurries as found in engineering applications [1]. The presentation will focus on the behaviour of mineral clay suspensions (kaolinite, montmorillonite, illite…) composed of particles of different particle sizes [2-5]. We will show that, depending on the particle size distribution and solvent properties, the system is either undergoing a slow sedimentation dominated by thermodynamic forces or a rapid sedimentation dominated by gravity. The sedimentation is followed in time using NMR and inferential image analysis, and the particles are characterized by size, density and electrokinetic charge. We show that the time evolution of the sedimentation behaviour can be modelled using an advection-diffusion equation. The advective term is a function of gravity, whereas the diffusion term represents either a hard-sphere repulsion or an effective stress, depending on whether thermodynamic forces dominate the system [6-8]. We show that after solving this advection-diffusion equation numerically, the results based on the theory of Gibson does match the experimental data collected from NMR in the phase of slow kinetics. For the early stages of settling and consolidation, where the system kinetics are fast, we show that the data are contaminated by artifacts due to the limited time of signal acquisition imposed by the NMR method. We show that is possible to overcome those limitations by either sacrificing some information related to particle’s sizes using the NMR or by combining the NMR method with excess pore pressure measurements along the height of the settling columns.

Crowder titrations enable the quantification of driving forces for macromolecular phase separation

Macromolecular solubility is an important contributor to the driving forces for phase separation. Formally, the driving forces in a binary mixture comprising a macromolecule dissolved in a solvent can be quantified in terms of the saturation concentration, which is the threshold macromolecular concentration above which the mixture separates into coexisting dense and dilute phases. In addition, the second virial coefficient, which measures the effective strength of solvent-mediated intermolecular interactions provides direct assessments of solvent quality. The sign and magnitude of second virial coefficients will be governed by a combination of solution conditions and the nature of the macromolecule of interest. Here, we show, using a combination of theory, simulation, and in vitro experiments, that titrations of crowders, providing they are true depletants, can be used to extract the intrinsic driving forces for macromolecular phase separation. This refers to saturation concentrations in the absence of crowders and the second virial coefficients that quantify the magnitude of the incompatibility between macromolecules and the solvent. Our results show how the depletion-mediated attractions afforded by crowders can be leveraged to obtain comparative assessments of macromolecule-specific, intrinsic driving forces for phase separation.

Review: Kirkwood-Riseman Model in Non-Dilute Polymeric Fluids.

In two prior articles, I demonstrated from extensive simulational studies by myself and others that the Rouse model of polymer dynamics is invalid in polymer melts and in dilute solution. However, the Rouse model is the foundational basis for most modern theories of polymeric fluid dynamics, such as reptation/scaling models. One therefore rationally asks whether there is a replacement. There is, namely by extending the Kirkwood-Riseman model. Here, I present a comprehensive review of one such set of extensions, namely the hydrodynamic scaling model. This model assumes that polymer dynamics in dilute and concentrated solution is dominated by solvent-mediated hydrodynamic interactions; chain crossing constraints are taken to create only secondary corrections. Many other models assume, contrariwise, that in concentrated solutions, the chain crossing constraints dominate the dynamics. An extended Kirkwood-Riseman model incorporating interchain hydrodynamic interactions is developed. It yields pseudovirial series for the concentration and molecular weight dependencies of the self-diffusion coefficient Ds and the low-shear viscosity η. To extrapolate to large concentrations, rationales based on self-similarity and on the Altenberger-Dahler positive-function renormalization group are presented. The rationales correctly predict how Ds and η depend on polymer concentration and molecular weight. The renormalization group approach leads to a two-parameter ansatz that correctly predicts the functional forms of the frequency dependencies of the storage and loss moduli. A short description is given of each of the papers that led to the hydrodynamic scaling model. Experiments supporting the aspects of the model are noted.

Solvent Mediated Interactions on Alkene Epoxidations in Ti-MFI: Effects of Solvent Identity and Silanol Density

Selective alkene oxidation rates within zeolite pores reflect differences in contributions from thermodynamic nonidealities introduced by noncovalent interactions at solid–liquid interfaces and spatial constraints enforced by the zeolite topology. Epoxidation turnover rates for 1-hexene in Ti-MFI zeolite differ by 1000-fold across 10 combinations of solvents, including alcohols and acetonitrile, over Ti-MFI with distinct silanol defect densities. Solvent mediated noncovalent interactions persist across an extended binding environment that influences the stability of epoxidation transition states. Apparent activation enthalpies (ΔHApp⧧) and entropies (ΔSApp⧧) span 80 kJ mol–1 and 200 J mol–1 K–1, respectively, with the most positive values for both appearing in methanol. Hydrophilic (i.e., (SiOH)x defect rich) Ti-MFI-OH catalysts in methanol give the greatest turnover rates because entropic gains associated with the disruption of hydrogen-bonded networks of intrapore methanol and water dominate activation free energies. In situ infrared spectra show that the adsorption of 1,2-epoxyhexane to Ti sites disturbs the equilibrium solvent structure within pores in ways that reflect the density of the hydrogen bond donor and acceptors near active sites. This interpretation agrees with measured enthalpies for adsorption of 1,2-epoxyhexane to Ti active sites within solvent filled pores that correlate with ΔHApp⧧ across solvent and catalyst combinations. The displacement of solvent molecules and the associated rupture and formation of hydrogen bonds among solvents, pore walls, and nearby reactive molecules during catalysis and adsorption events incur substantial excess contributions that govern the reaction rates and barriers. These realizations explain the particular success of alkene epoxidations in mixtures of H2O2 and methanol over hydrophilic forms of Ti-MFI in industrial processes (e.g., the hydrogen peroxide–propylene oxide process). These findings demonstrate the gains achieved by appropriately pairing organic solvents with microporous catalysts to manipulate the intrinsic kinetics of reactions and the thermodynamics of adsorption at solid–liquid interfaces.

