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Biomedical subjects

Ernesto Estrada

Publications and source records attributed to Ernesto Estrada.

At least 19 recordsLinked to original sources
PubMed2007

Point scattering: a new geometric invariant with applications from (nano)clusters to biomolecules.

A new geometric invariant is defined from "first principles" for a point ensemble, which can represent clusters, molecules, crystals, and biomolecules. The scattering of a point ensemble is defined in terms of the Euclidean distance matrix and a vector measuring the weighted departure of the points from the cluster centre. Using the Rayleigh-Ritz theorem this function is maximized obtaining the point scattering of the ensemble. The point scattering shows several properties which are useful for studying clusters, molecules, crystals, and biomolecules. We examined different natural clusters of hard spheres such as colloidal particles and fullerenes, as well as protein-peptide complexes and the effect of temperature on protein structure. In all cases point scattering differentiates point ensembles with different structures, which are not distinguished by other geometric invariants, such as the second moment of mass distribution, surface areas, and volumes. Point scattering also shows better correlation with thermodynamic parameters of binding and describes the interior cavities of hollowed ensembles better than the other geometric measures.

Carbon↗
PubMed2006

Predicting infinite dilution activity coefficients of organic compounds in water by quantum-connectivity descriptors.

Quantitative structure-property relationship (QSPR) models are developed to predict the logarithm of infinite dilution activity coefficient of hydrocarbons, oxygen containing organic compounds and halogenated hydrocarbons in water at 298.15 K. The description of the molecular structure in terms of quantum-connectivity descriptors allows to obtain more simple QSPR models because of the quantum-chemical and topological information coded in this type of descriptors. The models developed in this paper have fewer descriptors and better statistics than other models reported in literature. The current models allow a more transparent physical interpretation of the phenomenon in terms of intermolecular interactions which occur in solution and which explain the respective deviations from ideality.

Hydrocarbons↗
PubMed2006

Food webs robustness to biodiversity loss: the roles of connectance, expansibility and degree distribution.

We analyse the robustness of food webs against species loss by considering the influence of several structural factors of the networks, such as connectance, degree distribution and expansibility. The last concept refers to the absence of structural bottlenecks in the food web, whose removal separate the network into large isolate clusters. In theory networks with identical connectance can display different expansibility characteristics. Using the spectral scaling method we studied 17 food networks and classified them as good expansion (GE) and not-GE networks. The combination of GE properties and degree distribution of species permitted the classification of food webs into six different classes. These classes characterize the differences in robustness of food webs to species loss. While the webs having uniform degree distributions and displaying GE properties are the most robust to species loss, the presence of bottlenecks and skewed distribution of the number of links per species make food webs very vulnerable to primary removal of species.

Animals↗
PubMed2006

Automatic extraction of structural alerts for predicting chromosome aberrations of organic compounds.

We use the topological sub-structural molecular design (TOPS-MODE) approach to formulate structural alert rules for chromosome aberration (CA) of organic compounds. First, a classification model was developed to group chemicals as active/inactive respect to CA. A procedure for extracting structural information from orthogonalized TOPS-MODE descriptors was then implemented. The contributions of bonds to CA in all the molecules studied were then generated using the orthogonalized classification model. Using this information we propose 22 structural alert rules which are ready to be implemented in expert systems for the automatic prediction of CA. They include, among others, structural alerts for N-nitroso compounds (ureas, urethanes, guanidines, triazines), nitro compounds (aromatic and heteroaromatic), alkyl esters or phosphoric acids, alkyl methanesulfonates, sulphonic acids and sulphonamides, epoxides, aromatic amines, azaphenanthrene hydrocarbons, etc. The chemico-biological analysis of some of the structural alerts found is also carried out showing the potential of TOPS-MODE as a knowledge generator.

Automation↗
PubMed2006

Synthesis of compounds with antiproliferative activity as analogues of prenylated natural products existing in Brazilian propolis.

