Publications | The SAMPEL Lab

2025

N-Branched Tricyclic Guanidines as Novel Melanocortin-3 Receptor Agonists and Melanocortin-4 Receptor Antagonists

Nicholas A. Weirath, Jonathan W. P. Zajac, Haley M. Donow, Travis M. Lavoi, Clemencia Pinilla, Radleigh G. Santos, Ritu Prajapati, Robert Speth, Mark D. Ericson, Sapna Sarupria, Marcello A. Giulianotti, Carrie Haskell-Luevano. (2025) Journal of Medicinal Chemistry.

DOI: 10.1021/acs.jmedchem.4c01556

The melanocortin receptors are a class of centrally and peripherally expressed G protein-coupled receptors, of which the MC3R and MC4R subtypes are implicated in the regulation of appetite and energy homeostasis and can serve as potential therapeutic targets for disorders such as obesity and cachexia. An unbiased high-throughput mixture-based library screen was implemented to identify novel ligands with an emphasis on the identification of nanomolar-potent agonists of the mouse melanocortin-3 receptor. This screen yielded the discovery of an N-branched tricyclic guanidine scaffold (TPI2408) that contained three nanomolar potent mMC3R agonists and additional compounds that possessed antagonism for the mMC4R. The antagonist character of this scaffold library at the mMC4R was confirmed by a follow-up positional scanning antagonist screen. Additionally, molecular dynamics simulations herein provide mechanistic insight into the polypharmacological characteristics of melanocortin receptors. The disclosed materials have the potential to serve as important tools and SAR scaffolds in the study of melanocortin receptor function.

2024

Impact of Co-Excipient Selection on Hydrophobic Polymer Folding: Insights for Optimal Formulation Design

Jonathan W. P. Zajac, Praveen Muralikrishnan, Caryn L. Heldt, Sarah L. Perry, Sapna Sarupria. (2024) arXiv:2407.00885

The stabilization of liquid biological products is a complex task that depends on the chemical composition of both the active ingredient and any excipients in solution. Frequently, a large number of unique excipients are required to stabilize biologics, though it is not well-known how these excipients interact with one another. To probe these excipient-excipient interactions, we performed molecular dynamics simulations of arginine -- a widely used excipient with unique properties -- in solution either alone or with equimolar lysine or glutamate. We studied the effects of these mixtures on a hydrophobic polymer model to isolate excipient mechanisms on hydrophobic interactions, relevant to both protein folding and biomolecular self-assembly. We observed that arginine is the most effective single excipient in stabilizing hydrophobic polymer collapse, and its effectiveness can be augmented by lysine or glutamate addition. We utilized a decomposition of the potential of mean force to identify that the key source of arginine-lysine and arginine-glutamate synergy on polymer collapse is a reduction in attractive polymer-excipient direct interactions. Further, we applied principles from network theory to characterize the local solvent network that embeds the hydrophobic polymer. Through this approach, we found that arginine enables a more highly connected and stable network than in pure water, lysine, or glutamate solutions. Importantly, these network properties are preserved when lysine or glutamate are added to arginine solutions. Overall, we highlight the importance of identifying key molecular consequences of co-excipient selection, aiding in the establishment of rational formulation design rules.

LeaPP: Learning Pathways to Polymorphs through machine learning analysis of atomic trajectories

Steven W. Hall, Porhouy Minh, Sapna Sarupria. (2024) arXiv:2405.09642

Understanding the mechanisms underlying crystal formation is crucial. For most systems, crystallization typically goes through a nucleation process that involves dynamics that happen at short time and length scales. Due to this, molecular dynamics serves as a powerful tool to study this phenomenon. Existing approaches to study the mechanism often focus analysis on static snapshots of the global configuration, potentially overlooking subtle local fluctuations and history of the atoms involved in the formation of solid nuclei. To address this limitation, we propose a methodology that categorizes nucleation pathways into reactive pathways based on the time evolution of their constituent atoms. Our approach effectively captures the diverse structural pathways explored by crystallizing LennardJones-like particles and solidifying Ni3Al, providing a more nuanced understanding of nucleating pathways. Moreover, our methodology enables the prediction of the resulting polymorph from each reactive trajectory. This deep learning-assisted comprehensive analysis offers an alternative view of crystal nucleation mechanisms and pathways.

Flipping Out: Role of Arginine in Hydrophobic Polymer Collapse

Jonathan W. P. Zajac, Praveen Muralikrishnan, Caryn L. Heldt, Sarah L. Perry, Sapna Sarupria. (2024) arXiv:2403.11305

Arginine has been a mainstay in biological formulation development for decades. To date, the way arginine modulates protein stability has been widely studied and debated. Here, we employed a hydrophobic polymer to decouple hydrophobic effects from other interactions relevant to protein folding. While existing hypotheses for the effects of arginine can generally be categorized as either direct or indirect, our results indicate that direct and indirect mechanisms of arginine co-exist and oppose each other. At low concentrations, arginine was observed to stabilize hydrophobic polymer collapse via a sidechain-dominated direct mechanism, while at high concentrations, arginine stabilized polymer collapse via a backbone-dominated indirect mechanism. These findings highlight the modular nature of the widely used additive arginine, with relevance in the design of stable biological formulations.

2023

Exploitation of active site flexibility-low temperature activity relation for engineering broad range temperature active enzymes

Siva Dasetty, Jonathan W. P. Zajac and Sapna Sarupria. 8, 1355-1370, (2023) Molecular Systems Design & Engineering.

DOI: 10.1039/D3ME00013C

Differences in the structural and thermodynamic properties of enzymes adapted to different temperatures indicate that broad range temperature active enzymes can be designed by incorporating cold activity in thermophilic enzymes. This is based on a concept that the cold activity and thermostability are not mutually exclusive and that cold activity in psychrophilic enzymes is associated with active site flexibility. In Wang et al. Biochem. Eng. J. 2021, 174, 10803, we identified two point mutants of Geobacillus thermocatenulatus lipase (GTL) which were screened to improve active site flexibility. Even though the identified thermophilic mutants had psychrophilic traits, we observed complex trends such as higher kinetic stability and substrate-dependent activity-temperature relation on further analysis. In this work, we apply molecular dynamics simulations and network theory to show that the changes in GTL properties with the selected mutations cannot be directly associated with active site flexibility. Our computational results indicate the mutations resulted in residues with both higher and lower flexibility, which are both proximal and away (> 1.5 nm) from the active site. We show that the intricate changes in the flexibility of residues distal from the mutation site can be rationalized by the altered dependency between residue-residue fluctuations with mutation. These alterations in residue-residue flexibility dependency are a consequence of the redistribution of the inter-residue interactions from the mutation site to other residues, which are driven by several tightly connected charged residues. This indicates design rules associated with residue-residue flexibility correlations are critical in applying site-directed mutagenesis to successfully exploit active site flexibility-activity relation for incorporating low temperature activity in thermophilic enzymes. Similarly, such correlations can be valuable in minimizing false positives in high-throughput screening methods based on directed evolution and/or machine learning-based engineering of enzyme activitytemperature relation.

RSeeds: Rigid Seeding Method for Studying Heterogeneous Crystal Nucleation

Tianmu Yuan, Ryan S. DeFever, Jiarun Zhou, Ernesto Carlos Cortes-Morales, and Sapna Sarupria. 127, 4112–4125, (2023) The Journal of Physical Chemistry B.

