Connection Table Research Articles

Permuting input for more effective sampling of 3D conformer space

SMILES strings and other classic 2D structural formats offer a convenient way to represent molecules as a simplistic connection table, with the inherent advantages of ease of handling and storage. In the context of virtual screening, chemical databases to be screened are often initially represented by canonicalised SMILES strings that can be filtered and pre-processed in a number of ways, resulting in molecules that occupy similar regions of chemical space to active compounds of a therapeutic target. A wide variety of software exists to convert molecules into SMILES format, namely, Mol2smi (Daylight Inc.), MOE (Chemical Computing Group) and Babel (Openeye Scientific Software). Depending on the algorithm employed, the atoms of a SMILES string defining a molecule can be ordered differently. Upon conversion to 3D coordinates they result in the production of ostensibly the same molecule. In this work we show how different permutations of a SMILES string can affect conformer generation, affecting reliability and repeatability of the results. Furthermore, we propose a novel procedure for the generation of conformers, taking advantage of the permutation of the input strings--both SMILES and other 2D formats, leading to more effective sampling of conformation space in output, and also implementing fingerprint and principal component analyses step to post process and visualise the results.

Depicting combinatorial complexity with the molecular interaction map notation

To help us understand how bioregulatory networks operate, we need a standard notation for diagrams analogous to electronic circuit diagrams. Such diagrams must surmount the difficulties posed by complex patterns of protein modifications and multiprotein complexes. To meet that challenge, we have designed the molecular interaction map (MIM) notation (http://discover.nci.nih.gov/mim/). Here we show the advantages of the MIM notation for three important types of diagrams: (1) explicit diagrams that define specific pathway models for computer simulation; (2) heuristic maps that organize the available information about molecular interactions and encompass the possible processes or pathways; and (3) diagrams of combinatorially complex models. We focus on signaling from the epidermal growth factor receptor family (EGFR, ErbB), a network that reflects the major challenges of representing in a compact manner the combinatorial complexity of multimolecular complexes. By comparing MIMs with other diagrams of this network that have recently been published, we show the utility of the MIM notation. These comparisons may help cell and systems biologists adopt a graphical language that is unambiguous and generally understood.

Conformational Boosting

Stochastic proximity embedding (SPE) is a novel self-organizing algorithm for sampling conformational space using geometric constraints derived from the molecular connectivity table. Here, we describe a simple heuristic that can be used in conjunction with SPE to bias the conformational search towards more extended or compact conformations, and thus greatly expand the range of geometries sampled during the search. The method uses a boosting strategy to generate a series of conformations, each of which is at least as extended (or compact) as the previous one. The approach is compared to several popular conformational sampling techniques using a reference set of 59 bioactive ligands extracted from the Protein Data Bank, and is shown to be significantly more effective in sampling the full range of molecular radii, with the exception of the Catalyst program, which was equally effective.

Communication and re-use of chemical information in bioscience.

The current methods of publishing chemical information in bioscience articles are analysed. Using 3 papers as use-cases, it is shown that conventional methods using human procedures, including cut-and-paste are time-consuming and introduce errors. The meaning of chemical terms and the identity of compounds is often ambiguous. valuable experimental data such as spectra and computational results are almost always omitted. We describe an Open XML architecture at proof-of-concept which addresses these concerns. Compounds are identified through explicit connection tables or links to persistent Open resources such as PubChem. It is argued that if publishers adopt these tools and protocols, then the quality and quantity of chemical information available to bioscientists will increase and the authors, publishers and readers will find the process cost-effective.

A Simple Algorithm for Unique Representation of Chemical StructuresCyclic/Acyclic Functionalized Achiral Molecules

An algorithm, based on "vertex priority values" has been proposed to uniquely sequence and represent connectivity matrices of chemical structures of cyclic/acyclic functionalized achiral hydrocarbons and their derivatives. In this method, "vertex priority values" have been assigned in terms of atomic weights, subgraph lengths, loops, and heteroatom contents. Subsequently, the terminal vertices have been considered upon completing the sequencing of the core vertices. This approach provides a multilayered connectivity graph, which can be put to use in comparing two or more structures or parts thereof for any given purpose. Furthermore, the basic vertex connection tables generated here are useful in the computation of characteristic matrices/topological indices and automorphism groups and in storing, sorting, and retrieving chemical structures from databases.

