Smart Biomechanical Adaptation Revealed by the Structure of Ostrich Limb Bones.

Ostriches are known to be the fastest bipedal animal alive; to accomplish such an achievement, their anatomy evolved to sustain the stresses imposed by running at such velocities. Ostriches represent an excellent case study due to the fact that their locomotor kinematics have been extensively studied for their running capabilities. The shape and structure of ostrich bones are also known to be optimized to sustain the stresses imposed by the body mass and accelerations to which the bones are subjected during movements. This study focuses on the limb bones, investigating the structure of the bones as well as the material properties, and how both the structure and material evolved to maximise the performance while minimising the stresses applied to the bones themselves. The femoral shaft is hollowed and it presents an imbricate structure of fused bone ridges connected to the walls of the marrow cavity, while the tibial shaft is subdivided into regions having different mechanical characteristics. These adaptations indicate the optimization of both the structure and the material to bear the stresses. The regionalization of the material highlighted by the mechanical tests represents the capability of the bone to adapt to external stimuli during the life of an individual, optimizing not only the structure of the bone but the material itself.

Wordom update 2: A user-friendly program for the analysis of molecular structures and conformational ensembles.

We present the second update of Wordom, a user-friendly and efficient program for manipulation and analysis of conformational ensembles from molecular simulations. The actual update expands some of the existing modules and adds 21 new modules to the update 1 published in 2011. The new adds can be divided into three sets that: 1) analyze atomic fluctuations and structural communication; 2) explore ion-channel conformational dynamics and ionic translocation; and 3) compute geometrical indices of structural deformation. Set 1 serves to compute correlations of motions, find geometrically stable domains, identify a dynamically invariant core, find changes in domain-domain separation and mutual orientation, perform wavelet analysis of large-scale simulations, process the output of principal component analysis of atomic fluctuations, perform functional mode analysis, infer regions of mechanical rigidity, analyze overall fluctuations, and perform the perturbation response scanning. Set 2 includes modules specific for ion channels, which serve to monitor the pore radius as well as water or ion fluxes, and measure functional collective motions like receptor twisting or tilting angles. Finally, set 3 includes tools to monitor structural deformations by computing angles, perimeter, area, volume, ß-sheet curvature, radial distribution function, and center of mass. The ring perception module is also included, helpful to monitor supramolecular self-assemblies. This update places Wordom among the most suitable, complete, user-friendly, and efficient software for the analysis of biomolecular simulations. The source code of Wordom and the relative documentation are available under the GNU general public license at http://wordom.sf.net.

A Computational Framework for Determining the Breadth of Antibodies Against Highly Mutable Pathogens.

Highly mutable pathogens pose daunting challenges for antibody design. The usual criteria of high potency and specificity are often insufficient to design antibodies that provide long-lasting protection. This is due, in part, to the ability of the pathogen to rapidly acquire mutations that permit them to evade the designed antibodies. To overcome these limitations, design of antibodies with a larger neutralizing breadth can be pursued. Such broadly neutralizing antibodies (bnAbs) should remain targeted to a specific epitope, yet show robustness against pathogen mutability, thereby neutralizing a higher number of antigens. This is particularly important for highly mutable pathogens, like the influenza virus and the human immunodeficiency virus (HIV). The protocol describes a method for computing the "breadth" of a given antibody, an essential aspect of antibody design.

Multibody analysis and soft tissue strength refute supersonic dinosaur tail.

Sauropod dinosaurs are well known for their massive sizes and long necks and tails. Among sauropods, flagellicaudatan dinosaurs are characterized by extreme tail elongation, which has led to hypotheses regarding tail function, often compared to a whip. Here, we analyse the dynamics of motion of a 3D model of an apatosaurine flagellicaudatan tail using multibody simulation and quantify the stress-bearing capabilities of the associated soft tissues. Such an elongated and slender structure would allow achieving tip velocities in the order of 30 m/s, or 100 km/h, far slower than the speed of sound, due to the combined effect of friction of the musculature and articulations, as well as aerodynamic drag. The material properties of the skin, tendons, and ligaments also support such evidence, proving that in life, the tail would not have withstood the stresses imposed by travelling at the speed of sound, irrespective of the conjectural 'popper', a hypothetical soft tissue structure analogue to the terminal portion of a bullwhip able to surpass the speed of sound.

