Haohao Fu

Sonoporation at Small and Large Length Scales: Effect of Cavitation Bubble Collapse on Membranes

Ultrasound has emerged as a promising means to effect controlled delivery of therapeutic agents through cell membranes. One possible mechanism that explains the enhanced permeability of lipid bilayers is the fast contraction of cavitation bubbles produced on the membrane surface, thereby generating large impulses, which, in turn, enhance the permeability of the bilayer to small molecules. In the present contribution, we investigate the collapse of bubbles of different diameters, using atomistic and coarse-grained molecular dynamics simulations to calculate the force exerted on the membrane. The total impulse can be computed rigorously in numerical simulations, revealing a superlinear dependence of the impulse on the radius of the bubble. The collapse affects the structure of a nearby immobilized membrane, and leads to partial membrane invagination and increased water permeation. The results of the present study are envisioned to help optimize the use of ultrasound, notably for the delivery of drugs.

From material science to avant-garde cuisine. The art of shaping liquids into spheres.

Employing avant-garde cuisine techniques, in particular sodium alginates, liquid food can be shaped into spheres, thereby conferring to the former original and sometimes unexpected forms and textures. To achieve this result, rational understanding of the science that underlies food physical chemistry is of paramount importance. In this contribution, the process of spherification is dissected for the first time at the atomic level by means of classical molecular dynamics simulations. Our results show that a thin membrane consisting of intertwined alginate chains forms in an aqueous solution containing calcium ions, thereby encapsulating in a sphere the aliment in its liquid state. They also show why the polysaccharide chains will not cohere into such a membrane in a solution of sodium ions. Analysis of the trajectories reveals the emergence of so-called egg-box spatial arrangements, which connect the alginate chains by means of repeated chelation of one calcium ion by two carboxylate groups. Free-energy calculations delineating the formation of these egg-box structures further illuminate the remarkable stability of such tridimensional organizations, which ensures at room temperature the spontaneous growth of the polysaccharide membrane. Spherification has been also examined for liquid aliments of different nature, modeled by charged, hydrophilic and hydrophobic compounds. The membrane-encapsulated food is shaped into robust and durable spheres, irrespective of the liquid core material. By reconciling the views of spherification at small and large scales, the present study lays the groundwork for the rational design of innovative cooking techniques relevant to avant-garde cuisine.

Extended Adaptive Biasing Force Algorithm. An On-the-Fly Implementation for Accurate Free-Energy Calculations

Proper use of the adaptive biasing force (ABF) algorithm in free-energy calculations needs certain prerequisites to be met, namely, that the Jacobian for the metric transformation and its first derivative be available and the coarse variables be independent and fully decoupled from any holonomic constraint or geometric restraint, thereby limiting singularly the field of application of the approach. The extended ABF (eABF) algorithm circumvents these intrinsic limitations by applying the time-dependent bias onto a fictitious particle coupled to the coarse variable of interest by means of a stiff spring. However, with the current implementation of eABF in the popular molecular dynamics engine NAMD, a trajectory-based post-treatment is necessary to derive the underlying free-energy change. Usually, such a posthoc analysis leads to a decrease in the reliability of the free-energy estimates due to the inevitable loss of information, as well as to a drop in efficiency, which stems from substantial read-write accesses to file systems. We have developed a user-friendly, on-the-fly code for performing eABF simulations within NAMD. In the present contribution, this code is probed in eight illustrative examples. The performance of the algorithm is compared with traditional ABF, on the one hand, and the original eABF implementation combined with a posthoc analysis, on the other hand. Our results indicate that the on-the-fly eABF algorithm (i) supplies the correct free-energy landscape in those critical cases where the coarse variables at play are coupled to either each other or to geometric restraints or holonomic constraints, (ii) greatly improves the reliability of the free-energy change, compared to the outcome of a posthoc analysis, and (iii) represents a negligible additional computational effort compared to regular ABF. Moreover, in the proposed implementation, guidelines for choosing two parameters of the eABF algorithm, namely the stiffness of the spring and the mass of the fictitious particles, are proposed. The present on-the-fly eABF implementation can be viewed as the second generation of the ABF algorithm, expected to be widely utilized in the theoretical investigation of recognition and association phenomena relevant to physics, chemistry, and biology.

