Searching for pharmacophoric patterns in databases of three-dimensional chemical structures

This paper provides an overview of the research that has been carried out in Sheffield over the last decade into searching techniques for databases of three-dimensional (3D) chemical structures. A 3D structure or query pattern is represented by a labelled graph, in which the nodes and the edges of the graph are used to represent atoms and the associated inter-atomic distances, respectively. The presence of a pharmacophore in each of the structures in a database can then be tested by means of a subgraph isomorphism algorithm, the computational requirements of which are minimized by the use of an initial screening procedure that eliminates the majority of the structures from the subgraph-isomorphism search. Analogous graph-based representation and searching methods can also be used with flexible 3D structures: in this case, the edges of the graphs represent inter-atomic distance ranges and a final conformational search needs to be carried out for those molecules that match the query pharmacophore in the subgraph-isomorphism search. The paper also reviews related work on the automatic identification of pharmacophoric patterns and on 3D similarity searching.     

HOWDY: an integrated database system for human genome research

HOWDY is an integrated database system for accessing and analyzing human genomic information (http://www-alis.tokyo.jst.go.jp/HOWDY/). HOWDY stores information about relationships between genetic objects and the data extracted from a number of databases. HOWDY consists of an Internet accessible user interface that allows thorough searching of the human genomic databases using the gene symbols and their aliases. It also permits flexible editing of the sequence data. The database can be searched using simple words and the search can be restricted to a specific cytogenetic location. Linear maps displaying markers and genes on contig sequences are available, from which an object can be chosen. Any search starting point identifies all the information matching the query. HOWDY provides a convenient search environment of human genomic data for scientists unsure which database is most appropriate for their search.     

Pharmacophoric pattern matching in files of 3D chemical structures: evaluation of search performance

A computerized retrieval system is described which allows the interactive identification of pharmacophoric patterns in 3D chemical structures. A query pharmacophore in the system is matched against a file of structures using a three-stage retrieval mechanism. The initial search involves a rapid bit-string matching operation using screens denoting the presence or absence of interatomic distances that lie within certain predefined ranges. These ranges are selected by an analysis of the frequencies of occurrence of interatomic distances in the data file that is being searched. The second stage involves the generation of all interatomic distances in potentially matching structures in the file to ascertain whether all of the query distances are present. If this is the case, a final search is carried out to determine whether these distances are in the correct geometric orientation to each other; this search involves a novel matching algorithm based upon the set reduction techniques used for substructure searching in files of 2D chemical structures. The evaluation of the system has involved the searching of several pharmacophoric patterns against a 12 728-compound subset of the Cambridge Crystallographic Data Bank. Measurements of the numbers of structures matching at each of the three levels of search show that the system provides a highly efficient means of identifying structures containing a query pharmacophore.     

Motifer, a search tool for finding amino acid sequence patterns from nucleotide sequence databases.

Motifer is a software tool able to find directly in nucleotide databases very distant homologues to an amino acid query sequence. It focuses searches on a specific amino acid pattern, scoring the matching and intervening residues as specified by the user. The program has been developed for searching databases of expressed sequence tags (ESTs), but it is also well suited to search genomic sequences. The query sequence can be a variable pattern with alternative amino acids or gaps and the sequences searched can contain introns or sequencing errors with accompanying frame shifts. Other features include options to generate a searchable output, set the maximal sequencing error frequency, limit searches to given species, or exclude already known matches. Motifer can find sequence homologues that other search algorithms would deem unrelated or would not find because of sequencing errors or a too large number of other homologues. The ability of Motifer to find relatives to a given sequence is exemplified by searches for members of the transforming growth factor-beta family and for proteins containing a WW-domain. The functions aimed at enhancing EST searches are illustrated by the 'in silico' cloning of a novel cytochrome P450 enzyme.     

MMDB: Entrez’s 3D-structure database

Three-dimensional structures are now known within many protein families and it is quite likely, in searching a sequence database, that one will encounter a homolog with known structure. The goal of Entrez’s 3D-structure database is to make this information, and the functional annotation it can provide, easily accessible to molecular biologists. To this end Entrez’s search engine provides three powerful features. (i) Sequence and structure neighbors; one may select all sequences similar to one of interest, for example, and link to any known 3D structures. (ii) Links between databases; one may search by term matching in MEDLINE, for example, and link to 3D structures reported in these articles. (iii) Sequence and structure visualization; identifying a homolog with known structure, one may view molecular-graphic and alignment displays, to infer approximate 3D structure. In this article we focus on two features of Entrez’s Molecular Modeling Database (MMDB) not described previously: links from individual biopolymer chains within 3D structures to a systematic taxonomy of organisms represented in molecular databases, and links from individual chains (and compact 3D domains within them) to structure neighbors, other chains (and 3D domains) with similar 3D structure. MMDB may be accessed at http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=Structure.     

CO: A chemical ontology for identification of functional groups and semantic comparison of small molecules

A novel chemical ontology based on chemical functional groups automatically, objectively assigned by a computer program, was developed to categorize small molecules. It has been applied to PubChem and the small molecule interaction database to demonstrate its utility as a basic pharmacophore search system. Molecules can be compared using a semantic similarity score based on functional group assignments rather than 3D shape, which succeeds in identifying small molecules known to bind a common binding site. This ontology will serve as a powerful tool for searching chemical databases and identifying key functional groups responsible for biological activities.     