DOI: 10.1021/acs.jpcb.3c00910

Heterogeneous nucleation is the dominant form of liquid-to-solid transition in nature. Although molecular simulations are most uniquely suited to studying nucleation, the waiting time to observe even a single nucleation event can easily exceed the current computational capabilities. Therefore, there exists an imminent need for methods that enable computationally fast and feasible studies of heterogeneous nucleation. Seeding is a technique that has proven to be successful at dramatically expanding the range of computationally accessible nucleation rates in simulation studies of homogeneous crystal nucleation. In this article, we introduce a new seeding method for heterogeneous nucleation called Rigid Seeding (RSeeds). Crystalline seeds are treated as pseudorigid bodies and simulated on a surface with metastable liquid above its melting temperature. This allows the seeds to adapt to the surface and identify favorable seed–surface configurations, which is necessary for reliable predictions of crystal polymorphs that form and the corresponding heterogeneous nucleation rates. We demonstrate and validate RSeeds for heterogeneous ice nucleation on a flexible self-assembled monolayer surface, a mineral surface based on kaolinite, and two model surfaces. RSeeds predicts the correct ice polymorph, exposed crystal plane, and rotation on the surface. RSeeds is semiquantitative and can be used to estimate the critical nucleus size and nucleation rate when combined with classical nucleation theory. We demonstrate that RSeeds can be used to evaluate nucleation rates spanning many orders of magnitude.

Differences in solvation thermodynamics of oxygenates at Pt/Al2O3 perimeter versus Pt (111) terrace sites

Ricardo A Garcia Carcamo, Xiaohong Zhang, Ali Estejab, Jiarun Zhou, Bryan J Hare, Carsten Sievers, Sapna Sarupria, Rachel B Getman. 26, 105980, (2023) iScience.

DOI: 10.1016/j.isci.2023.105980

A prominent role of water in aqueous phase heterogeneous catalysis is to modify free energies; however, intuition about how is based largely on pure metal surfaces or even homogeneous solutions. Using multiscale modeling with explicit liquid water molecules, we show that the influence of water on the free energies of species at metal/support interfaces is different than pure metal surfaces. We specifically compute free energies of solvation for methanol and its constituents on a Pt/Al2O3 catalyst and compare the results to analogous values calculated on a pure Pt catalyst. We find that the more hydrophilic Pt/Al2O3 alumina support leads to smaller (more positive) free energies of solvation due to an increased entropy penalty resulting from the additional work necessary to disrupt the interfacial water structure and accommodate the interfacial species. The results will be of interest in other fields, including adsorption and proteins.

2022

Machine learning for molecular simulations of crystal nucleation and growth

Sapna Sarupria, Steven W. Hall, Jutta Rogal. 47, (2022) MRS Bulletin.

DOI: 10.1557/s43577-022-00407-1

Molecular simulations are a powerful tool in the study of crystallization and polymorphic transitions yielding detailed information of transformation mechanisms with high spatiotemporal resolution. However, characterizing various crystalline and amorphous phases as well as sampling nucleation events and structural transitions remain extremely challenging tasks. The integration of machine learning with molecular simulations has the potential of unprecedented advancement in the area of crystal nucleation and growth. In this article, we discuss recent progress in the analysis and sampling of structural transformations aided by machine learning and the resulting potential future directions opening in this area.

Practical guide to replica exchange transition interface sampling and forward flux sampling

Steven W. Hall, Grisell Díaz Leines, Sapna Sarupria, Jutta Rogal. 156, 200901, (2022) The Journal of Chemical Physics.

DOI: 10.1063/5.0080053

Path sampling approaches have become invaluable tools to explore the mechanisms and dynamics of so-called rare events that are characterized by transitions between metastable states separated by sizeable free energy barriers. Their practical application, in particular to ever more complex molecular systems, is, however, not entirely trivial. Focusing on replica exchange transition interface sampling (RETIS) and forward flux sampling (FFS), we discuss a range of analysis tools that can be used to assess the quality and convergence of such simulations which is crucial to obtain reliable results. The basic ideas of a step-wise evaluation are exemplified for the study of nucleation in several systems with different complexity, providing a general guide for the critical assessment of RETIS and FFS simulations.

2021

The Middle Science: Traversing Scale In Complex Many-Body Systems

Aurora E. Clark, Henry Adams, Rigoberto Hernandez, Anna I. Krylov, Anders M. N. Niklasson, Sapna Sarupria, Yusu Wang, Stefan M. Wild, and Qian Yang 7 1271-1287 (2021) ACS Central Science.

DOI: 10.1021/acscentsci.1c00685

The theory and simulation of systems that have realistic complexity and size and evolve across massive time scales are a critical challenge predicated upon the accurate description of many-body interactions. It builds upon the science of the small to create a new “Middle Science” whose research vision integrates modern math and data science with chemical theories as proposed in this In Focus article.

Toward enzyme-responsive polymersome drug delivery

Bipin Chakravarthy Paruchuri, Varun Gopal, Sapna Sarupria, and Jessica Larsen 16 2679-2693 (2021) Nanomedicine.

DOI: 10.2217/nnm-2021-0194

In drug delivery, enzyme-responsive drug carriers are becoming increasingly relevant because of the growing association of disease pathology with enzyme overexpression. Polymersomes are of interest to such applications because of their tunable properties. While polymersomes open up a wide range of chemical and physical properties to explore, they also present a challenge in developing generalized rules for the synthesis of novel systems. Motivated by this issue, in this perspective, we summarize the existing knowledge on enzyme-responsive polymersomes and outline the main design choices. Then, we propose heuristics to guide the design of novel systems. Finally, we discuss the potential of an integrated approach using computer simulations and experimental studies to streamline this design process and close the existing knowledge gaps.

Rational engineering of low temperature activity in thermoalkalophilic Geobacillus thermocatenulatus lipase

Weigao Wang, Siva Dasetty, Sapna Sarupria, and Mark Blenner 174 Page N.A. (2021) Biochemical Engineering Journal.

DOI: 10.1016/j.bej.2021.108093

While thermophilic enzymes have thermostability desired for broad industrial applications, they can lose activity at ambient temperatures far from their optimal temperature. Engineering cold activity into thermophilic enzymes has the potential to broaden the range of temperatures resulting in significant activity (i.e., decreasing the temperature dependence of kcat). Even though it has been widely suggested that cold activity, which results from active site flexibility, is at odds with thermostability, which results from enzyme rigidity, directed evolution experiments have shown that these properties are not mutually exclusive. In this study, rational protein engineering was used to introduce glycine as flexibility inducing mutations around the active site of Geobacillus thermocatenulatus lipase (GTL). Two mutants were found to have enhanced specific activity compared to wild-type at temperatures between 283 K to 363 K with p-nitrophenol butyrate but not with larger substrates. Kinetics assay revealed both mutations resulted in psychrophilic traits, such as lower activation enthalpy and more negative entropy values compared to wild type in all substrates. Furthermore, the mutants had significantly improved thermostability compared to wild type enzyme, which proves that it is feasible to improve the cold activity without trade-off. Our study provides insight into the enzyme cold adaptation mechanism and design principles for engineering cold activity into thermostable enzymes.