On the Rapid Calculation of Binding Affinities for Antigen and Antibody Design and Affinity Maturation Simulations.

The accurate and efficient calculation of protein-protein binding affinities is an essential component in antibody and antigen design and optimization, and in computer modeling of antibody affinity maturation. Such calculations remain challenging despite advances in computer hardware and algorithms, primarily because proteins are flexible molecules, and thus, require explicit or implicit incorporation of multiple conformational states into the computational procedure. The astronomical size of the amino acid sequence space further compounds the challenge by requiring predictions to be computed within a short time so that many sequence variants can be tested. In this study, we compare three classes of methods for antibody/antigen (Ab/Ag) binding affinity calculations: (i) a method that relies on the physical separation of the Ab/Ag complex in equilibrium molecular dynamics (MD) simulations, (ii) a collection of 18 scoring functions that act on an ensemble of structures created using homology modeling software, and (iii) methods based on the molecular mechanics-generalized Born surface area (MM-GBSA) energy decomposition, in which the individual contributions of the energy terms are scaled to optimize agreement with the experiment. When applied to a set of 49 antibody mutations in two Ab/HIV gp120 complexes, all of the methods are found to have modest accuracy, with the highest Pearson correlations reaching about 0.6. In particular, the most computationally intensive method, i.e., MD simulation, did not outperform several scoring functions. The optimized energy decomposition methods provided marginally higher accuracy, but at the expense of requiring experimental data for parametrization. Within each method class, we examined the effect of the number of independent computational replicates, i.e., modeled structures or reinitialized MD simulations, on the prediction accuracy. We suggest using about ten modeled structures for scoring methods, and about five simulation replicates for MD simulations as a rule of thumb for obtaining reasonable convergence. We anticipate that our study will be a useful resource for practitioners working to incorporate binding affinity calculations within their protein design and optimization process.

ppdx: Automated modeling of protein-protein interaction descriptors for use with machine learning.

This paper describes ppdx, a python workflow tool that combines protein sequence alignment, homology modeling, and structural refinement, to compute a broad array of descriptors for characterizing protein-protein interactions. The descriptors can be used to predict various properties of interest, such as protein-protein binding affinities, or inhibitory concentrations (IC50 ), using approaches that range from simple regression to more complex machine learning models. The software is highly modular. It supports different protocols for generating structures, and 95 descriptors can be currently computed. More protocols and descriptors can be easily added. The implementation is highly parallel and can fully exploit the available cores in a single workstation, or multiple nodes on a supercomputer, allowing many systems to be analyzed simultaneously. As an illustrative application, ppdx is used to parametrize a model that predicts the IC50 of a set of antigens and a class of antibodies directed to the influenza hemagglutinin stalk.

Multiscale affinity maturation simulations to elicit broadly neutralizing antibodies against HIV.

The design of vaccines against highly mutable pathogens, such as HIV and influenza, requires a detailed understanding of how the adaptive immune system responds to encountering multiple variant antigens (Ags). Here, we describe a multiscale model of B cell receptor (BCR) affinity maturation that employs actual BCR nucleotide sequences and treats BCR/Ag interactions in atomistic detail. We apply the model to simulate the maturation of a broadly neutralizing Ab (bnAb) against HIV. Starting from a germline precursor sequence of the VRC01 anti-HIV Ab, we simulate BCR evolution in response to different vaccination protocols and different Ags, which were previously designed by us. The simulation results provide qualitative guidelines for future vaccine design and reveal unique insights into bnAb evolution against the CD4 binding site of HIV. Our model makes possible direct comparisons of simulated BCR populations with results of deep sequencing data, which will be explored in future applications.

Persulfurated Benzene-Cored Asterisks with π-Extended ThioNaphthyl Arms: Synthesis, Structural, Photophysical and Covalent Dynamic Properties.

