AMBIT. Modules. Database. Chemical compounds. Table Error! No text of specified style in document..1

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1 AMBIT AMBIT is open source software for chemoinformatics data management developed with funding industry via CEFIC LRI funded project. AMBIT2 software consists of a database and functional modules allowing a variety of queries and data mining of the information, stored in the database and is distributed under xxx licence. AMBIT XT is a user friendly application with a graphical user interface, based on AMBIT2 modules and is distributed under LGPL licence. AMBIT XT provides a set of functionalities to facilitate evaluation and registration of the chemicals for REACH. AMBIT XT introduces the concept of workflows, allowing guiding the users step by step towards achieving particular goal, and provides workflows for analogue identification and PBT assessment. The software is a standalone application, with an option to install the database on a server. Modules Ambit is organised in several modules with well defined dependency. Table Error! No text of specified style in document..1 Database AMBIT database is a relational database, consisting of several repositories for compounds, properties, QSAR models, users, references, as well as several tables containing pre-processed information which allows speeding up the substructure and similarity queries. The current implementation is based on MySQL. Database functionality is provided by ambit2-db module. Table Error! No text of specified style in document..2 Chemical compounds The chemical compounds are stored in the table chemicals and assigned an unique number. If connectivity is available, an unique SMILES, as well as InChI and molecular formula is generated and stored. The database supports multiple 3D structures per compound, either coming from different inventories, or generated by external programs and imported into the database. The chemical structures are stored into table structure as a compressed text, where supported formats are SDF, MOL and CML. The choice of text format makes the database transparent and easy to be used by external software. Support of multiple formats is motivated by the need to keep the data in the original format. If the original format is not one of the above formats, it is converted to MOL. Support of internal formats will be extended in future releases. 1

2 Data provenance The database provides means to identify the origin of the data, i.e., the specific inventory a compound originated from. An inventory is identified by its name and reference (tables src_dataset). Each compound might belong to multiple inventories (table struc_dataset), thus allowing users to select the compounds of interest for specific regulatory purposes. Moreover, the data provenance indicator can distinguish between different conformations, for example in cases where a particular conformation of a compound comes from one inventory and a different conformation comes from another inventory. Updates of the chemical structures are recorded and subsequent versions are stored in the history table. While importing structures from a file, they are stored in its original format into the structure table. If the structure is subsequently updated as a result of a specific calculation (e.g. 3D conversion) or another structure import step (e.g. updated version of the original file), the new version will be stored and become currently available, while the previous version will be moved to the history table. Quality Assurance The discrepancy between structures, available in chemical databases presents a challenge for AMBIT as a data integration platform. In order to raise the awareness of possible incorrect structures that might be imported from external sources, AMBIT allows assigning quality labels to each chemical., as follows: Manual verification by expert(s). Any user can assign quality labels and explain the reason of the assignment (table quality_structure). The reasons can include discrepancies between registry numbers, names and structure, expert knowledge, manual comparison with external sources, etc. o 'OK' The structure is correct o 'ProbablyOK' Most probably the structure is correct, but some issues still need to be verified. o 'Unknown' Not possible to assign a definite label. o 'ProbablyERROR' Most probably there is an error o 'ERROR' The structure is definitely wrong. Automatically verified, by comparing the structures available under the same chemical compound entry (e.g. imported from different sources) table quality_chemicals o Consensus' all structures under the same chemical compound entry are the same o 'Majority' Majority of structures under the same chemical compound entry are the same, but there are small number of structures, which differ from the majority o 'Ambiguous' There is no majority of equal structures under the same chemical compound entry (e.g. structures come from 3 different sources and all the three structures are different) 2

3 o o 'Unconfirmed' The structure comes from a single source and it is impossible to make a comparison. 'Unknown' No information about the structure (e.g. no connectivity) Potential examples of QA in Ambit Automatic comparison with different sources of chemical structures may reveal discrepancies between, as illustrated below. The first one is the chemical with CAS The structure provided in the set is incomplete. In the second example the structure with CAS provided in tone of the datasets has erroneous structure, ethyl substitution on the wrong nitrogen in a ring. Identifiers, Descriptors and Properties 3