Advancing Rational Control of Peptide–Surface Complexes

Siva Dasetty and Sapna Sarupria 10 2644-2657 (2021) The Journal of Physical Chemistry B.

DOI: 10.1021/acs.jpcb.0c10740

Understanding peptide–surface interactions is crucial for programming self-assembly of peptides at surfaces and in realizing their applications, such as biosensors and biomimetic materials. In this study, we developed insights into the dependence of a residue’s interaction with a surface on its neighboring residue in a tripeptide using molecular dynamics simulations. This knowledge is integral for designing rational mutations to control peptide–surface complexes. Using graphene as our model surface, we estimated the free energy of adsorption (ΔAads) and extracted predominant conformations of 26 tripeptides with the motif LNR–CR–Gly, where LNR and CR are variable left-neighboring and central residues, respectively. We considered a combination of strongly adsorbing (Phe, Trp, and Arg) and weakly adsorbing (Ala, Val, Leu, Ser, and Thr) amino acids on graphene identified in a prior study to form the tripeptides. Our results indicate that ΔAads of a tripeptide cannot be estimated as the sum of ΔAads of each residue indicating that the residues in a tripeptide do not behave as independent entities. We observed that the contributions from the strongly adsorbing amino acids were dominant, which suggests that such residues could be used for strengthening peptide–graphene interactions irrespective of their neighboring residues. In contrast, the adsorption of weakly adsorbing central residues is dependent on their neighboring residues. Our structural analysis revealed that the dihedral angles of LNR are more correlated with that of CR in the adsorbed state than in bulk state. Together with ΔAads trends, this implies that different backbone structures of a given CR can be accessed for a similar ΔAads by varying the LNR. Therefore, incorporation of context effects in designing mutations can lead to desired peptide structure at surfaces. Our results also emphasize that these cooperative effects in ΔAads and structure are not easily predicted a priori. The collective results have applications in guiding rational mutagenesis techniques to control orientation of peptides at surfaces and in developing peptide structure prediction algorithms in adsorbed state from its sequence.

2020

Multivalent Surface Cations Enhance Heterogeneous Freezing of Water on Muscovite Mica

Nurun Nahar Lata, Jiarun Zhou, Pearce Hamilton, Michael Larsen, Sapna Sarupria, and Will Cantrell 11 8682-8689 (2020) The Journal of Physical Chemistry Letters.

DOI: 10.1021/acs.jpclett.0c02121

Heterogeneous ice nucleation is a crucial phenomenon in various fields of fundamental and applied science. We investigate the effect of surface cations on freezing of water on muscovite mica. Mica is unique in that the exposed ion on its surface can be readily and easily exchanged without affecting other properties such as surface roughness. We investigate freezing on natural (K+) mica and mica in which we have exchanged K+ for Al3+, Mg2+, Ca2+, and Sr2+. We find that liquid water freezes at higher temperatures when ions of higher valency are present on the surface, thus exposing more of the underlying silica layer. Our data also show that the size of the ion affects the characteristic freezing temperature. Using molecular dynamics simulations, we investigate the effects that the ion valency and exposed silica layer have on the behavior of water on the surface. The results indicate that multivalent cations enhance the probability of forming large clusters of hydrogen bonded water molecules that are anchored by the hydration shells of the cations. These clusters also have a large fraction of free water that can reorient to take ice-like configurations, which are promoted by the regions on mica devoid of the ions. Thus, these clusters could serve as seedbeds for ice nuclei. The combined experimental and simulation studies shed new light on the influence of surface ions on heterogeneous ice nucleation.

2019

A generalized deep learning approach for local structure identification in molecular simulations

RS DeFever, C Targonski, SW Hall, MC Smith, and S Sarupria 10 7503-7515 (2019) Chemical Science.

DOI: 10.1039/C9SC02097G

Identifying local structure in molecular simulations is of utmost importance. The most common existing approach to identify local structure is to calculate some geometrical quantity referred to as an order parameter. In simple cases order parameters are physically intuitive and trivial to develop (e.g., ion-pair distance), however in most cases, order parameter development becomes a much more difficult endeavor (e.g., crystal structure identification). Using ideas from computer vision, we adapt a specific type of neural network called a PointNet to identify local structural environments in molecular simulations. A primary challenge in applying machine learning tech- niques to simulation is selecting the appropriate input features. This challenge is system-specific and requires significant human input and intuition. In contrast, our approach is a generic frame- work that requires no system-specific feature engineering and operates on the raw output of the simulations, i.e., atomic positions. We demonstrate the method on crystal structure identification in Lennard-Jones (four different phases), water (eight different phases), and mesophase (six dif- ferent phases) systems. The method achieves as high as 99.5% accuracy in crystal structure identification. The method is applicable to heterogeneous nucleation and it can even predict the crystal phases of atoms near external interfaces. We demonstrate the versatility of our approach by using our method to identify surface hydrophobicity based solely upon positions and orienta- tions of surrounding water molecules. Our results suggest the approach will be broadly applicable to many types of local structure in simulations.

Building A Scalable Forward Flux Sampling Framework using Big Data and HPC

RS DeFever, W Hanger, J Kilgannon, A Apon, S Sarupria, and L Ngo (2019) Practice and Experience in Advanced Research Computing (PEARC19)

DOI: 10.1145/3332186.3332205

Forward flux sampling (FFS) is an established scientific method for sampling rare events in molecular simulations. However, as the difficulty of the scientific problem increases, the amount of data and the number of tasks required for FFS is challenging to manage with traditional scripting tools and languages for high performance computing. The SAFFIRE software framework has been developed to address these challenges. SAFFIRE utilizes Hadoop to manage a large number of tasks and data for large scale FFS simulations. The framework is shown to be highly scalable and able to support large scale FFS simulations. This enables studies of rare events in complex molecular systems on commodity cluster computing systems.

Simulations of interfacial processes: Recent advances in force field development

S Dasetty, P Meza-Morales, S Sarupria, and RB Getman 23 138-145 (2019) Current Opinion in Chemical Engineering.

DOI: 10.1016/j.coche.2019.04.003

Interfacial systems are ubiquitous and important to myriad processes of interest such as protein-protein interactions and catalysis of reactions. Investigating interfacial systems at the molecular level presents unique challenges to both experiments and molecular simulations. The challenges in molecular simulations of interfacial systems range from scalability of quantum simulations to transferability of empirical force fields in classical simulations. In this article, we focus on the advances in force field development to study interfacial systems using protein-surface interactions and heterogeneous catalysis as case studies. We also discuss the emerging role of machine learning in force field development. We conclude by providing our perspective on accelerating the progress in force field development through concerted efforts for data collection and standardization of parameter fitting protocols for extending the force fields to new interfacial systems.

Free energies of catalytic species adsorbed to Pt(111) surfaces under liquid solvent calculated using classical and quantum approaches

X Zhang, RS DeFever, S Sarupria, and RB Getman 595 2190-2198 (2019) Journal of Chemical Information and Modeling.

