Integration of algebra and chemistry concepts with molecular descriptors: A problem-based-learning exercise

A problem-based learning experience integrating mathematical concepts of linear and abstract algebra for undergraduate chemistry students is presented. The pedagogical framework was focused on the conceptual understanding of the vector space, graph theory and matrix algebra as a tool to obtain chemical information. The students were capable to solve a problem of physicochemical properties prediction through the calculation of molecular descriptors of the TOMOCOMD (acronym for TOpological MOlecular COMputational Design) approach. A “scientific congress” was organized by students to expose the results of the research. This evaluation strategy stimulated the self- and co-evaluation. The proposed experience demonstrated an enhanced learning compared to the traditional model.En este trabajo se presenta una experiencia de de aprendizaje basado en problemas que integra conceptos matemáticos de algebra lineal y abstracta para estudiante de pregrado de química. El marco pedagógico se enfocó en el entendimiento conceptual de espacios vectoriales, teoría de grafos y álgebra matricial como una herramienta para obtener información química. Los estudiantes fueron capaces de resolver un problema de predicción de propiedades fisicoquímicas a través del cálculo de descriptores del esquema TOMOCOMD (siglas en inglés de TOpological MOlecular COMputational Design). Los estudiantes organizaron un “congreso científico” para exponer los resultados de la investigación. Esta evaluación estimuló el auto- y co-evaluación. La experiencia propuesta demostró un aprendizaje mayor al ser comparado con el modelo tradicional

Prediction of ADME properties, Part 1: Classification models to predict Caco-2 cell permeability using atom-based bilinear indices

The prediction of the permeability through cultured Caco-2 cells (an often-used in vitro model for drug absorption) is carried out using theoretical models. Atom-based bilinear indices and linear discriminant analysis (LDA) are used to obtain quantitative models, which discriminate between higher absorption and moderate-poorer absorption compounds, form a database of measured PCaco-2 from a large data set with 157 structurally diverse compounds. We develop two LDA models with more than 90% of accuracy for training and test set; the best model presents accuracy of 91.79% and 91.30%, respectively. The results achieved in this work compare favourably with other approaches previously published in the technical literature. The percentage of good correlation was of 80%, in the virtual screening of 241 drugs with the reported values of the percentage of human intestinal absorption (HIA). Finally, we can say that, the present “in silico” method would be a valuabletool in the drug discovery process in order to select themolecules with the greatest chance before synthesis

Atom-based 3D-chiral quadratic indices. Part 3: prediction of the binding affinity of the stereoisomers of fenoterolto the β2 adrenergic receptor

The non-stochastic and stochastic atom-based three dimensional(3D)-chiral quadratic indices are applied to predictthe binding affinities of 26 stereoisomers of fenoterol with the  β2-adrenoceptor (β2-AR). The prediction of β2-ARbinding affinities of the stereoisomers is carried out by multiple linear regression analysis. Two statistically significant QSAR models are obtained when non-stochastic (R 2= 0.941 and  s = 0.19) and stochastic (R2 = 0.947 and s =0.18) 3D-chiral quadratic indices are used. These models show adequate predictive power (assessed by the leaveone-out cross-validation experiment), yielding values of  q2= 0.909 ( scv = 0.219) and q2 = 0.917 (scv = 0.208), respectively. These models compare favorably with a 3D-QSAR equation obtained with the CoMFA method (R 2 = 0.920, q2= 0.847 and  scv = 0.309). The results of our work demonstrate the usefulness of our topological approach for theprediction of biological activity, even in those studies in which the three-dimensional configuration of the chemicalsplay an important role in the bioactivity

Orthotropic Piezoelectricity in 2D Nanocellulose

The control of electromechanical responses within bonding regions is essential to face frontier challenges in nanotechnologies, such as molecular electronics and biotechnology. Here, we present I\b{eta}-nanocellulose as a potentially new orthotropic 2D piezoelectric crystal. The predicted in-layer piezoelectricity is originated on a sui-generis hydrogen bonds pattern. Upon this fact and by using a combination of ab-initio and ad-hoc models, we introduce a description of electrical profiles along chemical bonds. Such developments lead to obtain a rationale for modelling the extended piezoelectric effect originated within bond scales. The order of magnitude estimated for the 2D I\b{eta}-nanocellulose piezoelectric response, ~pm V-1, ranks this material at the level of currently used piezoelectric energy generators and new artificial 2D designs. Such finding would be crucial for developing alternative materials to drive emerging nanotechnologies.Comment: 5 figures included. Supp. Mat. available on the online version: https://www.nature.com/articles/srep34616, Others on: http://www.nanowerk.com/nanotechnology-news/newsid=44806.ph

La enzima tirosinasa: 2. Inhibidores de origen natural y sintético

En este trabajo se abordan de manera general los compuestosinhibidores de la tirosinasa, la enzima limitante y el pilar fundamental para el control de la pigmentación en la piel de los humanos. Se presentan las principales características de los agentes despigmentantes utilizados en la práctica médica. También se muestran los compuestos estudiados hasta la actualidad, los que son agrupados teniendo en cuenta su origen: naturales, sintéticos y fármacos con otros usos terapéuticos, descubiertos con actividadinhibidora contra la enzima. Finalmente se discuten los últimos avances en el campo de la quimioinformática y la modelación molecular relacionados con el estudio de la enzima y sus inhibidores

New set of 2D/3D thermodynamic indices for proteins. A formalism based on "Molten Globule" theory