This work describes the syntheses and antitumoral properties of five prenyl compounds from which antiproliferative activities were predicted by using the TOPS-MODE approach, a computational method for drug design. The syntheses of 2-(3-methylbut-2-enyloxy)acetophenone (2), 2-hydroxy-5-(3-methylbut-2-enyl)acetophenone (3), 2-hydroxy-3-(1,1-dimethylallyl)acetophenone (4), and 5-(3-methylbut-2-enyl)-2-(3-methylbut-2-enyloxy)acetophenone (5) were realized by O-prenylation of phenolic compounds with prenyl bromide and by Claisen rearrangement, respectively. Reaction of 2-hydroxy-5-(3-methylbut-2-enyl)acetophenone 3 under Vilsmeier-Haack conditions with phosphoryl chloride and N,N-dimethylformamide yielded 6-(3-methylbut-2-enyl)chromone-3-carbaldehyde (6). The compounds were tested for their cytotoxicity toward a diverse panel of cultured human tumor cell lines. Compound 3 showed significant selective cytotoxic activity (IC(50) < 9 microg/ml).

Acetophenones↗
PubMed2006

Virtual identification of essential proteins within the protein interaction network of yeast.

Topological analysis of large scale protein-protein interaction networks (PINs) is important for understanding the organizational and functional principles of individual proteins. The number of interactions that a protein has in a PIN has been observed to be correlated with its indispensability. Essential proteins generally have more interactions than the nonessential ones. We show here that the lethality associated with removal of a protein from the yeast proteome correlates with different centrality measures of the nodes in the PIN, such as the closeness of a protein to many other proteins, or the number of pairs of proteins which need a specific protein as an intermediary in their communications, or the participation of a protein in different protein clusters in the PIN. These measures are significantly better than random selection in identifying essential proteins in a PIN. Centrality measures based on graph spectral properties of the network, in particular the subgraph centrality, show the best performance in identifying essential proteins in the yeast PIN. Subgraph centrality gives important structural information about the role of individual proteins, and permits the selection of possible targets for rational drug discovery through the identification of essential proteins in the PIN.

Proteome↗
PubMed2006

Effect of protein backbone folding on the stability of protein-ligand complexes.

The role played by the degree of folding of protein backbones in explaining the binding energetics of protein-ligand interactions has been studied. We analyzed the protein/peptide interactions in the RNase-S system in which amino acids at two positions of the peptide S have been mutated. The global degree of folding of the protein S correlates in a significant way with the free energy and enthalpy of the protein-peptide interactions. A much better correlation is found with the local contribution to the degree of folding of one amino acid residue: Thr36. This residue is shown to have a destabilizing interaction with Lys41, which interacts directly with peptide S. Another system, consisting of the interactions of small organic molecules with HIV-1 protease was also studied. In this case, the global change in the degree of folding of the protease backbone does not explain the binding energetics of protein-ligand interactions. However, a significant correlation is observed between the free energy of binding and the contribution of two amino acid residues in the HVI-1 protease: Gly49 and Ile66. In general, it was observed that the changes in the degree of folding are not restricted to the binding site of the protein chain but are distributed along the whole protein backbone. This study provides a basis for further consideration of the degree of folding as a parameter for empirical structural parametrizations of the binding energetics of protein folding and binding.

Amino Acids↗
PubMed2006

Protein bipartivity and essentiality in the yeast protein-protein interaction network.

Protein-protein interaction networks (PINs) are structured by means of a few highly connected proteins linked to a large number of less-connected ones. Essential proteins have been found to be more abundant among these highly connected proteins. Here we demonstrate that the likelihood that removal of a protein in a PIN will prove lethal to yeast correlates with the lack of bipartivity of the protein. A protein is bipartite if it can be partitioned in such a way that there are two groups of proteins with intergroup, but not intragroup, interactions. The abundance of essential proteins found among the least bipartite proteins clearly exceeds that found among the most connected ones. For instance, among the top 50 proteins ranked by their lack of bipartivity 62% are essential proteins. However, this percentage is only 38% for proteins ranked according to their number of interactions. Protein bipartivity also surpasses another 5 measures of protein centrality in yeast PIN in identifying essential proteins and doubles the number of essential proteins selected at random. We propose a possible mechanism for the evolution of essential proteins in yeast PIN based on the duplication-divergence scheme. We conclude that a replica protein evolving from a nonbipartite target will also be nonbipartite with high probability. Consequently, these new replicas evolving from nonbipartite (essential) targets will with high probability be essential.