Solvent-Mediated Separation and Reversible Transformation of 1D Supramolecular Polymorphs Built from [W10O32]4– Templated 48-Nuclei Silver(I) Cluster

Although the C-H···O interaction is an essential component in determining the molecular packing in solids and the properties in supramolecular chemistry, it presents a significant challenge when trying to use it in the crystal engineering of complex metallosupramolecules, even though it is a relatively weak supramolecular force. The first pair of high-nuclearity silver-cluster-based one-dimensional (1D) polymorphs built from supramolecular synthon [W10O32@Ag48(CyS)24(NO3)16]·4NO3 (Cy = cyclohexyl) bridged by four grouped inorganic NO3- ligands is initially synthesized as a mixed phase and further individually crystallized as a pure phase by virtue of tuning intermolecular C-H···O interaction through altering the composition ratio of ternary solvent system. Increasing highly polar and hydrogen-bonding methanol strengthens the solvation effect reflected by the change of coordination orientation of surface NO3- ligands, which dominates the packing of the 1D chains in the crystal lattice, resulting in the crystallization of polymorphs from tetragonal to monoclinic. The two crystalline forms can also be reversibly transformed to each other in an appropriate solvent system. Correspondingly, the two polymorphs display distinct temperature-dependent photoluminescence behaviors, which are ascribed to the variation of noncovalent interchain C-H···O interactions along with the temperature. More importantly, benefiting from the suppression of fluorescence, both polymorphs offer excellent photothermal conversion properties which were further applied to remote-controlled laser ignition. These findings may open more avenues for the application of solvent-mediated intermolecular interaction in controlling the molecule arrangement as well as the optical properties.

Solvent Model Benchmark for Molecular Dynamics of Glycosaminoglycans.

In computational studies of glycosaminoglycans (GAGs), a group of anionic, periodic linear polysaccharides, so far there has been very little discussion about the role of solvent models in the molecular dynamics simulations of these molecules. Predominantly, the TIP3P water model is commonly used as one of the most popular explicit water models in general. However, there are numerous alternative explicit and implicit water models that are neglected in the computational research of GAGs. Since solvent-mediated interactions are particularly important for GAG dynamic and structural properties, it would be of great interest for the GAG community to establish the solvent model that is suited the best in terms of the quality of theoretically obtained GAG parameters and, at the same time, would be reasonably demanding in terms of computational resources required. In this study, heparin (HP) was simulated using five implicit and six explicit solvent models with the aim to find out how different solvent models influence HP's molecular descriptors in the molecular dynamics simulations. Here, we initiate the search for the most appropriate solvent representation for GAG systems and we hope to encourage other groups to contribute to this highly relevant subject.

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.

From single proteins to efficient simulation models of the cytoplasm.

The properties of biomolecules in crowded in-cell environments are governed by interactions that range from repulsive volume exclusions to non-specific transient binding and molecular recognition. Entropic volume exclusion and its impact on biomolecules can be estimated using analytical theory, but transient binding and molecular recognition further depend on electrostatics, hydrogen bonds, van der Waals forces and solvent-mediated interactions. These interactions strongly depend on microscopic details on the molecular scale, which impedes the development of general theories. Instead, computer simulations provide a useful tool to interpret in-cell experiments and to expand our understanding of biomolecular crowding.

Studies on the Interaction between Model Proteins and Fluorinated Ionic Liquids.

Proteins are inherently unstable, which limits their use as therapeutic agents. However, the use of biocompatible cosolvents or surfactants can help to circumvent this problem through the stabilization of intramolecular and solvent-mediated interactions. Ionic liquids (ILs) have been known to act as cosolvents or surface-active compounds. In the presence of proteins, ILs can have a beneficial effect on their refolding, shelf life, stability, and enzymatic activities. In the work described herein, we used small-angle X-ray scattering (SAXS) to monitor the aggregation of different concentrations of ILs with protein models, lysozyme (Lys) and bovine serum albumin (BSA), and fluorescence microscopy to assess micelle formation of fluorinated ILs (FILs) with Lys. Furthermore, coarse-grained molecular dynamics (CG-MD) simulations provided a better understanding of Lys-FIL interactions. The results showed that the proteins maintain their globular structures in the presence of FILs, with signs of partial unfolding for Lys and compaction for BSA with increased flexibility at higher FIL concentrations. Lys was encapsulated by FIL, thus reinforcing the potential of ILs to be used in the formulation of protein-based pharmaceuticals.

