1,720,978 research outputs found
Molecular quantum similarity in QSAR: applications in computer-aided molecular design
Get PDFLa present tesi està centrada en l'ús de la Teoria de Semblança Quàntica per a calcular descriptors moleculars. Aquests descriptors s'utilitzen com a paràmetres estructurals per a derivar correlacions entre l'estructura i la funció o activitat experimental per a un conjunt de compostos. Els estudis de Relacions Quantitatives Estructura-Activitat són d'especial interès per al disseny racional de molècules assistit per ordinador i, en particular, per al disseny de fàrmacs. Aquesta memòria consta de quatre parts diferenciades. En els dos primers blocs es revisen els fonaments de la teoria de semblança quàntica, així com l'aproximació topològica basada en la teoria de grafs. Ambdues teories es fan servir per a calcular els descriptors moleculars. En el segon bloc, s'ha de remarcar la programació i implementació de programari per a calcular els anomenats índexs topològics de semblança quàntica. La tercera secció detalla les bases de les Relacions Quantitatives Estructura-Activitat i, finalment, el darrer apartat recull els resultats d'aplicació obtinguts per a diferents sistemes biològics.The present thesis is centred in the use of the Quantum Similarity Theory to calculate molecular descriptors. These molecular descriptors are used as structural parameters to derive correlations between the structure and the function or experimental activity for a set of compounds. Quantitative Structure-Activity Relationship studies are of special interest for the rational Computer-Aided Molecular Design and, in particular, for Computer-Aided Drug Design. The memory has been structured in four differenced parts. The two first blocks revise the foundations of quantum similarity theory, as well as the topological approximation, based in classical graph theory. These theories are used to calculate the molecular descriptors. In the second block, the programming and implementation of Topological Quantum Similarity Indices must be remarked. The third section details the basis for Quantitative Structure-Activity Relationships and, finally, the last section gathers the application results obtained for different biological systems
Molecular quantum similarity in QSAR: applications in computer-aided molecular design
No full textLa present tesi està centrada en l'ús de la Teoria de Semblança Quàntica per a calcular descriptors moleculars. Aquests descriptors s'utilitzen com a paràmetres estructurals per a derivar correlacions entre l'estructura i la funció o activitat experimental per a un conjunt de compostos. Els estudis de Relacions Quantitatives Estructura-Activitat són d'especial interès per al disseny racional de molècules assistit per ordinador i, en particular, per al disseny de fàrmacs. Aquesta memòria consta de quatre parts diferenciades. En els dos primers blocs es revisen els fonaments de la teoria de semblança quàntica, així com l'aproximació topològica basada en la teoria de grafs. Ambdues teories es fan servir per a calcular els descriptors moleculars. En el segon bloc, s'ha de remarcar la programació i implementació de programari per a calcular els anomenats índexs topològics de semblança quàntica. La tercera secció detalla les bases de les Relacions Quantitatives Estructura-Activitat i, finalment, el darrer apartat recull els resultats d'aplicació obtinguts per a diferents sistemes biològics.The present thesis is centred in the use of the Quantum Similarity Theory to calculate molecular descriptors. These molecular descriptors are used as structural parameters to derive correlations between the structure and the function or experimental activity for a set of compounds. Quantitative Structure-Activity Relationship studies are of special interest for the rational Computer-Aided Molecular Design and, in particular, for Computer-Aided Drug Design. The memory has been structured in four differenced parts. The two first blocks revise the foundations of quantum similarity theory, as well as the topological approximation, based in classical graph theory. These theories are used to calculate the molecular descriptors. In the second block, the programming and implementation of Topological Quantum Similarity Indices must be remarked. The third section details the basis for Quantitative Structure-Activity Relationships and, finally, the last section gathers the application results obtained for different biological systems
Mini-Review on Chemical Similarity and Prediction of Toxicity
No full textThe notion of similarity relates to a relative comparison between different systems. The process of establishing similarities and analogies by humans is heuristic and subjective. Similarity is a context dependent and a relative measure. It is only meaningful to say that x is similar to y with respect to z. In toxicology and drug design it is important to have an objective measure of similarity to compare two or more chemicals with respect to their activity or toxicity. Similarity assessment based on structures is a convenient and popular means of comparison but needs to account for each specific activity or toxicity.
