A research team led by Washington State University professor Hanu Pappu has used artificial intelligence (AI) to predict a handful of likely proteins that a virus could attack in plants.
Researchers predicting which protein a virus will attempt to hijack can help in building a defense against the attack. But plants make thousands of proteins, making this kind of prediction very difficult. At least for humans.
Pappu and his team tested AI software on cotton plants, since scientists are familiar with that plant’s proteins. They went from thousands of possible proteins down to two likely targets for the virus that causes cotton leaf curl disease.
They then tested those likely targets and validated one of the plant protein, which plays a critical role in plant metabolism, as one that the virus attacks.
Finding the targeted proteins is the first step in a new way to fight viral attacks. Once these targets are found, it is possible to intervene and restrict the virus from hijacking the plant proteins. This approach has potential application to other crops including fruit trees, potatoes, and grapes.
“The field of computational biology has great potential for unraveling these complex plant-virus interactions,” Pappu said. “What we learned would enable us to devise new ways to interfere and even prevent this hijacking by viruses and eventually make plants resistant to viruses.”
Pappu worked with molecular virologist Imran Amin at the National Institute for Biotechnology and Genetic Engineering in Pakistan;
Fayyaz Minhas, a computer scientist at the (PIEAS) Pakistan Institute of Engineering and Applied Sciences; and with Amin’s PhD Student Hira Kamal, who worked in professor Hanu lab.