New Coarse Variables for the Accurate Determination of Standard Binding Free Energies

To improve sampling of the configurational entropy change upon protein-ligand binding, we have introduced a new set of coarse variables describing the relative orientation and position of the ligand via a global macromolecular orientational procedure, onto which geometrical restraints are applied. Evaluating the potential of mean force for the different coarse variables, the experimental standard binding free energy for three decapeptides associated with the SH3 domain of the Abl kinase is reproduced quantitatively.

The Extended Generalized Adaptive Biasing Force Algorithm for Multidimensional Free-Energy Calculations

Free-energy calculations in multiple dimensions constitute a challenging problem, owing to the significant computational cost incurred to achieve ergodic sampling. The generalized adaptive biasing force (gABF) algorithm calculates n one-dimensional lists of biasing forces to approximate the n-dimensional matrix by ignoring the coupling terms ordinarily taken into account in classical ABF simulations, thereby greatly accelerating sampling in the multidimensional space. This approximation may however occasionally lead to poor, incomplete exploration of the conformational space compared to classical ABF, especially when the selected coarse variables are strongly coupled. It has been found that introducing extended potentials coupled to the coarse variables of interest can virtually eliminate this shortcoming, and, thus, improve the efficiency of gABF simulations. In the present contribution, we propose a new free-energy method, coined extended generalized ABF (egABF), combining gABF with an extended Lagrangian strategy. The results for three illustrative examples indicate that (i) egABF can explore the transition coordinate much more efficiently compared with classical ABF, eABF, and gABF, in both simple and complex cases and (ii) egABF can achieve a higher accuracy than gABF, with a root mean-squared deviation between egABF and eABF free-energy profiles on the order of kBT. Furthermore, the new egABF algorithm outruns the previous ABF-based algorithms in high-dimensional free-energy calculations and, hence, represents a powerful importance-sampling alternative for the investigation of complex chemical and biological processes.

Pretreating cellulases with hydrophobins for improving bioconversion of cellulose: an experimental and computational study

Lignocellulosic biomass sugars bring benefits to both the economy and the environment, but their application is limited by their high process cost. In the present contribution, the class II hydrophobin (HFBII) was first reported to be used as an additive to pretreat cellulases prior to hydrolysis, leading to a remarkable improvement of the biodegradation of corn stover and microcrystalline cellulose. 2 mg g−1 HFBII resulted in 37.1% and 55.4% conversion of the substrates, increased by 32.5% and 40.6%, respectively, compared with the control. In particular, HFBII was shown to have a better effect than polyethylene glycol 6000 on the conversion of corn stover, increasing the degradation by 24.5%. 73.1% enzymatic activity was retained after 48 h, whereas the control was 65.3%. Furthermore, the binding of HFBII to cellulase was investigated by molecular dynamics simulations and free-energy calculations. The tunnel-forming loops of the cellulase exhibit a high binding affinity for HFBII. In the formed complex, about 70% hydrophobic patches of the HFBII were found to be exposed, which could compete with the cellulase for hydrophobic adsorption sites of lignin residues. The decrease of the adsorption between the latter two would benefit the enzymatic hydrolysis. Structural analysis indicates that the flexibility of enzymatic tunnel loops was significantly enhanced, and the active area was enlarged, thereby promoting the enzymatic activity. The experimental results and the underlying mechanism provided herein are envisioned to help understand the potential application of HFBII in the practical green hydrolysis of cellulose by reducing the enzyme load.

