Research for A.J. Rader -- especially FIRST

I am interested in developing a deeper understanding of the nature of elementary processes in biological systems. Synthesizing the immense amount of molecular information generated in the current genomic era into a coherent and useful body of knowledge requires finding patterns and establishing rules to describe the behavior of the underlying molecules forming these biosystems. The application of physical principles through computer simulations of these systems allows these biomolecules to be viewed as nanomachines whose functions are related to their structures. In order to accomplish these simulations, I have been using several network-based models of protein structures. The first of these (A) is a residue-level elastic network used for simplified normal mode analysis using GNM or ANM and the second (B) is an all-atom constraint network used for rigidity analysis using FIRST.


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	My research using the above network models of proteins has suggested that the network of intra-protein contacts contains information critical for reproducible folding. Comparison with experimental data including H-D exchange data, mutations, and F-value analysis confirms this hypothesis. The next challenge is use this information in conjunction with other data to predict and refine three-dimensional structures of proteins.
Universal unfolding of proteins		Folding core in bovine rhodopsin
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Even when a static structure is well known, a more complete understanding of biological function requires elucidating the structure’s likely biomolecular dynamics. In cases where structural knowledge of a given protein is incomplete, application of structural preferences deduced from the protein folding studies mentioned above will provide better structural models that can then be used as a starting point for exploring potential motions. Although biological functions can often be inferred for one molecule from a homologous one, the precise steps describing such processes require more detailed analysis. Using the elastic network method sketch above, a few global modes are able to characterize biologically relevant motions. For example, in ribosome, the ratcheting associated with translation is captured and in the HK97 bacteriophage virus capsid, maturation from prohead to mature form is observed.

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Presently there is a large disparity between what can be measured experimentally and simulated computationally. Due to the wide range of time and length scales observed in biological processes (Table 1), no single method is able to capture all motions and functions. Bridging the gap between experiments and simulations for these time scales requires the development of a new computational framework which embeds atomic-level detail into a hierarchy of various coarse-grained networks. The dynamics for a particular type of motion can then be deduced by analysis of the corresponding network.

Table 1. Characteristic time scales for biological dynamics
Type of motion	Example dynamics	Time scale	Amplitude
Atomic	Fluctuations	fs - ps	< 1 Å
Multi-atomic	Side chain rotations	10 ps - ns	1 - 5 Å
Submolecular	Conformational changes	ns - ms	5 -10 Å
Molecular	Folding, assembly	ms - s	1 -10 nm
Multimolecular	Reactions, binding	ms - min	10 nm - mm
Subcellular	Diffusion, transport	ms - hr	mm - mm
Cellular	Respiration	s - hr	> mm

*Past and present* research collaborators
who	project(s)
Dr. Ivet Bahar post-doctoral advisor	supramolecular & protein dynamics, flexibility & folding, GNM
Dr. Mike Thorpe PhD advisor (physics)	FIRST, protein folding, flexibility, & thermostability, rigidity percolation
Dr. Leslie Kuhn PhD advisor (biochem)	FIRST, protein folding, flexibility, & thermostability, rigidity percolation
Dr. Don Jacobs	FIRST, protein flexibility, rigidity percolation
Dr. Brandon Hespenheide	FIRST, protein folding & flexibility
Dr. Ming Lei	ROCK (protein dynamics)
Dr. Mykyta Chubynsky	rigidity percolation
Dr. Maria Zavodszky	ROCK (protein dynamics)
Dr. Claire Vieille	protein thermostability
Dr. Judith Klein-Seetharaman	rhodopsin folding & dynamics
Dr. Robert Jernigan	ribosome dynamics & flexibility
Dr. Yongmei Wang	ribosome dynamics & flexibility
Dr. Daniel Vlad	HK97 viral capsid dynamics
Basak Isin	rhodopsin folding & dynamics
Alpay Temiz	protein folding
Lee-wei Yang	protein dynamics, iGNM


Protein Folding Cores	Biomolecular Dynamics	Multi-scale Modeling	Protein Flexibility & Rigidity	List of Collaborators	List of Publications

Research Interests