Projects with Dragon

Dragon is used as a part of several QSAR modelling applications and suites, as well as in scientific studies. Here you can find a list of some projects that can be directly used on the web and exploit Dragon for the calculation of molecular descriptors.

Toxicity Estimation Software Tool (TEST) estimates the toxicity values and physical properties of organic chemicals from molecular structure by means of several QSAR models. TEST is released by the United States Environmental Protection Agency (US EPA) and it is one of the QSAR tools suggested as an alternative approach for the REACH legislation. Dragon was used as benchmark software for the calculation of the molecular descriptors included in the TEST models .

CAESAR is an European project specifically dedicated to develop QSAR models for the REACH legislation. Five endpoints are addressed: BCF, Skin Sensitization, Carcinogenicity, Mutagenicity, Developmental Toxicity. A free on-line application has been developed to make models fully usable by everyone. Most of the models use Dragon descriptors.

CzeekS is a computational molecule screening software. It utilizes a machine-learning method known as a Support Vector Machine (SVM) which has been shown to have efficient pattern recognition ability. Using existing assay data sets, CzeekS generates prediction models for compound-protein interactions. Based on the Chemical Genomics-based Virtual Screening (CGBVS) method, CzeekS offers fast and high-precision in-silico screening for drug candidate compounds. CzeekS employs approximately 1,000 molecular descriptors calculated by Dragon.

ChemGPS-NP Web ChemGPS-NPWeb is a web-based public tool, for comprehensive
chemical space navigation and exploration in terms of global mapping onto a consistent, eight dimensional map over structure derived physico-chemical characteristics. ChemGPS-NPWeb can assist in compound selection and prioritization; property description and interpretation; cluster analysis and neighbourhood mapping; as well as comparison and characterization of large compound datasets. By using ChemGPS-NPWeb, researchers can analyze and compare chemical libraries in a consistent manner. Through this web-based interface the users can submit a SMILES/SD file and receive the output as a result file showing the positions on the ChemGPS-NP map in terms of calculated predicted scores that then can be visualized. This works by calculating 40 selected Dragon descriptors used to define the ChemGPS-NP map from the submitted structure-file.

The CoLiBRI project focuses on simultaneously understanding the similarities between chemicals and their respective binding pockets. It is commonly understood that similar chemicals should have similar activities, but CoLiBRI is based on the premise that similar binding pockets will bind similar ligands. By generating pseudo-chemical descriptors of the binding sites and molecular descriptors of the ligands, and subsequently, selecting (weighting) descriptors with statistical tools, we can generate models which for new binding pockets are capable of defining (based on pocket similarity) a point in ligand descriptor space which is near the points of chemicals which will bind to that new pocket. Virtual screening of a chemical database is then carried out by calculating similarity in the optimized ligand descriptor space between this predicted ligand point and the chemicals in the database. Dragon descriptors are vital component in the CoLiBRI methodology as they have been proven to be excellent ligand descriptors in several QSAR studies.

MOLE db - Molecular Descriptors Data Base is a free on-line database comprised of 1124 molecular descriptors calculated for 234773 molecules. The molecules are mainly collected from the NCI database, while the molecular descriptors have been calculated by means of DRAGON. Basically, the MOLE db - Molecular Descriptors Data Base allows the user to search for a specific group of molecules and analyse the corresponding values of molecular descriptors.

The Materials and Processes Simulations – MAPS platform, developed by Scienomics, is a comprehensive environment for molecular modeling and simulations. MAPS provides a flexible framework for accessing the best simulation technology required for materials modeling and design in chemical, pharmaceutical and materials research projects. MAPS' plug-in based architecture enables users to integrate any proprietary or third party code when needed. MAPS has functionality to build molecular systems of finite, crystalline and amorphous nature and enables the user to visualize them with high quality graphics. Highly efficient engines in the area of quantum, classical, mesoscale, correlative and thermodynamic modeling allow predictions of relevant properties in various application areas including chemistry, petrochemistry, home and personal care, defense, transportation, pharmaceuticals and electronics. Sophisticated analysis tools are available for visualization and processing of the simulated results.

Environmental ChemOinformatics (ECO) Marie Curie Initial Training Network (ITN) is a collaborative action of 7 institutions from 5 EU countries (Germany, The Netherlands, Spain, Sweden, Italy). The primary objective of this ITN is to contribute to the education of environmental chemo-informaticians who will receive an advanced training in both environmental sciences and computational in silico methods. The fellows of the network are expected to apply their knowledge for the implementation of REACH (Registration, Evaluation, Authorization and Restriction of Chemicals) in particular with respect to the replacement, refinement and reduction of animal tests by alternative (in silico and in vitro) methods.

OCHEM Database (Online Chemical Database With Modeling Environment) is an online database with modeling environment. You can submit experimental data or use the other users' data to build predictive QSAR models for physical-chemical or biological properties. Dragon is used as internal engine to calculate descriptors.

CADASTER CADASTER is an european project aimed at providing the practical guidance to integrated risk assessment by carrying out a full hazard and risk assessment for chemicals belonging to four compound classes. Operational procedures will be developed, tested, and disseminated that guide a transparent evaluation of four classes of emerging chemicals, explicitly taking account of variability and uncertainty in data and in models. QSAR models will be developed and validated, also externally, according to the OECD principles for the validation of QSAR. The prediction of data for chemicals of the four selected classes, belonging to the applicability domain of the developed models, will be used for hazard and risk assessment, when experimental data are lacking. Dragon is used as internal engine to calculate descriptors.