Gevorg Grigoryan

Gevorg Grigoryan, PhD, is a co-founder and chief technical officer at Generate Biomedicines. He is also an associate professor of computer science, an adjunct associate professor of biological sciences, and an adjunct associate professor of chemistry at Dartmouth College.

He received two bachelor’s degrees, in computer science and biochemistry, and went on to do a PhD at the Massachusetts Institute of Technology, where he studied computational protein design and modeling of protein interactions. He did postdoctoral work at the University of Pennsylvania, which he completed in 2011. Then Gevorg was appointed to the faculty at Dartmouth, where he obtained tenure in 2017.

Gevorg’s work has been multidisciplinary from the start, combining elements of biology, computer science, chemistry, math, and physics. This reflects his approach to science: he is driven by the scientific problem at hand and comfortable crossing disciplinary boundaries as needed to obtain satisfactory solutions. As a PhD student, Gevorg addressed the long-standing challenge of accounting for specificity in protein design calculations, offering a solution inspired by statistical mechanics that introduced the notion and the computational power of sequence-based structure-derived models. He went on to develop several novel technologies that enabled multiple firsts in the field of protein design: an artificial de novo designed transmembrane transporter, peptides engineered to self-assemble on surfaces of nanotubes and graphene, and engineered proteins that co-assemble with C60 fullerene into an electrically conducting crystal.

In his academic work at Dartmouth he continues to innovate in the field of protein design and modeling, developing methods that bring the rigor of statistical physics into computational protein engineering and designing targeted proteins for biotherapeutic applications. Recently, Gevorg has focused on understanding the relationship between amino acid sequence and structure by taking advantage of the fact that the protein structural universe is highly degenerate—that is, composed of reused three-dimensional building blocks. The simple but powerful principle of modularity enables data-driven synthesis of principles governing protein folding, interaction, and function. This pioneering work has produced an entirely new paradigm with which to think about modeling and designing proteins.

Gevorg has authored over 50 peer-reviewed papers, and his work has received awards and recognition from the Alfred P. Sloan Foundation, the National Institutes of Health, the National Science Foundation, and the American Cancer Society.