DOI: 10.1021/acs.jcim.9b00089

Solvent plays an important role in liquid phase heterogeneous catalysis; however, methods for calculating the free energies of catalytic phenomena at the solid–liquid interface are not well-established. For example, solvent molecules alter the energies of catalytic species and participate in catalytic reactions and can thus significantly influence catalytic performance. In this work, we begin to establish methods for calculating the free energies of such phenomena, specifically, by employing an explicit solvation method using a multiscale sampling (MSS) approach. This MSS approach combines classical molecular dynamics with density functional theory. We use it to calculate the free energies of solvation of catalytic species, specifically adsorbed NH*, NH2*, CO*, COH*, CH2OH*, and C3H7O3* on Pt(111) surfaces under aqueous phase and under a mixed H2O/CH3OH solvent. We compare our calculated values with analogous values from implicit solvation for validation and to identify situations where implicit solvation is sufficient versus where explicit solvent is needed to compute adsorbate free energies. Our results indicate that explicit quantum-based methods are needed when adsorbates form chemical bonds and/or strong hydrogen bonds with H2O solvent. Using MSS, we further separate the calculated free energies into energetic and entropic contributions in order to understand how each influences the free energy. We find that adsorbates that exhibit strong energies also exhibit strong and negative entropies, and we attribute this relationship to hydrogen bonding between the adsorbates and the solvent molecules, which provides a large energetic contribution but reduces the overall mobility of the solvent.

Multiscale Sampling of a Heterogeneous Water/Metal Catalyst Interface using Density Functional Theory and Force-Field Molecular Dynamics

CJ Bordenschatz, X Zhang, T. Xie, J Arvay, S Sarupria, and RB Getman 146 e59284 (2019) Journal of Visualized Experiments.

DOI: 10.3791/59284-v

A significant number of heterogeneously-catalyzed chemical processes occur under liquid conditions, but simulating catalyst function under such conditions is challenging when it is necessary to include the solvent molecules. The bond breaking and forming processes modeled in these systems necessitate the use of quantum chemical methods. Since molecules in the liquid phase are under constant thermal motion, simulations must also include configurational sampling. This means that multiple configurations of liquid molecules must be simulated for each catalytic species of interest. The goal of the protocol presented here is to generate and sample trajectories of configurations of liquid water molecules around catalytic species on flat transition metal surfaces in a way that balances chemical accuracy with computational expense. Specifically, force field molecular dynamics (FFMD) simulations are used to generate configurations of liquid molecules that can subsequently be used in quantum mechanics-based methods such as density functional theory or ab initio molecular dynamics. To illustrate this, in this manuscript, the protocol is used for catalytic intermediates that could be involved in the pathway for the decomposition of glycerol (C3H8O3). The structures that are generated using FFMD are modeled in DFT in order to estimate the enthalpies of solvation of the catalytic species and to identify how H2O molecules participate in catalytic decompositions.

Adsorption of Amino Acids on Graphene: Assessment of Current Force Fields

S Dasetty, J Barrows, and S Sarupria 15 2359-2372 (2019) Soft Matter.

DOI: 10.1039/C8SM02621A

We compare the free energies of adsorption (Aads) and the structural preferences of amino acids on graphene obtained using the non-polarizable force fields—Amberff99SB-ILDN/TIP3P, CHARMM36/ modified-TIP3P, OPLS-AA/M/TIP3P, and Amber03w/TIP4P/2005. The amino acid–graphene interactions are favorable irrespective of the force field. While the magnitudes of Aads differ between the force fields, the relative free energy of adsorption across amino acids is similar for the studied force fields. Aads positively correlates with amino acid–graphene and negatively correlates with graphene–water interaction energies. Using a combination of principal component analysis and density-based clustering technique, we grouped the structures observed in the graphene adsorbed state. The resulting population of clusters, and the conformation in each cluster indicate that the structures of the amino acid in the graphene adsorbed state vary across force fields. The differences in the conformations of amino acids are more severe in the graphene adsorbed state compared to the bulk state for all the force fields. Our findings suggest that the force fields studied will give qualitatively consistent relative strength of adsorption across proteins but different structural preferences in the graphene adsorbed state.

Contour forward flux sampling: Sampling rare events along multiple collective variables

RS DeFever, S Sarupria 150 024103 (2019) Journal of Chemical Physics.

DOI: 10.1063/1.5063358

Many rare event transitions involve multiple collective variables (CVs), and the most appropriate combination of CVs is generally unknown a priori. We thus introduce a new method, contour forward flux sampling (cFFS), to study rare events with multiple CVs simultaneously. cFFS places nonlinear interfaces on-the-fly from the collective progress of the simulations, without any prior knowledge of the energy landscape or appropriate combination of CVs. We demonstrate cFFS on analytical potential energy surfaces and a conformational change in alanine dipeptide.

2018

Introduction to the special issue on advanced molecular simulations: Methods and applications”, Editorial to Special Issue “Advanced molecular simulations: Methods and application

S Sarupria 17 (2018) Journal of Theoretical and Computational Chemistry.

DOI: 10.1142/S0219633618020017

Does not have abstract

Surface chemistry effects on heterogeneous clathrate hydrate nucleation: A molecular dynamics study

RS DeFever, S Sarupria 117 205-213 (2018) Journal of Chemical Thermodynamics.

DOI: 10.1016/j.jct.2017.08.021

We report results from a molecular dynamics study of clathrate hydrate nu- cleation near model hydrophilic and hydrophobic surfaces. -CH3 and -OH ter- minated self-assembled monolayers (SAMs) are used as model surfaces. We study the nucleation of a soluble, structure II forming guest molecule with a coarse-grained model compatible with monatomic water. Despite the presence of SAMs, we show that nucleation occurs through a homogeneous mechanism in OHSAM and CH3SAM systems. Formation of ice-like or intermediate water structure is not observed near either surface prior to nucleation. Nucleation occurs more quickly in OHSAM systems than CH3SAM systems. However, the faster nucleation is driven by a partitioning of guest molecules which results in higher bulk guest concentration in OHSAM systems compared with CH3SAM systems. Despite significant aggregation of guest molecules near CH3SAM, no nucleation is observed near the surface. The formation of guest contact pairs, facilitated by the presence of CH3SAM, may prevent nucleation in this region. Our results highlight the numerous routes by which surfaces can affect hydrate nucleation due to the multicomponent nature of the phenomena.

2017

Nucleation mechanism of clathrate hydrates of water-soluble guest molecules

RS DeFever and S Sarupria 147 204503 (2017) Journal of Chemical Physics.

DOI: 10.1063/1.4996132

The mechanism of nucleation of clathrate hydrates of a water-soluble guest molecule is rigorously investigated with molecular dynamics (MD) simulations. Results from forward flux sampling, committor probability analysis, and twenty straightforward MD trajectories were combined to create a comprehensive understanding of the nucleation mechanism. Seven different classes of order parameters with a total of 33 individual variants were studied. We rank and evaluate the efficacy of prospective reaction coordinate models built from these order parameters and linear combinations thereof. Order parameters based upon water structuring provide a better approximation of the reaction coordinate than those based upon guest structuring. Our calculations suggest that the transition state is characterized by 2-3 partial, face-sharing 512 cages which form a structural motif observed in the structure II crystal. Further simulations show that once formed, this structure significantly affects the ordering of vicinal guest molecules, likely leading to hydrate nucleation. Our results contribute to the current understanding of the water–guest interplay involved in hydrate nucleation and have relevance to hydrate-based technologies which use water-soluble guest molecules (e.g. tetrahydrofuran) in mixed hydrate systems.

