Structural Biochemistry/Proteins/Continuous Theory of Protein Structure
Recently, the traditional view of the protein universe as a set of discrete secondary structures has been challenged by the proliferation of a complementary theory describing continuous protein structuring. This new theory does not replace or supersede the idea of a discrete protein universe, but is complementary to it, allowing for a wider range of observed phenomena to be explained. The relationship between a discreet and a continuous protein universe is similar in nature to the relationship between the particle theory and wave theory of electromagnetic radiation (light). Just as light is best described as both a particle and a wave, the protein universe can be best described as being discreet and continuous. The combination of these two views is known as the dual view. The following is a discussion of the two single views and their application, as well as the advantages of considering the dual view.
The discrete view of the protein universe was first established via x-ray crystallography. Upon the structural elucidation of myoglobin and hemoglobin, these two proteins were found to be very similar, despite their dissimilarity in primary structure. Secondary structures were the cause of their similarity, and thus the concept of ‘folding’ was introduced to describe discrete sections of the protein that exhibit a repeating structure. Examples of secondary structures include alpha helices, beta sheets, and turns. As more structures were solved, more types of secondary structural folds were established. This view was embraced due in part to perceived evolutionary relationships between discrete secondary structures. Homology is transitive with respect to discrete secondary structures.
The most compelling argument for the existence of a continuous protein universe is the growing evidence that almost any set of secondary structures is possible. The potential continuous structure is dictated by the rules of hydrogen bonding. Not all structures can be perfectly aligned with one another; with most structures, at least 40% alignment can be achieved. Unlike discrete structures, the continuous structure of a protein is not the result of evolutionary fine-tuning, but rather the result of simple H-bonds between corresponding structures that lie adjacent to one another in space. It then follows that continuous structure is also known as geometric structure. On a continuous scale, density is not constant. All proteins will have areas with high and low numbers of substructures. This concept is similar to that of a Ramachandran plot of peptide bond conformations. In both cases, many conformations are possible but only a select few will most often be observed.
A dual view of the protein universe allows biochemists to better categorize and ultimately understand protein structure. One such instance is centered on folding. Based on its definition, folding implies that attention should only be given to how a specific structure interacts with itself and keeps itself together. This means that potential functional connections with other folds will most likely be overlooked. For example, the study of most alpha helices is centered on the differences between angles that dictate helical packing. As a result, differences in helical surfaces would be deemed unimportant, even though they may likely elucidate protein function.
Another such instance is the tendency of over-classification of secondary structures under the discrete structural system. When only discrete structures are considered, any minute difference from one instance of a structure to another is enough to argue that the two structures are different. This leads to the “discovery” of too many new types of folds, which is ultimately inefficient when applied to better understanding the big picture. Alternately, the continuous view will help eliminate the mental inertia caused by this problem. Since almost any type of fold is possible under the parameters of the continuous structural view, “new” folds could simply be placed into existing categories based on the intrinsic properties of their secondary structures, and connections to adjacent structures could be categorized separately, and thus better studied.