1,721,355 research outputs found
WHIM descriptors of shape
No full textWHIM descriptors are 3D structural descriptors obtained from the (x,y,z)-atomic coordinates of a molecular conformation of a chemical, and are used successfully in QSAR modelling. They are built in so as to capture relevant 3D information regarding different features of molecular structure: size, shape, symmetry and atom distribution.
Different weights are used to obtain particular information for each set of descriptors.
Recently, some doubts have been raised in the literature regarding the ability of Weighted
Holistic Invariant Molecular (WHIM) descriptors of shape (the K non-directional WHIM descriptors) to describe the difference between linear and non-linear molecules. A data set of seventy aliphatic and aromatic chemicals of different shape (linear and branched
congeners) has been studied here, and is represented by K descriptors (global nondirectional WHIM descriptors of shape) based on different weights. The K descriptors range from 0 for a spherical molecule to 1 for a perfectly linear molecule. The present
study confirms the findings, already reported by the author, that the WHIM descriptors of shape (K) are unequivocally able to differentiate linear and non-linear molecules
Principles of QSAR Modeling
No full textAt the end of her academic career, the author summarizes the main aspects of QSAR modeling, giving comments and suggestions according to her 23 years’ experience in QSAR research on environmental topics. The focus is mainly on Multiple Linear Regression, particularly Ordinary Least Squares, using a Genetic Algorithm for variable selection from various theoretical molecular descriptors, but
the comments can be useful also for other QSAR methods. The need for rigorous validation, also external, and for applicability domain check to guarantee predictivity and reliability of QSAR models is particularly highlighted. The commented approach is the “predictive” one, based on chemometrics, and is usefully applied to the prioritization of environmental pollutants. All the discussed points and
the author’s ideas are implemented in the software QSARINS, as a legacy to the QSAR community
Introduction to the need of Alternative Methods in REACH
No full textIn vitro and in silico methods are foreseen in the EU regulation REACH, to prioritize more dangerous compounds, to focus expensive experiments, by reducing animal tests and to fill the data gaps. A brief historical introduction of QSAR modelling and the importance of model validation according to the OECD principles for reliable predictions is presented
Predictive QSAR modelling for Screening and Prioritization of Environmental Organic Pollutants
No full textQSAR models are mainly useful in the prediction of data for chemicals without experimental information, those not yet tested or even not yet synthesized. However, QSAR models must be carefully verified for their reliability in the specific context of application to be successfully used and not misused. The OECD principles for QSAR model validation have established crucial points for prediction reliability, mainly model reproducibility, external predictivity and applicability domain checking. Particular attention must be paid to QSAR models’ predictive performance, when the models are applied to the screening of large chemical sets, the specific aim being to focus on the most hazardous to prioritize them for experimental tests. Different approaches for splitting the available experimental data sets and various statistical parameters can be used to verify a model’s external predictivity. These fundamental aspects of QSAR model reliability are commented on, based on several examples of application to various environmental organic pollutants, such as Persistent, Bioaccumulative and Toxic (PBTs) chemicals, Endocrine Disruptors (EDs), flame retardants and polyfluorinated chemicals. Some of these compounds are included in the priority list of Persistent Organic Pollutants (POPs) and/or are among the substances of very high concern (SVHCs), which require authorization in REACH. Therefore methods are needed for an early identification of these pollutants. The QSAR models presented could be particularly useful for screening and prioritisation purposes, also a priori in a green chemistry approach, in the design of new products as safer alternatives to existing dangerous chemicals (“benign by design”)
QSAR e la nuova normativa europea REACH
No full textThe predictive QSAR (Quantitative Structure-Activity Relationships), whose basic principles are here illustrated, is a valid tool for the prediction of physico-chemical
properties and biological activities (toxicities, etc.) of chemicals that lack of experimental data. This modelling approach is here presented highlighting the potential
applications to fill the data gaps and for hazard assessment in the new European legislation Reach
External Evaluation of QSAR Models, in Addition to Cross-Validation: Verification of Predictive Capability on Totally New Chemicals
No full textThe necessity to externally validate QSAR models is highlighted with example of models stable by cross-validation but not predictive for new chemical
BEAM: Bridging effect assessment of mixtures to ecosystem situations and regulation. EU-FP5thEVK1-1999-000552000-2003
No full textEnvironmental Quality Standards are typically set up for individual chemicals. Nevertheless, natural environments are not exposed to individual chemicals but to complex mixtures of chemicals of various origin (e.g. industry, agriculture, urban sewage).
Therefore, there is the need for developing procedures capable to derive Environmental Qual-ity Standards for mixtures of chemicals likely to occur in the environment. The BEAM pro-ject aims at (a) achieving more realism in the analysis of ecosystem multiple exposure and combined effect situations; (b) to provide new mixture toxicity assessment tools and (c) to explore the options for implementation of mixture toxicity assessment into regulation.
In this case, a “priority mixture” is not necessarily a mixture of “priority chemicals”, but a combination of chemicals that can be often discharged together by relevant typologies of hu-man activities. Procedures for assessing exposure to mixtures of different origin (agricultural, industrial, urban) are proposed by BEAM. The effects of a mixture can be predicted by the two conceptual models of Concentration Ad-dition (CA), applicable to chemicals with the same mode of action, and Independent Action (IA), applicable to chemicals with different mode of action. Both concepts make use of in-formations on the toxicities of all the individual mixture components, which implies, that the composition of the mixture has to be known qualitatively as well as quantitatively.
Experimental results of BEAM, and of the previous project PREDICT show that, when deal-ing with standard single species assays, CA typically predicts a higher mixture toxicity in comparison with IA
Evaluation of different statistical approaches to the validation of Quantitative Structure-Activity Relationships
No full textECVAM, JRC, Ispra. http://ecb.jrc.it/QSAR
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