Protein structure known folds

As already discussed in Chapter 11, there are more than 10 000 protein structures known but only about 30 3D structure types. This might be traced to a limited number of possible stable polypeptide structures but most probably reflects the evolutionary history of the diversity of proteins. There are structural motifs which repeat themselves in a multitude of enzymes which are otherwise neither structurally nor functionally related, such as TIM barrel proteins, four-helix bundle proteins, Rossmann folds, or a/j3-folds of hydrolases (Figure 16.1). 

Life is driven by water. This is evident in the importance of the delicate balance between the hydrophilic and hydro-phobic forces responsible for protein structure and folding. It is nowhere as obvious as its role in the formation of biomembranes whose structures are principally determined by the amphipathic properties of the class of small biological molecules known as lipids. Membranes exist throughout organisms and many, perhaps most, important biological processes occur within them. In fact, the primordial formation of biomembranes might have been the first step in the emergence of life. 

Another of the successful methods that is based on a reverse approach relies on protein fold recognition by threading (31). This method takes advantage of the fact that the number of folds is limited. Instead of tr5nng to predict the fold of the protein on the basis of the amount of free energy, the method determines whether a given sequence can be fitted to a known fold. As the number of folds (Fig. 3) appears to be finite, it provides a way to look for the structure of new proteins using known folds. Another method for the prediction of three-dimensional structures of proteins is based on the in silico assembly of protein structure from shorter structural elements with more defined structures (32). 

Fig, 10.25 The six environment categories used by the 3D profiles method. (Figure adapted from Bowie j U, R Liith. and D Eisenberg 1991. A Method to Identify Protein Sequences That Fold into a Known Three-Dunensinnal Structure. Science 253 164-170.)... 

At this time, approximately one-half of all sequences are delectably related to at least one protein of known structure [8-11]. Because the number of known protein sequences is approximately 500,000 [12], comparative modeling could in principle be applied to over 200,000 proteins. This is an order of magnitude more proteins than the number of experimentally determined protein structures (—13,000) [13]. Furthermore, the usefulness of comparative modeling is steadily increasing, because the number of different structural folds that proteins adopt is limited [14,15] and because the number of experimentally determined structures is increasing exponentially [16]. It is predicted that in less than 10 years at least one example of most structural folds will be known, making comparative modeling applicable to most protein sequences [6]. 

Eortunately, a 3D model does not have to be absolutely perfect to be helpful in biology, as demonstrated by the applications listed above. However, the type of question that can be addressed with a particular model does depend on the model s accuracy. At the low end of the accuracy spectrum, there are models that are based on less than 25% sequence identity and have sometimes less than 50% of their atoms within 3.5 A of their correct positions. However, such models still have the correct fold, and even knowing only the fold of a protein is frequently sufficient to predict its approximate biochemical function. More specifically, only nine out of 80 fold families known in 1994 contained proteins (domains) that were not in the same functional class, although 32% of all protein structures belonged to one of the nine superfolds [229]. Models in this low range of accuracy combined with model evaluation can be used for confirming or rejecting a match between remotely related proteins [9,58]. 

JU Bowie, R Liithy, D Eisenberg. A method to identify protein sequences that fold into a known three-dimensional structure. Science 253 164-170, 1991. 

Recently Alan Fersht, Cambridge University, has developed a protein engineering procedure for such studies. The technique is based on investigation of the effects on the energetics of folding of single-site mutations in a protein of known structure. For example, if minimal mutations such as Ala to Gly in the solvent-exposed face of an a helix, destabilize both an intermediate state and the native state, as well as the transition state between them, it is likely that the helix is already fully formed in the intermediate state. If on the other hand the mutations destabilize the native state but do not affect the energy of the intermediate or transition states at all, it is likely that the helix is not formed until after the transition state. 

What can be done by predictive methods if the sequence search fails to reveal any homology with a protein of known tertiary structure Is it possible to model a tertiary structure from the amino acid sequence alone There are no methods available today to do this and obtain a model detailed enough to be of any use, for example, in drug design and protein engineering. This is, however, a very active area of research and quite promising results are being obtained in some cases it is possible to predict correctly the type of protein, a, p, or a/p, and even to derive approximations to the correct fold. 

For each fold one searches for the best alignment of the target sequence that would be compatible with the fold the core should comprise hydrophobic residues and polar residues should be on the outside, predicted helical and strand regions should be aligned to corresponding secondary structure elements in the fold, and so on. In order to match a sequence alignment to a fold, Eisenberg developed a rapid method called the 3D profile method. The environment of each residue position in the known 3D structure is characterized on the basis of three properties (1) the area of the side chain that is buried by other protein atoms, (2) the fraction of side chain area that is covered by polar atoms, and (3) the secondary stmcture, which is classified in three states helix, sheet, and coil. The residue positions are rather arbitrarily divided into six classes by properties 1 and 2, which in combination with property 3 yields 18 environmental classes. This classification of environments enables a protein structure to be coded by a sequence in an 18-letter alphabet, in which each letter represents the environmental class of a residue position. 

The N-terminal domain of the OCP is an orthogonal alpha-helical bundle, subdivided into two four-helix bundles (Figure 1.3a and c). These subdomains are composed of discontinuous segments of the polypeptide chain (gray and white in Figure 1.3c). To date, the OCP N-terminal domain is the only known protein structure with this particular fold (Pfam 09150). The hydroxyl terminus of the 3 -hydroxyechinenone is nestled between the two bundles. The C-terminal domain (dark... 

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