Equilibrium Molecular Dynamics Simulations Research Articles

Contributions of the individual domains of αIIbβ3 integrin to its extension: Insights from multiscale modeling.

The platelet integrin αIIbβ3 undergoes long-range conformational transitions between bent and extended conformations to regulate platelet aggregation during hemostasis and thrombosis. However, how exactly αIIbβ3 transitions between conformations remains largely elusive. Here, we studied how transitions across bent and extended-closed conformations of αIIbβ3 integrin are regulated by effective interactions between its functional domains. We first carried out μs-long equilibrium molecular dynamics (MD) simulations of full-length αIIbβ3 integrins in bent and intermediate conformations, the latter characterized by an extended headpiece and closed legs. Then, we built heterogeneous elastic network models, perturbed inter-domain interactions, and evaluated their relative contributions to the energy barriers between conformations. Results showed that integrin extension emerges from: (i) changes in interfaces between functional domains; (ii) allosteric coupling of the head and upper leg domains with flexible lower leg domains. Collectively, these results provide new insights into integrin conformational activation based on short- and long-range interactions between its functional domains and highlight the importance of the lower legs in the regulation of integrin allostery.

Prediction of phonon properties of cubic boron nitride with vacancy defects and isotopic disorders by using a neural network potential

Cubic boron nitride (c-BN) is a promising ultra-wide bandgap semiconductor for high-power electronic devices. Its thermal conductivity can be substantially modified by controlling the isotope abundance and by the quality of a single crystal. Consequently, an understanding of the phonon transport in c-BN crystals, with both vacancy defects and isotopic disorders at near-ambient temperatures, is of practical importance. In the present study, a neural network potential (NNP) for c-BN has been developed, which has facilitated the investigation of phonon properties under these circumstances. As a result, the phonon dispersion and the three- and four-phonon scattering rates that were predicted with this NNP were in close agreement with those obtained from density-functional theory (DFT) calculations. The thermal conductivities of the c-BN crystals were also investigated, with boron (B) vacancies ranging from 0.0% to 0.6%, by using equilibrium molecular dynamics simulations based on the Green-Kubo formula. These simulations accurately capture vacancy-induced phonon softening, localized vibration modes, and phonon localization effects. As has previously been experimentally prepared, four isotope-modified c-BN samples were selected for analyses in the evaluation of the impact of isotopic disorders. The calculated thermal conductivities aligned well with the DFT benchmarks. In addition, the present study was extended to include a c-BN crystal with a natural abundance of B atoms, which also contained B vacancies. Reasonable thermal conductivities and vibrational characteristics, within the temperature range of 250–500 K, were then obtained.

Electrically regulated thermal conductivity of aramid polymer systems

Aramid polymers, renowned for their electronic insulation and thermal conductive properties, are widely adopted as thermal management materials in power electronics. However, the thermal conductivity of aramid polymers under electric field has not been thoroughly understood. In this study, we investigated the thermal conductivity of amorphous and aligned aramid polymer systems under electrical field utilizing equilibrium molecular dynamics simulations. Simulation results showed that the alignment of polymer chain can significantly enhance the thermal conductivity of aramid polymer systems, achieving up to 10.13 W/m-K. Moreover, polarization of aligned aramid polymer was observed when the applied electric field exceeded 14 V/nm. Interestingly, the thermal conductivity of aligned aramid polymer was selectively modulated by the applied electric field. To unravel the underlying phonon mechanism, the molecular orientation of polymer chains and phonon spectral information were analyzed. Our study provides guidance into understanding thermal transport mechanism and thermal conductivity modulation in polymers.