We define eight new macromolecular indices, and several related descriptors for proteins. The coarse grained methodology used for its deduction ensures its fast execution and becomes a powerful potential tool to explore large databases of protein structures. The indices are intended for stability studies, predicting Φ-values, predicting folding rate constants, protein QSAR/QSPR as well as protein alignment studies. Also, these indices could be used as scoring function in protein-protein docking or 3D protein structure prediction algorithms and any others applications which need a numerical code for proteins and/or residues from 2D or 3D format

Orthotropic Piezoelectricity in 2D Nanocellulose

The control of electromechanical responses within bonding regions is essential to face frontier challenges in nanotechnologies, such as molecular electronics and biotechnology. Here, we present Iβ-nanocellulose as a potentially new orthotropic 2D piezoelectric crystal. The predicted in-layer piezoelectricity is originated on a sui-generis hydrogen bonds pattern. Upon this fact and by using a combination of ab-initio and ad-hoc models, we introduce a description of electrical profiles along chemical bonds. Such developments lead to obtain a rationale for modelling the extended piezoelectric effect originated within bond scales. The order of magnitude estimated for the 2D Iβ-nanocellulose piezoelectric response, ∼pm V, ranks this material at the level of currently used piezoelectric energy generators and new artificial 2D designs. Such finding would be crucial for developing alternative materials to drive emerging nanotechnologies

Comparación de modelos novedosos de proximidad en Quimioinformática

El presente trabajo comprende la implementación computacional en el ambiente Java de 21 modelos de proximidad para usarlos en experimentos simulados de busqueda de similitud; nueve de estos modelos son novedosos en Quimioinformática pues proceden del área de la Psicología, los otros 12 son medidas ya establecidas de la literatura especializada. Posteriormente, las medidas de similitud fueron comparadas y validadas en la “recuperación temprana” usando nueve conjuntos de datos de la Química Medicinal, representados por descriptores numéricos seleccionados por Aprendizaje Automático y un algoritmo de búsqueda eficiente. Los resultados muestran que en tendencia promedio los nuevos modelos se comportan superiormente a los de referencia y que más de la mitad de los mismos se situan entre los diez modelos mas potentes

Metodología multi-modal en relaciones cuantitativas estructura-actividad

Los estudios QSAR definidos en la literatura están basados en enfoques uni-modales, dejando de analizar conjuntos de datos que contienen distintas informaciones químicas. En esta investigación se propone aplicar por primera vez y analizar el comportamiento del enfoque multi-modal en el desarrollo de estudios QSAR. Para este fin se utilizó una base de compuestos con actividad hepatotóxica, a partir de la cual se construyeron cuatro modalidades considerando distintos descriptores moleculares basados en diversas teorías y enfoques. Se desarrollaron varios modelos usando los enfoques uni-modales y multi-modales utilizando algoritmos de clasificación reportados en la literatura e implementados en el lenguaje R. Los parámetros de cada uno de los algoritmos se optimizaron con el procedimiento "parametertuningwithrepeatedgrid-searchcross-validation", mientras la validación de dichos modelos se realizó mediante validación cruzada de 10 pliegues con 10 repeticiones. Estadísticamente se comprobó que el enfoque multimodal mejora el desempeño de los modelos predictivos comparado con algunos de los modelos derivados de los conjuntos de datos con modalidades individuales.Palabras Clave: enfoque multi-modal, enfoque uni-modal, estudios QSAR.</p

Atom, atom-type, and total linear indices of the "molecular pseudograph's atom adjacency matrix": Application to QSPR/QSAR studies of organic compounds

In this paper we describe the application in QSPR/QSAR studies of a new group of molecular descriptors: atom, atom-type and total linear indices of the molecular pseudograph's atom adjacency matrix. These novel molecular descriptors were used for the prediction of boiling point and partition coefficient (log P), specific rate constant (log k), and antibacterial activity of 28 alkyl-alcohols and 34 derivatives of 2-furylethylenes, respectively. For this purpose two quantitative models were obtained to describe the alkyl-alcohols' boiling points. The first one includes only two total linear indices and showed a good behavior from a statistical point of view (R2 = 0.984, s = 3.78, F = 748.57, q2 = 0.981, and scv = 3.91). The second one includes four variables [3 global and 1 local (heteroatom) linear indices] and it showed an improvement in the description of physical property (R 2 = 0.9934, s = 2.48, F = 871.96, q2 = 0.990, and s cv = 2.79). Later, linear multiple regression analysis was also used to describe log P and log k of the 2-furyl-ethylenes derivatives. These models were statistically significant [(R2 = 0.984, s = 0.143, and F = 113.38) and (R2 = 0.973, s = 0.26 and F = 161.22), respectively] and showed very good stability to data variation in leave-one-out (LOO) cross-validation experiment [(q2 = 0.93.8 and scv = 0.178) and (q2 = 0.948 and scv = 0.33), respectively]. Finally, a linear discriminant model for classifying antibacterial activity of these compounds was also achieved with the use of the atom and atom-type linear indices. The global percent of good classification in training and external test set obtained was of 94.12% and 100.0%, respectively. The comparison with other approaches (connectivity indices, total and local spectral moments, quantum chemical descriptors, topographic indices and Estate/biomolecular encounter parameters) reveals a good behavior of our method. The approach described in this paper appears to be a very promising structural invariant, useful for QSPR/QSAR studies and computer-aided "rational" drug design.Instituto de Investigaciones Fisicoquímicas Teóricas y Aplicadas (INIFTA