Biomedical subjects

Irene Luque Ruiz

Publications and source records attributed to Irene Luque Ruiz.

10 recordsLinked to original sources

PubMedDate not supplied

Cyclical conjunction: an efficient operator for the extraction of cycles from a graph.

The structural characteristics of a molecule, namely size, bond type and number, cycles, shape, and functional groups, will largely determine its physicochemical properties and biological activity. Extraction of data such as the complete structural information of a molecule's ring system is complex (NP-complete) and has traditionally involved high computational cost. The present study proposes a new operator for the extraction of cycles from a graph. Based on an initial cycle set, the operator employs a reduced number of operations in an iterative process of error-free cycle extraction, hence greatly reducing computational cost. Algorithm efficiency has been enhanced by designing new data structures suited to cycle storage, useful not only for interactive solutions but also for applications managing large volumes of information such as descriptor calculation, QSPR/QSAR, matching, clustering, screening, and filtering. Validation was performed by applying the algorithm to a test suite of chemical compounds of varying complexity.

Journal Article↗

PubMedDate not supplied

Computer-assisted learning using a dialogue system for virtual teacher-student communication.

Over the past decade, computer-assisted learning in the field of chemistry has given rise to a large number of systems that approach this objective from different viewpoints: static courses aimed at specific concepts, tutorial systems, 2D and 3D virtual environments, and so on. Correct structuring and representation of the knowledge to be taught, the building of a suitable student interface, and the adaptation of the learning process to the knowledge of the student are but a few of the challenges to be faced in the development of efficient computer-assisted learning systems. The present study tackles the use of computerized dialogue systems as a viable alternative for the simulation of teacher-student interaction and proposes an ontology for the characterization of such interaction, employing the object-oriented paradigm in the modeling of both the knowledge to be taught and the actual level of the student. The proposed solution is based on the representation of the knowledge to be taught through a network of multiconnected knowledge frames (chunks), where each chunk may be specialized in more specific frames (prerequisites and subobjectives), contain associated explanations of varying complexity and with a range of explanatory models, and be associated with one or a set of possible questions the student might ask; to this end, a constantly evolving knowledge model is maintained throughout the explanatory process. Based on the proposed model, Java was used to develop and manage an explanatory system that could be used in any type of teaching system based on student-dominated dialogues. Here, the system has been applied to the teaching of chemistry laboratory practice by its integration into the Virtual Chemistry Laboratory (VCL), a system designed by the authors to simulate chemistry techniques in a virtual 3D world.

Journal Article↗

PubMedDate not supplied

Step-by-step calculation of all maximum common substructures through a constraint satisfaction based algorithm.

In this paper we propose a new algorithm for subgraph isomorphism based on the representation of molecular structures as colored graphs and the representation of these graphs as vectors in n-dimensional spaces. The presented process that obtains all maximum common substructures is based on the solution of a constraint satisfaction problem defined as the common m-dimensional space (m< or =n) in which the vectors representing the matched graphs can be defined.

Journal Article↗

PubMedDate not supplied

Representation of the molecular topology of cyclical structures by means of cycle graphs. 1. Extraction of topological properties.

In this paper, a new representation model using the existing cycles in the topological structure of the molecules is proposed. Extracting all cycles of a molecule, its topological structure can be represented by means of a weighted, colored, and nondirected graph named "cycle graph", where the nodes represent the cycles in the molecule and the edges the common nodes among those cycles. In this paper, the capacity of cycle graph for the extraction of topological descriptors contributing appropriate measures of complexity, cyclicity, and symmetry of cyclical systems is presented.

Journal Article↗

PubMedDate not supplied

Representation of the molecular topology of cyclical structures by means of cycle graphs. 2. Application to clustering of chemical databases.

The great size of chemical databases and the high computational cost required in the atom-atom comparison of molecular structures for the calculation of the similarity between two chemical compounds necessitate the proposal of new clustering models with the aim of reducing the time of recovery of a set of molecules from a database that satisfies a range of similarities with regard to a given molecule pattern. In this paper we make use of the information corresponding to the cycles existing in the structure of molecules as an approach for the classification of chemical databases. The clustering method here proposed is based on the representation of the topological structure of molecules stored in chemical databases through its corresponding cycle graph. This method presents a more appropriate behavior for others described in the bibliography in which the information corresponding to the cyclicity of the molecules is also used.

Journal Article↗

PubMedDate not supplied

From Wiener index to molecules.