Engineering Lipases: Walking the Fine Line Between Activity and Stability

S Dasetty, MA Blenner, and S Sarupria 4 113008 (2017) Materials Research Express.

DOI: 10.1088/2053-1591/aa9946

Lipases are enzymes that hydrolyze lipids and have several industrial applications. There is a tremendous effort in engineering the activity, specificity and stability of lipases to render them functional in a variety of environmental conditions. In this review, we discuss the recent experimental and simulation studies focused on engineering lipases. Experimentally, mutagenesis studies have demonstrated that the activity, stability, and specificity of lipases can be modulated by mutations. It has been particularly challenging however, to elucidate the underlying mechanisms through which these mutations affect the lipase properties. We summarize results from experiments and molecular simulations highlighting the emerging picture to this end. We end the review with suggestions for future research which underscores the delicate balance of various facets in the lipase that affect their activity and stability necessitating the consideration of the enzyme as a network of interactions.

Heterogeneous ice nucleation: Interplay of surface properties and their impact on water orientations

B Glatz and S Sarupria 34 1190-1198 (2017) Langmuir.

DOI: 10.1021/acs.langmuir.7b02859

Ice is ubiquitous in nature and heterogeneous ice nucleation is the most common pathway of ice formation. How surface properties affect the propensity to observe ice nucleation on that surface remains an open question. We present results of molecular dynamics studies of heterogeneous ice nucleation on model surfaces. The models surfaces considered emulate the chemistry of kaolinite, an abundant component of mineral dust. We investigate the interplay of surface lattice and hydrogen bonding properties in affecting ice nucleation. We find that lattice matching and hydrogen bonding are necessary but not sufficient conditions for observing ice nucleation at these surfaces. We correlate this behavior to the orientations sampled by the metastable supercooled water in contact with the surfaces. We find that ice is observed in cases where water molecules not only sample orientations favorable for bilayer formation but also do not sample unfavorable orientations. This distribution depends on both surface-water and water-water interactions and can change with subtle modifications to the surface properties. Our results provide insights into the diverse behavior of ice nucleation observed at different surfaces and highlights the complexity in elucidating heterogeneous ice nucleation.

On the water structure at hydrophobic interfaces and the roles of water on transition-metal catalyzed reactions: A short review

X Zhang, TE Sewell, B Glatz, S Sarupria, and RB Getman 285 57-64 (2017) Catalysis Today.

DOI: 10.1016/j.cattod.2017.02.002

Interest into the roles of water on aqueous phase heterogeneous catalysis is burgeoning. This short review summarizes the influences of hydrogen bonding on adsorption and how water molecules act as co-catalysts in aqueous phase heterogeneous catalysis. These phenomena, which involve interactions and/or reactions with “dangling” hydroxyl or hydroxide groups from nearby water molecules, are related to interfacial phenomena that have been observed at water/oil interfaces in organic synthesis. The hypothesized water structures at water/oil interfaces in organic synthesis is presented, and predictions about how analogous structural effects could influence catalytic chemistry at water/transition metal interfaces are discussed. The focus of this review is on computational methods and observations, but some experimental methods and findings are discussed as well.

A DFT and MD study of aqueous-phase dehydrogenation of glycerol on Pt(1 1 1): comparing chemical accuracy versus computational expense in different methods for calculating aqueous-phase system energies

T Xie, S Sarupria, and RB Getman 43 370-378 (2017) Molecular Simulation.

DOI: 10.1080/08927022.2017.1285403

Glycerol, which is one of the most abundant by-products in biodiesel production, can be converted into H2 through aqueous-phase reforming (APR). Dehydrogenation is one of the main processes in glycerol APR. In this work, we use computational methods to study Pt(1 1 1)-catalysed glycerol dehydrogenation under aqueous conditions. There are 84 intermediates and 250 possible reactions in the dehydrogenation network. Inclusion of the liquid environment adds computational expense, especially if we are to study all the reaction intermediates and reactions under explicit water solvation using quantum methods. In this work, we present a method that can be used to efficiently estimate reaction energies under explicit solvation with reasonable accuracy and computational expense. The method couples a linear scaling relationship for obtaining adsorbate binding energies with Lennard-Jones + Coulomb potentials for obtaining water–adsorbate interaction energies. Comparing reaction energies calculated with this approach to reaction energies obtained from a more extensive approach that attains quantum-level accuracy (published previously by our group), we find good correlation (R2 = 0.84) and reasonable accuracy (the mean absolute error, MAE = 0.28 eV).

2016

The surface charge distribution affects the ice nucleating efficiency of silver iodide

B Glatz and S Sarupria 145 211924 (2016) Journal of Chemical Physics.

DOI: 10.1063/1.4966018

Heterogeneous ice nucleation is the primary pathway for ice formation. However, the detailed molecular mechanisms by which surfaces promote or hinder ice nucleation are not well understood. We present results from extensive molecular dynamics simulations of ice nucleation near modified silver iodide (AgI) surfaces. The AgI surfaces are modified to investigate the effects of the surface charge distribution on the rate of ice nucleation. We find that the surface charge distribution has significant effects on ice nucleation. Specifically, AgI surfaces with the positive charges above the negative charges in the surface promote ice nucleation, while ice nucleation is hindered for surfaces in which the negative charges are above or in-plane with the positive charges. The structure of water molecules in the interfacial region as measured by the orientations of the water molecules relative to the surface can explain the differences in the ice nucleation at the different surfaces. We suggest that the distributions of the orientations of the interfacial water molecules could be used more broadly as a measure of ice nucleating propensity.

2015

Influence of carbon nanomaterial defects on the formation of protein corona

B Sengupta, WE Gregory, J Zhu, S Dasetty, M Karakaya, JM Brown, AM Rao, JK Barrows, S Sarupria, and R Podilla 5 82395-82402 (2015) RSC Advances.

DOI: 10.1039/C5RA15007H

In any physiological media, carbon nanomaterials (CNM) strongly interact with biomolecules leading to the formation of biocorona, which subsequently dictate the physiological response and the fate of CNMs. Defects in CNMs play an important role not only in material properties but also in the determination of how materials interact at the nano-bio interface. In this article, we probed the influence of defect-induced hydrophilicity on the biocorona formation using micro-Raman, photoluminescence, infrared spectroscopy, electrochemistry, and molecular dynamics simulations. Our results show that the interaction of proteins (albumin and fibrinogen) with CNMs is strongly influenced by charge-transfer between them, inducing protein unfolding which enhances conformational entropy and higher protein adsorption.

Association of small aromatic molecules with PAMAM dendrimers

RS DeFever and S Sarupria 17 29548-29557 (2015) Physical Chemistry Chemical Physics.

