An interdisciplinary team of Rutgers researchers led by Professor Sagar Khare has been awarded the NSF Molecular Foundations of Biotechnology grant in the amount of $1.5 million over 3 years. The NSF typically awards only 6 such "high-risk high-reward" grants in a year aimed at "fundamentally new approaches in molecular sciences to drive new directions in biotechnology". This year the theme was "synergistic scientific research collaborations that involve innovative machine learning (ML) methods to foster advances in research on the function of biomolecular systems and have the potential to drive innovation in biotechnology.” (https://beta.nsf.gov/funding/opportunities/molecular-foundations-biotechnology-mfb). The Interdisciplinary team includes co-PIs Jean Baum (CCB), Adam Gormley (BME), Sijian Wang (Statistics) and Guillaume Lamoureux (Rutgers Camden).
The team has proposed to lay the foundations of a novel protein “editing" technology that, if successful, would allow targeting and modifying a single protein from among the thousands in a cell in a highly precise manner. Such precise and on-demand targeting would enable many applications in biomedical research. A key aspect of their approach is a close interplay between machine learning model development and experiments in the “wet” lab where proteins designed using machine learning are tested using high-throughput and robotics-enabled experiments. These experiments and the determined structures of the proteins are then used to further train the machine learning model to make better predictions in iterative design-build-test-learn cycles.