4 The database schema is designed to provide unified storage for arbitrary number of text (e.g. registry numbers or names), and numerical properties (e.g. descriptors, experimental data). The properties are not predefined, but stored in the database on demand, e.g. AMBIT database is ready to incorporate any number of chemical compounds, identifiers, descriptors and experimental data. A property (table properties) is identified by a name and reference, thus allowing properties with coinciding names, but originating from different sources to be distinguished (e.g. LogP calculated internally by different methods and LogP imported from an external file). Every newly added property or descriptor is added to a properties table, with information about the property/descriptor name, units, alias and reference. The reference for a property, imported from a file is the name of the file itself, while the reference for a descriptor contains the name of the software used for calculation. The alias usually contains a copy of the name, except in cases, when the property is recognised as a specific type of registry number or a chemical name. In this case, the alias is assigned a fixed value (e.g. CasRN or Names). Fields with the same meaning, but different names can be assigned the same alias, in order to facilitate queries (e.g. species field same across all endpoints in order to be able to search for species). The flat list of properties provides a flexible storage, but presenting a long list of properties and descriptors in the user interface might be confusing. Templates (tables template and template_def) allows to organize properties in groups: Table Error! No text of specified style in document..3 Templates themselves can be organized hierarchically, with the help of table dictionary. The database is distributed with a set of default templates, including top level templates Endpoints, Identifiers, Datasets and Descriptors and a number of endpoints, according to ECHA endpoints classification 1. Convenience view ontology, combines the templates with its hierarchical organisation. An excerpt of this view is shown below: Table Error! No text of specified style in document..4 The user interface navigator allows viewing and organizing properties and templates in convenient mode. 4

5 By default, properties imported from a file with chemical compounds belong to the dataset of origin, but can be moved to any user selected group. Quality labels can also be assigned to any property value, stored in the database (table quality_labels): 'OK' The value assigned to property is correct 5

6 'ProbablyOK' Most probably the value is correct, but some issues still need to be verified. 'Unknown' Not possible to assign a definite label. 'ProbablyERROR' Most probably there is an error 'ERROR' The value assigned to this property is definitely wrong. Queries The results of the searches a user performs are stored into query and queryresults tables. Besides providing ability to record user actions, this enables browsing query results at a later moment and combining queries with arbitrary logic. Search methods Exact structure, fixed sub-structures, similarity, SMARTS The core substructure search functionality (graph isomorphism) is provided either by the CDK cheminformatics library or by a faster algorithm, implemented in AMBIT. Substructure search is an computationaly intensive (NP 1 -hard) problem, which means that the complexity of the algorithm increases rapidly with the size of the molecule. To speed-up substructure searching in large datasets, a pre-calculated fingerprints are used to identify structures, potentially containing the substructure. The AMBIT database and software combines this technique with fast relational database queries, which results in very fast substructure searching in large datasets. In addition, fingerprints are a standard tool for representing chemical structures to assess structural similarity by calculating Tanimoto coefficient between two fingerprints. Similarity Fingerprint generation was based on the fingerprint implementation by open source cheminformatics library, The Chemistry Development Kit and follows the ideas of Daylight fingerprint theory that states 2 : (1) for a given molecule all possible paths for a predefined length (default is 7) are generated, (2) the path is submitted to a hash function which uses it as a seed to a pseudo-random generator, (3) the hash function outputs a set of bits, and (4) the set of bits thus produced is added (with a logical OR) to the fingerprint. Ambit uses 1024 bit fingerprints by default. The Tanimoto coefficient is calculated as Tanimoto N A N B /(N A +N B -N A N B ), where N A is the number of bits on in fingerprint A, N B is the number of bits on in fingerprint B and N A \N B is the number of bits on in both fingerprints. Since Tanimoto distance is a pair-wise measure, and here the objective is to assess the similarity to the set of molecules, we generate a consensus fingerprint, which is again 1024 bit fingerprint where each bit is set. 1 non-deterministic polynomial-time 6

