Andrew J. Rader
Assistant Professor

Email Dr. Rader

Education

B.S. Physics and Mathematics (Honors), University of Houston, Houston, TX, 1996
M.S. Physics Michigan State University, East Lansing, MI, 1998
Ph.D. Physics and Biochemistry, Michigan State University, East Lansing, MI, 2002

Research

My research involves building a deeper understanding of the nature of elementary processes in biological systems from their inherent physical properties. Employing network representations of the molecular structures of such systems, allows one to calculate putative motions and simulate the dynamics of proteins and nucleotides. The functions of these molecules depend upon their structure-inspired motions and dynamics. Investigation of such mesoscopic systems requires adopting a range of detailed and coarse-grained models to capture the essential features of interest.

The fact that protein structures reliably fold into defined 3D structures poses an interesting and challenging problem. Simulations of thermal denaturation using theoretical models have suggested clues about this process. By synthesizing vast amounts of molecular data, one project seeks to not only generate statistically weighed ensembles of unfolding pathways, but also identify the coherent patterns among these pathways. Such insight can then be implemented in biomedical applications such as rational drug design, protein engineering, and homology modeling.

These computationally efficient methods are well-suited for investigation of large-scale and long-range interactions in biomolecules and their complexes. Understanding the mechanism governing allostery, cooperative motions, and signal transduction within enzymes is one area of interest. Another project centers on extending these network methods to elucidate the assembly, large-scale motions, and biological functions of biomolecules and very large supramolecular complexes including virus capsids, the ribosome and the nuclear pore comples among others. This project involves the development of hierarchical network methods to span multiple scales ranging from the subnanometer to micrometer and from the picosecond to millisecond. Such work has applications for improved analysis of experimental techniques such as cryo-EM and can lead to a structurally-based understanding of biological systems.

Publications