Calculating High-Pressure PAO4 Viscosity with Equilibrium Molecular Dynamics Simulations

The development of optimized lubricants is hindered by missing knowledge of fluid properties, in particular the viscosity, in the range of extreme pressures and temperatures relevant for application. Molecular dynamics simulations can be used to calculate viscosity, but the necessary computational effort imposes practical limits for high viscosities. In this study, the viscosity of PAO4 oil was extracted from equilibrium molecular dynamics simulations as a function of pressure and temperature reaching viscosities up to 20 Pas. Three calculation methods based on different microscopic expressions for the viscosity were used. The methods exhibit considerably different performance with respect to preciseness and computational efficiency. The highest viscosities were found to be calculated most efficiently via the Stokes–Einstein relation, by computing the diffusion coefficient from the velocity correlation function. This offers a new, more effective route to push viscosity calculations in equilibrium molecular dynamics simulations to higher pressure systems.Graphical

Shock Hugoniot Calculations of Newly Designed Thermoplastic Elastomers and Comparison with Classical Binder Estane.

Our purpose is to design excellent binder candidates used in polymer-bonded explosives (PBX) according to the calculated shock of Hugoniot. Here, we mainly examined the thermoplastic elastomer (TPE) binders commonly used in PBX formulations. Equilibrium molecular dynamics (MD) simulation and mixing rule methods were used to calculate the shock Hugoniot values of 180 newly designed TPEs. We focused on the influence of the polymerization degree, contents, and types of soft and hard segments composed of TPEs on the shock Hugoniot and compared them with the classic PBX binder, Estane. The results show that the hard segment has an effect on the Hugoniot curve, which gradually diminishes as the degree of polymerization increases. The underlying physical mechanism can be attributed to the presence of a large number of hydrogen bonds in hard segment domains. The shock Hugoniot of TPEs also depends on the type of soft segments. The volume compression rate of TPEs decreases with increasing content of hard segments under a given shock. By comparing with Estane, a TPE binder commonly used in PBX, we ultimately chose several new TPEs with the potential to serve as PBX binders in terms of shock performance.

Enhanced phonon transport in sI-type methane hydrate under uniaxial compression strain: Unveiling the opening of an advantageous channel

Unveiling the thermal transport mechanisms of natural gas hydrate under strain conditions is fundamental to the heat transfer of the hydrate reservoir during drilling and production. This work investigated the structural stability and phonon transport mechanisms of methane hydrate using equilibrium molecular dynamics simulations subjected to uniaxial compression strain. The results indicate that the stability of large cages within methane hydrates weakens under strain. However, the presence of methane molecules effectively stabilizes the cage structure, enabling it to remain intact even under significant deformation. Furthermore, the thermal conductivity of methane hydrate demonstrates non-linear behavior, characterized by an initial increase followed by a subsequent decrease with increasing uniaxial compression strain. Particularly, the thermal conductivity of methane hydrate attains a maximum value of 0.87±0.018 W⋅m−1⋅K−1 at a strain of -0.04. The results suggest that the elevated spectral energy density and the prolonged phonon lifetime contribute to the enhanced thermal conductivity of methane hydrate. Interestingly, it was observed that the overlapping of phonon vibration modes between water and methane molecules results in the suppression of the peaks and valleys when the strain reaches -0.04. This overlap eliminates the gap and opens up an advantageous channel for phonon transport, thereby enhancing the heat transport capability of methane hydrate. The opening of an advantageous channel for phonon transport results in an extended phonon lifetime and a subsequent increase in thermal conductivity. This study presents a novel perspective for comprehending the unusual thermal conductivity of methane hydrate under strain conditions.

Thermal conductivity and structural behavior of confined H2 from molecular dynamics simulation

