Kochev N.T.,Plovdiv University |
Paskaleva V.H.,Plovdiv University |
Jeliazkova N.,Ideaconsult Ltd.
Molecular Informatics | Year: 2013
We present a new open source tool for automatic generation of all tautomeric forms of a given organic compound. Ambit-Tautomer is a part of the open source software package Ambit2. It implements three tautomer generation algorithms: combinatorial method, improved combinatorial method and incremental depth-first search algorithm. All algorithms utilize a set of fully customizable rules for tautomeric transformations. The predefined knowledge base covers 1-3, 1-5 and 1-7 proton tautomeric shifts. Some typical supported tautomerism rules are keto-enol, imin-amin, nitroso-oxime, azo-hydrazone, thioketo-thioenol, thionitroso-thiooxime, amidine-imidine, diazoamino-diazoamino, thioamide-iminothiol and nitrosamine-diazohydroxide. Ambit-Tautomer uses a simple energy based system for tautomer ranking implemented by a set of empirically derived rules. A fine-grained output control is achieved by a set of post-generation filters. We performed an exhaustive comparison of the Ambit-Tautomer Incremental algorithm against several other software packages which offer tautomer generation: ChemAxon Marvin, Molecular Networks MN.TAUTOMER, ACDLabs, CACTVS and the CDK implementation of the algorithm, based on the mobile H atoms listed in the InChI. According to the presented test results, Ambit-Tautomer's performance is either comparable to or better than the competing algorithms. Ambit-Tautomer module is available for download as a Java library, a command line application, a demo web page or OpenTox API compatible Web service. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Source
Jeliazkova N.,Ideaconsult Ltd. |
Kochev N.,Plovdiv University
Molecular Informatics | Year: 2011
We present new developments in the AMBIT open source software package for efficient searching of chemical structures and structural fragments. AMBIT-SMARTS is a Java based software built on top of The Chemistry Development Kit. The AMBIT-SMARTS parser implements the entire SMARTS language specification with several syntax extensions that enable support for custom modifications introduced by third party software packages such as OpenEye, MOE and OpenBabel. The goal of yet another open-source SMARTS parser implementation is to achieve better performance and compatibility with multiple existing flavours of the SMARTS language, as well as to provide utilities for running efficient SMARTS queries in large structural databases. We describe a combination of approaches towards lowering the computational cost and improving the response time of substructure queries. An exhaustive comparison of the AMBIT algorithm with several subgraph isomorphism implementations is performed. To demonstrate the performance of the entire system from an end-user point of view, response time statistics for Web service substructure search queries against a database of 4.5M structures are also reported. The package has wide applicability in the implementation of various chemoinformatics tasks. It has already been used in several projects dealing with descriptor calculation and predictive algorithms, database queries, web applications and web services. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Source
Hastings J.,European Bioinformatics Institute |
Jeliazkova N.,Ideaconsult Ltd. |
Owen G.,European Bioinformatics Institute |
Tsiliki G.,National Technical University of Athens |
And 4 more authors.
Journal of Biomedical Semantics | Year: 2015
Engineered nanomaterials (ENMs) are being developed to meet specific application needs in diverse domains across the engineering and biomedical sciences (e.g. drug delivery). However, accompanying the exciting proliferation of novel nanomaterials is a challenging race to understand and predict their possibly detrimental effects on human health and the environment. The eNanoMapper project (www.enanomapper.net) is creating a pan-European computational infrastructure for toxicological data management for ENMs, based on semantic web standards and ontologies. Here, we describe the development of the eNanoMapper ontology based on adopting and extending existing ontologies of relevance for the nanosafety domain. The resulting eNanoMapper ontology is available at http://purl.enanomapper.net/onto/enanomapper.owl. We aim to make the re-use of external ontology content seamless and thus we have developed a library to automate the extraction of subsets of ontology content and the assembly of the subsets into an integrated whole. The library is available (open source) at http://github.com/enanomapper/slimmer/. Finally, we give a comprehensive survey of the domain content and identify gap areas. ENM safety is at the boundary between engineering and the life sciences, and at the boundary between molecular granularity and bulk granularity. This creates challenges for the definition of key entities in the domain, which we also discuss. © 2015 Hastings et al.; licensee BioMed Central. Source
Cassani S.,University of Insubria |
Kovarich S.,University of Insubria |
Papa E.,University of Insubria |
Roy P.P.,University of Insubria |
And 13 more authors.
ATLA Alternatives to Laboratory Animals | Year: 2013
QSAR regression models of the toxicity of triazoles and benzotriazoles ([B]TAZs) to an alga (Pseudokirchneriella subcapitata), Daphnia magna and a fish (Onchorhynchus mykiss), were developed by five partners in the FP7-EU Project, CADASTER. The models were developed by different methods - Ordinary Least Squares (OLS), Partial Least Squares (PLS), Bayesian regularised regression and Associative Neural Network (ASNN) - by using various molecular descriptors (DRAGON, PaDEL-Descriptor and QSPRTHESAURUS web). In addition, different procedures were used for variable selection, validation and applicability domain inspection. The predictions of the models developed, as well as those obtained in a consensus approach by averaging the data predicted from each model, were compared with the results of experimental tests that were performed by two CADASTER partners. The individual and consensus models were able to correctly predict the toxicity classes of the chemicals tested in the CADASTER project, confirming the utility of the QSAR approach. The models were also used for the prediction of aquatic toxicity of over 300 (B)TAZs, many of which are included in the REACH pre-registration list, and were without experimental data. This highlights the importance of QSAR models for the screening and prioritisation of untested chemicals, in order to reduce and focus experimental testing. Source
Willighagen E.L.,Uppsala University |
Willighagen E.L.,Karolinska Institutet |
Jeliazkova N.,Ideaconsult Ltd. |
Hardy B.,Douglas Connect |
And 3 more authors.
BMC Research Notes | Year: 2011
Background: Toxicity is a complex phenomenon involving the potential adverse effect on a range of biological functions. Predicting toxicity involves using a combination of experimental data (endpoints) and computational methods to generate a set of predictive models. Such models rely strongly on being able to integrate information from many sources. The required integration of biological and chemical information sources requires, however, a common language to express our knowledge ontologically, and interoperating services to build reliable predictive toxicology applications. Findings. This article describes progress in extending the integrative bio- and cheminformatics platform Bioclipse to interoperate with OpenTox, a semantic web framework which supports open data exchange and toxicology model building. The Bioclipse workbench environment enables functionality from OpenTox web services and easy access to OpenTox resources for evaluating toxicity properties of query molecules. Relevant cases and interfaces based on ten neurotoxins are described to demonstrate the capabilities provided to the user. The integration takes advantage of semantic web technologies, thereby providing an open and simplifying communication standard. Additionally, the use of ontologies ensures proper interoperation and reliable integration of toxicity information from both experimental and computational sources. Conclusions: A novel computational toxicity assessment platform was generated from integration of two open science platforms related to toxicology: Bioclipse, that combines a rich scriptable and graphical workbench environment for integration of diverse sets of information sources, and OpenTox, a platform for interoperable toxicology data and computational services. The combination provides improved reliability and operability for handling large data sets by the use of the Open Standards from the OpenTox Application Programming Interface. This enables simultaneous access to a variety of distributed predictive toxicology databases, and algorithm and model resources, taking advantage of the Bioclipse workbench handling the technical layers. © 2011 Willighagen et al; licensee BioMed Central Ltd. Source