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Intervertebral disc (IVD) degeneration is a frequent disease in modern societies and at its later stages is likely to cause chronic low back pain. Although many studies have been published, the available treatments for IVD degeneration fail to promote regeneration or even marginal repair of the IVD structure. In this study, we aimed to establish veterinary canine patients as a translational large animal model that recapitulates IVD degeneration that occurs in humans, and to investigate the suitability of intradiscal application of mesenchymal stromal cells (MSC). Twenty client-owned dogs diagnosed with spontaneous degenerative lumbosacral IVD and low back pain were included in the study. Autologous MSC were isolated from bone marrow and cultured for 2 weeks. Prior to injection, MSC were attached on collagen microcarriers for delivery, with or without TGF-β1 crosslinking. After decompressive spinal surgery, dogs received an intradiscal injection of MSC-microcarriers ( n = 11), MSC-TGF-β1-microcarriers ( n = 6) or microcarriers only (control, n = 3). MSC-microcarriers were initially evaluated in vitro and ex vivo, to test cell chondrogenic potential and biomechanical properties of the microcarriers, respectively. Clinical performance and Pfirrmann grading were evaluated at 10 months after the injection by magnetic resonance imaging. MSC differentiated successfully in vitro towards chondrogenic phenotype and biomechanical tests showed no significant differences of IVD stiffness after microcarrier injection. In vivo injection was successful in all dogs, without any visible leakage, and clinical functioning was restored back to normality. However, postoperative Pfirrmann grade remained identical in all dogs, and formation of Schmorl's nodes was detected in 45% of dogs. This side effect was reduced by halving the injection volume, which was then observed only in 11% of dogs. In conclusion, we observed marked clinical improvement in all groups, despite the formation of Schmorl's nodes, but microcarriers and MSC failed to regenerate the structure of degenerated IVD.

Insufficient primary stability of screws in bone leads to screw loosening and failure. Unlike conventional continuum finite-element models, micro-CT based finite-element analysis (micro-FE) is capable of capturing the patient-specific bone micro-architecture, providing accurate estimates of bone stiffness. However, such in silico models for screws in bone highly overestimate the apparent stiffness. We hypothesized that a more accurate prediction of primary implant stability of screws in bone is possible by considering insertion-related bone damage. We assessed two different screw types and loading scenarios in 20 trabecular bone specimens extracted from 12 cadaveric human femoral heads (N = 5 for each case). In the micro-FE model, we predicted specimen-specific Young's moduli of the peri-implant bone damage region based on morphometric parameters such that the apparent stiffness of each in silico model matched the experimentally measured stiffness of the corresponding in vitro specimen as closely as possible. The standard micro-FE models assuming perfectly intact peri-implant bone overestimated the stiffness by over 330%. The consideration of insertion related damaged peri-implant bone corrected the mean absolute percentage error down to 11.4% for both loading scenarios and screw types. Cross-validation revealed a mean absolute percentage error of 14.2%. We present the validation of a novel micro-FE modeling technique to quantify the apparent stiffness of screws in trabecular bone. While the standard micro-FE model overestimated the bone-implant stiffness, the consideration of insertion-related bone damage was crucial for an accurate stiffness prediction. This approach provides an important step toward more accurate specimen-specific micro-FE models. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:2415-2424, 2017., (© 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.)

A virtual organisation approach was applied to collaborative drug discovery integrating experimental and computational design approaches. Scientists Against Malaria was formed with the goal of designing novel antimalarial drug candidates. The collaboration of nine founding partners carried out computational and laboratory work that produced significant volumes of data and metadata, the interpretation for the analysis of which, as well as the related decision making, was challenging. During the first phase the partners developed this 'green-field' project from initiation through to target selection and modelling, computational screening, biological materials and assay preparation, culminating in the completion of initial experimental testing. A support infrastructure involving a semantic collaborative laboratory framework, interoperating with a cloud of web services through an ontology describing the virtual and experimental screening data, was designed and tested., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Escherichia coli β-galactosidase is probably the most widely used reporter enzyme in molecular biology, cell biology, and biotechnology because of the easy detection of its activity. Its large size and tetrameric structure make this bacterial protein an interesting model for crystallographic studies and atomic mapping. In the present study, we investigate a version of Escherichia coli β-galactosidase produced under oxidizing conditions, in the cytoplasm of an Origami strain. Our data prove the activation of this microbial enzyme under oxidizing conditions and clearly show the occurrence of a disulfide bond in the β-galactosidase structure. Additionally, the formation of this disulfide bond is supported by the analysis of a homology model of the protein that indicates that two cysteines located in the vicinity of the catalytic center are sufficiently close for disulfide bond formation.

