Biomedical subjects

Emilio Benfenati

Publications and source records attributed to Emilio Benfenati.

At least 19 recordsLinked to original sources

PubMed2006

Optimisation of correlation weights of SMILES invariants for modelling oral quail toxicity.

The SMILES (simplified molecular input line entry system) nomenclature was used to elucidate the molecular structure in constructing the quantitative structure-property/activity relationships (QSPR/QSAR) for predicting quail toxicity after oral exposure. The presence of chemical elements in different electronic states (e.g., C, c, O, o, Cl, Br, etc.) and of different covalent bonds (i.e., -,=, and #) was used as local invariants. Combinations of different presence/absence codes for local features of the SMILES were used as global invariants. The statistical characteristics of this model are n=97, r(2)=0.755, s=0.445, F=293 (training set); n=18, r(2)=0.731, s=0.587, F=43 (test set).

Administration, Oral↗

PubMed2006

Virtual screening for aryl hydrocarbon receptor binding prediction.

The overall goal of this study has been to validate computational models for predicting aryl hydrocarbon receptor (AhR) binding. Due to the unavailability of the AhR X-ray crystal structure we have decided to use QSARs models for the binding prediction virtual screening. We have built up CoMFA, Volsurf, and HQSAR models using as a training set 84 AhR ligands. Additionally, we have built a hybrid model combining two of the final selected models in order to give a single operational system. The results show that CoMFA, VolSurf, HQSAR, and the hybrid models gives good results (R(2) equal to 0.91, 0.79, 0.85, and 0.82 and q(2) 0.62, 0.58, 0.62, and 0.70, respectively). Since the techniques analyzed show a good correlation and good prediction also for an external test set, particularly the HQSAR and the hybrid model, we can conclude that these models can be used for predicting AhR binding in virtual screening.

Dioxins↗

PubMed2006

Preliminary analysis of toxicity of benzoxazinones and their metabolites for folsomia Candida.

The overall objective of this study was to explore the toxicity of benzoxazinone allelochemicals and their metabolites to Folsomia candida (Collembola: Isotomidae) (Willem, 1902). Experimental tests showed transformation products to have more pronounced toxicity than parent compounds. The underlying relationship between the chemical structure and toxicity was then studied using three-dimensional QSAR approaches, and results highlighted the role of the steric contribution.

Animals↗

PubMed2006

QSAR models for Daphnia magna toxicity prediction of benzoxazinone allelochemicals and their transformation products.

The overall objective of this study is the ecotoxicological characterization of the benzoxazinone 2,4-dihydroxy-7-methoxy-1,4-benzoxazin-3-one (DIMBOA), the benzoxazolinones benzoxazolin-2-one (BOA) and 6-methoxybenzoxazolin-2-one (MBOA), and their transformation products: phenoxazinones 2-acetylamino-7-methoxy-3H-phenoxazin-3-one (AAMPO), 2-acetylamino-3H-phenoxazin-3-one (AAPO), 2-amino-7-methoxy-3H-phenoxazin-3-one (AMPO), and 2-amino-3H-phenoxazin-3-one (APO); aminophenol 2-aminophenol AP); acetamide N-(2-hydroxyphenyl)acetamide (HPAA); and malonamic acid amide N-(2-hydroxyphenyl)malonamic acid (HPMA). A comparison between empirical results and theoretical ones using rules-based prediction of toxicity was done, and it can be concluded that only the degradation metabolites exhibited significant ecotoxic effect. Using synthetic pesticides knowledge, several QSAR models were trained with various approaches and descriptors. The models generated exhibited good internal predictive ability (R(cv)2 > 0.6) and were used to predict the toxicity of the natural compounds studied.

Animals↗

PubMed2006

Correlation weighting of valence shells in QSAR analysis of toxicity.

In the rainbow trout (Oncorhynchus mykiss), we studied the acute toxicity LC(50)-96 h of 274 organic pesticides with a wide variety of molecular structures. Optimization of correlation weights of local and global graph invariants (OCWLGI) gave quantitative structure-activity relationships (QSARs) for predicting toxicity. We used a labeled hydrogen-filled graph (LHFG) to elucidate the molecular structure. We also used the extended connectivity of zero ((0)EC(k)), first ((1)EC(k)), and second ((2)EC(k)) order, numbers of path lengths 2 (P2(k)) and 3 (P3(k)) starting from a given vertex in the LHFG, and valence shells of second order (S2(k)). S2(k) is the sum of the degree of vertices at distance 2 from a given vertex k. The presence of three-, five-, and six-member cycles and hydrogen bond indices suggested they might be used as global LHFG invariants. We applied this method to a broad set of pesticides, to predict toxicity for the trout. The best model used weighted S2(k) and global LHFG invariants. Statistical characteristics of this model are as follows: n=233, r(2)=0.7689, r(2)(pred)=0.7688, s=0.75, F=769 (training set); n=41, r(2)=0.6421, r(2)(pred)=0.4241, s=1.14, F=70 (test set).

