Showing papers by "Francisco Torrens published in 2012"

Classification of Phenolic Compounds by Chemical Structural Indicators and Its Relation to Antioxidant Properties of Posidonia Oceanica (L.) Delile

Abstract: A total of 33 phenolic compounds are classified into a periodic table by using an algorithm based on the theory of information entropy. Five features in hierarchical order are used to classify structurally the phenols. From these features, the first three mark the group or column, while the last two mark the row or period in the table. Those phenols in the same group and period are suggested to have maximum similarity in properties. Furthermore, those with only the same group will present moderate similarity. The Mediterranean endemic seagrass Posidonia oceanica is constituted by cells rich in phenolic compounds. In this report, we related the phenolic components of this phanerogam to compounds of the table whose bioactivity and antioxidant properties have been previously published.

A Review of QSAR studies to Discover New Drug-like Compounds Actives Against Leishmaniasis and Trypanosomiasis

Abstract: The neglected tropical diseases (NTDs) affect more than one billion people (one-sixth of the world's population) and occur primarily in undeveloped countries in sub-Saharan Africa, Asia, and Latin America. Available drugs for these diseases are decades old and present an important number of limitations, especially high toxicity and, more recently, the emergence of drug resistance. In the last decade several Quantitative Structure-Activity Relationship (QSAR) studies have been developed in order to identify new organic compounds with activity against the parasites responsible for these diseases, which are reviewed in this paper. The topics summarized in this work are: 1) QSAR studies to identify new organic compounds actives against Chaga's disease; 2) Development of QSAR studies to discover new antileishmanial drusg; 3) Computational studies to identify new drug-like compounds against human African trypanosomiasis. Each topic include the general characteristics, epidemiology and chemotherapy of the disease as well as the main QSAR approaches to discovery/identification of new actives compounds for the corresponding neglected disease. The last section is devoted to a new approach know as multi-target QSAR models developed for antiparasitic drugs specifically those actives against trypanosomatid parasites. At present, as a result of these QSAR studies several promising compounds, active against these parasites, are been indentify. However, more efforts will be required in the future to develop more selective (specific) useful drugs.

Derivatives in discrete mathematics: a novel graph-theoretical invariant for generating new 2/3D molecular descriptors. I. Theory and QSPR application

Abstract: In this report, we present a new mathematical approach for describing chemical structures of organic molecules at atomic-molecular level, proposing for the first time the use of the concept of the derivative ( $$ \partial $$ ) of a molecular graph (MG) with respect to a given event (E), to obtain a new family of molecular descriptors (MDs). With this purpose, a new matrix representation of the MG, which generalizes graph’s theory’s traditional incidence matrix, is introduced. This matrix, denominated the generalized incidence matrix, Q, arises from the Boolean representation of molecular sub-graphs that participate in the formation of the graph molecular skeleton MG and could be complete (representing all possible connected sub-graphs) or constitute sub-graphs of determined orders or types as well as a combination of these. The Q matrix is a non-quadratic and unsymmetrical in nature, its columns (n) and rows (m) are conditions (letters) and collection of conditions (words) with which the event occurs. This non-quadratic and unsymmetrical matrix is transformed, by algebraic manipulation, to a quadratic and symmetric matrix known as relations frequency matrix, F, which characterizes the participation intensity of the conditions (letters) in the events (words). With F, we calculate the derivative over a pair of atomic nuclei. The local index for the atomic nuclei i, Δ i , can therefore be obtained as a linear combination of all the pair derivatives of the atomic nuclei i with all the rest of the j′s atomic nuclei. Here, we also define new strategies that generalize the present form of obtaining global or local (group or atom-type) invariants from atomic contributions (local vertex invariants, LOVIs). In respect to this, metric (norms), means and statistical invariants are introduced. These invariants are applied to a vector whose components are the values Δ i for the atomic nuclei of the molecule or its fragments. Moreover, with the purpose of differentiating among different atoms, an atomic weighting scheme (atom-type labels) is used in the formation of the matrix Q or in LOVIs state. The obtained indices were utilized to describe the partition coefficient (Log P) and the reactivity index (Log K) of the 34 derivatives of 2-furylethylenes. In all the cases, our MDs showed better statistical results than those previously obtained using some of the most used families of MDs in chemometric practice. Therefore, it has been demonstrated to that the proposed MDs are useful in molecular design and permit obtaining easier and robust mathematical models than the majority of those reported in the literature. All this range of mentioned possibilities open “the doors” to the creation of a new family of MDs, using the graph derivative, and avail a new tool for QSAR/QSPR and molecular diversity/similarity studies.