QSAR analyses of conformationally restricted 1,5-diaryl pyrazoles as selective COX-2 inhibitors: application of connection table representation of ligands

As a part of our continuing efforts in discerning the structural and physicochemical requirements for selective COX-2 over COX-1 inhibition among the fused pyrazole ring systems, herein we report the QSAR analyses of the title compounds. The conformational flexibility of the title compounds was examined using a simple connection table representation. The conformational investigation was aided by calculating a connection table parameter called fraction of rotable bonds, b_rotR encompassing the number of rotable bonds and b_count, the number of bonds including implicit hydrogens of each ligand. The hydrophobic and steric correlation of the title compounds towards selective COX-2 inhibition was reported previously in one of our recent publications. In this communication, we attempt to calculate Wang–Ford charges of the non-hydrogen common atoms of AM1 optimized geometries of the title compounds. Owing to the partial conformational flexibility of title compounds, conformationally restricted and unrestricted descriptors were calculated from MOE. Correlation analysis of these 2D, 3D and Wang–Ford charges was accomplished by linear regression analysis. 2D molecular descriptor b_single, 3D molecular descriptors glob, std_dim3 showed significant contribution towards COX-2 inhibitory activity. Balaban J, a connectivity topological index showed a negative and positive contribution towards COX-1 and selective COX-2 over COX-1 inhibition, respectively. Wang–Ford charges calculated on C 7 showed a significant contribution towards COX-1 inhibitory activity whereas charges calculated on C 8 were crucial in governing the selectivity of COX-2 over COX-1 inhibition among these congeners.

QSAR Modeling Based on Structure-Information for Properties of Interest in Human Health*

The development of QSAR models based on topological structure description is presented for problems in human health. These models are based on the structure-information approach to quantitative biological modeling and prediction, in contrast to the mechanism-based approach. The structure-information approach is outlined, starting with basic structure information developed from the chemical graph (connection table). Information explicit in the connection table (element identity and skeletal connections) leads to significant (implicit) structure information that is useful for establishing sound models of a wide range of properties of interest in drug design. Valence state definition leads to relationships for valence state electronegativity and atom/group molar volume. Based on these important aspects of molecules, together with skeletal branching patterns, both the electrotopological state (E-state) and molecular connectivity (chi indices) structure descriptors are developed and described. A summary of four QSAR models indicates the wide range of applicability of these structure descriptors and the predictive quality of QSAR models based on them: aqueous solubility (5535 chemically diverse compounds, 938 in external validation), percent oral absorption (%OA, 417 therapeutic drugs, 195 drugs in external validation testing), AMES mutagenicity (2963 compounds including 290 therapeutic drugs, 400 in external validation), fish toxicity (92 substituted phenols, anilines and substituted aromatics). These models are established independent of explicit three-dimensional (3-D) structure information and are directly interpretable in terms of the implicit structure information useful to the drug design process.

Development and Application of XyM2Mol System for Converting Structural Data by XyM Notation into Connection Tables

The XyM2Mol system, which consists of the XyM2Mol application and the XyM2Mol applet, is developed to convert XyM-notation codes into connection tables. Thereby, the structural data by XyM Notation become applicable to a wide variety of chemical applications through such connection tables.

Selecting contact particles in dynamics granular mechanics systems

Dynamic granular mechanics systems are problems with variable connectivity between the particles. This property makes it difficult for rigourous analysis since it implies reformulation of the problem each time the connectivity changes. In this paper an improved procedure for selecting contact particles is considered for large granular mechanics applications (≃104 particles). The method for the selecting uses a connectivity table. The main claimed advantage of the method is simplicity since it uncouples the system of particle in subsystems. It is shown, for example, that for N particles system, the classic method of selecting requires (N(N+1))/2 operations compared to N for the new approach.