DOI: 10.1039/C5CP03717D

Many proposed applications using dendrimers, such as drug delivery and environmental remediation, involve dendrimer interactions with small molecules. Understanding the details of these interactions is important for designing dendrimers with tunable association with guest molecules. In this work, we investigate dendrimer interactions with small aromatic hydrocar- bons using all-atom molecular dynamics simulations. We study the association of naphthalene (NPH) — the smallest polycyclic aromatic hydrocarbon — with 3rd–6th generation (G3–G6) polyamidoamine (PAMAM) dendrimers. Our work emphasizes that the association of small aromatic molecules with PAMAM dendrimers involves the formation of dynamic pocket-like association sites through interactions between flexible dendrimer branches and NPH molecules. The association sites are primarily formed by branches from the two outermost dendrimer sub- generations, and often involve the tertiary amine groups. Irrespective of their location on the dendrimer — whether buried or near the outer surface — these pocket-like structures lower the hydration of the associated NPH molecules. We show that on average NPH molecules with a lower hydration have a greater tendency to remain associated with the dendrimer for longer times. In general, the association sites are similar for the G3–G6 PAMAM dendrimers indicating similarities in the association mechanisms across different dendrimer generations.

Molecular-Level Details about Liquid H2O Interactions with CO and Sugar Alcohol Adsorbates on Pt(111) Calculated Using Density Functional Theory and Molecular Dynamics

CJ Bordenschatz, S Sarupria, and RB Getman 119 13642-13651 (2015) Journal of Physical Chemistry C.

DOI: 10.1021/acs.jpcc.5b02333

Catalytic fuel production and energy generation from biomass-derived compounds generally involve the aqueous phase, and water molecules at the catalyst interface have energetic and entropic consequences on the reaction free energies. These effects are difficult to elucidate, hindering rational catalyst design for these processes and inhibiting their widespread adoption. In this work, we combine density functional theory (DFT) and classical molecular dynamics (MD) simulations to garner molecular-level insights into H2O–adsorbate interactions. We obtain ensembles of liquid configurations with classical MD and compute the electronic energies of these systems with DFT. We examine CO, CH2OH, and C3H7O3 intermediates, which are critical in biomass reforming and direct methanol electrooxidation, on the Pt(111) surface under various explicit and explicit/implicit water configurations. We find that liquid H2O molecules arrange around surface intermediates in ways that favor hydrogen bonding, with larger and more hydrophilic intermediates forming significantly more hydrogen bonds with H2O. For example, CO hydrogen-bonds with 1.5 ± 0.4 nearest neighbor H2O molecules and exhibits an interaction energy with these H2O molecules near 0 (−0.01 ± 0.09 eV), while CH2OH forms 2.2 ± 0.6 hydrogen bonds and exhibits an interaction energy of −0.43 ± 0.07 eV. C3H7O3 forms 6.7 ± 0.9 hydrogen bonds and exhibits an interaction energy of −1.18 ± 0.21 eV. The combined MD/DFT method identifies the number of liquid H2O molecules that are strongly bound to surface adsorbates, and we find that these H2O molecules influence the energies and entropies of the aqueous systems. This information will be useful in future calculations aimed at interrogating the surface thermodynamics and kinetics of reactions involving these adsorbates.

PAMAM dendrimers and graphene: Materials for removing aromatic contaminants from water

RS DeFever, NK Geitner, P Bhattacharya, F Ding, PC Ke, and S Sarupria 49 4490-4497 (2015) Environmental Science and Technology.

DOI: 10.1021/es505518r

We present results from experiments and atomistic molecular dynamics simulations on the remediation of naphthalene by polyamidoamine (PAMAM) dendrimers and graphene oxide (GrO). Specifically, we investigate 3(rd)-6(th) generation (G3-G6) PAMAM dendrimers and GrO with different levels of oxidation. The work is motivated by the potential applications of these emerging nanomaterials in removing polycyclic aromatic hydrocarbon contaminants from water. Our experimental results indicate that GrO outperforms dendrimers in removing naphthalene from water. Molecular dynamics simulations suggest that the prominent factors driving naphthalene association to these seemingly disparate materials are similar. Interestingly, we find that cooperative interactions between the naphthalene molecules play a significant role in enhancing their association to the dendrimers and GrO. Our findings highlight that while selection of appropriate materials is important, the interactions between the contaminants themselves can also be important in governing the effectiveness of a given material. The combined use of experiments and molecular dynamics simulations allows us to comment on the possible factors resulting in better performance of GrO in removing polyaromatic contaminants from water. We present results from experiments and atomistic molecular dynamics simulations on the remediation of naphthalene by polyamidoamine (PAMAM) dendrimers and graphene oxide (GrO). Specifically, we investigate 3rd-6th generation (G3-G6) PAMAM dendrimers and GrO with different levels of oxidation. The work is motivated by the potential applications of these emerging nanomaterials in removing polycyclic aromatic hydrocarbon contaminants from water. Our experimental results indicate that GrO outperforms dendrimers in removing naphthalene from water. Molecular dynamics simulations suggest that the prominent factors driving naphthalene association to these seemingly disparate materials are similar. Interestingly, we find that cooperative interactions between the naphthalene molecules play a significant role in enhancing their association to the dendrimers and GrO. Our findings highlight that while selection of appropriate materials is important, the interactions between the contaminants themselves can also be important in governing the effectiveness of a given material. The combined use of experiments and molecular dynamics simulations allows us to comment on the possible factors resulting in better performance of GrO in removing polyaromatic contaminants from water.

2014

Suppression of sub-surface freezing in free-standing thin films of a coarse-grained model of water

A Haji-Akbari, RS DeFever, S Sarupria, and PG Debenedetti 16 25916-25927 (2014) Physical Chemistry Chemical Physics.

DOI: 10.1039/C4CP03948C

Freezing in the vicinity of water–vapor interfaces is of considerable interest to a wide range of disciplines, most notably the atmospheric sciences. In this work, we use molecular dynamics and two advanced sampling techniques, forward flux sampling and umbrella sampling, to study homogeneous nucleation of ice in free-standing thin films of supercooled water. We use a coarse-grained monoatomic model of water, known as mW, and we find that in this model a vapor–liquid interface suppresses crystallization in its vicinity. This suppression occurs in the vicinity of flat interfaces where no net Laplace pressure in induced. Our free energy calculations reveal that the pre-critical crystalline nuclei that emerge near the interface are thermodynamically less stable than those that emerge in the bulk. We investigate the origin of this instability by computing the average asphericity of nuclei that form in different regions of the film, and observe that average asphericity increases closer to the interface, which is consistent with an increase in the free energy due to increased surface-to-volume ratios.

2013

Molecular Dynamics Simulations of Peptide–SWCNT Interactions Related to Enzyme Conjugates for Biosensors and Biofuel Cells

O Karunwi, C Baldwin, G Griecheimer, S Sarupria, and A Guiseppi-Elie 3 (4) 1343007 (2013) Nano LIFE.