7 Atom environments (AE) can be regarded as fragments 3,4, surrounding each atom in a molecule, up to a predefined level. The calculation procedure is as follows. First, atom types to be included in the generation of AEs are selected. We use 34 atom types, listed in table 2, which are very similar to Sybyl atom types that have been recommended in Bender et al. The choice is based on the available atom type parameterization in CDK library. Next, a vector of length (34 *L+1) is constructed for each atom, where L is the maximum level for generating atom environments and L=3 by default. Third, for each atom, neighbors at level 1, 2, 3 are identified and corresponding counts stored in the vector. An example of a string representation of the result for a single atom (C.sp2) is: C.sp2, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 2, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1 Note that if there are several C.sp2 atoms with the same neighbours up to 3rd level in the molecule, they will have the same string representation. We will refer to this representation as a fragment. AEs could be compared by Tanimoto distance (see above), where NA is the number of fragments in molecule A, NB is the number of fragments in molecule B and NA NB is the number of common fragments between the two molecules. Here, we take average Tanimoto distance for the nearest neighbours, instead of defining consensus fingerprint. For each molecule, the similarity measure is the averaged Tanimoto distance between the molecule and its 5 nearest molecules. Table Error! No text of specified style in document..5 Substructure search The implementation of sub-structure searching allows only fixed structures (e.g. no wild cards for atoms and bonds). The structure is drawn using structure diagram editor (JChemPaint 5 ) and submitted as a hydrogen depleted structure, which might presents difficulties in distinguishing certain types of functional groups (e.g. aldehydes vs. carbonyls, amines vs. nitro groups). AMBIT also allows querying the database by Smiles ARbitrary Target Specification (SMARTS) language 6, accelerated with certain pre-processed information for structural features, stored in the database. The SMARTS specification was originally developed and maintained by Daylight Inc. 7, but is supported by many more commercial and open source software suites 8, 9, 10. A list of predefined functional groups and their SMARTS definition is available but formulating more complex queries requires knowledge of SMARTS. The SMARTS line notation allows extremely precise and transparent substructural specification and atom typing. SMARTS expressions for atoms and bonds can be combined by logical operators to form more complex queries. Recursive SMARTS allow detailed specification of an atom's environment. For example the more reactive (with respect to electrophilic aromatic substitution) ortho and para carbon atoms of phenol can be defined as: [$(c1c([oh])cccc1),$(c1ccc([oh])cc1)]; Atoms that are in an environment where (the atom is connected to an aliphatic oxygen) and where (the atom is connected to two sequential aliphatic carbons) as [$(*O);$(*CC)]. 7

8 Various queries and their combinations on properties, inventories and quality labels are available. A query can be restricted to search for compounds within specified dataset or another query. 3D structure generation AMBIT module ambit2-smi23d integrates the open source 3D coordinate generation smi23d for generation of an initial 3D structure from connectivity matrix 11. The initial structure is further optimized by OpenMOPAC , which is embedded into ambit2-mopac module. Molecular descriptors Ambit provides facilities to calculate and store descriptors for all chemical structures in the database, as well as specification of search criteria based on descriptor values. The CDK library based descriptors 13 are shown in Table Error! No text of specified style in document..6. Descriptors, implemented in ambit descriptors module are listed in Table Error! No text of specified style in document..7. [Table Error! No text of specified style in document..6] [Table Error! No text of specified style in document..7.] Workflow engine 8

