Antibodies have been increasingly used as pharmaceuticals in clinical treatment. Thermal stability and unfolding process are important properties that must be considered in antibody design. In this paper, the structure-encoded dynamical properties and the unfolding process of the Fab fragment of the phosphocholine-binding antibody McPC603 are investigated by use of the normal mode analysis of Gaussian network model (GNM). Firstly, the temperature factors for the residues of the protein were calculated with GNM and then compared with the experimental measurements. A good result was obtained, which provides the validity for the use of GNM to study the dynamical properties of the protein. Then, with this approach, the mean-square fluctuation (MSF) of the residues, as well as the MSF in the internal distance (MSFID) between all pairwise residues, was calculated to investigate the mobility and flexibility of the protein, respectively. It is found that the mobility and flexibility of the constant regions are higher than those of the variable regions, and the six complementarity-determining regions (CDRs) in the variable regions also exhibit relative large mobility and flexibility. The large amplitude motions of the CDRs are considered to be associated with the immune function of the antibody. In addition, the unfolding process of the protein was simulated by iterative use of the GNM. In our method, only the topology of protein native structure is taken into account, and the protein unfolding process is simulated through breaking the native contacts one by one according to the MSFID values between the residues. It is found that the flexible regions tend to unfold earlier. The sequence of the unfolding events obtained by our method is consistent with the hydrogen-deuterium exchange experimental results. Our studies imply that the unfolding behavior of the Fab fragment of antibody McPc603 is largely determined by the intrinsic dynamics of the protein.

BtuCD–BtuF from Escherichia coli is a binding protein-dependent adenosine triphosphate (ATP)-binding cassette (ABC) transporter system that uses the energy of ATP hydrolysis to transmit vitamin B12 across cellular membranes. Experimental studies have showed that during the transport cycle, the transporter undergoes conformational transitions between the “inward-facing” and “outward-facing” states, which results in the open–closed motions of the cytoplasmic gate of the transport channel. The opening–closing of the channel gate play critical roles for the function of the transporter, which enables the substrate vitamin B12 to be translocated into the cell. In the present work, the extent of opening of the cytoplasmic gate was chosen as a function-related internal coordinate. Then the mean-square fluctuation of the internal coordinate, as well as the cross-correlation between the displacement of the internal coordinate and the movement of each residue in the protein, were calculated based on the normal mode analysis of the elastic network model to analyze the function-related motions encoded in the structure of the system. In addition, the key residues important for the functional motions of the transporter were predicted by using a perturbation method. In order to facilitate the calculations, the internal coordinate was introduced as one of the axes of the coordinate space and the conventional Cartesian coordinate space was transformed into the internal/Cartesian space with linear approximation. All the calculations were carried out in this internal/Cartesian space. Our method can successfully identify the functional motions and key residues for the transporter BtuCD–BtuF, which are well consistent with the experimental observations.

Fluid shear stress (FSS) plays a crucial role for cell migration within bone cavities filled with interstitial fluid. Whether the local wall FSS distribution on cell surface depends on the global gradient FSS of flow field should be clarified to explain our previous experimental observation. In this study, finite element models of discretely distributed or hexagonal closely packed cells adherent on the bottom plate in a modified plate flow chamber with different global FSS gradient were constructed. Fluid-solid coupling simulation of wall fluid shear stress on cells was performed, and two types of data analysis methods were used. The results showed that the profile of local FSS distribution on cell surface coincides with the angle of cell migration determined in the previous study, suggesting that RAW264.7 osteoclast precursors may sense the global FSS gradient and migrate toward the low-FSS region under a high gradient. For hexagonal closely packed cells, this profile on the surface of central cells decreased along with the increase of cell spacing, which may be caused by the higher local FSS difference along the direction of FSS gradient in the regions close to the bottom plate. This study may explain the phenomenon of the targeted migration of osteoclast precursors under gradient FSS field and further provide insights into the mechanism of mechanical stimulation-induced bone remodeling.

During mechanical stimulation-induced bone remodeling, interstitial fluid around microcracks may produce a flow field with gradient fluid shear stress (FSS). Osteoclast precursors can sense this gradient FSS and migrate toward the low FSS region. However, the local distribution of wall FSS on bone cells under a flow field with globally gradient FSS remains unknown. In this study, finite element models of a modified plate flow chamber with cells were constructed. The effect of oscillatory flow with different FSS levels and cell spacings or frequencies on the distribution of local wall FSS around cells was simulated by using a fluid–solid coupling method. Results showed that the polarization of wall FSS distribution in a cell decreased with the increase in cell spacing. At a low FSS level, the frequency of oscillatory flow had a minimal effect on the wall FSS distribution. At a high FSS level, the increase in flow frequency enhanced the fluctuation of local wall FSS distribution on cells. These results provide a basis for future research on the flow-induced migration of osteoclast precursors and clarify the mechanism of mechanical stimulation-induced bone resorption.

The drop landing (DL) process is a complex neuromuscular control process influenced by multiple factors, among which fatigue state and landing height play significant roles. This study aimed to investigate the influence mechanisms of these two factors on lower-limb landing strategies and to examine the feasibility of explainable machine learning methods in analyzing landing strategies. Joint angles and joint moments of the hip, knee, and ankle in the sagittal plane, as well as vertical ground reaction force (vGRF), were collected under different landing conditions (40 cm and 80 cm heights and their corresponding fatigue states). Cohen’s d effect size analysis was applied to examine group differences in each feature across the time series, and seven classification models were constructed based on multi-dimensional biomechanical features to identify different landing states. Meanwhile, SHapley Additive exPlanations (SHAP) method was employed to analyze feature importance and interactions. Results showed that the Light Gradient Boosting Machine achieved classification accuracies above 0.915 across all four tasks, verifying the feasibility of machine learning methods for landing strategy analysis. Temporal effect size analysis revealed that differences induced by changes in landing height were mainly concentrated in the early landing phase (0%–40%). In contrast, the fatigue effect resulted in a wider distribution and higher magnitude of regions with large effect sizes. SHAP analysis indicated that the knee joint moment had the highest importance across all classification tasks, vGRF contributed prominently in fatigue-related tasks, and feature interaction patterns differed significantly across tasks. In conclusion, explainable machine learning methods can effectively identify and explain differences in DL strategies under various landing conditions, providing a theoretical basis and methodological support for sports injury risk assessment and training strategy optimization.