In this paper we present an algorithm for the generation of molecular graphs with a given value of the Wiener index. The high number of graphs for a given value of the Wiener index is reduced thanks to the application of a set of heuristics taking into account the structural characteristics of the molecules. The selection of parameters as the interval of values for the Wiener index, the diversity and occurrence of atoms and bonds, the size and number of cycles, and the presence of structural patterns guide the processing of the heuristics generating molecular graphs with a considerable saving in computational cost. The modularity in the design of the algorithm allows it to be used as a pattern for the development of other algorithms based on different topological invariants, which allow for its use in areas of interest, say as involving combinatorial databases and screening in chemical databases.

Journal Article↗

PubMedDate not supplied

Representation of the molecular topology of cyclical structures by means of cycle graphs. 3. Hierarchical model of screening of chemical databases.

The increase in the size and complexity of chemical databases necessitates the proposal and development of efficient methods of classification and recovery of information, which supposes proposal of a model of classification of database records and the use of a compatible model of screening for inspection of clusters and recovery of the molecules that satisfy the search criterion. The cycle graphs model based on consideration of all the cycles and chains (and equivalent cycles and chains) present in the molecular structure has been proven appropriate for classification of chemical databases, giving rise to a generation of different classification levels depending on the structural elements (cycles and chains) that are considered. In this paper we propose a screening model, compatible with the cycle graphs model, based on a hierarchy of levels of abstraction. The set of molecules that satisfies a screening model (or selection criterion) diminishes as we advance in the hierarchy of levels of the model, which allows filtering of records and, therefore, an increase in the efficiency of the screening process. In the following work of this series we describe and validate the screening tool developed.

Journal Article↗

PubMedDate not supplied

Clustering chemical databases using adaptable projection cells and MCS similarity values.

In this paper we propose a new method based on measurements of the structural similarity for the clustering of chemical databases. The proposed method allows the dynamic adjustment of the size and number of cells or clusters in which the database is classified. Classification is carried out using measurements of structural similarity obtained from the matching of molecular graphs. The classification process is open to the use of different similarity indexes and different measurements of matching. This process consists of the projection of the obtained measures of similarity among the elements of the database in a new space of similarity. The possibility of the dynamic readjustment of the dimension and characteristic of the projection space to adapt to the most favorable conditions of the problem under study and the simplicity and computational efficiency make the proposed method appropriate for its use with medium and large databases. The clustering method increases the performance of the screening processes in chemical databases, facilitating the recovery of chemical compounds that share all or subsets of common substructures to a given pattern. For the realization of the work a database of 498 natural compounds with wide molecular diversity extracted from SPECS and BIOSPECS B.V. free database has been used.

Journal Article↗

PubMedDate not supplied

A steroids QSAR approach based on approximate similarity measurements.

A new QSAR method based on approximate similarity measurements is described in this paper. Approximate similarity is calculated using both the classical similarity based on the graph isomorphism and a distance computation between nonisomorphic subgraphs. The latter is carried out through a parametric function where different topological invariants can be considered. After optimizing the contribution of nonisomorphic distance to the new graph similarity, predictive models built with approximate similarity matrixes show higher predictive ability than those using traditional similarity matrixes. The new method has been applied to the prediction of steroids binding to the corticosteroid globulin receptor. The proposed model allows us to obtain valuable external predictions (r=0.82 and SEP=0.30) after training the model by cross-validation (Q2=0.84 and SECV=0.47). Slope and bias parameters are also given.

Least-Squares Analysis↗

PubMedDate not supplied

Refinement and use of the approximate similarity in QSAR models for benzodiazepine receptor ligands.

Several considerations for refining the approximate similarity measurements have been introduced in this paper: the use of topological invariants for the calculation of similarity indexes and the development of new similarity correction processes. The quality of the new similarity measurements obtained with the proposed methods has permitted the development of fast, cheap, and simple quantitative structure-activity relationship models for the prediction of biological activities of nonbenzodiazepine gamma-aminobutyric acid(A)/benzodiazepine receptor ligands (58 compounds). Internal and external validations were carried out for the approximate similarity matrices computed using different approaches. Satisfactory results which compare reasonably well with a 3D approach were obtained: Q2= 0.65 and standard error in cross validation SECV= 0.83 for the training stage; r = 0.79 and error in external prediction = 0.82 for the test step. In addition, the method proposed was compared with other topological approaches based on constitutional similarity and on fingerprints. Satisfactory results were obtained.

Journal Article↗