Rivality index neighbourhood algorithm with density and distances weighted schemes for the building of robust QSAR classification models with high reliable applicability domain

The rivality index (RI) is a normalized distance measurement between a molecule and their first nearest neighbours providing a robust prediction of the activity of a molecule based on the known activity of their nearest neighbours. Negative values of the RI describe molecules that would be correctly classified by a statistic algorithm and, vice versa, positive values of this index describe those molecules detected as outliers by the classification algorithms. In this paper, we have described a classification algorithm based on the RI and we have proposed four weighted schemes (kernels) for its calculation based on the measuring of different characteristics of the neighbourhood of molecules for each molecule of the dataset at established values of the threshold of neighbours. The results obtained have demonstrated that the proposed classification algorithm, based on the RI, generates more reliable and robust classification models than many of the more used and well-known machine learning algorithms. These results have been validated and corroborated by using 20 balanced and unbalanced benchmark datasets of different sizes and modelability. The classification models generated provide valuable information about the molecules of the dataset, the applicability domain of the models and the reliability of the predictions.     

Induction of decision trees using genetic programming for modelling ecotoxicity data: adaptive discretization of real-valued endpoints

Recent literature has demonstrated the applicability of genetic programming to induction of decision trees for modelling toxicity endpoints. Compared with other decision tree induction techniques that are based upon recursive partitioning employing greedy searches to choose the best splitting attribute and value at each node that will necessarily miss regions of the search space, the genetic programming based approach can overcome the problem. However, the method still requires the discretization of the often continuous-valued toxicity endpoints prior to the tree induction. A novel extension of this method, YAdapt, is introduced in this work which models the original continuous endpoint by adaptively finding suitable ranges to describe the endpoints during the tree induction process, removing the need for discretization prior to tree induction and allowing the ordinal nature of the endpoint to be taken into account in the models built.     

Testing an alternative search algorithm for compound identification with the ‘Wiley Registry of Tandem Mass Spectral Data,MSforID’

A tandem mass spectral database system consists of a library of reference spectra and a search program. State‐of‐the‐art search programs show a high tolerance for variability in compound‐specific fragmentation patterns produced by collision‐induced decomposition and enable sensitive and specific ‘identity search’. In this communication, performance characteristics of two search algorithms combined with the ‘Wiley Registry of Tandem Mass Spectral Data, MSforID’ (Wiley Registry MSMS, John Wiley and Sons, Hoboken, NJ, USA) were evaluated. The search algorithms tested were the MSMS search algorithm implemented in the NIST MS Search program 2.0g (NIST, Gaithersburg, MD, USA) and the MSforID algorithm (John Wiley and Sons, Hoboken, NJ, USA). Sample spectra were acquired on different instruments and, thus, covered a broad range of possible experimental conditions or were generated in silico. For each algorithm, more than 30 000 matches were performed. Statistical evaluation of the library search results revealed that principally both search algorithms can be combined with the Wiley Registry MSMS to create a reliable identification tool. It appears, however, that a higher degree of spectral similarity is necessary to obtain a correct match with the NIST MS Search program. This characteristic of the NIST MS Search program has a positive effect on specificity as it helps to avoid false positive matches (type I errors), but reduces sensitivity. Thus, particularly with sample spectra acquired on instruments differing in their setup from tandem‐in‐space type fragmentation, a comparably higher number of false negative matches (type II errors) were observed by searching the Wiley Registry MSMS. Copyright © 2013 John Wiley & Sons, Ltd.     

Assessing Solvation Effects on Chemical Reactions with Globally Optimized Solvent Clusters

We have examined the influence of water solvent on the Menshutkin reaction of methyl chloride with ammonia by performing static, quantum chemical calculations. We have employed large, explicit, and globally structure‐optimized water clusters around the reaction center, in a mixed explicit/implicit solvent model. This approach deliberately deviates from attempts to capture the most likely solvent‐molecule distribution around a reaction center. Instead, it explores extremes on the scale of rearrangement speed in terms of the surrounding solvent cluster, relative to the reaction progress itself. A comparison to traditional theoretical and experimental results enables us to quantify the energy penalty that is induced by the inability of the water cluster to instantaneously and completely follow the reaction progress. In addition, the influence of water clusters on the reaction energy profile can be much larger than merely changing it somewhat. Certain clusters can completely annihilate the sizeable activation barrier of 23.5 kcal mol^?1.     

Fast Determination of Phenanthrene in Soil by Gas Chromatography-Mass Spectrometry Using Chemometric Resolution and Standard Addition Method

A method for fast determination of the component in complex samples by using gas chromatography‐mass spectrometry (GC‐MS) was developed and used for quantitative analysis of phenanthrene in soils. In the method, window independent component analysis (WICA) was used for resolving the mass spectrum and non‐negative immune algorithm (NNIA) was employed for obtaining the chromatographic profile. Therefore, spectral and chromatographic information of a specific component can be obtained from the measured GC‐MS data of overlapping and high background. Six soil samples collected from different places were analyzed. The tedious pretreatments in preparing the samples and the elution in the separation were simplified for speeding up the analysis. Due to the complexity of the matrix, standard addition method was adopted for the final quantification. The applicability of the method was validated with a spiked sample and the results of the six samples are reasonable.     

Calculations of dynamic dipole polarizabilities of Li and Na atoms in debye plasma using the model potential technique

The effects of Debye plasma on the frequency‐dependent polarizabilities of Li and Na atoms are investigated using symplectic algorithm within the framework of the pseudostate summation technique. Dynamic dipole polarizabilities of Li (2s ²S) and Na(3s ²S) as functions of scaled number density of the plasma electrons for arbitrary plasma temperature are presented. Screening effects on the resonance frequencies are also presented. In free‐atomic cases, our calculated results are comparable with the reported theoretical and experimental predictions. © 2012 Wiley Periodicals, Inc.