In this work, we perform equilibrium molecular dynamics simulation to study the thermal conductivity of hydrogen molecules (H2) under extreme confinement within graphene nanochannel. We analyze the structural behavior of H2 molecules inside the nanochannel and also examine the effect of nanochannel height, the number of H2 molecules, and temperature of the system on the thermal conductivity. Our results reveal that H2 molecules exhibit a strong propensity for absorption onto the nanochannel wall, consequently forming a dense packed layer in close to the wall. This phenomenon significantly impacts the thermal conductivity of the confined system. We made a significant discovery, revealing a strong correlation between the mass density near the nanochannel wall and the thermal conductivity. This finding highlights the crucial role played by the density near the wall in determining the thermal conductivity behavior. Surprisingly, the average thermal conductivity for nanochannels with a height (h) less than 27 Å exhibited an astonishing increase of over 12 times when compared to the bulk. Moreover, we observe that increasing the nanochannel height, while the number of H2 molecules fixed, leads to a notable decrease in thermal conductivity. Furthermore, we investigate the influence of temperature on thermal conductivity. Our simulations demonstrate that higher temperature enhance the thermal conductivity due to increased phonon activity and energy states, facilitating more efficient heat transfer and higher thermal conductivity. To gain deeper insights into the factors affecting thermal conductivity, we explored the phonon density of states. Studying the behavior of hydrogen in confined environments can offer valuable insights into its transport properties and its potential for industrial applications.

Structural and thermal analyses in semiconducting and metallic zigzag single-walled carbon nanotubes using molecular dynamics simulations.

Equilibrium molecular dynamics (EMD) simulations have been performed to investigate the structural analysis and thermal conductivity (λ) of semiconducting (8,0) and metallic (12,0) zigzag single-walled carbon nanotubes (SWCNTs) for varying ±γ(%) strains. For the first time, the present outcomes provide valuable insights into the relationship between the structural properties of zigzag SWCNTs and corresponding thermal behavior, which is essential for the development of high-performance nanocomposites. The radial distribution function (RDF) has been employed to assess the buckling and deformation understandings of the (8,0) and (12,0) SWCNTs for a wide range of temperature T(K) and varying ±γ(%) strains. The visualization of SWCNTs shows that the earlier buckling and deformation processes are observed for semiconducting SWCNTs as compared to metallic SWCNTs for high T(K) and it also evident through an abrupt increase in RDF peaks. The RDF and visualization analyses demonstrate that the (8,0) SWCNTs can more tunable under compressive than tensile strains, however, the (12,0) zigzag SWCNTs indicate an opposite trend and may tolerate more tensile than compressive strains. Investigations show that the tunable domain of ±γ(%) strains decreases from (-10%≤ γ ≤+19%) to (-5%≤ γ ≤+10%) for (8,0) SWCNTs and the buckling process shifts to lower ±γ(%) for (12,0) SWCNTs with increasing T(K). For intermediate-high T(K), the λ(T) of (12,0) SWCNTs is high but the (8,0) SWCNTs show certainly high λ(T) for low T(K). The present λ(T, ±γ) data are in reasonable agreement with parts of previous NEMD, GK-HNEMD data and experimental investigations with simulation results generally under predicting the λ(T, ±γ) by the ∼1% to ∼20%, regardless of the ±γ(%) strains, depending on T(K). Our simulation data significantly expand the strain range to -10% ≤ γ ≤ +19% for both zigzag SWCNTs, depending on temperature T(K). This extension of the range aims to establish a tunable regime and delve into the intrinsic characteristics of zigzag SWCNTs, building upon previous work.

Salt Effects on the Mechanical Properties of Ionic Conductive Polymer: A Molecular Dynamics Study.

Functional polymers can be used as electrolyte and binder materials in solid-state batteries. This often requires performance targets in terms of both the transport and mechanical properties. In this work, a model ionic conductive polymer system, i.e., poly(ethylene oxide)-LiTFSI, was used to study the impact of salt concentrations on mechanical properties, including different types of elastic moduli and the viscoelasticity with both nonequilibrium and equilibrium molecular dynamics simulations. We found an encouragingly good agreement between experiments and simulations regarding Young's modulus, bulk modulus, and viscosity. In addition, we identified an intermediate salt concentration at which the system shows high ionic conductivity, high Young's modulus, and short elastic restoration time. Therefore, this study laid the groundwork for investigating ionic conductive polymer binders with self-healing functionality from molecular dynamics simulations.

