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X Gironés

Publications and source records attributed to X Gironés.

9 recordsLinked to original sources

Application of promolecular ASA densities to graphical representation of density functions of macromolecular systems.

In this article we report the application of the Promolecular Atomic Shell Approximation (Promolecular ASA) to the graphical representation of the density function (DF) of large macromolecular systems. Promolecular ASA DF, constructed from previously computed and fitted atomic densities, provides a fast and practical representation of Molecular IsoDensity Contours (MIDCOs). These representations can be extended to macromolecular systems composed by > 1000 atoms easily and with low computational costs, allowing the visualization of protein DF. The method is at first presented with a small molecule (2,4,6-trinitrophenol), comparing the resulting ASA MIDCOs with direct ab initio contours. For macromolecular tests the Promolecular ASA densities are also applied to the generation of macromolecular density surfaces of two proteins: myoglobin (2541 atoms) and gene V protein (1362 atoms).

Computer Graphics↗

Structure-toxicity relationships of polycyclic aromatic hydrocarbons using molecular quantum similarity.

The establishment of quantitative structure-activity relationship (QSAR) models for the toxicity of polycylic aromatic hydrocarbons (PAHs) is described. Two properties, in vitro percutaneous absorption in rat skin and discrete levels of carcinogenic activity, are examined using molecular quantum similarity measures (MQSM). The results show that MQSM produces comparable, or even better, results than other approaches using physicochemical, topological and quantum-chemical molecular descriptors. Furthermore, a careful analysis puts into evidence that most of the information characterized by the original descriptors is in fact contained in the molecular density functions, the basis of MQSM. The present paper, together with several other reported by our laboratory, proves that MQSM might be appropriate theoretical tools for QSAR and computer-aided drug design, comparable to other highly predictive QSAR methodologies.

Carcinogens↗

Antimalarial activity of synthetic 1,2,4-trioxanes and cyclic peroxy ketals, a quantum similarity study.

In this work, the antimalarial activity of two series of 20 and 7 synthetic 1,2,4-trioxanes and a set of 20 cyclic peroxy ketals are tested for correlation search by means of Molecular Quantum Similarity Measures (MQSM). QSAR models, dealing with different biological responses (IC90, IC50 and ED90) of the parasite Plasmodium Falciparum, are constructed using MQSM as molecular descriptors and are satisfactorily correlated. The statistical results of the 20 1,2,4-trioxanes are deeply analyzed to elucidate the relevant structural features in the biological activity, revealing the importance of phenyl substitutions.

Animals↗

Use of electron-electron repulsion energy as a molecular descriptor in QSAR and QSPR studies.

Electron-electron repulsion energy ( ) is presented as a new molecular descriptor to be employed in QSAR and QSPR studies. Here it is shown that this electronic energy parameter is connected to molecular quantum similarity measures (MQSM), and as a consequence can be considered as a complement to steric and electronic parameters in description of molecular properties and biological responses of organic compounds. The present strategy considers the molecule as a whole, thus there is no need to employ contributions of isolated fragments as in many calculations of molecular descriptors, like log P or the Free-Wilson analysis. The procedure has been tested in a widespread set of molecules: alcohols, alkanamides, indole derivatives and 1-alkylimidazoles. Molecular properties, as well as toxicity, are correlated using as a parameter, and extensions to the method are given for handling difficult systems. In almost all studied cases, satisfactory linear relationships were finally obtained.

Computer-Aided Design↗

Facet diagrams for quantum similarity data.

The objective of this work is to demonstrate that an appropriate treatment of quantum similarity matrices can reveal hidden data grouping related to relevant structural features and even to biological properties of interest. Classical scaling is used here to extract the information contained in the similarity relationships between the elements of a molecular set. Facet theory is invoked to relate, in a qualitative way, the spatial regions to structural characteristics as well as to properties of interest. Two application examples are discussed: the Cramer steroid set and a benzene, toluene and xylene derivatives set.

Benzene↗

Using molecular quantum similarity measures as descriptors in quantitative structure-toxicity relationships.

In this paper molecular quantum similarity measures (MQSM) are used to describe molecular toxicity and to construct Quantitative Structure-Toxicity Relationships (QSTR) models. This study continues the recently described relationships between MQSM and log P values, which permits to use the theoretical MQSM as an alternative to the empirical hydrophobic parameter in QSPR studies. In addition a new type of MQSM is presented in this work: it is based on the expectation value of electron-electron repulsion energy. The molecular properties studied here, as application examples are aquatic toxicity, toxicology on Bacteria and inhibition of a macromolecule employing four different molecular sets.

Quantum Theory↗

A comparative study of isodensity surfaces using ab initio and ASA density functions.

In this article, we report a visual comparison between several of the available methods for constructing electronic density functions. The density forms studied include ab initio, atomic shell approximation, and promolecular densities. A graphical comparison is made for six different molecules at different levels of density function values. The differences between the various density functions are analysed by considering a molecular quantum self-similarity measure and the required computational time for all molecules at all computation levels is considered.

Algorithms↗

Modeling antimalarial activity: application of Kinetic Energy Density Quantum Similarity Measures as descriptors in QSAR.

In this work, is studied the application, within a quantum similarity framework, of the recently described Kinetic Energy Density Function in the evaluation of the antimalarial activity. First, this new type of Density Function is briefly presented from its theoretical foundations, and its inclusion in the molecular quantum similarity is discussed afterward. The application of Kinetic Energy-based Quantum Similarity Measures to QSAR is tested with 2 molecular sets composed of artemisinin derivatives, in which the 50% inhibition of synthesis and reduction of hidrofolate (IC50) in different Plasmodium falciparum clones are analyzed. Satisfactory correlations are obtained for all antimalarial activities in all studied molecular sets. Molecular Quantum Similarity analysis provides a consistent, unbiased, and homogeneous set of molecular descriptors and is a feasible alternative to the use of classical physicochemical descriptors.

Antimalarials↗

Quantification of the influence of single-point mutations on haloalkane dehalogenase activity: a molecular quantum similarity study.

Controlled modifications in certain protein amino acid residues can lead to changes in their function and stability. Amino acid structural features and their relation to these changes were examined by using quantum molecular similarity techniques. The effect of deliberate mutations in position 172 of the haloalkane dehalogenase enzyme, yielding to variations on the dehalogenation of 1,2-dibromoethane, was studied qualitatively and quantitatively using molecular quantum similarity techniques. A valuable classification of the residues according to their effect on activity was obtained by representing the optimal two-dimensional classical scaling solution. In addition, satisfactory quantitative relationships were found, comparable to those attained by previous studies on this same data set using other techniques. Molecular quantum similarity analysis provides a consistent, unbiased, and homogeneous set of molecular descriptors and is a feasible alternative to the use of physicochemical properties.

Hydrolases↗