Enzyme Conformation Influences the Performance of Lipase‐powered Nanomotors

Abstract

Enzyme‐powered micro/nanomotors have myriads of potential applications in various areas. To efficiently reach those applications, it is necessary and critical to understand the fundamental aspects affecting the motion dynamics. Herein, we explored the impact of enzyme orientation on the performance of lipase‐powered nanomotors by tuning the lipase immobilization strategies. The influence of the lipase orientation and lid conformation on substrate binding and catalysis was analyzed using molecular dynamics simulations. Besides, the motion performance indicates that the hydrophobic binding (via OTES) represents the best orienting strategy, providing 48.4 % and 95.4 % increase in diffusion coefficient compared to hydrophilic binding (via APTES) and Brownian motion (no fuel), respectively (with C[triacetin] of 100 mm). This work provides vital evidence for the importance of immobilization strategy and corresponding enzyme orientation for the catalytic activity and in turn, the motion performance of nanomotors, and is thus helpful to future applications.

Conformational Landscapes of Halohydrin Dehalogenases and Their Accessible Active Site Tunnels

“…This enables the reconstruction of the enzyme conformation landscape and assess how this is shifted by ligand binding, sequence differences between protein family members, and/or the introduction of mutations in the enzyme active site or at distal positions [7,26]. Recovery of time-dependent dynamical descriptors, such as volume cavities, solvent-accessible surface area, or changes in internal tunnels/channels is also possible by post-processing the highly dimensional MD datasets [4,27]. Particularly useful is the application of dimensionality reduction techniques for automatically identifying key enzymatic states from MD simulations and account for as much information as possible.…”

“…Combinations of linear and non-linear methods have also been proposed to take advantage of both approximations, with the time-lagged t-Distributed Stochastic Neighbor Embedding (t-SNE) [33] as a clear example [34]. In this direction, we have previously developed a computational protocol based on the combination of the linear time-Independent Component Analysis (tICA) [35] and t-SNE [33] for elucidating the conformational ensemble of Candida rugosa lipase and its accessible tunnels for substrate binding to the active site [27].…”

Biohybrid robotics: From the nanoscale to the macroscale

“…It was found that high catalytic activity was crucial for efficient motion and that conformational dynamics were required for certain biocatalyzes to take place (Figure 4d). On this topic, the orientation of the enzyme when immobilized to a particle's surface was found to play a key role in its motility, demonstrating that hydrophobic adsorption of lipase in nanomotors led to the most efficient catalytic process (L. Wang et al, 2020).…”

A Practical Guide to Analyzing and Reporting the Movement of Nanoscale Swimmers

“…To prevent this misinterpretation, the original tracking data must be drift-corrected (see description and methods introduced above). A straightforward way to check whether drift has been successfully corrected is to plot the corrected trajectories of a few nanoswimmers within the same frame, and see if they diffuse independently (see ref 63,67 for good examples) or all in the same direction. The above principles and operations are illustrated in Fig.…”