Glass Transition Temperatures and Thermal Conductivities of Polybutadiene Crosslinked with Randomly Distributed Sulfur Chains Using Molecular Dynamic Simulation.

The thermal conductivities and glass transition temperatures of polybutadiene crosslinked with randomly distributed sulfur chains having different lengths from mono-sulfur (S1) to octa-sulfur (S8) were investigated. The thermal conductivities of the related models as a function of the heat flux autocorrelation function, applying an equilibrium molecular dynamic (EMD) simulation and the Green-Kubo method, were studied for a wide range of temperatures. The influence of the length of sulfur chains, degree of crosslinking, and molar mass of the crosslinker on the glass transition temperature and final values of thermal conductivities were studied. First, the degree of crosslinking is considered constant for the eight simulation models, from mono-sulfur (S1) to octa-sulfur (S8), while the molar mass of the sulfur is increases. The results show that the thermal conductivities of the crosslinked structure decrease with increasing temperature for each model. Moreover, by increasing the lengths of the sulfur chains and the molar weight of the crosslinker, thermal conductivity increases at a constant temperature. The MD simulation demonstrates that the glass transition temperature and density of the crosslinked structure enhance as the length of the sulfur chains and molar mass of the sulfur increase. Second, the molar weight of sulfur is considered constant in these eight models; therefore, the degree of crosslinking decreases with the increase in the lengths of the sulfur chains. The results show that the thermal conductivities of the crosslinked structure decrease with the increase in the temperature for each model. Moreover, by increasing the lengths of sulfur chains and thus decreasing the degree of crosslinking, the trend in changes in thermal conductivities are almost the same for all of these models, so thermal conductivity is constant for a specific temperature. In addition, the glass transition temperature and density of the crosslinked structure decrease.

Efficient single-run implementation of generalized Einstein relation to compute transport coefficients: A binary-based time sampling.

A robust and simple implementation of the generalized Einstein formulation using single equilibrium molecular dynamics simulation is introduced to compute diffusion and shear viscosity. The unique features underlying this framework are as follows: (1) The use of a simple binary-based method to sample time-dependent transport coefficients results in a uniform distribution of data on a logarithmic time scale. Although we sample "on-the-fly," the algorithm is readily applicable for post-processing analysis. Overlapping same-length segments are not sampled as they indicate strong correlations. (2) Transport coefficients are estimated using a power law fitting function, a generalization of the standard linear relation, that accurately describes the long-time plateau. (3) The use of a generalized least squares (GLS) fitting estimator to explicitly consider correlations between fitted data points results in a reliable estimate of the statistical uncertainties in a single run. (4) The covariance matrix for the GLS method is estimated analytically using the Wiener process statistics and computed variances. (5) We provide a Python script to perform the fits and automate the procedure to determine the optimal fitting domain. The framework is applied to two fluids, binary hard sphere and a Lennard-Jones near the triple point, and the validity of the single-run estimates is verified against multiple independent runs. The approach should be applicable to other transport coefficients since the diffusive limit is universal to all of them. Given its rigor and simplicity, this methodology can be readily incorporated into standard molecular dynamics packages using on-the-fly or post-processing analysis.

Simulation and Data-Driven Modeling of the Transport Properties of the Mie Fluid.

This work reports the computation and modeling of the self-diffusivity (D*), shear viscosity (η*), and thermal conductivity (κ*) of the Mie fluid. The transport properties were computed using equilibrium molecular dynamics simulations for the Mie fluid with repulsive exponents (λr) ranging from 7 to 34 and at a fixed attractive exponent (λa) of 6 over the whole fluid density (ρ*) range and over a wide temperature (T*) range. The computed database consists of 17,212, 14,288, and 13,099 data points for self-diffusivity, shear viscosity, and thermal conductivity, respectively. The database is successfully validated against published simulation data. The above-mentioned transport properties are correlated using artificial neural networks (ANNs). Two modeling approaches were tested: a semiempirical formulation based on entropy scaling and an empirical formulation based on density and temperature as input variables. For the former, it was found that a unique formulation based on entropy scaling does not yield satisfactory results over the entire density range due to a divergent and incorrect scaling of the transport properties at low densities. For the latter empirical modeling approach, it was found that regularizing the data, e.g., modeling ρ*D* instead of D*, ln η* instead of η*, and ln κ* instead of κ*, as well as using the inverse of the temperature as an input feature, helps to ease the interpolation efforts of the artificial neural networks. The trained ANNs can model seen and unseen data over a wide range of density and temperature. Ultimately, the ANNs can be used alongside equations of state to regress effective force field parameters from volumetric and transport data.