9 A workflow engine is a software application, which manages and executes modelled business processes. In general, the models can be edited by non-programmers, using workflow editors. The workflow models might be as simple as series of sequential steps, but also be complex, including many conditions and loops. The Workflow Management Coalition provides standards for defining workflows in a XML based format 14. Following the recognized importance of support for workflows in AMBIT, number of existing open source workflow engines were evaluated for suitability to be embedded into AMBIT XT application. The final decision of embedding micro-workflow is based on a trade-off between simplicity and available functionalities 15. AMBIT XT is entirely based on micro-workflow engine, providing extensible platform for workflow based wizards and facilitating recording of user actions. Workflow for analogue identification The workflow will consist of the following steps 1. Definition of the starting structure or set of structures. The structure(s) can be defined as: Identifiers (e.g. CAS, EINECS number, name). Structure, represented as SMILES, MOL, SDF, drawn manually by the structure diagram editor, available in AMBIT or drawn using externally installed ISIS/Draw software, copied to the system clipboard and then pasted into AMBIT user interface. 2. Basic analogue search, consists of a similarity search (hashed fingerprints compared by Tanimoto distance by default). 3. The results are displayed in the Structure browser. The user can decide to restrict the forthcoming queries within the set of selected structures. 4. Substructure search by user-defined fragment. 5. The results are displayed in the Structure browser. The user can decide to restrict forthcoming queries within the set of selected structures. 6. Further filtering of the results by conducting additional compound profiling based on experimental and calculated data (LogKow, Dmax, other 2D and 3D descriptors chosen by the user). 7. The results are displayed in the Structure browser. The user can decide to restrict the forthcoming queries within the set of selected structures. 8. The selected structures are grouped into typical chemical classes or by clustering, allowing the user to inspect small groups of analogues and derive the final decision of the query compound(s). 9. The system proposes to calculate the final value by average, min-max, Euclidean distance to user selected properties Workflow for REACH PBT and vpvb (Persistence, Bioaccumulation and Toxicity) assessment 9

10 REACH requires for every substance to be registered and not exempted a PBT & vpvb Assessment if the tonnage exceeds 10 tons/year. The REACH PBT & vpvb Assessment allows a straightforward, user friendly and quick assessment if the necessary information is available. An important goal is to rapidly identify those REACH substances which are not PBT & vpvb. In addition those substances identified as a potential PBT or vpvb can immediately investigated in a higher tier assessment to find out what is necessary as a next step. Such higher tier assessments are very often time consuming and costly and it has to be avoided that the strict registration deadlines cannot be met due to an ongoing PBT assessment. As the assessment is done transparently and always the same way it will allow a standardized PBT & vpvb Assessement throughout the company, independent from personal judgments of an assessor. Printing the result sheet e.g. as a PDF file allows proper documentation of the PBT & vpvb Assessment Only organic substances can be assessed. This workflow should not be applied to inorganic or organometalic substances, polymers and mixtures. PBT assessment is visually organized in five pages: definition of the substance, persistency check, bioaccumulation check, toxicity check and presenting the final results. Population of AMBIT database with data The following datasets are imported and distributed with AMBIT database: 1. EINECS list. 2. Bioconcentration factor dataset ECETOC Aquatic Toxicity data Local Lymph Node Assay (LLNA) data ECETOC Skin irritation data 19 The data is imported using the standard data import functionality. The EINECS list is publicly available at ECB site and consists of chemicals 20. Extensive verification of EINECS structures, in order to improve their reliability, based on comparison of structures with matching registry numbers and available from public sources. Quality labels has been assigned, as explained above. Bioconcentration factor dataset is distributed without structural information and chemical compounds are identified only by CAS numbers and chemical names. Structures has been retrieved from publicly available sources and imported into database. Datasets 3-5 consist of relatively small number of compounds and presumably contain high quality structures, manually checked by experts before making them publicly available. WWW- REST services Web services, allowing to use AMBIT functionality from web applications are under development. Similarity example: 10

11 -- Acknowledgements: AMBIT software was developed within the framework of CEFIC LRI project EEM- 9 Building blocks for a future (Q)SAR decision support system: databases, applicability domain, similarity assessment and structure conversions and extended under subsequent CEFIC LRI contract for developing AmbitXT. 11