This mini review will start by providing an overview of the history and philosophy of similarity in general. It will then describe the different means of quantifying chemicals and how these numerical descriptors can be applied in so-called similarity indices to compare chemicals with respect to their activity or toxicity. The use of a varied wealth of similarity indices applied to the same study case is analyzed and compared throughout.JRC.I.3 - Toxicology and chemical substance
Testing Strategies for the Prediction of Skin and Eye Irritation and Corrosion for Regulatory Purposes
Get PDFThis report reviews the use of stepwise testing approaches for the prediction of skin and eye irritation and corrosion in a regulatory context. It is published as a companion report to the "Review of Literature-Based Models for Skin and Eye Irritation and Corrosion", an ECB report which reviewed the state-of-the-art of in silico and in vitro dermal and ocular irritation and corrosion human health hazard endpoints. In the former review, the focus was placed on reviewing alternative in silico approaches to assess acute local toxic effects, such as QSARs, SARs, chemical categories, and read-across and analogue approaches. Special emphasis was placed on literature-based (Q)SAR models for skin and eye irritation and corrosion and expert systems. In the present review, the emphasis is on different schemes (testing strategies) that have been conceived for the integrated use of different approaches, including in silico, in vitro and in vivo methods.JRC.I.3 - Toxicology and chemical substance
Development and Beta Testing of the Toxmatch Similarity Tool
Get PDFToxmatch was developed as a result of a proposal approved within the JRC Innovation Project Competition in 2005. The aim of the project proposal was to develop the prototype of a software tool for supporting the risk assessment of chemical substances. Such a tool will be useful for scientific researchers, for end-users in industry, for regulatory authorities, and in the future EU Chemicals Agency.
Toxmatch (Ideaconsult Ltd.) is a flexible user-friendly, computer-based open source application specifically commissioned by ECB which is accessible via internet. It encodes and applies a range of different structural and descriptor based chemical similarity indices. The novelty of this software lies in its ability to calculate similarity measures that are tailored for specific activities/toxicities. Thus, relevant chemical representations can be selected for a given activity and the chemicals of interest can hence be classified into toxicity classes.
The present document summarises the beta testing of Toxmatch, reporting general comments and suggestions for further improvement.JRC.I.3 - Toxicology and chemical substance
A Similarity Based Approach for Chemical Category Classification
Get PDFThis report aims to describe the main outcomes of an IHCP Exploratory Research Project carried out during 2005 by the European Chemicals Bureau (Computational Toxicology Action). The original aim of this project was to develop a computational method to facilitate the classification of chemicals into similarity-based chemical categories, which would be both useful for building (Q)SAR models (research application) and for defining chemical category proposals (regulatory application).JRC.I - Institute for Health and Consumer Protection (Ispra
Toward In Silico Approaches for Investigating the Activity of Nanoparticles in Therapeutic Development
No full textThe distinctive characteristics of nanoparticles (NPs), resulting from properties that arise at the nanoscale, are stimulating the use of
these particles in the biomedical sector for diagnostic and therapeutic purposes. However, these same characteristics of NPs also underlie widespread concerns regarding potential toxic effects. Given the large number of NPs that are being developed for possible biomedical
use, there is a need to develop rapid screening methods based on in silico methods. This feature review provides an overview of some of
the main in silico methods that are already used in the assessment of chemicals. The current status of these methods, in terms of availability and applicability to NPs, and recommendations for further research, are highlighted.JRC.I.3 - Consumer products safety and qualit
Prediction of Estrogenicity: Validation of a Classification Model
No full text(Q)SAR methods can be used to reduce animal testing as well as to minimise the testing costs. In particular, classification models have been widely used for estimating endpoints with binary activity. The aim of the present study was to develop and validate a classification-based quantitative structure-activity relationship (QSAR) model for endocrine disruption, based on interpretable mechanistic descriptors related to estrogenic gene activation. The model predicts the presence or absence of estrogenic activity as determined in a recombinant yeast assay. The experimental data was obtained from the literature. A two-descriptor classification model was developed that has the form of a decision tree. The predictivity of the model was evaluated by using an external test set and by taking into account the limitations associated with the applicability domain (AD) of the model. The AD was determined as coverage in the model descriptor space. After removing the compounds present in the training set and the compounds outside of the AD, the overall accuracy of classification of the test chemicals was used to assess the predictivity of the model. In addition, the model was shown to meet the OECD Principles for (Q)SAR Validation, making it potentially useful for regulatory purposes.JRC.I.3 - Toxicology and chemical substance
Review of (Q)SAR Models for Skin and Eye Irritation and Corrosion
No full textThis paper reviews the state-of-the-art of in silico methods for assessing dermal and ocular irritation and corrosion. It is based on an in-depth review performed by the European Chemicals Bureau of the European Commission's Joint Research Centre in support of the development of technical guidance for the implementation of the REACH legislation, and is one of a series of mini-reviews in this journal. The most widely used in silico approaches are classified into methods to assess 1) skin irritation; 2) skin corrosion; and 3) eye irritation. In this review, emphasis is placed on literature-based (Q)SAR models.JRC.I.3 - Toxicology and chemical substance
Review of Literature-Based Models for Skin and Eye Irritation and Corrosion
Get PDFThis report reviews the state-of-the-art of in silico and in vitro methods for assessing dermal and ocular irritation and corrosion. Following a general introduction, the current EU legislation for the classification and labelling of chemicals causing irritation and corrosivity is summarised. Then currently available non-animal approaches are reviewed. The main alternative approaches to assess acute local toxic effects are: a) in silico approaches, including SARs, QSARs and expert systems integrating multiple approaches; and b) in vitro test methods. In this review, emphasis is placed on literature-based (Q)SAR models for skin and eye irritation and corrosion as well as computer-based expert systems.JRC.F.3 - Chemicals Safety and Alternative Method
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