Effects of Organic Surface Contamination on the Mass Accommodation Coefficient of Water: A Molecular Dynamics Study.

The mass accommodation coefficient (MAC), a parameter that quantifies the possibility of a phase change to occur at a liquid-vapor interface, can strongly affect the evaporation and condensation rates at a liquid surface. Due to the various challenges in experimental determination of the MAC, molecular dynamics (MD) simulations have been widely used to study the MAC on liquid surfaces with no impurities or contaminations. However, experimental studies show that airborne hydrocarbons from various sources can adsorb on liquid surfaces and alter the liquid surface properties. In this work, therefore, we study the effects of organic surface contamination, which is immiscible with water, on the MAC of water by equilibrium and nonequilibrium MD simulations. The equilibrium MD simulation results show that the MAC decreases almost linearly with increasing surface coverage of the organic contaminants. With the MAC determined from EMD simulations, the nonequilibrium MD simulation results show that the Schrage equation, which has been proven to be accurate in predicting the evaporation/condensation rates on clean liquid surfaces, is also accurate in predicting the condensation rate at contaminated water surfaces. The key assumption about the molecular velocity distribution in the Schrage analysis is still valid for condensing vapor molecules near contaminated water surfaces. We also find that under nonequilibrium conditions the adsorption of the water vapor molecules on the organic surface results in an adsorption vapor flux near the contaminated water surface. When the water surface is almost fully covered by the model organic contaminants, the adsorption flux dominates over the water condensation flux and leads to a false prediction of the MAC from the Schrage equation.

Thermal transport in a defective pillared graphene network: insights from equilibrium molecular dynamics simulation.

Graphene-based hybrid nanostructures have great potential to be ideal candidates for developing tailored thermal transport materials. In this study, we perform equilibrium molecular dynamics simulations employing the Green-Kubo method to investigate the influence of topological defects in three-dimensional pillared graphene networks. Similar to single-layer graphene and carbon nanotubes, the thermal conductivity (k) of pillared graphene systems exhibits a strong correlation with the system size (L), following a power-law relation k ∼ Lα, where α ranges from 0.12 to 0.15. Our results indicate that the vacancy defects significantly reduce thermal conductivity in pillared graphene systems compared to Stone-Wales defects. We observe that, beyond defect concentration, the location of the defects also plays a crucial role in determining thermal conductivity. We further analyze the phonon vibrational spectrum and the phonon participation ratio to obtain more insight into the thermal transport in the defective pillared graphene network. In most scenarios, longitudinal and flexural acoustic phonons experience significant localization within the 15-45 THz frequency range in the defective pillared graphene system.