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14 Table Error! No text of specified style in document..1 Modules Module Description AmbitXT GUI application AmbitXT plugin: Database search and Analogue identification Ambit XT plugin, allowing various database queries and analogues identification. AmbitXT plugin: Category building Ambit XT plugin for analogues identification AmbitXT plugin: Database tools Ambit XT plugin for database import and management AmbitXT plugin: Database AmbitXT plugin for database administration activities administration AmbitXT plugin: REACH PBT assessment ambit2-base ambit2-core ambit2-hashcode ambit2-smarts ambit2-db ambit2-smi23d ambit2-mopac ambit2-ui ambit2-dbui ambit2-workflow ambit2-namestructure ambit2-model ambit2-taglibs Pubchem utilities Ambit2 REST web services AmbitXT plugin, implementing an workflow for REACH compliant Persistence, Biodegradation and Toxicity (PBT) assessment. Base classes, without cheminformatics functionality Core classes, with cheminformatics functionality Hashcodes SMARTS parser Database functionality Wrapper for Smi23d executables wrapper for OpenMopac User interface Database user interface Workflow module Chemical name to structure convertor, based on OPSIN package Similarity calculation, feature selection and QSAR model development JSP tags Pubchem access utilities Allows to query AMBIT database by REST style web services. 14

15 Table Error! No text of specified style in document..2 Tables in AMBIT2 database. Table Description Chemical structures chemicals structure history src_dataset struc_dataset catalog_references properties property_values property_string property_tuples tuples template template_def dictionary query query_results sessions user_roles roles users quality_chemicals quality_labels quality_pair quality_structure fp1024 fp1024_struc Chemical compounds Chemical structures, conformers Previous versions of chemical structures Inventories Datasets Lookup table for structures, belonging to a dataset Identifiers, Descriptors, Properties References Property definition (name,reference, units) Numerical property values or links to string values String values Tuples of properties Tuples per dataset Templates Template definition (which properties belng to a template) Templates hierarchy Queries Queries Structures per query Sessions Users support Roles, assigned to users User roles Users Quality assessment support Quality labels of structures and properties Pre-processed data for substructure, similarity and SMARTS queries Pre-processed fingerprints for pre-screening and similarity search sk1024 Pre-processed fragments for accelerating SMARTS searches 15

16 atom_distance atom_structure version Pre-processed data for atom environments similarity Schema version Database version 16

17 Table Error! No text of specified style in document..3 Templates Template Relationship Parent template Endpoints Identifiers Dataset Descriptors Top level templates Other is_a Endpoint Ecotoxic effects is_a Endpoint Toxicokinetics is_a Endpoint Environmental fate parameters is_a Endpoint Human health effects is_a Endpoint Physicochemical effects is_a Endpoint Short-term toxicity to algae (inhibition of the exponential growth rate) is_a Ecotoxic effects Toxicity to birds is_a Ecotoxic effects Direct photolysis is_a Environmental fate parameters Oxidation is_a Environmental fate parameters BAF fish is_a Bioaccumulation BAF other organisms is_a Bioaccumulation BCF fish is_a Bioconcentration BCF other organisms is_a Bioconcentration CAS number is_a Identifier RSCBook_Skinsens_dataset.sdf is_a Dataset org.openscience.cdk.qsar.descriptors.molecular.hbon dacceptorcountdescriptor org.openscience.cdk.qsar.descriptors.molecular.hbon ddonorcountdescriptor is_a is_a Descriptor Descriptor Verhaar scheme is_a Descriptor Table Error! No text of specified style in document..4 An excerpt view of ontology Template Relationship Parent template Endpoints Identifiers Dataset Descriptors Top level templates Other is_a Endpoint Ecotoxic effects is_a Endpoint Toxicokinetics is_a Endpoint Environmental fate parameters is_a Endpoint 17