Bundlet Model for Single-Wall Carbon Nanotubes, Nanocones and Nanohorns

Abstract: This paper discusses the existence of single-wall carbon nanocones (SWNCs), especially nanohorns (SWNHs), in organic solvents in the form of clusters. A theory is developed based on a bundlet model describing their distribution function by size. Phenomena have a unified explanation in bundlet model in which free energy of an SWNC, involved in a cluster, is combined from two components: a volume one, proportional to number of molecules n in a cluster, and a surface one proportional to n1/2. Bundlet model enables describing distribution function of SWNC clusters by size. From purely geometrical differences, bundlet (SWNCs) and droplet (fullerene) models predict different behaviours. The SWNCs of various disclinations are investigated via energetic–structural analyses. Several SWNC’s terminations are studied, which are different among one another because of type of closing structure and arrangement. The packing efficiencies and interaction-energy parameters of SWNCs/SWNHs are intermediate between fullerene and single-wall carbon nanotube (SWNT) clusters; an in-between behaviour is expected. However, the properties of SWNCs, especially SWNHs, are calculated close to SWNTs. The structural asymmetry in the different SWNCs, entirely characterized by their cone angle, distinguishes the properties of some, such as P2.

QSPR prediction of retention times of phenylurea herbicides by biological plastic evolution.

Abstract: A simple/sensitive high-performance liquid chromatographic method, with ultraviolet (UV) detection, was developed for phenylurea-herbicide analysis, which involves preconcentration using solid-phase extraction. Mobile phase was acetonitrile/water at flow-rate of 1 mL.min-1 with direct UV absorbance detection at 210 nm. Analyte separation studied on a C18 column was applied successfully to herbicide analysis in soft drink's brands and tap water. Good linearity/repeatability was observed for all pesticides. Retention times increase as: metoxuron < monuron < diuron < matazachlor < linuron. They are modelled by structure-property relations. The effect of different types of features is analyzed: electronic, solvation, lipophilic and steric, etc. Formation enthalpy and molecular dipole moment are calculated with MOPAC-AM1. Most important properties are hydration free energy and dipole moment. Results are improved if competitive conformation with higher dipole moment is considered at 1.1kJ.mol-1. Plastic evolution is an evolutionary perspective conjugating the effect of acquired characters, and relations that emerge among the principles of evolutionary indeterminacy, morphologic determination and natural selection. Plastic evolution is applied to design co-ordination index Ic, which is used to characterize phenylurea herbicides and compared to molecular dipole moment for retention time. Parametres needed to calculate Ic are formation enthalpy and molecular weight/surface area. Ic improves multivariable regression equations for retention and is predictive when it is used together with dipole and hydration free energy. Correction introduced in retention is produced in the correct direction. Hierarchical quantitative structure-property relationship provided simplified properties analysis. Structural classification is based on the presence of two Cl/O/N atoms.