A connectivity table for cluster similarity checking in the evolutionary optimization method

A novel and effective cluster similarity checking method using the connectivity table (CT) is proposed in this study. Because CT contains the topological information of a cluster, configurations at different funnels on the potential energy surface (PES) show great difference in their CTs. An adaptive immune optimization algorithm (AIOA) is utilized for optimization of Lennard–Jones (LJ) clusters up to LJ 110 using the CT for similarity checking. It is proved that the method is very efficient, and the method is also capable for optimizations of larger clusters, e.g., LJ 200.

A Structure‐Information Approach to the Prediction of Biological Activities and Properties

The structure-information approach to quantitative biological modeling and prediction is presented in contrast to the mechanism-based approach. Basic structure information is developed from the chemical graph (connection table). The development, beginning with information explicit in the connection table (element identity and skeletal connections), leads to significant structure information useful for establishing sound models of a wide range of properties of interest in drug design. Skeletal branching patterns and valence state definition lead to relationships for valence-state electronegativity and atom or group molar volumes. Based on these important aspects of molecules, both the electrotopological state (E-State) and molecular-connectivity structure descriptors (chi indices) are developed. A summary of QSAR models indicates the wide range of applicability of these structure descriptors and the predictive quality of QSAR models for protein binding, HIV-1 protease inhibition, blood-brain-barrier partitioning, fish toxicity, carcinogenicity risk, structure space for similarity searching, and data mining. These models are independent of three-dimensional structure information and are directly interpretable in terms of structure information useful to the drug-design process.

Enabling the exploration of biochemical pathways

The Biochemical Pathways Wall Chart (http://www.expasy.org/tools/pathways/ref.1) has been converted into a molecule and reaction database. Major features of this database are that each molecule is represented by lists of all atoms and bonds (as connection tables), and in the reactions the reaction centre, the atoms and bonds directly involved in the bond rearrangement process, are marked. The information in the database has been enriched by a set of diverse 3D structure conformations generated by the programs CORINA and ROTATE. The web-based structure and reaction retrieval system C@ROL provides a wide range of search methods to mine this rich database. The database is accessible at http://www2.chemie.uni-erlangen.de/services/biopath/index.html and http://www.mol-net.de/databases/biopath.html .

The Challenges with Substance Databases and Structure Search Engines

Structure connection tables, which are commonly used for the representation of chemical structures in electronic databases, are valuable for substances where specific valence bond structures are known or can be drawn. How-ever there are many classes of substances (for example alloys, catenanes, polymers, or salts) which cannot be fully represented by valence bond structures. There are also issues of definition (such as when a substance is a co-ordination compound, or hydrate, or salt), and of bonding types (resonance, donor complexes, π-complexes). Producers of chemical substance databases may address these issues in different ways and generally need to introduce concepts (for example multicomponent substances) with which chemical scientists may not be familiar. In addition to these aspects of database content, the searcher needs to understand the algorithms behind the structure search engines. For example, the SciFinder search engine has considerable in-built chemical intelligence at the initial search level and then has many tools to mine the data once obtained; the CrossFire search engine also employs several algorithms by default and allows further options to vary them.

Derivation and applications of molecular descriptors based on approximate surface area.

Three sets of molecular descriptors that can be computed from a molecular connection table are defined. The descriptors are based on the subdivision and classification of the molecular surface area according to atomic properties (such as contribution to logP, molar refractivity, and partial charge). The resulting 32 descriptors are shown (a) to be weakly correlated with each other; (b) to encode many traditional molecular descriptors; and (c) to be useful for QSAR, QSPAR, and compound classification.

Chemical machine vision: automated extraction of chemical metadata from raster images.