DOI: 10.1142/S1793984413430071

With the demonstration of direct electron transfer between the redox active prosthetic group, flavin adenine dinucleotide (FAD), of glucose oxidase (GOx) and single-walled carbon nanotubes (SWCNT), there has been growing interest in the fabrication of CNT-enzyme supramolecular constructs that control the placement of SWCNTs within the tunneling distance of co-factors for enhanced electron transfer efficiency in generation-3 biosensors and advanced biofuel cells. These conjugate systems raise a series of questions such as: which peptide sequences within the enzymes have high affinity for the SWCNTs? And, are these high affinity sequences likely to be in the vicinity of the redox-active co-factor to allow for direct electron transfer? Phage display has recently been used to identify specific peptide sequences that have high affinity for SWCNTs. Molecular dynamics simulations were performed to study the interactions of five discrete peptides with (16,0) SWCNT in explicit water as well as with graphene. From the progression of the radius of gyration, Rg, the peptides studied were concertedly adsorbed to both the SWCNT and graphene. Peptide properties calculated using individual amino acid values, such as hydrophobicity indices, did not correlate with the observed adsorption behavior as quantified by Rg, indicating that the adsorption behavior of the peptide was not based on the individual amino acid residues. However, the Rg values, reflective of the physicochemical embrace of the surface (SWCNT or graphene) had a strong positive correlation with the solubility parameter, indicating concerted, cooperative interaction of peptide segments with the materials. The end residues appear to dominate the progression of adsorption regardless of character. Sequences identified by phage display share some homology with key enzymes (GOx, lactate oxidase and laccase) used in biosensors and enzyme-based biofuel cells. These analogous sequences appear to be buried deep within the shell of fully folded proteins and as such are expected to be close to the redox-active prosthetic group.

SciFlow: A dataflow-driven model architecture for scientific computing using Hadoop

P Xuan, Y Zheng, S Sarupria, and A Apon 36-44 (2013) IEEE International Conference on Big Data.

DOI: 10.1109/BigData.2013.6691725

Many computational science applications utilize complex workflow patterns that generate an intricately connected set of output files for subsequent analysis. Some types of applications, such as rare event sampling, additionally require guaranteed completion of all subtasks for analysis, and place significant demands on the workflow management and execution environment. SciFlow is a user interface built over the Hadoop infrastructure that provides a framework to support the complex process and data interactions and guaranteed completion requirements of scientific workflows. It provides an efficient mechanism for building a parallel scientific application with dataflow patterns, and enables the design, deployment, and execution of data intensive, many-task computing tasks on a Hadoop platform. The design principles of this framework emphasize simplicity, scalability and fault-tolerance. A case study using the forward flux sampling rare event simulation application validates the functionality, reliability and effectiveness of the framework.

On the Thermodynamics and Kinetics of Hydrophobic Interactions at Interfaces

S Vembanur, AJ Patel, S Sarupria, and S Garde 117 (35) 10261-10270 (2013) Journal of Physical Chemistry B.

DOI: 10.1021/jp4050513

We have studied how primitive hydrophobic interactions between two or more small nonpolar solutes are affected by the presence of surfaces. We show that the desolvation barriers present in the potential of mean force between the solutes in bulk water are significantly reduced near an extended hydrophobic surface. Correspondingly, the kinetics of hydrophobic contact formation and breakage are faster near a hydrophobic surface than near a hydrophilic surface or in the bulk. We propose that the reduction in the desolvation barrier is a consequence of the fact that water near extended hydrophobic surfaces is akin to that at a liquid–vapor interface and is easily displaced. We support this proposal with three independent observations. First, when small hydrophobic solutes are brought near a hydrophobic surface, they induce local dewetting, thereby facilitating the reduction of desolvation barriers. Second, our results and those of Patel et al. ( Proc. Natl. Acad. Sci. U.S.A. 2011, 108, 17678−17683) show that, whereas the association of small solutes in bulk water is driven by entropy, that near hydrophobic surfaces is driven by enthalpy, suggesting that the physics of interface deformation is important. Third, moving water away from its vapor–liquid coexistence, by applying hydrostatic pressure, leads to recovery of bulklike signatures (e.g., the presence of a desolvation barrier and an entropic driving force) in the association of solutes. These observations for simple solutes also translate to end-to-end contact formation in a model peptide with hydrophobic end groups, for which lowering of the desolvation barrier and acceleration of contact formation are observed near a hydrophobic surface. Our results suggest that extended hydrophobic surfaces, such as air–water or hydrocarbon–water surfaces, could serve as excellent platforms for catalyzing hydrophobically driven assembly.

Exploiting the physicochemical properties of dendritic polymers for environmental and biological applications

P Bhattacharya, NK Geitner, S Sarupria, and PC Ke 15 (13) 4477-4490 (2013) Physical Chemistry Chemical Physics.

DOI: 10.1039/C3CP44591G

In this perspective we first examine the rich physicochemical properties of dendritic polymers for hosting cations, anions, and polyaromatic hydrocarbons. We then extrapolate these conceptual discussions to the use of dendritic polymers in humic acid antifouling, oil dispersion, copper sensing, and fullerenol remediation. In addition, we review the state-of-the-art of dendrimer research and elaborate on its implications for water purification, environmental remediation, nanomedicine, and energy harvesting.

2012

Homogeneous Nucleation of Methane Hydrate in Microsecond Molecular Dynamics Simulations

S Sarupria and PG Debenedetti 3 (20) 2942-2947 (2012) Journal of Physical Chemistry Letters.

DOI: 10.1021/jz3012113

We report atomistically detailed molecular dynamics simulations of homogeneous nucleation of methane hydrate in bulk aqueous phase in the absence of any interface. Subcritical clusters of water and methane molecules are formed in the initial segment of the simulations, which then aggregate to give the critical hydrate nucleus. This occurs over time scales of several hundred nanoseconds, indicating that the formation and aggregation of subcritical clusters can contribute significantly to the overall rate of hydrate nucleation. The clusters have elements of sI hydrate structure, such as 512 and 51262 cages as well as other uncommon 51263 and 51264 cages, but do not possess long-range order. Clusters are dynamic in nature and undergo continuous structural rearrangements.

2011

Molecular Dynamics Study of Carbon Dioxide Hydrate Dissociation

S Sarupria and PG Debenedetti 115 (23) 6101-6111 (2011) Journal of Physical Chemistry A.

DOI: 10.1021/jp110868t

We present results from a molecular dynamics study of the dissociation behavior of carbon dioxide (CO2) hydrates. We explore the effects of hydrate occupancy and temperature on the rate of hydrate dissociation. We quantify the rate of dissociation by tracking CO2 release into the liquid water phase as well as the velocity of the hydrate−liquid water interface. Our results show that the rate of dissociation is dependent on the fractional occupancy of each cage type and cannot be described simply in terms of overall hydrate occupancy. Specifically, we find that hydrates with similar overall occupancy differ in their dissociation behavior depending on whether the small or large cages are empty. In addition, individual cages behave differently depending on their surrounding environment. For the same overall occupancy, filled small and large cages dissociate faster in the presence of empty large cages than when empty small cages are present. Therefore, hydrate dissociation is a collective phenomenon that cannot be described by focusing solely on individual cage behavior.

2010

Studying pressure denaturation of a protein by molecular dynamics simulations

S Sarupria, T Ghosh, AE Garcia, and S Garde 78 (7) 1641-1651 (2010) Proteins.