18 Human health effects is_a Endpoint Physicochemical effects is_a Endpoint Short-term toxicity to algae (inhibition of the is_a Ecotoxic effects exponential growth rate) Toxicity to birds is_a Ecotoxic effects Direct photolysis is_a Environmental fate parameters Oxidation is_a Environmental fate parameters BAF fish is_a Bioaccumulation BAF other organisms is_a Bioaccumulation BCF fish is_a Bioconcentration BCF other organisms is_a Bioconcentration CAS number is_a Identifier RSCBook_Skinsens_dataset.sdf is_a Dataset org.openscience.cdk.qsar.descriptors.molecular. HBondAcceptorCountDescriptor org.openscience.cdk.qsar.descriptors.molecular. HBondDonorCountDescriptor is_a is_a Descriptor Descriptor Verhaar scheme is_a Descriptor Table Error! No text of specified style in document..5 types used to generate atom environments H C.default N.sp2 P3 F I Hplus Cplus.sp2 Nplus P4 F- I- Hminus Cminus.sp2 Nplus.sp3 S2 Cl Misc C.sp3 Caromatic.sp2 O.sp2 S2- Cl- C.sp2 Cminus Oplus S4 Br C.sp N Ominus S Br- 18

19 Table Error! No text of specified style in document..6 The CDK library based descriptors ALogP and Molar Refractivity Largest Chain Atomic Polarizabilities Largest Pi System Amino Acids Count Aromatic Atoms Count Aromatic Bonds Count Atom count BCUT Bond Polarizabilities Bond Count Largest Aliphatic Chain Moments of Inertia Petitjean Number Petitjean Shape Indices Rotatable Bonds Count Lipinski's Rule of Five Topological Polar Surface Area Charged Partial Surface Area Vertex adjacency information magnitude Gravitational Index Hydrogen Bond Acceptors Hydrogen Bond Donors Kier and Hall kappa molecular shape indices WHIM Wiener Numbers XLogP Zagreb Index 19

20 Table Error! No text of specified style in document..7 AMBIT Descriptors Common functional groups ToxTree classification schemes 21 : pka 22, Cramer rules Molecule Size (3D), Molecular weight Electronic descriptors, calculated by OpenMopac EHOMO Extended Cramer rules Verhaar scheme Eye irritation rules Skin irritation rules ELUMO Benigni/Bossa rulebase for mutagenicity and carcinogenicity TOTAL ENERGY FINAL HEAT OF FORMATION IONIZATION POTENTIAL ELECTRONIC ENERGY CORE-CORE REPULSION MOLECULAR WEIGHT Structural rules for Michael acceptors Structure Alerts for the in vivo micronucleus assay in rodents 20

21 References 1http://guidance.echa.europa.eu/docs/guidance_document/information_requirements_r6_en. pdf?%20vers=20_08_08, accessed on June L. Xing, R.C. Glen. J. Chem. Inf. Comput. Sci. 42, 2002, p A. Bender, H.Y. Mussa, R.C. Glen, S. Reiling. J. Chem. Inf. Comput. Sci. 44, 2004, p accessed on June Daylight SMARTS theory. accessed on June Daylight Inc. accessed on June Open Babel SMARTS implementation. accessed on June The Chemical Development Library SMARTS implementation. accessed on June JOELIB accessed on June 8th smi23d - 3D Coordinate Generation, accessed on June OpenMopac accessed on June-8, A subset of descriptors, listed at accessed on July accessed on June accessed on June Bioconcentration factor (BCF) Gold Standard Database accessed on June ECETOC Aquatic Toxicity (EAT) Database. Supplement to ECETOC., Aquatic Hazard Assessment II. Technical Report No. 91, European Centre for Ecotoxicology and Toxicology of Chemicals, Brussels,

22 18 Gerberick GF, Ryan CA, Kern PS, Schlatter H, Dearman RJ, Kimber I, Patlewicz G, Basketter DA, Compilation of historical local lymph node assay data for the evaluation of skin sensitization alternatives. Dermatitis 16(4), 2005, pp ECETOC Technical Report No. 66 Skin irritation and corrosion Reference Chemicals data base, accessed on June accessed on July Adam C. Lee, Jing-yu Yu, and Gordon M. Crippen, pka Prediction of Monoprotic Small Molecules the SMARTS Way, J. Chem. Inf. Model.48(10), 2008, pp