Why do the structural properties of complexes formed by glucans and carbon nanotubes differ so much

In supramolecular wrapping chemistry, polysaccharides are widely used as wrapping agents for the dissolution, dispersion and functionalization of carbon nanotubes. It is, therefore, of paramount importance to understand the effect of the topology – specifically the linkage – of the polymer chain on its spatial arrangement around the hollow tubular structure, and, hence, on the configuration and the nature of the supramolecular complex. To this end, the β-1,4, α-1,4 and β-1,3-glucans were chosen to wrap a single-walled carbon nanotube (SWCNT) as three prototypical assemblies. Molecular simulations reveal that α-1,4-glucan has the ability to wrap SWCNTs very tightly, whereas β-1,3-glucans can only form irregular helices. The calculated binding affinity of the polysaccharide to the tubular surface follows the order α-1,4 > β-1,4 > β-1,3-glucan. The differences between the three hybrids can be generally described in terms of the inherent propensity of glucans to fold into helices, the hydrophobic interaction of the polysaccharide with the SWCNT, and the formation of intramolecular hydrogen bonds within the polymer chain. The wrapping mode of the glucan chain is mainly determined by its inherent helicity. The hydrophobic interaction is the driving force for helical wrapping. Moreover, the intramolecular hydrogen-bonding interaction can stabilize ideal, compact helical scaffolds. These factors determine the conformation and the binding affinity of the polysaccharide to the SWCNT. The present results can be generalized to other polymers like DNA, and shed new light on the universal principles that underlie the formation of supramolecular complexes using wrapping agents.

Zooming across the Free-Energy Landscape: Shaving Barriers, and Flooding Valleys

A robust importance-sampling algorithm for mapping free-energy surfaces over geometrical variables, coined meta-eABF, is introduced. This algorithm shaves the free-energy barriers and floods valleys by incorporating a history-dependent potential term in the extended adaptive biasing force (eABF) framework. Numerical applications on both toy models and nontrivial examples indicate that meta-eABF explores the free-energy surface significantly faster than either eABF or metadynamics (MtD) alone, without the need to stratify the reaction pathway. In some favorable cases, meta-eABF can be as much as five times faster than other importance-sampling algorithms. Many of the shortcomings inherent to eABF and MtD, like kinetic trapping in regions of configurational space already adequately sampled, the requirement of prior knowledge of the free-energy landscape to set up the simulation, are readily eliminated in meta-eABF. Meta-eABF, therefore, represents an appealing solution for a broad range of applications, especially when both eABF and MtD fail to achieve the desired result.

BFEE: A User-Friendly Graphical Interface Facilitating Absolute Binding Free-Energy Calculations

Quantifying protein-ligand binding has attracted the attention of both theorists and experimentalists for decades. Many methods for estimating binding free energies in silico have been reported in recent years. Proper use of the proposed strategies requires, however, adequate knowledge of the protein-ligand complex, the mathematical background for deriving the underlying theory, and time for setting up the simulations, bookkeeping, and postprocessing. Here, to minimize human intervention, we propose a toolkit aimed at facilitating the accurate estimation of standard binding free energies using a geometrical route, coined the binding free-energy estimator (BFEE), and introduced it as a plug-in of the popular visualization program VMD. Benefitting from recent developments in new collective variables, BFEE can be used to generate the simulation input files, based solely on the structure of the complex. Once the simulations are completed, BFEE can also be utilized to perform the post-treatment of the free-energy calculations, allowing the absolute binding free energy to be estimated directly from the one-dimensional potentials of mean force in simulation outputs. The minimal amount of human intervention required during the whole process combined with the ergonomic graphical interface makes BFEE a very effective and practical tool for the end-user.

ELF: An Extended-Lagrangian Free-Energy Calculation Module for Multiple Molecular Dynamics Engines

Extended adaptive biasing force (eABF), a collective variable (CV)-based importance-sampling algorithm, has proven to be very robust and efficient compared with the original ABF algorithm. Its implementation in Colvars, a software addition to molecular dynamics (MD) engines, is, however, currently limited to NAMD and LAMMPS. To broaden the scope of eABF and its variants, like its generalized form (egABF), and make them available to other MD engines, e.g., GROMACS, AMBER, CP2K, and openMM, we present a PLUMED-based implementation, called extended-Lagrangian free energy calculation (ELF). This implementation can be used as a stand-alone gradient estimator for other CV-based sampling algorithms, such as temperature-accelerated MD (TAMD) and extended-Lagrangian metadynamics (MtD). ELF provides the end user with a convenient framework to help select the best-suited importance-sampling algorithm for a given application without any commitment to a particular MD engine.