Evolution, Molecular↗
PubMed2005

Simplex optimization of generalized topological index (GTI-simplex): a unified approach to optimize QSPR models.

GTI-simplex is a new methodology that combines the generalized topological indices and the down hill simplex optimization procedure to search for optimized quantitative structure-property relationship models (Chem. Phys. Lett. 2005, 410, 343). In this study, the fundamental role of the graph topological distance inducing a local shell structure on vertexes and a detailed derivation of the GTI-decomposition in terms of the so-called "geodesic-brackets", i.e., functions that mix the local shell structure for different vertexes are presented. Applications of the GTI-simplex to a set of physicochemical properties covering those depending on intramolecular and/or intermolecular interactions are included. GTI-simplex has showed to be a very effective methodology for the description of different properties from a unified point of view. No ad hoc definition for topological index is required to each property as in the traditional use of topological indices or other molecular descriptors to QSAR/QSPR studies.

Journal Article↗
PubMed2005

Spectral measures of bipartivity in complex networks.

We introduce a quantitative measure of network bipartivity as a proportion of even to total number of closed walks in the network. Spectral graph theory is used to quantify how close to bipartite a network is and the extent to which individual nodes and edges contribute to the global network bipartivity. It is shown that the bipartivity characterizes the network structure and can be related to the efficiency of semantic or communication networks, trophic interactions in food webs, construction principles in metabolic networks, or communities in social networks.

Journal Article↗
PubMed2005

Folding degrees of azurins and pseudoazurins. Implications for structure and function.

A quantitative measure of the degree of folding of azurins and pseudoazurins has been made. We have found that the reduction potential of azurins and pseudoazurins is a function of the contribution to the degree of folding of His117, a key amino acid in electron transfer which is directly bonded to copper in these proteins. The folding degree of His117 explains 95% of the variance in the experimental values of the reduction potential of azurins and pseudoazurins. The change in the folding degree of this amino acid influences several geometric parameters of the main backbones of these proteins. Among them, the angle formed between N(His117)...Cu...S(Cys112), which plays an important role in electron transport, but not the N(His117)...Cu distance, shows some non-linear correlation with the reduction potential of azurins and pseudoazurins. However, it is only able to explain less than 75% in the variance of the reduction potential of these proteins instead of the 95% explained by the folding degree of His117.

Algorithms↗
PubMed2005

Subgraph centrality in complex networks.

We introduce a new centrality measure that characterizes the participation of each node in all subgraphs in a network. Smaller subgraphs are given more weight than larger ones, which makes this measure appropriate for characterizing network motifs. We show that the subgraph centrality [C(S)(i)] can be obtained mathematically from the spectra of the adjacency matrix of the network. This measure is better able to discriminate the nodes of a network than alternate measures such as degree, closeness, betweenness, and eigenvector centralities. We study eight real-world networks for which C(S)(i) displays useful and desirable properties, such as clear ranking of nodes and scale-free characteristics. Compared with the number of links per node, the ranking introduced by C(S)(i) (for the nodes in the protein interaction network of S. cereviciae) is more highly correlated with the lethality of individual proteins removed from the proteome.

Journal Article↗
PubMed2004

Quantum-connectivity descriptors in modeling solubility of environmentally important organic compounds.

Quantum-connectivity indices are topographic descriptors combining quantum-chemical and topological information. They are used to describe the water solubility of a noncongeneric data set of organic compounds. A QSPR model is obtained with two quantum-connectivity indices that accounts for more than 90% of the variance in the water solubility of these chemicals. This model is compared to other five QSPR models using constitutional, electrostatic, geometric, quantum-chemical, and topological descriptors calculated by CODESSA. None of these models accounts for more than 85% of the variance in water solubility of the compounds in this data set. The QSPR model obtained with quantum-connectivity indices is also better than that generated from the general pool of 508 CODESSA indices. Models with up to five variables were explored and compared with the model obtained here. It is shown that quantum-connectivity indices contain more structural information than other classes of descriptors at least for describing the water solubility of these 53 chemicals. Structural interpretation of the QSPR model developed as well as the role of the quantum-connectivity indices included in it are also analyzed.