Animals↗

PubMed2006

QSAR models of quail dietary toxicity based on the graph of atomic orbitals.

Graphs of atomic orbitals (GAOs) have been used to represent molecular structures. We describe rules to convert the labelled hydrogen-filled graphs (LHFGs) into GAOs. The GAO is one possible way of taking account of the structure of atoms (i.e., atomic orbitals, such as 1s(1), 2p(2) and 3d(10)) for QSPR/QSAR analyses. Optimization of correlation weights of local invariants (OCWLI) of the LHFGs and the GAOs was used to obtain a method of quail dietary toxicity modelling. Statistical characteristics of the models based on the OCWLI of GAO are better than those based on the OCWLI of the LHFGs.

Animals↗

PubMed2006

Harmonised pesticide risk trend indicator for food (HAPERITIF): The methodological approach.

To provide a harmonised European approach for pesticide risk indicators, the Sixth EU Framework Programme recently financed the HAIR (HArmonised environmental Indicators for pesticide Risk) project. This paper illustrates the methodology underlying a new indicator-HAPERITIF (HArmonised PEsticide RIsk Trend Indicator for Food), developed in HAIR, for tracking acute and chronic pesticide risk trends for consumers. The acute indicator, HAPERITIF(ac), is based on the ratio between an estimated short-term intake (ESTI), calculated as recommended by the World Health Organisation (WHO), and the acute reference dose (ARfD); the chronic indicator HAPERITIF(chr) is based on the ratio between an estimated daily intake (EDI) and the admissible daily intake (ADI). HAPERITIF can be applied at different levels of aggregation. Each level gives information for proper risk management of pesticides to reduce the risk associated with food consumption. An example of application using realistic scenarios of pesticide treatments on a potato crop in central-northern Italy is reported to illustrate the different steps of HAPERITIF.

Environmental Monitoring↗

PubMed2006

Top-priority fragment QSAR approach in predicting pesticide aquatic toxicity.

In the framework of pesticide risk assessment, a fragment-based QSAR approach is presented to correlate LC50-96 h acute toxicity to the rainbow trout (Oncorhynchus mykiss). While there are other fragment-based modeling routes, our approach exploits the possibility of prioritizing fragments' contributions to toxicity. On the assumption that one fragment might be mainly responsible for the molecular toxicity, we developed a three-stage modeling strategy to select the most important moieties and to establish their priorities at a molecular level. This strategy was tested on a heterogeneous dataset containing 282 pesticides, collected under the EU-funded project Demetra. Quantitative toxicity prediction yielded good results for the training set (R2TR = 0.85) and the test set (R2TS = 0.75). The advantages and limitations of the current priority strategy are examined.

Animals↗

PubMed2005

QSAR models for Daphnia toxicity of pesticides based on combinations of topological parameters of molecular structures.

A topological parameter is defined as an integer value of a given local or global invariant of a molecular graph. We examined three types of local graph invariants, the vertex degrees (0EC), the extended connectivity of first order (1EC), and the numbers of paths of length two (P2), as elementary invariants for construction of quantitative structure-activity relationships (QSAR). We also examined combined invariants, obtained by multiplying one of these three elementary types with another (i.e., [0EC.1EC], [0EC.P2], and [1EC.P2]), as graph invariants. Finally, global invariants were used in the QSAR analyses, codifying the presence and nature of cycles in the molecular structures under consideration. We used the correlation weights of these invariants to obtain optimal descriptors. These descriptors have been used in one-variable models to predict toxicity toward Daphnia magna for a set of pesticides. Statistical characteristics of the best model, based on the correlation weight of local topological parameters (the [0EC.P2]) together with the global topological parameters, are the following: n=220, r2=0.7822, s=0.849, F=783 (training set); n=42, r2=0.7388, s=0.941, F=113 (test set). The role of these topological parameters is discussed.