The synthesis of regioisomeric asterisks (5) and (6) incorporating a benzene core with six 1-naphthylthio or six 2-naphthylthio arms are reported in search for new materials with optoelectronic properties. The consequences on the extension of a π system surrounding a persulfurated benzene core provide a new avenue to study the structural, photophysical, and chemical properties of such family of all-organic phosphors. It also diverts the persulfuration mechanism after two radical cyclizations for making a [5]dithiohelicene by-product (7) and favors dynamic sulfur component exchange reactions surrounding the core. These exchanges convert asterisks (5) and (6), non-phosphorescent at 20 °C to the highly phosphorescent (4) (ϕ ∼100 %, solid state at 20 °C). For asterisks (5) and (6), the absence of the typical phosphorescence of the per(phenylthio)benzene core in the solid state at 20 °C and the presence of a weak naphthalene-based phosphorescence at 77 K is attributed to an energy transfer from the triplet state of the persulfurated benzene core to the outer naphthalene moieties, resulting in an antenna system.

Design of immunogens to elicit broadly neutralizing antibodies against HIV targeting the CD4 binding site.

A vaccine which is effective against the HIV virus is considered to be the best solution to the ongoing global HIV/AIDS epidemic. In the past thirty years, numerous attempts to develop an effective vaccine have been made with little or no success, due, in large part, to the high mutability of the virus. More recent studies showed that a vaccine able to elicit broadly neutralizing antibodies (bnAbs), that is, antibodies that can neutralize a high fraction of global virus variants, has promise to protect against HIV. Such a vaccine has been proposed to involve at least three separate stages: First, activate the appropriate precursor B cells; second, shepherd affinity maturation along pathways toward bnAbs; and, third, polish the Ab response to bind with high affinity to diverse HIV envelopes (Env). This final stage may require immunization with a mixture of Envs. In this paper, we set up a framework based on theory and modeling to design optimal panels of antigens to use in such a mixture. The designed antigens are characterized experimentally and are shown to be stable and to be recognized by known HIV antibodies.

A restrained locally enhanced sampling method (RLES) for finding free energy minima in complex systems.

We present an extension of the locally enhanced sampling method. A restraint potential is introduced to drive the many-replica system to the canonical ensemble corresponding to the physical, single-replica system. Convergence properties are demonstrated using a model rugged two-dimensional potential, for which sampling by conventional equilibrium molecular dynamics is inefficient. Restrained locally enhanced sampling (RLES) is found to explore the space of configurations with an efficiency comparable to that of temperature replica exchange. To demonstrate the potential of RLES for realistic applications, the method is used to fold the 12-residue tryptophan zipper miniprotein in explicit solvent. The RLES algorithm can be incorporated into existing LES implementations with minor code modifications.

Microsecond Molecular Dynamics Simulations of Proteins Using a Quasi-Equilibrium Solvation Shell Model.

We describe the development and implementation of a quasi-equilibrium hydration shell model of biomolecular solvation with adaptive boundaries. Applying the model to microsecond-long molecular dynamics simulations of several protein systems of varying complexity, we find that the model simulation results are of comparable quality to those obtained from simulations of fully solvated systems, but at a reduced computational cost. We discuss the dominant sources of error in the model and outline directions for future improvements.

Estimation of the breadth of CD4bs targeting HIV antibodies by molecular modeling and machine learning.

HIV is a highly mutable virus for which all attempts to develop a vaccine have been unsuccessful. Nevertheless, few long-infected patients develop antibodies, called broadly neutralizing antibodies (bnAbs), that have a high breadth and can neutralize multiple variants of the virus. This suggests that a universal HIV vaccine should be possible. A measure of the efficacy of a HIV vaccine is the neutralization breadth of the antibodies it generates. The breadth is defined as the fraction of viruses in the Seaman panel that are neutralized by the antibody. Experimentally the neutralization ability is measured as the half maximal inhibitory concentration of the antibody (IC50). To avoid such time-consuming experimental measurements, we developed a computational approach to estimate the IC50 and use it to determine the antibody breadth. Given that no direct method exists for calculating IC50 values, we resort to a combination of atomistic modeling and machine learning. For each antibody/virus complex, an all-atoms model is built using the amino acid sequence and a known structure of a related complex. Then a series of descriptors are derived from the atomistic models, and these are used to train a Multi-Layer Perceptron (an Artificial Neural Network) to predict the value of the IC50 (by regression), or if the antibody binds or not to the virus (by classification). The neural networks are trained by use of experimental IC50 values collected in the CATNAP database. The computed breadths obtained by regression and classification are reported and the importance of having some related information in the data set for obtaining accurate predictions is analyzed. This approach is expected to prove useful for the design of HIV bnAbs, where the computation of the potency must be accompanied by a computation of the breadth, and for evaluating the efficiency of potential vaccination schemes developed through modeling and simulation.

