Associate Professor Daniel Schmidt

This group invents and applies protein engineering technologies to study fundamental functional principles of natural and artificial living systems at a cellular level. They are seeking mechanistic explanations for how cells sense, integrate, and exchange information, how pathologic changes in these processes relate to health and disease, and provide insights into new therapies. They answer these questions by inventing methods to observe, delineate, and precisely control cellular physiology. Their approach employs techniques from multiple disciplines including optogenetics, electrophysiology, rational protein design, and, most recently, molecular dynamics.

Inward Rectifier K⁺ channels (K_IR) play key roles in the operation of cells in neuromuscular and other tissue. Pathogenic variants are linked to numerous neurological, cardiovascular, and metabolic disorders. Although some variants cause gating defects in K_IR by altering ligand regulation or ion permeation, there is growing evidence that many - perhaps most - variants cause defects in folding and trafficking of K_IR. Despite the central role for folding and trafficking in the disease etiology, there have been to date no comprehensive large-scale studies that determine sequence and structural determinants of K_IR trafficking and functional robustness. Without these data, quantitative models of sequence, structure, and function relationship in K_IR cannot be built. It is not possible to understand the mechanistic basis for clinically observed K_IR missense mutation or predict their pathogenicity. Identifying new treatment strategies for K_IR channelopathies that cause folding and trafficking defects, such as molecular chaperones, is harder in the absence of these data.

These researchers previously established Saturated Programmable Insertion Engineering (SPINE) and Domain Insertion Profiling as scalable approaches to study ion channel structure and function. These technological innovations now allow them to conduct comprehensive, massively parallel phenotyping of K_IR at both the single amino acid and topological level. The group makes heavy use of NextGen sequencing, machine learning, and molecular dynamics simulation, all of which make use of MSI resources. Completion of this project will give the group the ability to obtain an unprecedented depth of information about molecular determinants of channel trafficking and function. It will provide a rich resource of information to understand K_IR mutations in human disease. This will also enable engineering of new tools for studying K⁺ channel function in intact tissues.