We present a novel application of machine vision methods for the identification of chemical composition diagrams from two-dimensional digital raster images. The method is based on the use of Gabor wavelets and an energy function to derive feature vectors from digital images. These are used for training and classification purposes using a Kohonen network for classification with the Euclidean distance norm. We compare this method with previous approaches to transforming such images to a molecular connection table, which are designed to achieve complete atom connection table fidelity but at the expense of requiring human interaction. The present texture-based approach is complementary in attempting to recognize higher order features such as the presence of a chemical representation in the original raster image. This information can be used for providing chemical metadata descriptors of the original image as part of a robot-based Internet resource discovery tool.

Conformational sampling by self-organization.

A new stochastic algorithm for conformational sampling is described. The algorithm generates molecular conformations that are consistent with a set of geometric constraints, which include interatomic distance bounds and chiral volumes derived from the molecular connectivity table. The algorithm repeatedly selects individual geometric constraints at random and updates the respective atomic coordinates toward satisfying the chosen constraint. When compared to a conventional distance geometry algorithm based on the same set of geometric constraints, our method is faster and generates conformations that are more diverse and more energetically favorable.

Single-Mode Compound Retrieval for QSAR, QSPR Data Sets, and Batch Mode Exact Structure Searching

This commentary describes two simple procedures using commercially available software packages that greatly facilitate the creation of and replication of data sets intended for quantitative structure activity relationship (QSAR) and quantitative structure property relationship (QSPR) studies. Used properly, the procedures allow the capture of individual chemical structures from the Chemical Abstracts Service (CAS) SciFinder software in a computer readable format that is recognized by most chemical database and computational calculation software packages. The researcher need not draw in a chemical structure to create a Molecular Design Limited (MDL) mol file, the 2D connection table format most commonly used to create the chemical depiction of compound or drug. The MDL mol format is needed so that properties can be calculated from the chemical structure alone. All that is required is that the compound or drug be located in SciFinder. The procedures are described in considerable detail because the key procedures for capturing structures from Chemical Abstracts Service (CAS) SciFinder through the use of Accelrys’Accord for Excel software are undocumented in either software. Also described is a batch procedure that allows search of CAS SciFinder for the exact chemical structure of up to 25 compounds. Without use of this procedure, Scifinder can only be searched for an exact chemical structure a single compoundat a time using a query consisting of a drawn in structure. Both the single-mode structure retrieval and batch-mode compound search procedures result in very significant time savings to the researcher creating or replicating QSAR/QSPR data sets and likelymay enable structure searches that previously might not have been attempted because of researcher time constraints. These procedures do not affect positively or negatively the cost to the user of the searches against the SciFinder software. These costs are determined by CAS policy, and depend on the numbers of structures/compounds searched. Locating a compound or drug in SciFinder is most accurately done using the CAS Registry Number. The CAS Registry Number uniquely identifies a specific compound and salt form. Older deleted CAS Registry Numbers for a specific compound may be encountered, but a search on the current (or older) CAS Registry Numbers will always bring up the correct compound. If different salt forms of the same compound exist in the CAS databases, they will have different CAS Registry Numbers. By contrast, a search by compound or drug namemay fail. IUPAC names for compounds are of no value in searches against SciFinder because IUPAC Names are not listed in the records. Commonly used drug names work fairly well. However, it is frequent to find variant or misspelled drug names in the scientific literature. A deviation between a search input name and the names stored in CAS databases in only a single letter or number will result in a search failure. Searchesusingdrug tradenames (as invery recent drugs) or company code numbers (as in early discovery stage compounds) fail more frequently than searches using common names.

Software for automating analysis of encoded combinatorial libraries.