Modeling the adsorption equilibrium of small-molecule gases on graphene: effect of the volume to surface ratio.

In most technological applications involving liquids or gases interacting with solids, the first event is the adsorption of molecules onto a solid surface. Here, we focus on the theoretical understanding of adsorption equilibrium at the solid-gas interface. In the limit of physisorption, we find that adsorption probability is independent of the initial concentration of monomers, whereas it varies with the available volume to surface ratio, which depends on the experimental setup. This theoretical finding is verified numerically by molecular dynamics simulations of five small-molecule gases physisorbing on graphene. The simulations provide quantitative estimates of the adsorption free energy, which are used to benchmark analytical and numerical integrations of the corresponding partition functions. The significance of the above theoretical result is analyzed in the context of molecular self-assembly at surfaces and interfaces. Our interpretation indicates that there exist (at least) two distinct pathways for 2D self-assembly, which may or may not involve the formation of a 2D disordered intermediate. Also, it predicts that the critical concentration for self-assembly may be shifted by varying the aspect ratio of the experimental setup.

Predicting molecular self-assembly at surfaces: a statistical thermodynamics and modeling approach.

Molecular self-assembly at surfaces and interfaces is a prominent example of self-organization of matter with outstanding technological applications. The ability to predict the equilibrium structure of a self-assembled monolayer (SAM) is of fundamental importance and would boost the development of bottom-up strategies in a number of fields. Here, we present a self-consistent theory for a first-principles interpretation of 2D self-assembly based on modeling and statistical thermodynamics. Our development extends the treatment from finite-size to infinite supramolecular objects and delineates a general framework in which previous approaches can be recovered as particular cases. By proving the existence of a chemical potential per unit cell, we derive an expression for the surface free energy of the SAM (γ), which provides access to the thermodynamic stability of the monolayer in the limit of the ideal gas approximation and the model of energetics in use. Further manipulations of this result provide another expression of γ, which makes the concentration dependence as well as the temperature dependence of 2D self-assembly explicit. In the limit of the approximations above, this second result was used to analyze competitive equilibria at surfaces and rationalize the concentration- and temperature-dependent polymorphism in 2D. Finally, the theory predicts that there exists a critical aggregation concentration (Ccac) of monomers above which 2D self-assembly can be viewed as a "precipitation" in a solubility equilibrium. Numerical analysis of thirteen model SAMs on graphene shows that the value of Ccac sets an absolute scale of 2D self-assembly propensity, which is useful to compare chemically distinct and apparently unrelated self-assembly reactions.

Perchlorination of Coronene Enhances its Propensity for Self-Assembly on Graphene.

Providing a quantitative understanding of the thermodynamics involved in molecular adsorption and self-assembly at a nanostructured carbon material is of fundamental importance and finds outstanding applications in the graphene era. Here, we study the effect of edge perchlorination of coronene, which is a prototypical polyaromatic hydrocarbon, on the binding affinity for the basal planes of graphite. First, by comparing the desorption barrier of hydrogenated versus perchlorinated coronene measured by temperature-programmed desorption, we quantify the enhancement of the strength of physisorption at the single-molecule level though chlorine substitution. Then, by a thermodynamic analysis of the corresponding monolayers based on force-field calculations and statistical mechanics, we show that perchlorination decreases the free energy of self-assembly, not only enthalpically (by enhancing the strength of surface binding), but also entropically (by decreasing the surface concentration). The functional advantage of a chemically modulated 2D self-assembly is demonstrated in the context of the molecule-assisted liquid-phase exfoliation of graphite into graphene.

