Medical Research

University of Virginia

Michael Wiener, Lei Wang, Ken Dill
Charlottesville, VA
December 2018

Structural biology is a critical component of modern biomedical research.  Multiple experimental techniques, primarily X-ray crystallography and cryo-electron microscopy (which has recently advanced remarkably), can yield macromolecular structure at atomic- or near-atomic resolution.  The current structural biology paradigm is that high information content samples, yielding large amounts of data per sample, are used to solve the structure.  However, obtaining such high information content samples, particularly for more complicated systems such as protein complexes, membrane proteins, or transient conformational states of macromolecules, is often very risky, with concomitantly large amounts of time, money, and effort required to maximize the likelihood of success.  An investigator at the University of Virginia, in collaboration with investigators at the University of California, San Francisco and Stony Brook University, proposes an alternative structural biology paradigm: multiple low information content samples, yielding small amounts of data per sample, are used to solve the structure.  This alternative structural biology paradigm will be actualized via development of a new integrated experimental/computational approach, Serial Solution Scattering Structure Determination (S4D). S4D will utilize atomic pairwise distances obtained by solution X-ray scattering from protein samples containing electron-dense “R-group” labels incorporated by in vitro chemical or in vivo unnatural amino acid incorporation methods.  These pairwise distances will be utilized by the “sparse constraint” Bayesian structure determination program termed Modeling Employing Limited Data (MELD).  The culmination of this approach would permit facile macromolecular structure determination in vitro and in vivo.  Success with this “alternative paradigm” for structural biology would enable true high-throughput structure determination that better keeps pace with the increasingly rapid acquisition of genomic and proteomic data.

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