Dr. Irina Kufareva

Mammalian cells process information via a vast network of dynamic, context-dependent molecular interactions to maintain homeostasis, respond to the outside cues, and make cell fate decisions. Breakdowns in intracellular communication invariably accompany diseases, while therapeutic agents selectively target nodes in the communication network to bring it back to a balanced state. Our research seeks understanding of cellular information processing from computational, structural, and network biology perspectives, starting from ligand binding to surface receptors and extending all the way to cellular morphogenesis. We develop approaches for accurate computational prediction of transient interactions of proteins and chemicals with conformationally variable protein interfaces, and apply these approaches to important cell signaling targets. This is complemented by experimental work aimed at interface mapping, target characterization, structure determination, and identification of bioactive molecules. Furthermore, inspired by the philosophy of "understanding-by-building", and in order to bridge the gap between molecular level and cellular level phenomena, we develop system-level computational models of cell signaling downstream of selected targets. Much of our work is focused on G protein coupled receptors (e.g. chemokine receptors and SMO) because of their promise as therapeutic targets in inflammatory diseases and cancer. We also study GEMs, a novel family of non-canonical signaling molecules that link heterotrimeric G protein signaling to non-GPCR receptors.