Biomedical subjects

Antonio del Sol

Publications and source records attributed to Antonio del Sol.

8 recordsLinked to original sources

PubMed2006

Residue centrality, functionally important residues, and active site shape: analysis of enzyme and non-enzyme families.

The representation of protein structures as small-world networks facilitates the search for topological determinants, which may relate to functionally important residues. Here, we aimed to investigate the performance of residue centrality, viewed as a family fold characteristic, in identifying functionally important residues in protein families. Our study is based on 46 families, including 29 enzyme and 17 non-enzyme families. A total of 80% of these central positions corresponded to active site residues or residues in direct contact with these sites. For enzyme families, this percentage increased to 91%, while for non-enzyme families the percentage decreased substantially to 48%. A total of 70% of these central positions are located in catalytic sites in the enzyme families, 64% are in hetero-atom binding sites in those families binding hetero-atoms, and only 16% belong to protein-protein interfaces in families with protein-protein interaction data. These differences reflect the active site shape: enzyme active sites locate in surface clefts, hetero-atom binding residues are in deep cavities, while protein-protein interactions involve a more planar configuration. On the other hand, not all surface cavities or clefts are comprised of central residues. Thus, closeness centrality identifies functionally important residues in enzymes. While here we focus on binding sites, we expect to identify key residues for the integration and transmission of the information to the rest of the protein, reflecting the relationship between fold and function. Residue centrality is more conserved than the protein sequence, emphasizing the robustness of protein structures.

Amino Acid Sequence↗

PubMed2006

TreeDet: a web server to explore sequence space.

The TreeDet (Tree Determinant) Server is the first release of a system designed to integrate results from methods that predict functional sites in protein families. These methods take into account the relation between sequence conservation and evolutionary importance. TreeDet fully analyses the space of protein sequences in either user-uploaded or automatically generated multiple sequence alignments. The methods implemented in the server represent three main classes of methods for the detection of family-dependent conserved positions, a tree-based method, a correlation based method and a method that employs a principal component analyses coupled to a cluster algorithm. An additional method is provided to highlight the reliability of the position in the alignments. The server is available at http://www.pdg.cnb.uam.es/servers/treedet.

Amino Acid Sequence↗

PubMed2006

Residues crucial for maintaining short paths in network communication mediate signaling in proteins.

Here, we represent protein structures as residue interacting networks, which are assumed to involve a permanent flow of information between amino acids. By removal of nodes from the protein network, we identify fold centrally conserved residues, which are crucial for sustaining the shortest pathways and thus play key roles in long-range interactions. Analysis of seven protein families (myoglobins, G-protein-coupled receptors, the trypsin class of serine proteases, hemoglobins, oligosaccharide phosphorylases, nuclear receptor ligand-binding domains and retroviral proteases) confirms that experimentally many of these residues are important for allosteric communication. The agreement between the centrally conserved residues, which are key in preserving short path lengths, and residues experimentally suggested to mediate signaling further illustrates that topology plays an important role in network communication. Protein folds have evolved under constraints imposed by function. To maintain function, protein structures need to be robust to mutational events. On the other hand, robustness is accompanied by an extreme sensitivity at some crucial sites. Thus, here we propose that centrally conserved residues, whose removal increases the characteristic path length in protein networks, may relate to the system fragility.

Allosteric Regulation↗

PubMed2005

A framework for computational and experimental methods: identifying dimerization residues in CCR chemokine receptors.

Solving relevant biological problems requires answering complex questions. Addressing such questions traditionally implied the design of time-consuming experimental procedures which most of the time are not accessible to average-sized laboratories. The current trend is to move towards a multidisciplinary approach integrating both theoretical knowledge and experimental work. This combination creates a powerful tool for shedding light on biological problems. To illustrate this concept, we present here a descriptive example of where computational methods were shown to be a key aspect in detecting crucial players in an important biological problem: the dimerization of chemokine receptors. Using evolutionary based sequence analysis in combination with structural predictions two CCR5 residues were selected as important for dimerization and further validated experimentally. The experimental validation of computational procedures demonstrated here provides a wealth of valuable information not obtainable by any of the individual approaches alone.

Amino Acid Sequence↗

PubMed2005

Small-world network approach to identify key residues in protein-protein interaction.

We show that protein complexes can be represented as small-world networks, exhibiting a relatively small number of highly central amino-acid residues occurring frequently at protein-protein interfaces. We further base our analysis on a set of different biological examples of protein-protein interactions with experimentally validated hot spots, and show that 83% of these predicted highly central residues, which are conserved in sequence alignments and nonexposed to the solvent in the protein complex, correspond to or are in direct contact with an experimentally annotated hot spot. The remaining 17% show a general tendency to be close to an annotated hot spot. On the other hand, although there is no available experimental information on their contribution to the binding free energy, detailed analysis of their properties shows that they are good candidates for being hot spots. Thus, highly central residues have a clear tendency to be located in regions that include hot spots. We also show that some of the central residues in the protein complex interfaces are central in the monomeric structures before dimerization and that possible information relating to hot spots of binding free energy could be obtained from the unbound structures.

Amino Acids↗

PubMed2005

Topology of small-world networks of protein-protein complex structures.

UNLABELLED: The majority of real examples of small-world networks exhibit a power law distribution of edges among the nodes, therefore not fitting into the wiring model proposed by Watts and Strogatz. However, protein structures can be modeled as small-world networks, with a distribution of the number of links decaying exponentially as in the case of this wiring model. We approach the protein-protein interaction mechanism by viewing it as a particular rewiring occurring in the system of two small-world networks represented by the monomers, where a re-arrangement of links takes place upon dimerization leaving the small-world character in the dimer network. Due to this rewiring, the most central residues at the complex interfaces tend to form clusters, which are not homogenously distributed. We show that these highly central residues are strongly correlated with the presence of hot spots of binding free energy. CONTACT: ao-mesa@fujirebio.co.jp SUPPLEMENTARY INFORMATION: http://www.fujirebio.co.jp/support/index.php (under construction).

Binding Sites↗

PubMed2004

Identification of amino acid residues crucial for chemokine receptor dimerization.

Chemokines coordinate leukocyte trafficking by promoting oligomerization and signaling by G protein-coupled receptors; however, it is not known which amino acid residues of the receptors participate in this process. Bioinformatic analysis predicted that Ile52 in transmembrane region-1 (TM1) and Val150 in TM4 of the chemokine receptor CCR5 are key residues in the interaction surface between CCR5 molecules. Mutation of these residues generated nonfunctional receptors that could not dimerize or trigger signaling. In vitro and in vivo studies in human cell lines and primary T cells showed that synthetic peptides containing these residues blocked responses induced by the CCR5 ligand CCL5. Fluorescence resonance energy transfer showed the presence of preformed, ligand-stabilized chemokine receptor oligomers. This is the first description of the residues involved in chemokine receptor dimerization, and indicates a potential target for the modification of chemokine responses.

Amino Acids↗

PubMed2003

Automatic methods for predicting functionally important residues.

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.

Algorithms↗