This review provides an overview of animal models for the evaluation, comparison, and systematic optimization of tissue engineering and regenerative medicine strategies related to bone tissue. This review includes an overview of major factors that influence the rational design and selection of an animal model. A comparison is provided of the 10 mammalian species that are most commonly used in bone research, and existing guidelines and standards are discussed. This review also identifies gaps in the availability of animal models: (1) the need for assessment of the predictive value of preclinical models for relative clinical efficacy, (2) the need for models that more effectively mimic the wound healing environment and mass transport conditions in the most challenging clinical settings (e.g., bone repair involving large bone and soft tissue defects and sites of prior surgery), and (3) the need for models that allow more effective measurement and detection of cell trafficking events and ultimate cell fate during the processes of bone modeling, remodeling, and regeneration. The ongoing need for both continued innovation and refinement in animal model systems, and the need and value of more effective standardization are reinforced.

Implants invoke inflammatory responses from the body even if they are chemically inert and nontoxic. It has been shown that a crucial precedent event in the inflammatory process is the spontaneous adsorption of fibrinogen (Fg) on implant surfaces, which is typically followed by the presence of phagocytic cells. Interactions between the phagocyte integrin Mac-1 and two short sequences within the fibrinogen gamma chain, gamma190-202 and gamma377-395, may partially explain phagocyte accumulation at implant surfaces. These two sequences are believed to form an integrin binding site that is inaccessible when Fg is in its soluble-state structure but then becomes available for Mac-1 binding following adsorption, presumably due to adsorption-induced conformational changes. The objective of this research was to theoretically investigate this possibility by using molecular dynamics simulations of the gamma-chain fragment of Fg over self-assembled monolayer (SAM) surfaces presenting different types of surface chemistry. The GROMACS software package was used to carry out the molecular simulations in an explicit solvation environment over a 5 ns period of time. The adsorption of the gamma-chain of fibrinogen was simulated on five types of SAM surfaces. The simulations showed that this protein fragment exhibits distinctly different adsorption behavior on the different surface chemistries. Although the trajectory files showed that significant conformational changes did not occur in this protein fragment over the time frame of the simulations, it was predicted that the protein does undergo substantial rotational and translational motions over the surface prior to stabilizing in various preferred orientations. This suggests that the kinetics of surface-induced conformational changes in a protein's structure might be much slower than the kinetics of orientational changes, thus enabling the principles of adsorption thermodynamics to be used to guide adsorbing proteins into defined orientations on surfaces before large conformational changes can occur. This finding may be very important for biomaterial surface design as it suggests that surface chemistry can potentially be used to directly control the orientation of adsorbing proteins in a manner that either presents or hides specific bioactive sites contained within a protein's structure, thereby providing a mechanism to control cellular responses to the adsorbed protein layer.

Proteins, which are bioactive molecules, adsorb on implants placed in the body through complex and poorly understood mechanisms and directly influence biocompatibility. Molecular dynamics modeling using empirical force fields provides one of the most direct methods of theoretically analyzing the behavior of complex molecular systems and is well-suited for the simulation of protein adsorption behavior. To accurately simulate protein adsorption behavior, a force field must correctly represent the thermodynamic driving forces that govern peptide residue-surface interactions. However, since existing force fields were developed without specific consideration of protein-surface interactions, they may not accurately represent this type of molecular behavior. To address this concern, we developed a host-guest peptide adsorption model in the form of a G(4)-X-G(4) peptide (G is glycine, X is a variable residue) to enable determination of the contributions to adsorption free energy of different X residues when adsorbed to functionalized Au-alkanethiol self-assembled monolayers (SAMs). We have previously reported experimental results using surface plasmon resonance (SPR) spectroscopy to measure the free energy of peptide adsorption for this peptide model with X = G and K (lysine) on OH and COOH functionalized SAMs. The objectives of the present research were the development and assessment of methods to calculate adsorption free energy using molecular dynamics simulations with the GROMACS force field for these same peptide adsorption systems, with an oligoethylene oxide (OEG) functionalized SAM surface also being considered. By comparing simulation results to the experimental results, the accuracy of the selected force field to represent the behavior of these molecular systems can be evaluated. From our simulations, the G(4)-G-G(4) and G(4)-K-G(4) peptides showed minimal to no adsorption to the OH SAM surfaces and the G(4)-K-G(4) showed strong adsorption to the COOH SAM surface, which is in agreement with our SPR experiments. Contrary to our experimental results, however, the simulations predicted a relatively strong adsorption of G(4)-G-G(4) peptide to the COOH SAM surface. In addition, both peptides were unexpectedly predicted to adsorb to the OEG surface. These findings demonstrate the need for GROMACS force field parameters to be rebalanced for the simulation of peptide adsorption behavior on SAM surfaces. The developed methods provide a direct means of assessing, modifying, and validating force field performance for the simulation of peptide and protein adsorption to surfaces, without which little confidence can be placed in the simulation results that are generated with these types of systems.

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