Journal Article↗
PubMed2004

Characterization of the amino acid contribution to the folding degree of proteins.

The folding degree index (Estrada, Bioinformatics 2002;18:697-704) is extended to account for the contribution of amino acids to folding. First, the mathematical formalism for extending the folding degree index is presented. Then, the amino acid contributions to folding degree of several proteins are used to analyze its relation to secondary structure. The possibilities of using these contributions in helping or checking the assignation of secondary structure to amino acids are also introduced. The influence of external factors to the amino acids contribution to folding degree is studied through the temperature effect on ribonuclease A. Finally, the analysis of 3D protein similarity through the use of amino acid contributions to folding degree is studied by selecting a series of lysozymes. These results are compared to that obtained by sequence alignment (2D similarity) and 3D superposition of the structures, showing the uniqueness of the current approach.

Amino Acids↗
PubMed2004

Creating molecular diversity from antioxidants in Brazilian propolis. Combination of TOPS-MODE QSAR and virtual structure generation.

A QSAR model for antioxidative activity based on the Sub-Structural Molecular Design (TOPS-MODE) approach is developed for a series of compounds present in Brazilian propolis. This approach permitted the structural interpretation of the antioxidative activity of these compounds in terms of bond contributions. By these means we have identified the structural groups and regions that contribute to the antioxidative activity of the cinnamic acid and flavonoid derivatives present in the propolis. These results were then used to identify the positions and substituents to be used in a virtual compound generation experiment. Using this approach a total of 327 compounds were generated from which more than 70 are predicted to be more active than the most powerful antioxidants in the Brazilian propolis. From these 70 compounds less than 20 have been reported in the literature. Consequently, a high proportion of novel compounds with potential antioxidative activity has been identified by the current approach. This contributes to enhance the molecular diversity of the analogues of Brazilian propolis compounds with antioxidative properties.

Antioxidants↗
PubMed2003

Continuous symmetry numbers and entropy.

Traditionally, entropy changes are corrected for rotational permutability only if the molecule is perfectly rotationally symmetric. By this approach, only a small fraction of all known molecules must be evaluated in terms of symmetry numbers, while all other molecules are totally exempt of these considerations. A general approach which encompasses all molecules, symmetric or not, is proposed here. It is based on introducing the notion of continuity to symmetry numbers and on allowing noninteger values. In the first part of the account, we provide arguments as to why continuity is needed and what difficulties one may encounter by adopting the "black-or-white" approach to symmetry. In the second part, we provide a working methodology of how to evaluate the symmetry number content of any molecule, symmetric or not. Finally, in the third part, we demonstrate the implications of this approach on entropy issues involving melting points, Jahn-Teller distortions (of fullerene) upon ionization, molecular distortion due to overcrowdedness, permutability of isotopes, and the structure of proton sponges. It is shown that continuous symmetry numbers provide entropy values, which better agree with experimental observations, and that they are capable of identifying correlations between symmetry and physical/chemical measurables.

Journal Article↗
PubMed2003

Application of a novel graph-theoretic folding degree index to the study of steroid-DB3 antibody binding affinity.

A novel folding degree index, together with other macromolecular descriptors, is used to study steroid-DB3 antibody interactions. This index is based on graph spectral moments of a matrix representing the dihedral angles of a protein backbone. The causes influencing the different order of binding affinity of steroids to DB3 antibody are identified. It is shown that the changes in the chain compactness of the DB3 antibody with respect to its center of mass (radius of gyration) is compensated by a change in the folding degree index in the contrary sense. In fact, the increment in compactness of chain L and the lower increment in the folding degree index of chain H are able to explain the variations in affinity for DB3 of the steroids studied. Consequently, the highest binding affinities are reached by increasing the compactness of chain L in DB3 at the same time that producing the smallest increment in the folding degree of chain H. This study shows the possibilities of application for the graph-theoretic folding degree index in studying drug-protein interactions.

Animals↗