Machine learning may enable bioengineering of the most abundant enzyme on the planet

A Newcastle University study has for the first time shown that machine learning can predict the biological properties of the most abundant enzyme on Earth – Rubisco.

Rubisco (Ribulose-1,5-bisphosphate carboxylase/oxygenase) is responsible for providing carbon for almost all life on Earth. Rubisco functions by converting atmospheric CO2 from the Earth's atmosphere to organic carbon matter, which is essential to sustain most life on Earth.

For some time now, natural variation has been observed among Rubisco proteins of land plants and modeling studies have shown that transplanting Rubisco proteins with certain functional properties can increase the amount of atmospheric CO2 crop plants can uptake and store.

Study lead author, Wasim Iqbal, a Ph.D. researcher at Newcastle University's School of Natural and Environmental Sciences, part of Dr. Maxim Kapralov's group, developed a machine learning tool which can predict the performance properties of numerous land plant Rubisco proteins with surprisingly good accuracy. The hope is that this tool will enable the hunt for a 'supercharged' Rubisco protein that can be bioengineered into major crops such as wheat.

Image source: Pixabay/CC0 Public Domain.