- Utilizing AI to Design a Novel Peptide Antidote for Snake Venom

Recent advances in artificial intelligence (AI) and machine learning (ML) have enabled the design of tailor-made proteins. By utilizing co-evolutionary and structural data, these algorithms can aid researchers in crafting specific binders to target proteins.

In our laboratory, we have successfully designed a novel peptide antidote that targets a key snake venom component. Snake venom has an enzymatic activity responsible for blood hemolysis, and the newly designed antidote was able to significantly weaken or inhibit its toxic effects.

A research team from the University of Jordan, led by Dr. Tareq Alhindi, Associate Professor in the Department of Life Sciences at the Faculty of Science, in collaboration with Dr. Randa Al-Badawi from Al-Balqa Applied University, has discovered and decoded the genetic makeup of a new species of rhizosphere bacteria. Experiments have shown that this bacterium can help wheat plants grow under high salinity conditions and increase productivity in saline environments in Jordan. The newly discovered species has been named Pseudomonas jordanii strain G34.

It has been found that this bacterial strain can produce several plant growth-promoting substances and can enable wheat plants to resist certain fungal pathogens, such as Fusarium rot.

The team has completed a full genetic sequence analysis of the bacterium, identifying multiple genes associated with promoting plant growth under saline stress. This data has been uploaded to the global NCBI database. The team is currently continuing research on new bacterial strains isolated from Jordanian environments to understand mechanisms of plant resistance to salinity and pests, with the goal of eventually developing eco-friendly organic fertilizers and pesticides.