The possibility of estimating equilibrium free-energy profiles from multiple non-equilibrium simulations using the fluctuation-dissipation theory or the relation proposed by Jarzynski has attracted much attention. Although the Jarzynski estimator has poor convergence properties for simulations far from equilibrium, corrections have been derived for cases in which the work is Gaussian distributed. Here, we examine the utility of corrections proposed by Gore and collaborators using a simple dissipative system as a test case. The system consists of a single methane-like particle in explicit water. The Jarzynski equality is used to estimate the change in free energy associated with pulling the methane particle a distance of 3.9 nm at rates ranging from ~0.1 to 100 m s(-1). It is shown that although the corrections proposed by Gore and collaborators have excellent numerical performance, the profiles still converge slowly. Even when the corrections are applied in an ideal case where the work distribution is necessarily Gaussian, performing simulations under quasi-equilibrium conditions is still most efficient. Furthermore, it is shown that even for a single methane molecule in water, pulling rates as low as 1 m s(-1) can be problematic. The implications of this finding for studies in which small molecules or even large biomolecules are pulled through inhomogeneous environments at similar pulling rates are discussed.

We present an interdisciplinary approach that, by incorporating a range of experimental and computational techniques, allows the identification and characterization of functional/immunogenic domains. This approach has been applied to ArtJ, an arginine-binding protein whose orthologs in Chlamydiae trachomatis (CT ArtJ) and pneumoniae (CPn ArtJ) are shown to have different immunogenic properties despite a high sequence similarity (60% identity). We have solved the crystallographic structures of CT ArtJ and CPn ArtJ, which are found to display a type II transporter fold organized in two α-β domains with the arginine-binding region at their interface. Although ArtJ is considered to belong to the periplasm, we found that both domains contain regions exposed on the bacterial surface. Moreover, we show that recombinant ArtJ binds to epithelial cells in vitro, suggesting a role for ArtJ in host-cell adhesion during Chlamydia infection. Experimental epitope mapping and computational analysis of physicochemical determinants of antibody recognition revealed that immunogenic epitopes reside mainly in the terminal (D1) domain of both CPn and CT ArtJ, whereas the surface properties of the respective binding-prone regions appear sufficiently different to assume divergent immunogenic behavior. Neutralization assays revealed that sera raised against CPn ArtJ D1 partially reduce both CPn and CT infectivity in vitro, suggesting that functional antibodies directed against this domain may potentially impair chlamydial infectivity. These findings suggest that the approach presented here, combining functional and structure-based analyses of evolutionary-related antigens can be a valuable tool for the identification of cross-species immunogenic epitopes for vaccine development.

Mapping the conformational space of a polypeptide onto a network of conformational states involves a number of subjective choices, mostly in relation to the definition of conformation and its discrete nature in a network framework. Here, we evaluate the robustness of the topology of conformational-space networks derived from Molecular Dynamics (MD) simulations with respect to the use of different discretization (clustering) methods, variation of their parameters, simulation length and analysis time-step, and removing high-frequency motions from the coordinate trajectories. In addition, we investigate the extent to which polypeptide dynamics can be reproduced on the resulting networks when assuming Markovian behavior. The analysis is based on eight 500 ns and eight 400 ns MD simulations in explicit water of two 10-residue peptides. Three clustering algorithms were used, two of them based on the pair-wise root-mean-square difference between structures and one on dihedral-angle patterns. A short characteristic path length and a power-law behavior of the probability distribution of the node degree are obtained irrespective of the clustering method or the value of any of the tested parameters. The average cliquishness is consistently one or two orders of magnitude larger than that of a random realization of a network of corresponding size and connectivity. The cliquishness as function of node degree and the kinetic properties of the networks are found to be most dependent on clustering method and/or parameters. Although Markovian simulations on the networks reproduce cluster populations accurately, their kinetic properties most often differ from those observed in the MD simulations., (Copyright 2010 Wiley Periodicals, Inc.)

Limited searching in the conformational space is one of the major obstacles for investigating protein dynamics by numerical approaches. For this reason, classical all-atom molecular dynamics (MD) simulations of proteins tend to be confined to local energy minima, particularly when the bulk solvent is treated explicitly. To overcome this problem, we have developed a novel replica exchange protocol that uses modified force-field parameters to treat interparticle nonbonded potentials within the protein and between protein and solvent atoms, leaving unperturbed those relative to solvent-solvent interactions. We have tested the new protocol on the 18-residue-long tip of the P domain of calreticulin in an explicit solvent. With only eight replicas, we have been able to considerably enhance the conformational space sampled during a 100 ns simulation, compared to as many parallel classical molecular dynamics simulations of the same length or to a single one lasting 450 ns. A direct comparison between the various simulations has been possible thanks to the implementation of the weighted histogram analysis method, by which conformations simulated with modified force-field parameters can be assigned different weights. Interatom, inter-residue distances in the structural ensembles obtained with our novel replica exchange approach and by classical MD simulations compare equally well with those derived from NMR data. Rare events, such as unfolding and refolding, occur with reasonable statistical frequency. Visiting of conformations characterized by very small Boltzmann weights is also possible. Despite their low probability, such regions of the conformational space may play an important role in the search for local potential-energy minima and in dynamically controlled functions.