144 research outputs found

    Linear Regression QSAR Models for Polo-Like Kinase-1 Inhibitors

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    A structurally diverse dataset of 530 polo-like kinase-1 (PLK1) inhibitors is compiled from the ChEMBL database and studied by means of a conformation-independent quantitative structure-activity relationship (QSAR) approach. A large number (26,761) of molecular descriptors are explored with the main intention of capturing the most relevant structural characteristics affecting the bioactivity. The structural descriptors are derived with different freeware, such as PaDEL, Mold2, and QuBiLs-MAS; such descriptor software complements each other and improves the QSAR results. The best multivariable linear regression models are found with the replacement method variable subset selection technique. The balanced subsets method partitions the dataset into training, validation, and test sets. It is found that the proposed linear QSAR model improves previously reported models by leading to a simpler alternative structure-activity relationship.Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicada

    Improved atom equivalents method for converting density functional theory energies calculated on molecular mechanics structures to heats of formation

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    We present an improved atom equivalents method for converting Density Functional Theory energies calculated on molecular mechanics structures to enthalpies of formation. The introduction of bond parameters to an original sent of atom parameters yields a sensible improvement of the enthalpy predictions. The comparison with other similar approaches shows that our present method is a rather better calculation scheme. Some further possible improvements are pointed out.Centro de Química Inorgánic

    Prediction of Critical Temperatures and Critical Pressures of Some Industrially Relevant Organic Substances from Rather Simple Topological Descriptors

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    The simplest topological molecular parameters were applied to predict critical temperatures and critical pressures in terms of the QSAR/QSPR theory. Through the development of four different calculation schemes, the convenience of using the atomic coordination numbers for different atoms and the corresponding identity of chemical bonds was shown. A satisfactory agreement between the theoretical and experimental data was attained. Some limitations of the proposed approach are pointed out.Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicada

    Quantitative Structure-Property Relationships for Predicting the Retention Indices of Fragrances on Stationary Phases of Different Polarity

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    El objetivo de este trabajo fue el desarrollo de relaciones cuantitativas estructura–propiedad predictivas para el modelado de índices de retención (I) de fragancias, medidas en tres fases estacionarias de diferente polaridad: DB–225MS, HP5–MS y HP–1. Se ha prestado particular atención al curado de los datos experimentales. Posteriormente, se usó el método de subconjuntos balanceados (BSM) para dividir cada base de datos en grupos de calibración, validación y predicción. Los modelos se construyeron a partir de 1819 descriptores moleculares independientes de la conformación, los cuales fueron analizados mediante el método de reemplazo (RM) para la selección de los mismos, con la finalidad de obtener los mejores modelos. Para la fase estacionaria DB–225MS se obtuvo un modelo basado en cuatro descriptores, mientras que para las columnas HP5–MS y HP–1 se propusieron modelos con tres descriptores. Los modelos fueron validados mediante validación cruzada de dejar–uno–fuera y dejar–varios–fuera, así como otros criterios de validación. Adicionalmente, con la finalidad de cumplir los principios propuestos por la Organization for Economic Co–operation and Development (OECD), la capacidad predictiva de los modelos se evaluó mediante la predicción de los índices de retención del grupo externo de predicción, el dominio de aplicabilidad fue apropiadamente definido y se realizó una interpretación de cada descriptor molecular involucrado.The purpose of this work was to develop predictive quantitative structure–property relationships for modeling the retention indices (I) of fragrances measured in three stationary phases of different polarities: DB–225MS, HP5–MS and HP–1. Attention was paid to the curation of the experimental data. Subsequently, the Balanced Subsets method (BSM) was used to split each dataset into training, validation and test sets. Models were established by using 1819 conformation–independent molecular descriptors which were analyzed by the replacement method (RM) variable subset selection in order to obtain the optimal models. A four–descriptor model was obtained for the DB–225MS stationary phase while a three–parametric model was proposed for both the HP5–MS and HP–1 columns. Models were validated by means of the leave–one–out and leave–many–out cross–validation procedures, as well as other validation criteria. Moreover, in order to accomplish the principles proposed by the Organization for Economic Co–operation and Development (OECD), the model’s predictive ability was measured by predicting retention indices of the external test set. The applicability domain was properly defined and the interpretation of each of the molecular descriptors used in this study was provided.Fil: Rojas Villa, Cristian Xavier. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; ArgentinaFil: Duchowicz, Pablo Román. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; ArgentinaFil: Tripaldi, P.. Universidad de Azuay; EcuadorFil: Pis Diez, Reinaldo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Centro de Química Inorgánica "Dr. Pedro J. Aymonino". Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Centro de Química Inorgánica "Dr. Pedro J. Aymonino"; Argentin

    QSAR analysis for the inhibition of the mutagenic activity by anthocyanin derivatives

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    Flavonoid compounds modulate the cytochrome P450 3A4 enzyme activity and inhibit the mutagenic activity of mammalian cells, preventing carcinogen activation and cellular DNA damage. In this work, the quantitative structure-activity relationships (QSAR) theory is applied to predict the cytochrome P450 3A4 inhibition constant by anthocyanin derivatives. Different freely available software calculates 102,260 non-conformational molecular descriptors. A training set of 12 compounds is used to calibrate the best univariable linear regression models, while a test set of 4 compounds is used to explore their predictive capability. The present results are compared with previously reported ones by using 3D-QSAR, thus demonstrating that the proposed topological QSAR models achieve acceptable statistical quality. The proposed model provides a prospective QSAR guide for the search of new anthocyanin derivatives possessing high or low predicted mutagenicity.Fil: Szewczuk, Nicolas Alejadro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; ArgentinaFil: Duchowicz, Pablo Román. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; ArgentinaFil: Pomilio, Alicia Beatriz. Universidad de Buenos Aires. Facultad de Farmacia y Bioquímica. Departamento de Bioquímica Clínica; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentin

