Cryo-EM as it is now practiced in many laboratories is limited to the visualization of molecules that are in thermal equilibrium at the time before freezing. A further limitation is that existing software does not fully exploit the information that is contained in images of large ensembles of molecules in thermal equilibrium. This book is a collection of recent articles by the author, reprinted with introductions, and they mainly describe two novel methods in cryo-EM, one computational and the other experimental requiring the use of a microfluidic device. Both methods have the capacity to shed light on the dynamic behavior of biomolecules. Combined, they greatly expand the range of applications of cryo-EM.
The book describes a successful approach in which, based on cryo-EM data, all states visited by the molecule in thermal equilibrium are mapped by manifold embedding—a method of geometric machine learning—and the energy landscape of the molecule is derived. It also discusses methods and biological results of time-resolved cryo-EM, following a reaction in a non-equilibrium system over a short period of time and resulting in the capture of short-lived states that have been inaccessible by standard methods of cryo-EM.
Key Features:
- Experimental determination of free-energy landscape of a molecule
- Short-lived states during a defined reaction visualized, without the need for chemical intervention
- Both methods can be implemented in all labs practicing cryo-EM of biomolecules
- Original articles and reviews based on research in the author’s lab
- Currently the only book in the literature covering these subjects
