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

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

Quoted spreads and trade imbalance dynamics in the European treasury bond market

Using high-frequency transaction data for the three largest European markets (France, Germany and Italy), this paper documents the existence of an asymmetric relationship between market liquidity and trading imbalances: when quoted spreads rise (fall) and liquidity falls (increases) buy (sell) rders tend to prevail. Risk-averse market-makers, with inventory-depletion risk being their main concern, tend to quote wider narrower) spreads when they think bond appreciation is more (less) likely to occur. It is also found that the probability of being in a specific regime is related to observable bond market characteristics, tock market volatility, macroeconomic releases and liquidity management operations of the monetary authorities

Predicting Skin Permeability by means of Computational Approaches : Reliability and Caveats in Pharmaceutical Studies

© 2019 American Chemical Society.The skin is the main barrier between the internal body environment and the external one. The characteristics of this barrier and its properties are able to modify and affect drug delivery and chemical toxicity parameters. Therefore, it is not surprising that permeability of many different compounds has been measured through several in vitro and in vivo techniques. Moreover, many different in silico approaches have been used to identify the correlation between the structure of the permeants and their permeability, to reproduce the skin behavior, and to predict the ability of specific chemicals to permeate this barrier. A significant number of issues, like interlaboratory variability, experimental conditions, data set building rationales, and skin site of origin and hydration, still prevent us from obtaining a definitive predictive skin permeability model. This review wants to show the main advances and the principal approaches in computational methods used to predict this property, to enlighten the main issues that have arisen, and to address the challenges to develop in future research.Peer reviewedFinal Accepted Versio

QSAR study for carcinogenicity in a large set of organic compounds

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

Model fitting for small skin permeability data sets: hyperparameter optimisation in Gaussian Process Regression

This is the pre-peer reviewed version of the following article: Parivash Ashrafi, Yi Sun, Neil Davey, Roderick G. Adams, Simon C. Wilkinson, and Gary Patrick Moss, ‘Model fitting for small skin permeability data sets: hyperparameter optimisation in Gaussian Process Regression’, Journal of Pharmacy and Pharmacology, Vol. 70 (3): 361-373, March 2018, which has been published in final form at https://doi.org/10.1111/jphp.12863. Under embargo until 17 January 2019. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.Objectives The aim of this study was to investigate how to improve predictions from Gaussian Process models by optimising the model hyperparameters. Methods Optimisation methods, including Grid Search, Conjugate Gradient, Random Search, Evolutionary Algorithm and Hyper-prior, were evaluated and applied to previously published data. Data sets were also altered in a structured manner to reduce their size, which retained the range, or ‘chemical space’ of the key descriptors to assess the effect of the data range on model quality. Key findings The Hyper-prior Smoothbox kernel results in the best models for the majority of data sets, and they exhibited significantly better performance than benchmark quantitative structure–permeability relationship (QSPR) models. When the data sets were systematically reduced in size, the different optimisation methods generally retained their statistical quality, whereas benchmark QSPR models performed poorly. Conclusions The design of the data set, and possibly also the approach to validation of the model, is critical in the development of improved models. The size of the data set, if carefully controlled, was not generally a significant factor for these models and that models of excellent statistical quality could be produced from substantially smaller data sets.Peer reviewedFinal Accepted Versio

Quoted Spreads and Trade Imbalance Dynamics in the European Treasury Bond Market

Using high-frequency transaction data for the three largest European markets (France, Germany and Italy), this paper documents the existence of an asymmetric relationship between market liquidity and trading imbalances: when quoted spreads rise (fall) and liquidity falls (increases) buy (sell) orders tend to prevail. Risk-averse market-makers, with inventory-depletion risk being their main concern, tend to quote wider (narrower) spreads when they think bond appreciation is more (less) likely to occur. It is also found that the probability of being in a specific regime is related to observable bond market characteristics, stock market volatility, macroeconomic releases and liquidity management operations of the monetary authorities.liquidity, trading activity, treasury bond market, Europe, commonality

Modeling of the Acute Toxicity of Benzene Derivatives by Complementary QSAR Methods

A data set containing acute toxicity values (96-h LC50) of 69 substituted benzenes for fathead minnow (Pimephales promelas) was investigated with two Quantitative Structure- Activity Relationship (QSAR) models, either using or not using molecular descriptors, respectively. Recursive Neural Networks (RNN) derive a QSAR by direct treatment of the molecular structure, described through an appropriate graphical tool (variable-size labeled rooted ordered trees) by defining suitable representation rules. The input trees are encoded by an adaptive process able to learn, by tuning its free parameters, from a given set of structureactivity training examples. Owing to the use of a flexible encoding approach, the model is target invariant and does not need a priori definition of molecular descriptors. The results obtained in this study were analyzed together with those of a model based on molecular descriptors, i.e. a Multiple Linear Regression (MLR) model using CROatian MultiRegression selection of descriptors (CROMRsel). The comparison revealed interesting similarities that could lead to the development of a combined approach, exploiting the complementary characteristics of the two approaches