Automatic Methods for Predicting Functionally Important Residues

Abstract

Sequence analysis is often the first guide for the prediction of residues in a protein family that may have functional significance. A few methods have been proposed which use the division of protein families into subfamilies in the search for those positions that could have some functional significance for the whole family, but at the same time which exhibit the specificity of each subfamily ("Tree-determinant residues"). However, there are still many unsolved questions like the best division of a protein family into subfamilies, or the accurate detection of sequence variation patterns characteristic of different subfamilies. Here we present a systematic study in a significant number of protein families, testing the statistical meaning of the Tree-determinant residues predicted by three different methods that represent the range of available approaches. The first method takes as a starting point a phylogenetic representation of a protein family and, following the principle of Relative Entropy from Information Theory, automatically searches for the optimal division of the family into subfamilies. The second method looks for positions whose mutational behavior is reminiscent of the mutational behavior of the full-length proteins, by directly comparing the corresponding distance matrices. The third method is an automation of the analysis of distribution of sequences and amino acid positions in the corresponding multidimensional spaces using a vector-based principal component analysis. These three methods have been tested on two non-redundant lists of protein families: one composed by proteins that bind a variety of ligand groups, and the other composed by proteins with annotated functionally relevant sites. In most cases, the residues predicted by the three methods show a clear tendency to be close to bound ligands of biological relevance and to those amino acids described as participants in key aspects of protein function. These three automatic methods provide a wide range of possibilities for biologists to analyze their families of interest, in a similar way to the one presented here for the family of proteins related with ras-p21.

Automated prediction of protein function and detection of functional sites from structure

“…However, their approach is restricted in the profile size, its inability to handle any kind of residue (including hydrophobic), and the lack of flexibility associated with the PSSM representation of the profiles. Moreover, their method (26) are shown in blue, residues predicted by the MTREEDET program (29) are shown in red, and residues predicted by both methods (like the well studied Glu-37, which is marked with an arrow) are shown in purple. Other views of the structures are available in supporting information.…”

“…Early work considered fully conserved residues (25). This approach was extended to the detection of family-specific conservation (residues responsible for specificity) (26)(27)(28)(29)(30). 3D structural information has also been used to detect functionally important residues and regions, either alone (31)(32)(33)(34) or in combination with sequence information (35)(36)(37)(38)(39).…”

Relating Protein Structure and Function Through a Bijection and Its Implications on Protein Structure Prediction

“…Thus, these residues constitute a key piece of knowledge that can be exploited to relate activity and 3D structure. Not surprisingly, methods have been developed to predict critical residues from protein sequence and/or 3D structure (Elcock, 2001;del Sol Mesa et al, 2003;Glaser et al, 2003;Thibert et al, 2005;Cusack et al, 2007).…”

A Family of Evolution–Entropy Hybrid Methods for Ranking Protein Residues by Importance

“…10,11 Mirny & Shakhnovich 12 as well as Hannenhalli & Russell 13 introduced the notion of summing or averaging the site entropy over several related protein groups, but stopped short of iteratively applying this approach to the hierarchical division of sequences into groups induced by evolutionary tree, the idea that we propose here.…”

“…A comparative study of various methods mentioned, in terms of their capability to rank the residues, was, to the best of our knowledge, never performed (see del Sol Mesa et al 11 for comparison of several methods' ability to pick residues physically close to functionally important residues). In good part, the reason is that it is impossible to obtain from the experiment equivalent and independent information, an experimental yardstick against which to measure the performance of various theoretical approaches.…”