This paper describes the applications which are used to automate the analysis of encoded combinatorial libraries. Commercial packages from MDL, Oracle and Agilent are linked with application software written in C/C++, in Microsoft Access and in ChemStation macro language. Encoding correspondence lists for each of up to three synthetic steps are conveniently associated with building block lists using the first application, CodeGen. The second application Decode allows the user to identify the individual beads picked onto a 96-well plate and the pool number for each bead. The decoding chromatography data for each well is then loaded into the program. The chromatography data is used to identify the tags used in the synthesis. Along with the building block information from ISIS/Host, the building block used in each step of the synthesis can be identified. A third routine, Code-to-Structure, takes the coded library building blocks and creates the connection table in ISIS for each structure found by the decode program. For quality control of encoded library synthesis, the decoded structures on a set of beads is compared to the LC/UV/MS data for the ligand cleaved from the same bead. CAPTURE, a GlaxoSmithKline proprietary application, is used to display and analyze the decoded structures and associated mass spectral data. This application uses simple isotopic composition and electrospray ionization rule sets to predict mass spectra and judge the concordance of a structure- mass spectrum data set. An ancillary program, EIC, is used to extract predicted single ion chromatograms from the full scan LC/MS data.

ChemDig: new approaches to chemically significant indexing and searching of distributed web collectionsElectronic supplementary information (ESI) available: list of less common chemical MIME media types, output template definitions and stylesheets associated with Table 4. See http://www.rsc.org/suppdata/nj/b1/b110693g/

We describe an extension of the ht://Dig robot-based internet indexing and search engine to include the retrieval of information included in a variety of molecular data formats as defined by chemical MIME types. This is achieved by invoking chemical meta-parsers, software agents designed to provide key meta-data information about the content of the external chemical files. This meta-data can include, for example, derived molecular formula, molecular mass and atom connection table (SMILES) where the content of the file allows this, and other types of content such as author information and supplied keywords. These terms can be automatically added to the searchable terms, and the search outputs can be automatically linked via database requests to other external databases containing chemical information. We report our experience in applying this robot to indexing five different remote sites. We discuss different mechanisms for storing and searching for the chemical content, ranging from simple keyword-based searches qualified by chemically significant boolean terms, chemical similarity searches and our experiments in creating more highly structured content that expresses the chemical data using XML-based markup and where XSLT transforms for filtering, searching and rendering the information are used.

Morpheme-based grapheme to phoneme conversion using phonetic patterns and morphophonemic connectivity information

Both dictionary-based and rule-based methods on grapheme-to-phoneme conversion have their own advantages and limitations. For example, a large sized phonetic dictionary and complex morphophonemic rules are required for the dictionary-based method and the LTS (letter to sound) rule-based method itself cannot model the complete morphophonemic constraints.This paper describes a grapheme-to-phoneme conversion method for Korean using a dictionary-based and rule-based hybrid method with a phonetic pattern dictionary and CCV (consonant consonant vowel) LTS (letter to sound) rules. The phonetic pattern dictionary, standing for the dictionary-based method, contains entries in the form of a morpheme pattern and its phonetic pattern. The patterns represent candidate phonological changes in left and right boundaries of morphemes. Obviously, the CCV LTS rules stand for the rule-based method. The rules are in charge of grapheme-to-phoneme conversion within morphemes.The conversion method consists of mainly two steps including morpheme to phoneme conversion and morphophonemic connectivity check, and two preprocessing steps including phrase break prediction and morpheme normalization. Phrase break prediction presumes phrase breaks using the stochastic method on part-of-speech (POS) information. Morpheme normalization is to replace non-Korean symbols with their corresponding standard Korean graphemes. In the morpheme-phoneticizing module, each morpheme in the phrase is converted into phonetic patterns by looking it up in the phonetic pattern dictionary. Graphemes within a morpheme are grouped into CCV units and converted into phonemes by the CCV LTS rules. The morphophonemic connectivity table supports grammaticality checking of the two adjacent phonetic morphemes.In experiments with a non-Korean symbol free corpus of 4,973 sentences, we achieved a 99.98% grapheme-to-phoneme conversion performance rate and a 99.0% sentence conversion performance rate. With a broadcast news corpus of 621 sentences, 99.7% of the graphemes and 86.6% of the sentences are correctly converted. The full Korean TTS (Text-to-Speech) system is now being implemented using this conversion method.