Protein Tertiary Structure - Research

Research

The majority of protein structures known to date have been solved with the experimental technique of X-ray crystallography, which typically provides data of high resolution but provides no time-dependent information on the protein's conformational flexibility. A second common way of solving protein structures uses NMR, which provides somewhat lower-resolution data in general and is limited to relatively small proteins, but can provide time-dependent information about the motion of a protein in solution. Dual polarisation interferometry is a time resolved analytical method for determining the overall conformation and conformational changes in surface captured proteins providing complementary information to these high resolution methods. More is known about the tertiary structural features of soluble globular proteins than about membrane proteins because the latter class is extremely difficult to study using these methods.

Stanford University's Folding@home project is a distributed computing research effort which uses its approximately 5 petaFLOPS (~10 x86 petaFLOPS) of computing power to attempt to model the tertiary (and quaternary) structures of proteins, as well as other aspects of how and why proteins fold into the inordinately complex and varied shapes they take. No currently existing algorithm is yet able to consistently predict a proteins' tertiary or quaternary structure given only its primary structure; learning how to accurately predict the tertiary and quaternary structure of any protein given only its amino acid sequence and the pertinent cellular conditions would be a monumental achievement. The calculations performed by the algorithms are constantly evolving, increasing in complexity and nuance, and involve enormous numbers of variables. These techniques are superficially comparable to weather models that show hurricane storm tracks; each of several algorithms independently models a complex system (the weather, in this case) somewhat differently from each of its sister weather algorithms, and the average of all the algorithms' output is taken to be the most likely "storm track". The shape of proteins can be elucidated through a somewhat similar process.

Researchers are also interested in proteins that can fold into more than one stable configuration; protein aggregation diseases such as Alzheimer's Disease and Huntington's Disease as well as prion diseases such as Mad Cow disease can be better understood by constructing (and deconstructing) disease models; the most common way of doing this is by developing a way of inducing the desired disease state in test animals (administering MPTP to give the animals Parkinson's disease, or knocking out a gene essential for the prevention of certain tumors from the animals' genomes). The Folding@home project and other projects like it are now allowing for the modelling of such disease states not easily induced and without the need for test animals. Perhaps more importantly, fully human proteins encoded by fully human genes can be used without any of the ethical problems that arise in studying living human beings. They are quickly becoming indispensable tools among researchers from a broad variety of disciplines.