Rheological properties of water-based amino acid ionic liquids

The rheological properties and zero-shear viscosity of water-based lubricants (WBLs) containing amino acid ionic liquids (AAILs) were investigated using both equilibrium (EMD) and non-equilibrium molecular dynamics (NEMD) simulations. We also performed experimental measurements to validate the simulations. The simulations demonstrated that adding AAIL additives to water increased both the shear viscosity and zero-shear viscosity. We added tetrabutylphosphonium (P4444) as a cation and three different amino acids, serine (Ser), lysine (Lys), or phenylalanine (Phe), as anions. We varied the AAIL concentration from 5 to 10 wt. % for tetrabutylphosphonium-serine (P4444-Ser) ionic liquid additives, showing that AAILs increased water viscosity by 68%–125%, depending on concentration. The P4444-Ser WBLs also exhibited a significantly higher first normal stress difference than water, meaning they could support more load in lubrication. The improved rheology persisted over a wide range of shear rates up to ∼1011 s−1. We have extracted full rheological parameters by fitting data into Cross, Carreau–Yasuda, and Eyring models, including zero-shear viscosity and critical shear rates of onset shear thinning. The experimental values of zero-shear viscosity were close to zero-shear viscosity results obtained from fitting NEMD results to these models, demonstrating the high fidelity of the molecular model. We explored the formation of hydration shells around amino acid anions as a marker for low friction behavior. These findings suggest that AAIL WBLs can be potentially low-friction and biodegradable lubricants in tribological applications.

PES and transport properties of the He⋯HBr complex from kinetic theory and molecular dynamics simulations.

The ab initio intermolecular potential of the He⋯HBr van der Waals (vdW) complex was calculated at the CCSD(T)/a5zBF level of theory and expanded in terms of the orthogonal Legendre polynomials. The PES then was implemented to calculate the interaction viscosity (η12) and diffusion (D12) coefficients through classical Mason-Monchick approximation (MMA), quantum mechanical close-coupling (CC), and molecular dynamics (MD) simulations. Energy-dependent Senftleben-Beenakker (SB) cross-sections were calculated using rotationally averaged cross-sections, and Boltzmann averaging was used to reveal the temperature dependence of the SB cross-sections over the temperature range of T = 50-1000 K. The calculated transport properties from MMA are in close agreement with the CC results, especially for temperatures lower than T = 900 K. The ab initio potential data then were used to derive LJ (12,6) and Vashishta MD force fields, and the equilibrium MD simulation methods were implemented to extract η12 and D12 coefficients using Einstein formulas. It was found that the Vashishta 3-body interaction potential model shows better accuracy than the LJ (12,6) model in MD simulations of D12. For η12, however, both MD potential models are successful, and an average absolute deviation of lower than 1% was obtained when compared to the quantum mechanical CC method.

MD Simulation of Water Using a Rigid Body Description Requires a Small Time Step to Ensure Equipartition.

In simulations of aqueous systems, it is common to freeze the bond vibration and angle bending modes in water to allow for a longer time step δt for integrating the equations of motion. Thus, δt = 2 fs is often used in simulating rigid models of water. We simulate the SPC/E model of water using δt from 0.5 to 3.0 fs and up to 4 fs using hydrogen mass repartitioning. In these simulations, we find that for all but δt = 0.5 fs, equipartition is not obtained between translational and rotational modes, with the rotational modes exhibiting a lower temperature than the translation modes. To probe the reasons for the lack of equipartition, we study the autocorrelation of the translational velocity of the center of mass and the angular velocity of the rigid water molecule, respectively. We find that the rotational relaxation occurs on a timescale comparable to vibrational periods, calling into question the original motivations for freezing the vibrations. Furthermore, a time step with δt ≥ 1 fs is not able to capture accurately the fast rotational relaxation, which reveals its impact as an effective slowing-down of rotational relaxation. The fluctuation-dissipation relation then leads to the conclusion that the rotational temperature should be cooler for δt greater than the reference value of 0.5 fs. Consideration of fluctuation-dissipation in equilibrium molecular dynamics simulations also emphasizes the need to capture the temporal evolution of fluctuations with fidelity and the role of δt in this regard. The time step also influences the solution thermodynamic properties: both the mean system potential energies and the excess entropy of hydration of a soft repulsive cavity are sensitive to δt.