Animals↗

PubMed2005

Identification of the structural requirements of the receptor-binding affinity of diphenolic azoles to estrogen receptors alpha and beta by three-dimensional quantitative structure-activity relationship and structure-activity relationship analysis.

Three-dimensional (3D) quantitative structure-activity relationship (QSAR) and structure-activity relationship (SAR) analyses were applied concurrently to a data set of highly selective estrogen receptor beta (ERbeta) agonists. The data set consisted of diphenolic azoles characterized by similar structural skeletons but with different binding modes to the estrogen receptor site. Models were developed separately with respect to the relative binding affinities (RBAs) to ERalpha and ERbeta. Steric and electrostatic fields were calculated for a training set of 72 compounds using comparative molecular field analysis (CoMFA). The model developed for ERalpha RBA yielded R2 of 0.91 and q(cv)2 of 0.60. The model developed for ERbeta RBA yielded R2 of 0.95 and q(cv)2 of 0.40. Both models were validated successfully using an external test set of 32 compounds. A new concept of test set evaluation based on the variability of the biological response due to the variability of the living organism has been introduced. The CoMFA analysis was supported by a SAR study. In addition to the most favorable steric and electrostatic regions identified by CoMFA, a number of structural descriptors were identified as being important for binding. These are the number of substituents attached to the main skeleton of each compound, the largest distance between the oxygen atoms of each molecule, and the angle defined by the planes that split the phenyl or the naphthyl and the benzisoxazole or the benzoxazole moiety in a morphometrically longitudinal way.

Azoles↗

PubMed2005

An automated group contribution method in predicting aquatic toxicity: the diatomic fragment approach.

We developed a group contribution method (GCM) to correlate acute toxicity (96 h LC50) for the fathead minnow (Pimephales promelas) for 607 organic chemicals. Unlike most of the existing methods, the new one makes no use of predefined groups as descriptors. A simple general rule is proposed to break down any molecule into diatomic fragments. The entire data set was partitioned three times. Each time, a training set and a test set were obtained with a ratio of 2:1. For each partition quantitative structure-activity relationship, models were developed using Powell's minimization method, multilinear regression, neural networks, and partial least squares. The GCM method achieved a good correlation of the data for both training and test sets, regardless of the partition considered. The method is therefore robust and can be generally applied. Further model improvements are described.

Animals↗

PubMed2004

Volatile organic compounds produced during the aerobic biological processing of municipal solid waste in a pilot plant.

The volatile organic carbon (VOC) and odours emitted during the aerobic biological processing of municipal solid waste (MSW) was studied in a pilot-scale reactor. VOCs were detected by different techniques on solid waste samples and the outlet air stream, before and after a biofilter. Organic compounds (alpha-pinene, beta-myrcene, D-limonene) were also measured in condensate water and leachate from the process. Results showed uniformity in the composition of the air in the solid waste samples, air sampled during the process and condensed water, indicating a matrix-derived origin of these compounds. Leachates, however, contained substances with a quite different molecular structure from the compounds identified in the gaseous fraction. Most of the substances in the gaseous effluent had a hydrocarbon-like structure, mainly terpenoids. The odour produced and detected through olfactometry agreed with GC-MS analyses. This was true above all for terpenes.

Air Pollutants↗

PubMed2004

A protocol to select high quality datasets of ecotoxicity values for pesticides.

The key to any QSAR model is the underlying dataset. In order to construct a reliable dataset to develop a QSAR model for pesticide toxicity, we have derived a protocol to critically evaluate the quality of the underlying data. In developing an appropriate protocol that would enable data to be selected in constructing a QSAR, we concentrated on one toxicity end point, the 96 h LC50 from the acute rainbow trout study. This end point is key in pesticide regulation carried out under 91/414/EEC. The dataset used for this exercise was from the US EPA-OPP database.

Animals↗

PubMed2003

Polychlorinated dibenzo-p-dioxins and dibenzofurans in the air of Seveso, Italy, 26 years after the explosion.

