Relationship between global structural parameters and Enzyme Commission hierarchy: Implications for function prediction

In protein databases there is a substantial number of proteins structurally determined but without function annotation. Understanding the relationship between function and structure can be useful to predict function on a large scale. We have analyzed the similarities in global physicochemical parameters for a set of enzymes which were classified according to the four Enzyme Commission (EC) hierarchical levels. Using relevance theory we introduced a distance between proteins in the space of physicochemical characteristics. This was done by minimizing a cost function of the metric tensor built to reflect the EC classification system. Using an unsupervised clustering method on a set of 1025 enzymes, we obtained no relevant clustering formation compatible with EC classification. The distance distributions between enzymes from the same EC group and from different EC groups were compared by histograms. Such analysis was also performed using sequence alignment similarity as a distance. Our results suggest that global structure parameters are not sufficient to segregate enzymes according to EC hierarchy. This indicates that features essential for function are rather local than global. Consequently, methods for predicting function based on global attributes should not obtain high accuracy in main EC classes prediction without relying on similarities between enzymes from training and validation datasets. Furthermore, these results are consistent with a substantial number of studies suggesting that function evolves fundamentally by recruitment, i.e., a same protein motif or fold can be used to perform different enzymatic functions and a few specific amino acids (AAs) are actually responsible for enzyme activity. These essential amino acids should belong to active sites and an effective method for predicting function should be able to recognize them. (C) 2012 Elsevier Ltd. All rights reserved.

Probing the interaction of brain fatty acid binding protein (B-FABP) with model membranes

Brain fatty acid-binding protein (B-FABP) interacts with biological membranes and delivers polyunsaturated fatty acids (FAs) via a collisional mechanism. The binding of FAs in the protein and the interaction with membranes involve a motif called "portal region", formed by two small α-helices, A1 and A2, connected by a loop. We used a combination of site-directed mutagenesis and electron spin resonance to probe the changes in the protein and in the membrane model induced by their interaction. Spin labeled B-FABP mutants and lipidic spin probes incorporated into a membrane model confirmed that BFABP interacts with micelles through the portal region and led to structural changes in the protein as well in the micelles. These changes were greater in the presence of LPG when compared to the LPC models. ESR spectra of B-FABP labeled mutants showed the presence of two groups of residues that responded to the presence of micelles in opposite ways. In the presence of lysophospholipids, group I of residues, whose side chains point outwards from the contact region between the helices, had their mobility decreased in an environment of lower polarity when compared to the same residues in solution. The second group, composed by residues with side chains situated at the interface between the α-helices, experienced an increase in mobility in the presence of the model membranes. These modifications in the ESR spectra of B-FABP mutants are compatible with a less ordered structure of the portal region inner residues (group II) that is likely to facilitate the delivery of FAs to target membranes. On the other hand, residues in group I and micelle components have their mobilities decreased probably as a result of the formation of a collisional complex. Our results bring new insights for the understanding of the gating and delivery mechanisms of FABPs.