The temperature-dependence of host-guest binding thermodynamics: experimental and simulation studies.

The thermodynamic parameters of host-guest binding can be used to describe, understand, and predict molecular recognition events in aqueous systems. However, interpreting binding thermodynamics remains challenging, even for these relatively simple molecules, as they are determined by both direct and solvent-mediated host-guest interactions. In this contribution, we focus on the contributions of water to binding by studying binding thermodynamics, both experimentally and computationally, for a series of nearly rigid, electrically neutral host-guest systems and report the temperature-dependent thermodynamic binding contributions ΔGb(T), ΔHb(T), ΔSb(T), and ΔCp,b. Combining isothermal titration calorimetry (ITC) measurements with molecular dynamics (MD) simulations, we provide insight into the binding forces at play for the macrocyclic hosts cucurbit[n]uril (CBn, n = 7-8) and β-cyclodextrin (β-CD) with a range of guest molecules. We find consistently negative changes in heat capacity on binding (ΔCp,b) for all systems studied herein - as well as for literature host-guest systems - indicating increased enthalpic driving forces for binding at higher temperatures. We ascribe these trends to solvation effects, as the solvent properties of water deteriorate as temperature rises. Unlike the entropic and enthalpic contributions to binding, with their differing signs and magnitudes for the classical and non-classical hydrophobic effect, heat capacity changes appear to be a unifying and more general feature of host-guest complex formation in water. This work has implications for understanding protein-ligand interactions and other complex systems in aqueous environments.

Effect of solvent on the emulsion and morphology of polyfluorene films: all-atom molecular dynamics approach.

The morphology of conjugated polymer thin films deposited by the resonant infrared matrix-assisted pulsed laser evaporation (RIR-MAPLE) process is related to the emulsion characteristics. However, a fundamental understanding of how and why the emulsion characteristics control the film properties and device performance is yet unclear. We performed all-atom molecular dynamics simulations of emulsions containing a mixture of polyfluorene (PFO) polymer, various primary solvents, secondary solvent, and water. The emulsion properties were then examined as a function of variable primary solvent and correlated with the morphology of deposited PFO thin films. The examination of the explicit interactions between all components of the emulsion indicated that using a primary solvent with a lower solubility-in-water and a higher non-bonded interaction energy ratio, between the solvent, polymer, and water in the emulsion recipe, produced the best result with smoother and denser films. Additionally, our simulation results are consistent with the AFM experimental results, indicating that interactions driven by trichlorobenzene (TCB) primary solvent within the emulsion are responsible for high-quality, smooth, and continuous thin film surfaces. Overall, this study can support the choice of a suitable primary solvent and provides the computational framework for predictions of new recipes for polymeric emulsion systems.

Self-assembly of anionic surfactant and its effect on oil–water interface: Implications for enhanced oil recovery

Surfactant micellization is a self-assembly process governed by complex interplay of solvent-mediated interactions. However, quantitative modeling of micelle formation and its effect on oil–water interface are not yet completely understood. In this work, dissipative particle dynamics simulations were used to investigate the self-assembly behavior of anionic surfactants of alcohol alkoxy sulfate (AAS) and its structural influence on the interfacial properties of oil–water at the mesoscopic scale. Our results indicate that with the increase of surfactant concentration, the morphology of surfactant aggregates varied from spherical micelles to rod-shaped micelles, and finally formed worm-like micelles. The larger the number of propylene oxide (PO) groups, the easier the formation of large micelles and the more tightness of formed micelles. On the oil–water interface, the interfacial tension of solutions decreased with increasing surfactant concentration below the critical micelle concentration, whereas a positive correlation was found for the tightness of surfactant arrangement. When surfactants formed micelles, the overall coverage area of AAS decreased and a lower root mean square end distance of individual PO group directly affected interfacial properties of AAS. The obtained results could provide a solid theoretical basis for the rational design of efficient surfactants in oil recovery and soft matter applications.

On the interactions of diols and DMPC monolayers

The interactions of lipid molecules with various solvent molecules is of utmost importance in the formulation of various drug delivery and personal care formulations. In this manuscript, a series of all-atom molecular dynamics simulations were used to investigate how the structural and interfacial properties of a DMPC (1,2-dimyristoyl-sn-glycero-3-phosphocholine) monolayer change when interacting with a range of diols that have varying carbon chain lengths and patterns of hydroxylation. In comparison to water, we find that all of the diols studied result in a more disordered and thinner monolayer. Additionally, we find that the shorter diols with the hydroxyl groups on neighbouring carbons (1,2-ethanediol and 1,2-propanediol) are able to penetrate deeper into the head group region of the lipid monolayers and as a result significantly disorder and thin the monolayers. Like water, we find that the diols also form hydrogen-bonded networks that connect the DMPC head groups in neighbouring molecules. Interestingly, we find that the number of butanediol molecules that form these solvent-mediated interactions between the DMPC head groups is directly affected by the distribution of the hydroxyl groups within the diol molecules. The results presented here provide a mechanistic description of how the chemistry of diol solvent molecules will affect the structural and interfacial properties of lipid structures in solution.