    New Molecular Descriptors based upon the Euler Equations for Chemical Graphs

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    The Euler equations for the chemical graphs are an extension of such equations for the polyhedra. These equations admit several potential forms of molecular descriptors that can be used in the characterizations of the properties of polycyclic aromatic hydrocarbons (PAH) in a typical Quantitative Structure Property–Activity Relationship (QSPR-QSAR). In this paper we describe the nature of these Euler relations for hydrocarbon graphs and the descriptors they admit, applying them to predict 37 boiling points (BP), 26 n-octanol/water partition coefficients (log(kow)), and 47 retention time indexes (RI) for reversed-phase liquid chromatography analysis. Final results suggest that these new descriptors can be used to complement others in a QSPR-QSAR study.Facultad de Ciencias Exacta

    Partial Order Ranking for the aqueous toxicity of aromatic mixtures

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    We apply a predictive method based on Partial Order Ranking that employs a single molecular descriptor in the model and that is simple enough to perform calculations by hand. A comparison of this procedure with results obtained from the least squares technique is carried out, using aqueous toxicity values elicited by 67 compounds and their aromatic mixtures, and the octanol/water partition coefficient as structural descriptor. Both techniques verify that, by means of a previous classification of the compounds in polar and non-polar groups, it is possible to predict the joint toxicological effect.Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicada

    Structure-toxicity relationships for aliphatic compounds based on Correlation Weighting of Local Graph Invariants

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    Quantitative Structure-Activity Relationships based on molecular descriptors calculated with Correlation Weights of Local Graph Invariants were developed to model the toxicity of aliphatic compounds to the 50% population growth inhibition. The relationships were computed on the basis of Labeled Hydrogen- Filled Graphs and correlation weights were obtained by an optimization to render as large as possible correlation coefficients between log(IGC 50-1) and descriptors calculated with correlation weights. Morgan extended connectivity indices of zero, first, and second orders, paths of lengths two and three and valence shells of second and third ranges have been tested as local invariants of the Labeled Hydrogen-Filled Graphs. The best quantitative relationship obtained from the optimization of correlation weights is that one based on the valence shell of range two. First, second, and third order fitting equations were determined and statistical results are better than other similar data for the same molecular set.Facultad de Ciencias Exacta

    QSAR modeling of anticancer activity of heterocyclichydrazone

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    In this study, validated PLS-DA models that discriminate heterocyclichydrazones with potent anticancer activity (GI50/IC50=50x10- 6M) against the cancer cell lines HCT-116 (colon), OVCAR-8 (human ovary), HL-60 (leukemia), and SF-295 (glioblastoma) were developed. A dataset of 24-a-(N)-heterocyclichydrazones and 14 N-acylhydrazonyl-thienyl and various global and local reactivity descriptors were used for modeling. The best models classified for training and test sets with an accuracy range between 67-100%, a class specificity and sensitivity range between 71-100%, error rate range between 0-0.27, and nonerror rate range between 0.73-1.0. An external set of 20 compounds was predicted and the models showed which new compounds are not suggested for further biological investigation. The molecular properties with impact on the modeled endpoints show that the antitumor activity can be improved with electron-acceptor N-acylhydrazonyl-thienyl derivatives and a-(N)-heterocyclichydrazones with moderate electron-donating character.Fil: Rodríguez, María Rosa. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet Noa Sur. Centro Regional de Energia y Ambiente Para El Desarrollo Sustentable. - Universidad Nacional de Catamarca. Centro Regional de Energia y Ambiente Para El Desarrollo Sustentable.; ArgentinaFil: Duchowicz, Pablo Román. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; ArgentinaFil: Comelli, Nieves Carolina. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet Noa Sur. Centro Regional de Energia y Ambiente Para El Desarrollo Sustentable. - Universidad Nacional de Catamarca. Centro Regional de Energia y Ambiente Para El Desarrollo Sustentable.; Argentin

    QSAR study for carcinogenicity in a large set of organic compounds

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    In our continuing efforts to find out acceptable Absorption, Distribution, Metabolization, Elimination and Toxicity (ADMET) properties of organic compounds, we establish linear QSAR models for the carcinogenic potential prediction of 1464 compounds taken from the "Galvez data set", that include many marketed drugs. More than a thousand of geometry-independent molecular descriptors are simultaneously analyzed, obtained with the softwares E-Dragon and Recon. The variable subset selection method employed is the Replacement Method, and also the improved version Enhanced Replacement Method. The established models are properly validated through an external test set of compounds, and by means of the Leave-Group-Out Cross Validation method. In addition, we apply the Y-Randomization strategy and analyze the Applicability Domain of the developed model. Finally, we compare the results obtained in present study with the previous ones from the literature. The novelty of present work relies on the development of an alternative predictive structure-carcinogenicity relationship in a large heterogeneous set of organic compounds, by only using a reduced number of geometry independent molecular descriptors.Fil: Duchowicz, Pablo Román. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; ArgentinaFil: Comelli, Nieves Carolina. Universidad Nacional de Catamarca. Facultad de Ciencias Agrarias; ArgentinaFil: Ortiz, Erlinda del Valle. Universidad Nacional de Catamarca. Facultad de Tecnología y Ciencias Aplicadas; ArgentinaFil: Castro, Eduardo Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas; Argentin
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