Abstract
Protein dynamics has been investigated since almost half a century, as it is believed to constitute the fundamental connection between structure and function. Elastic network models (ENMs) have been widely used to predict protein dynamics, flexibility and the biological mechanism, from which remarkable results have been found regarding the prediction of protein conformational changes. Starting from the knowledge of the reference structure only, these conformational changes have been usually predicted either by looking at the individual mode shapes of vibrations (i.e., by considering the free vibrations of the ENM) or by applying static perturbations to the protein network (i.e., by considering a linear response theory). In this paper, we put together the two previous approaches and evaluate the complete protein response under the application of dynamic perturbations. Harmonic forces with random directions are applied to the protein ENM, which are meant to simulate the single frequency-dependent components of the collisions of the surrounding particles, and the protein response is computed by solving the dynamic equations in the underdamped regime, where mass, viscous damping and elastic stiffness contributions are explicitly taken into account. The obtained motion is investigated both in the coordinate space and in the sub-space of principal components (PCs). The results show that the application of perturbations in the low-frequency range is able to drive the protein conformational change, leading to remarkably high values of direction similarity. Eventually, this suggests that protein conformational change might be triggered by external collisions and favored by the inherent low-frequency dynamics of the protein structure.
Highlights
Proteins affect virtually every biological process occurring in the human body [1].Their correct functioning is pivotal for a variety of tasks, such as delivery of nutrients throughout and across cells, recognition and neutralization of pathogenic bacteria and viruses, providing of suitable strength and rigidity to tissues, activation of signaling pathways and catalytic reactions, etc. [2]
The anisotropic network model (ANM) treats the protein structure as a network of atoms connected by Hookean connections, which are meant to simulate the interatomic interactions in a simplified manner
Free-vibration modal analysis is run first, in order to obtain the theoretical B-factors from Equation (6) and the value of the spring constant γ, which is found to be equal to 0.10 N/m (~0.15 kcal/molÅ2 )
Summary
Proteins affect virtually every biological process occurring in the human body [1].Their correct functioning is pivotal for a variety of tasks, such as delivery of nutrients throughout and across cells, recognition and neutralization of pathogenic bacteria and viruses, providing of suitable strength and rigidity to tissues, activation of signaling pathways and catalytic reactions, etc. [2]. Proteins affect virtually every biological process occurring in the human body [1] Their correct functioning is pivotal for a variety of tasks, such as delivery of nutrients throughout and across cells, recognition and neutralization of pathogenic bacteria and viruses, providing of suitable strength and rigidity to tissues, activation of signaling pathways and catalytic reactions, etc. All these activities are performed within the physiological environment and in a highly dynamic fashion This explains why so much research has been carried out in the last decades regarding protein dynamics and its relationship with the biological functionality. Despite the high potential of MD simulations, its applicability to large peptide chains and protein complexes, especially for the investigation of the large-scale slow dynamics, remains quite elusive and requires cautious analysis of the results
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