Structural Classification of Complex Molecules by Artificial Intelligence Techniques

Abstract: Algorithms for classification and taxonomy bases on criteria, e.g., information entropy. The feasibility of replacing a given molecule by similar ones in the composition of a complex drug is studied. Some local anaesthetics currently in use are classified using structural properties. In taxonomy the detailed comparison of the sequences of biomolecules, proteins or nucleic acids, allows the reconstruction of a molecular phylogenetic tree. The method is applied to the classifications of (1) indazolols (against Trichomonas vaginalis), (2) fullerenes and fullerite, (3) living and heat-inactivated lactic acid bacteria against cytokines, (4) phylogenesis of avian birds and 1918 influenza virus, (5) local anaesthetics, (6) transdermal-delivery percutaneous enhancers, (7) quantitative structure–activity relationship of anti-human immunodeficiency virus (HIV) compounds, (8) HIV inhibitors, e.g., thiocarbamates, N-aryloxazolidinone-5-carboxamides and styrylquinolines, (9) antimalarial aryltriazolylhydroxamates, (10) N-aryl-N-(3-aryl-1,2,4-oxadiazol-5-yl) amines against prostate cancer, antimitotic 2-phenylindole3-carbaldehydes against breast cancer and anti-tubulin agents against gastric cancer with indole ring. The entropy contributions may be studied with the equipartition conjecture. It is not within the scope of our simulation method to replace biological tests of drugs or field data in palaeontology, but such simulation methods can be useful to assert priorities in detailed experimental research. Available experimental and field data should be examined by different classification algorithms to reveal possible features of real biological significance.

Retrained Classification of Tyrosinase Inhibitors and “In Silico” Potency Estimation by Using Atom-Type Linear Indices: A Powerful Tool for Speed up the Discovery of Leads

Abstract: In this paper, the authors present an effort to increase the applicability domain (AD) by means of retraining models using a database of 701 great dissimilar molecules presenting anti-tyrosinase activity and 728 drugs with other uses. Atom-based linear indices and best subset linear discriminant analysis (LDA) were used to develop individual classification models. Eighteen individual classification-based QSAR models for the tyrosinase inhibitory activity were obtained with global accuracy varying from 88.15-91.60% in the training set and values of Matthews correlation coefficients (C) varying from 0.76-0.82. The external validation set shows globally classifications above 85.99% and 0.72 for C. All individual models were validated and fulfilled by OECD principles. A brief analysis of AD for the training set of 478 compounds and the new active compounds included in the re-training was carried out. Various assembled multiclassifier systems contained eighteen models using different selection criterions were obtained, which provide possibility of select the best strategy for particular problem. The various assembled multiclassifier systems also estimated the potency of active identified compounds. Eighteen validated potency models by OECD principles were used.

Modelling Monomer/Disc Composites Phase Behaviour

Abstract: Summary: A model developed by Balazs' group to explain the phase behaviour of polymer/clay composites is extended to obtain an expression for the free energy of polymer/thin disc mixtures. Phase diagrams for monomer/disc mixtures are built by minimizing the free energy and calculating the chemical potentials of the three system components. Via the comparison of the diagrams, it is studied the effects of nanodisc size and interaction parameters on mixture stability and attained morphology. The performed predictions between monomers and discs give criteria that advance the properties of the mixture. Changes in monomer concentration and interaction parameters provide a means to prevent van der Waals-induced agglomeration. The model takes into account, in only a rather approximate manner, the long-range interactions between clay sheets.

Cluster Origin of Solvent Features of Fullerenes, Single-Wall Carbon Nanotubes, Nanocones, and Nanohorns

Abstract: This chapter discusses the existence of single-wall carbon nanocones (SWNCs), especially nanohorns (SWNHs) in organic solvents in the form of clusters. A theory is developed based on a bundlet model describing their distribution function by size. Phenomena have a unified explanation in bundlet model in which free energy of an SWNC, involved in a cluster, is combined from two components: a volume one, proportional to number of molecules n in a cluster, and a surface one proportional to n1/2. A bundlet model enables describing distribution function of SWNC clusters by size. From purely geometrical differences, bundlet (SWNCs) and droplet (fullerene) models predict different behaviours. The SWNCs of various disclinations are investigated via energetic–structural analyses. Several SWNC’s terminations are studied which are different among one another because of the type of closing structure and arrangement. Packing efficiencies and interaction-energy parameters of SWNCs/SWNHs are intermediate between fullerene and single-wall carbon nanotube (SWNT) clusters.