Reduction of thermal conductivity in carbon nanotubes by fullerene encapsulation from machine-learning molecular dynamics simulations

The carbon nano-peapod is a representative structure with interlayer van der Waals (vdW) interactions, in which encapsulated fullerene molecules play a critical role in modulating the transport properties of the carbon nanotubes (CNTs). In particular, their influence on the thermal transport characteristics has been the focal point of considerable attention. In this study, we trained an accurate machine learning potential for fullerene-encapsulated CNTs based on the efficient NEP model to investigate their thermal properties. Using equilibrium molecular dynamics simulation along with the spectral decomposition method for thermal conductivity, we find that the thermal conductivity of fullerene-encapsulated CNTs is roughly 55% lower than that of empty CNTs, aligning with experimental observations for CNT bundles with fullerene encapsulation [Kodama et al., Nat. Mater. 16, 892 (2017)]. The research suggests that weak vdW interactions between both the fullerene and CNTs, as well as between fullerene molecules themselves, hinder phonon propagation. The encapsulated fullerene contributes to an increase in phonon scattering within the CNTs, ultimately leading to a reduction in thermal conductivity. We utilized machine learning potential to investigate the structure of fullerene-encapsulated CNTs and their heat transport property. This approach provides valuable insights for performance research of complex systems featuring interlayer vdW interactions.

Twofold Machine-Learning and Molecular Dynamics: A Computational Framework

Data science and machine learning (ML) techniques are employed to shed light into the molecular mechanisms that affect fluid-transport properties at the nanoscale. Viscosity and thermal conductivity values of four basic monoatomic elements, namely, argon, krypton, nitrogen, and oxygen, are gathered from experimental and simulation data in the literature and constitute a primary database for further investigation. The data refers to a wide pressure–temperature (P-T) phase space, covering fluid states from gas to liquid and supercritical. The database is enriched with new simulation data extracted from our equilibrium molecular dynamics (MD) simulations. A machine learning (ML) framework with ensemble, classical, kernel-based, and stacked algorithmic techniques is also constructed to function in parallel with the MD model, trained by existing data and predicting the values of new phase space points. In terms of algorithmic performance, it is shown that the stacked and tree-based ML models have given the most accurate results for all elements and can be excellent choices for small to medium-sized datasets. In such a way, a twofold computational scheme is constructed, functioning as a computationally inexpensive route that achieves high accuracy, aiming to replace costly experiments and simulations, when feasible.

Mechanical forces control the valency of the malaria adhesin VAR2CSA by exposing cryptic glycan binding sites.

Plasmodium falciparum (Pf) is responsible for the most lethal form of malaria. VAR2CSA is an adhesin protein expressed by this parasite at the membrane of infected erythrocytes for attachment to the placenta, leading to pregnancy-associated malaria. VAR2CSA is a large 355 kDa multidomain protein composed of nine extracellular domains, a transmembrane helix, and an intracellular domain. VAR2CSA binds to Chondroitin Sulphate A (CSA) of the proteoglycan matrix of the placenta. Shear flow, as the one occurring in blood, has been shown to enhance the (VAR2CSA-mediated) adhesion of Pf-infected erythrocytes on the CSA-matrix. However, the underlying molecular mechanism governing this enhancement has remained elusive. Here, we address this question by using equilibrium, force-probe, and docking-based molecular dynamics simulations. We subjected the VAR2CSA protein-CSA sugar complex to a force mimicking the tensile force exerted on this system due to the shear of the flowing blood. We show that upon this force exertion, VAR2CSA undergoes a large opening conformational transition before the CSA sugar chain dissociates from its main binding site. This preferential order of events is caused by the orientation of the molecule during elongation, as well as the strong electrostatic attraction of the sugar to the main protein binding site. Upon opening, two additional cryptic CSA binding sites get exposed and a functional dodecameric CSA molecule can be stably accommodated at these force-exposed positions. Thus, our results suggest that mechanical forces increase the avidity of VAR2CSA by turning it from a monovalent to a multivalent state. We propose this to be the molecular cause of the observed shear-enhanced adherence. Mechanical control of the valency of VAR2CSA is an intriguing hypothesis that can be tested experimentally and which is of relevance for the understanding of the malaria infection and for the development of anti placental-malaria vaccines targeting VAR2CSA.