DOI: 10.1002/prot.22680

Many globular proteins unfold when subjected to several kilobars of hydrostatic pressure. This “unfolding-up-on-squeezing” is counter-intuitive in that one expects mechanical compression of proteins with increasing pressure. Molecular simulations have the potential to provide fundamental understanding of pressure effects on proteins. However, the slow kinetics of unfolding, especially at high pressures, eliminates the possibility of its direct observation by molecular dynamics (MD) simulations. Motivated by experimental results—that pressure denatured states are water-swollen, and theoretical results—that water transfer into hydrophobic contacts becomes favorable with increasing pressure, we employ a water insertion method to generate unfolded states of the protein Staphylococcal Nuclease (Snase). Structural characteristics of these unfolded states—their water-swollen nature, retention of secondary structure, and overall compactness—mimic those observed in experiments. Using conformations of folded and unfolded states, we calculate their partial molar volumes in MD simulations and estimate the pressure-dependent free energy of unfolding. The volume of unfolding of Snase is negative (approximately −60 mL/mol at 1 bar) and is relatively insensitive to pressure, leading to its unfolding in the pressure range of 1500–2000 bars. Interestingly, once the protein is sufficiently water swollen, the partial molar volume of the protein appears to be insensitive to further conformational expansion or unfolding. Specifically, water-swollen structures with relatively low radii of gyration have partial molar volume that are similar to that of significantly more unfolded states. We find that the compressibility change on unfolding is negligible, consistent with experiments. We also analyze hydration shell fluctuations to comment on the hydration contributions to protein compressibility. Our study demonstrates the utility of molecular simulations in estimating volumetric properties and pressure stability of proteins, and can be potentially extended for applications to protein complexes and assemblies.

2009

Hydrate Molecular Ballet

PG Debenedetti and S Sarupria 326 (5956) 1070-1071 (2009) Science.

DOI: 10.1126/science.1183027

Hydrates are crystalline solids in which guest molecules are trapped within polyhedral water cages (1). They are important in hydrocarbon processing (2) and could play a major role in sustainable energy production (3, 4). Methane hydrate occurs naturally and in vast quantities on ocean floors and in permafrost, with implications for climate change and energy recovery (2). However, the molecular mechanisms leading to hydrate formation are poorly understood; this knowledge gap affects not just the science and technology of these materials, but our comprehension of hydrophobicity (5) and of disorder-order phase transitions. On page 1095 of this issue, Walsh et al. report a computational tour de force that offers a fascinating glimpse of the molecular events leading to methane hydrate formation (6).

Addition/Correction: Ion Pairing in Molecular Simulations of Aqueous Alkali Halide Solutions

CJ Fennell, A Bizjak, V Vlachy, KA Dill, S Sarupria, S Rajamani, and S Garde 113 (44) 14837-14838 (2009) Journal of Physical Chemistry B.

DOI: 10.1021/jp908484v

Quantifying Water Density Fluctuations and Compressibility of Hydration Shells of Hydrophobic Solutes and Proteins

S Sarupria and S Garde 103 (3) 37803 (2009) Physical Review Letters.

DOI: 10.1103/PhysRevLett.103.037803

We probe the effects of solute length scale, attractions, and hydrostatic pressure on hydrophobic hydration shells using extensive molecular simulations. The hydration shell compressibility and water fluctuations both display a nonmonotonic dependence on solute size, with a minimum near molecular solutes and enhanced fluctuations for larger ones. These results and calculations on proteins suggest that the hydration shells of unfolded proteins are more compressible than of folded ones contributing to pressure denaturation. More importantly, the nonmonotonicity implies a solute curvature-dependent pressure sensitivity for interactions between hydrophobic solutes.

2008

Enthalpy-Entropy Contributions to Salt and Osmolyte Effects on Molecular-Scale Hydrophobic Hydration and Interactions

MV Athawale, S Sarupria, and S Garde 112 (18) 5661-5670 (2008) Journal of Physical Chemistry B.

DOI: 10.1021/jp073485n

Salts and additives can significantly affect the strength of water-mediated interactions in solution. We present results from molecular dynamics simulations focused on the thermodynamics of hydrophobic hydration, association, and the folding−unfolding of a hydrophobic polymer in water and in aqueous solutions of NaCl and of an osmolyte trimethylamine oxide (TMAO). It is known that addition of NaCl makes the hydration of hydrophobic solutes unfavorable and, correspondingly, strengthens their association at the pair as well as the many-body level (Ghosh, T.; Kalra, A.; Garde, S. J. Phys. Chem. B 2005, 109, 642), whereas the osmolyte TMAO has an almost negligible effect on the hydrophobic hydration and association (Athawale, M. V.; Dordick, J. S.; Garde, S. Biophys. J. 2005, 89, 858). Whether these effects are enthalpic or entropic in origin is not fully known. Here we perform temperature-dependent simulations to resolve the free energy into entropy and enthalpy contributions. We find that in TMAO solutions, there is an almost precise entropy−enthalpy compensation leading to the negligible effect of TMAO on hydrophobic phenomena. In contrast, in NaCl solutions, changes in enthalpy dominate, making the salt-induced strengthening of hydrophobic interactions enthalpic in origin. The resolution of total enthalpy into solute−solvent and solvent−solvent terms further shows that enthalpy changes originate primarily from solvent−solvent energy terms. Our results are consistent with experimental data on the hydration of small hydrophobic solutes by Ben-Naim and Yaacobi (Ben-Naim, A.; Yaacobi, M. J. Phys. Chem. 1974, 78, 170). In combination with recent work by Zangi, Hagen, and Berne (Zangi, R.; Hagen, M.; Berne, B. J. J. Am. Chem. Soc. 2007, 129, 4678) and the experimental data on surface tensions of salt solutions by Matubayasi et al. (Matubayasi, N.; Matsuo, H.; Yamamoto, K.; Yamaguchi, S.; Matuzawa, A. J. Colloid Interface Sci. 1999, 209, 398), our results highlight interesting length scale dependences of salt effects on hydrophobic phenomena. Although NaCl strengthens hydrophobic interactions at both small and large length scales, that effect is enthalpy-dominated at small length scales and entropy-dominated for large solutes and interfaces. Our results have implications for understanding of additive effects on water-mediated interactions, as well as on biocompatibility of osmolyte molecules in aqueous solutions.

2007

Pressure dependence of the compressibility of a micelle and a protein: insights from cavity formation analysis

B Pereira, S Jain, S Sarupria, L Yang, and S Garde 105 (2) 189-199 (2007) Molecular Physics.

DOI: 10.1080/00268970601140750

We present results from molecular dynamics simulations of a spherical micelle comprising 80 non-ionic C8E5 surfactants in water, a protein staphylococcal nuclease in water, and bulk n-hexane and water liquids over a range of hydrostatic pressures. We focus specifically on the pressure dependence of the volumetric properties—the partial molar volume and partial molar compressibility—of the micelle, the protein, and bulk liquids. We find that the micelle interior displays properties similar to liquid alkanes over a range of pressures and has a compressibility of 100−110×10−6 bar−1 under ambient conditions, which is more than twice that of liquid water. In contrast, the pressure dependence of the protein interior resembles that of solid organic polymeric materials and has a compressibility of 5−10×10−6 bar−1. We performed extensive analysis of cavity formation in all systems. Interestingly, it is not the average cavity size but the width of the cavity size distribution in a given medium that correlates with the compressibility of that medium over a broad range of pressures up to several kilobars. Correspondingly, the cavity size distribution is most sharply defined in protein interiors and is broadest in the micelle interior and in n-hexane. To explore the correlation between cavity formation and compressibility, we present preliminary calculations using the information theory approach in the bulk water phase. Analysis of cavity formation and, especially, the nature of the cavity size distribution may provide a sensitive probe of the compressibility and flexibility of local molecular environments in inhomogeneous condensed media.