In order to develop synthetic muscles for applications in regenerative medicine or robotics, scientists must understand which combination of myosin produces each desired action. This would require a labor-intensive process of nanoscale trial and error that could take years in the laboratory.

Researchers at have taken a multidisciplinary approach to solving this problem. By coupling computational design search methods with biomechanical fundamentals, they created a formal approach for designing myosin systems with specific properties.

The team developed a new computational model that designs systems where multiple myosin types operate together and demonstrates the benefits over different single types of myosin. Laboratory experiments then confirmed the computational predictions.

These findings, which represent a unique collaboration between engineering disciplines, could further impact future applications for understanding and treating myosin-related diseases and developing new approaches for motor molecule-based technologies.