Surface-induced selection during in†situ photoswitching at the solid/liquid interface.

Here we report for the first time a submolecularly resolved scanning tunneling microscopy (STM) study at the solid/liquid interface of the in situ reversible interconversion between two isomers of a diarylethene photoswitch, that is, open and closed form, self-assembled on a graphite surface. Prolonged irradiation with UV light led to the in situ irreversible formation of another isomer as by-product of the reaction, which due to its preferential physisorption accumulates at the surface. By making use of a simple yet powerful thermodynamic model we provide a quantitative description for the observed surface-induced selection of one isomeric form.

A supramolecular strategy to leverage the liquid-phase exfoliation of graphene in the presence of surfactants: unraveling the role of the length of fatty acids.

Achieving the full control over the production as well as processability of high-quality graphene represents a major challenge with potential interest in the field of fabrication of multifunctional devices. The outstanding effort dedicated to tackle this challenge in the last decade revealed that certain organic molecules are capable of leveraging the exfoliation of graphite with different efficiencies. Here, a fundamental understanding on a straightforward supramolecular approach for producing homogenous dispersions of unfunctionalized and non-oxidized graphene nanosheets in four different solvents is attained, namely N-methyl-2-pyrrolidinone, N,N-dimethylformamide, ortho-dichlorobenzene, and 1,2,4-trichlorobenzene. In particular, a comparative study on the liquid-phase exfoliation of graphene in the presence of linear alkanes of different lengths terminated by a carboxylic-acid head group is performed. These molecules act as graphene dispersion-stabilizing agents during the exfoliation process. The efficiency of the exfoliation in terms of concentration of exfoliated graphene is found to be proportional to the length of the employed fatty acid. Importantly, a high percentage of single-layer graphene flakes is revealed by high-resolution transmission electron microscopy and Raman spectroscopy analyses. A simple yet effective thermodynamic model is developed to interpret the chain-length dependence of the exfoliation yield. This approach relying on the synergistic effect of a ad-hoc solvent and molecules to promote the exfoliation of graphene in liquid media represents a promising and modular strategy towards the rational design of improved dispersion-stabilizing agents.

Enterobacteriaceae and pseudomonadaceae on the dorsum of the human tongue.

OBJECTIVE: The aim of this study was to correlate the presence of Enterobacteriaceae, Pseudomonadaceae, Moraxellaceae and Xanthomonadaceae on the posterior dorsum of the human tongue with the presence of tongue coating, gender, age, smoking habit and denture use. MATERIAL AND METHODS: Bacteria were isolated from the posterior tongue dorsum of 100 individuals in MacConkey agar medium and were identified by the API 20E system (Biolab-Mérieux). RESULTS: 43% of the individuals, presented the target microorganisms on the tongue dorsum, with greater prevalence among individuals between 40 and 50 years of age (p = 0.001) and non-smokers (p=0.0485). CONCLUSIONS: A higher prevalence of Enterobacteriaceae and Pseudomonadaceae was observed on the tongue dorsum of the individuals evaluated. There was no correlation between these species and the presence and thickness of tongue coating, gender and presence of dentures.

Enterobacteriaceae and pseudomonadaceae on the dorsum of the human tongue

OBJECTIVE: The aim of this study was to correlate the presence of Enterobacteriaceae, Pseudomonadaceae, Moraxellaceae and Xanthomonadaceae on the posterior dorsum of the human tongue with the presence of tongue coating, gender, age, smoking habit and denture use. MATERIAL AND METHODS: Bacteria were isolated from the posterior tongue dorsum of 100 individuals in MacConkey agar medium and were identified by the API 20E system (Biolab-Mérieux). RESULTS: 43 percent of the individuals, presented the target microorganisms on the tongue dorsum, with greater prevalence among individuals between 40 and 50 years of age (p = 0.001) and non-smokers (p=0.0485). CONCLUSIONS: A higher prevalence of Enterobacteriaceae and Pseudomonadaceae was observed on the tongue dorsum of the individuals evaluated. There was no correlation between these species and the presence and thickness of tongue coating, gender and presence of dentures.