Designing a miniature microscale engine that can override the role of thermal fluctuations has remained elusive and is an important open challenge. Here, we provide the design and theoretical framework for a unique information-based engine—a work-to-work converter—comprising a submicron-sized bead and motor protein microtubule (MT) complex in an optical trap setup. We demonstrate how, by implementing a simple motor protein state-dependent feedback protocol of the optical trap stiffness, this engine is able to harness and convert the movement of a motor protein into work output. Unlike other conventional microengines, the fidelity and performance of this engine are determined by the stochasticity of motor (un)binding characteristics. We obtain an analytical form of the work distribution function, average work output, and average power output, providing quantitative predictions for engine performance which are validated by stochastic simulations. Remarkably, the average work output per cycle is at least an order of magnitude higher than the thermal fluctuations and supersedes the performance of other microscale engines realized so far.

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• Biomolecular & subcellular processes
• Biomolecular dynamics
• Brownian motion
• Stochastic processes
• Stochastic thermodynamics
• Heat engines
• Kinesin
• Microtubules
• Motor proteins
• Langevin equation
• Optical tweezers