This study reports the current levels of polychlorinated dibenzo-p-dioxins (PCDDs) and furans (PCDFs) in air at Seveso, where an explosion in a 2,4,5,-trichlorophenol production reactor occurred 26 years ago. The aims were to assess if residues of the 2,3,7,8-tetrachlorodibenzo-p-dioxin (2,3,7,8-TCDD) released during the accident and still present in soil could contaminate the above air and to investigate other potential sources in the area. Long-term air collection was carried out in zones A and B in Seveso and in a reference location in Milan, and samples were analyzed for PCDD and PCDF concentrations by gas chromatography-mass spectrometry (GC-MS). Experimental results showed that no important contribution to the air concentrations is due to the soil contamination and that contemporary sources essentially control the atmospheric burden of PCDDs and PCDFs in the Seveso area. The theoretical release of 2,3,7,8-TCDD from the soils of zones A and B of Seveso was calculated using the SoilFug model. In the worst case, the model simulated an enrichment in atmospheric 2,3,7,8-TCDD concentrations of 4 and 22% for zones A and B, respectively. The investigation of the potential emission sources in the area indicated that combustion of wood residues from furniture factories may be an additional local source of PCDDs and PCDFs.

Air Pollutants↗

PubMed2003

Database mining with adaptive fuzzy partition: application to the prediction of pesticide toxicity on rats.

A data set of 235 pesticide compounds, divided into three classes according to their toxicity toward rats, was analyzed by a fuzzy logic procedure called adaptive fuzzy partition (AFP). This method allows the establishment of molecular descriptor/chemical activity relationships by dynamically dividing the descriptor space into a set of fuzzily partitioned subspaces. A set of 153 molecular descriptors was analyzed, including topological, physicochemical, quantum mechanical, constitutional, and electronic parameters, and the most relevant descriptors were selected with the help of a procedure combining genetic algorithm concepts and a stepwise method. The ability of this AFP model to classify the three toxicity classes was validated after dividing the data set compounds into training and test sets, including 165 and 70 molecules, respectively. The experimental class was correctly predicted for 76% of the test-set compounds. Furthermore, the most toxic class, particularly important for real applications of the toxicity models, was correctly predicted in 86% of cases. Finally, a comparison between the results obtained by AFP and those obtained by other classic classification techniques showed that AFP improved the predictive power of the proposed models.

Algorithms↗

PubMed2002

Chemical analysis, distributed modelling and risk indices. Three fundamental pillars in Risk Assessment.

The Risk Assessment (RA) of pollutants from contaminated sites and landfills is a major environmental issue in Europe, due to the large number of sites and to the importance of groundwater protection. The high number of contaminants and the lack of knowledge of their environmental properties and their ecotoxicological and toxicological characteristics complicate the problem. Furthermore, this information about the chemicals has to be combined with the data relative to the territory and to the targets. We will describe the problems relative to each topic involved in the process, and we will propose an integrated methodology for coping with these problems, using state-of-the-art approaches in each part of the protocol. This methodology has been applied in several real cases.

Arsenic↗

PubMed2002

Polychlorinated dibenzo-p-dioxins and dibenzofurans in River Po sediments.

The River Po is the main Italian river draining one of the most populated and industrialised regions in Italy. As part of a monitoring project to assess environmental quality in the River Po, we measured the concentrations of polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs) in bottom sediments collected along the whole course of the river, from the spring to the delta, downstream from the confluence of its main tributaries. The aim was to investigate the level of contamination in the main Italian river and the contribution of contaminant loads from the subbasins. Composite sediment samples were collected in summer and winter surveys in low-flow water conditions and analysed by HRGC-HRMS for PCDD and PCDF homologue groups and for the 2,3,7,8-substituted congeners. The spatial trend observed in the Po River for PCDD and PCDF concentrations varied depending on the load of contaminants received from the tributaries and the processes of sedimentation. The sum of PCDD and PCDF concentrations, and the toxic equivalent content, ranged from 121 to 814 and from 1.3 to 13 ng/kg dry weight sediment, respectively. These levels of contamination seem lower than in the sediments of rivers draining highly industrialised areas. The PCDD and PCDF homologue profiles in all the samples were very similar, suggesting a common source of this contamination in the River Po. Principal component analysis suggested that widespread sources, such as urban runoff and domestic wastewaters, are probably the main cause of these levels of PCDDs and PCDFs.

Benzofurans↗

PubMedDate not supplied

The importance of scaling in data mining for toxicity prediction.

While mining a data set of 554 chemicals in order to extract information on their toxicity value, we faced the problem of scaling all the data. There are numerous different approaches to this procedure, and in most cases the choice greatly influences the results. The aim of this paper is 2-fold. First, we propose a universal scaling procedure for acute toxicity in fish according to the Directive 92/32/EEC. Second, we look at how expert preprocessing of the data effects the performance of qualitative structure-activity relationship (QSAR) approach to toxicity prediction.

Animals↗