Molecular determinants of non-specific recognition of delta, mu, and kappa opioid receptors

Identification of the molecular determinants of recognition common to all three opioid receptors embedded in a single three-dimensional (3D) non-specific recognition pharmacophore has been carried out. The working hypothesis that underlies the computational study reported here is that ligands that bind with significant affinity to all three cloned opioid receptors, delta, mu, and kappa, but with different combinations of activation and inhibition properties at these receptors, could be promising behaviorally selective analgesics with diminished side effects. The study presented here represents the first step towards the rational design of such therapeutic agents. The common 3D pharmacophore developed for recognition of delta, mu, and kappa opioid receptors was based on the receptor affinities determined for 23 different opioid ligands that display no specificity for any of the receptor subtypes. The pharmacophore centers identified are a protonated amine, two hydrophobic groups, and the centroid of an aromatic group in a geometric arrangement common to all 23, non-specific, opioid ligands studied. Using this three-dimensional pharmacophore as a query for searching 3D structural databases, novel compounds potentially involved in non-specific recognition of delta, mu, and kappa opioid receptors were retrieved. These compounds can be valuable candidates for novel behaviorally selective analgesics with diminished or no side effects, and thus with potential therapeutic usefulness.     

FR3D: finding local and composite recurrent structural motifs in RNA 3D structures

New methods are described for finding recurrent three-dimensional (3D) motifs in RNA atomic-resolution structures. Recurrent RNA 3D motifs are sets of RNA nucleotides with similar spatial arrangements. They can be local or composite. Local motifs comprise nucleotides that occur in the same hairpin or internal loop. Composite motifs comprise nucleotides belonging to three or more different RNA strand segments or molecules. We use a base-centered approach to construct efficient, yet exhaustive search procedures using geometric, symbolic, or mixed representations of RNA structure that we implement in a suite of MATLAB programs, “Find RNA 3D” (FR3D). The first modules of FR3D preprocess structure files to classify base-pair and -stacking interactions. Each base is represented geometrically by the position of its glycosidic nitrogen in 3D space and by the rotation matrix that describes its orientation with respect to a common frame. Base-pairing and base-stacking interactions are calculated from the base geometries and are represented symbolically according to the Leontis/Westhof basepairing classification, extended to include base-stacking. These data are stored and used to organize motif searches. For geometric searches, the user supplies the 3D structure of a query motif which FR3D uses to find and score geometrically similar candidate motifs, without regard to the sequential position of their nucleotides in the RNA chain or the identity of their bases. To score and rank candidate motifs, FR3D calculates a geometric discrepancy by rigidly rotating candidates to align optimally with the query motif and then comparing the relative orientations of the corresponding bases in the query and candidate motifs. Given the growing size of the RNA structure database, it is impossible to explicitly compute the discrepancy for all conceivable candidate motifs, even for motifs with less than ten nucleotides. The screening algorithm that we describe finds all candidate motifs whose geometric discrepancy with respect to the query motif falls below a user-specified cutoff discrepancy. This technique can be applied to RMSD searches. Candidate motifs identified geometrically may be further screened symbolically to identify those that contain particular basepair types or base-stacking arrangements or that conform to sequence continuity or nucleotide identity constraints. Purely symbolic searches for motifs containing user-defined sequence, continuity and interaction constraints have also been implemented. We demonstrate that FR3D finds all occurrences, both local and composite and with nucleotide substitutions, of sarcin/ricin and kink-turn motifs in the 23S and 5S ribosomal RNA 3D structures of the H. marismortui 50S ribosomal subunit and assigns the lowest discrepancy scores to bona fide examples of these motifs. The search algorithms have been optimized for speed to allow users to search the non-redundant RNA 3D structure database on a personal computer in a matter of minutes.     

Query Chem: a Google-powered web search combining text and chemical structures

Query Chem (www.QueryChem.com) is a Web program that integrates chemical structure and text-based searching using publicly available chemical databases and Google's Web Application Program Interface (API). Query Chem makes it possible to search the Web for information about chemical structures without knowing their common names or identifiers. Furthermore, a structure can be combined with textual query terms to further restrict searches. Query Chem's search results can retrieve many interesting structure-property relationships of biomolecules on the Web.     

signatureSearch: environment for gene expression signature searching and functional interpretation

signatureSearch is an R/Bioconductor package that integrates a suite of existing and novel algorithms into an analysis environment for gene expression signature (GES) searching combined with functional enrichment analysis (FEA) and visualization methods to facilitate the interpretation of the search results. In a typical GES search (GESS), a query GES is searched against a database of GESs obtained from large numbers of measurements, such as different genetic backgrounds, disease states and drug perturbations. Database matches sharing correlated signatures with the query indicate related cellular responses frequently governed by connected mechanisms, such as drugs mimicking the expression responses of a disease. To identify which processes are predominantly modulated in the GESS results, we developed specialized FEA methods combined with drug-target network visualization tools. The provided analysis tools are useful for studying the effects of genetic, chemical and environmental perturbations on biological systems, as well as searching single cell GES databases to identify novel network connections or cell types. The signatureSearch software is unique in that it provides access to an integrated environment for GESS/FEA routines that includes several novel search and enrichment methods, efficient data structures, and access to pre-built GES databases, and allowing users to work with custom databases.     

XFINGER: A tool for searching and visualising protein fingerprints and patterns

A tool for searching pattern and fingerprint databases is described.Fingerprints are groups of motifs excised from conserved regionsof sequence alignments and used for iterative database scanning.The constituent motifs are thus encoded as small alignmentsin which sequence information is maximised with each databasepass; they therefore differ from regular-expression patterns,in which alignments are reduced to single consensus sequences.Different database formats have evolved to store these disparatetypes of information, namely the PROSITE dictionary of patternsand the PRINTS fingerprint database, but programs have not beenavailable with the flexibility to search them both. We havedeveloped a facility to do this: the system allows query sequencesto be scanned against either PROSITE, the full PRINTS database,or against individual fingerprints. The results of fingerprintsearches are displayed simultaneously in both text and graphicalwindows to render them more tangible to the user. Where structuralcoordinates are available, identified motifs may be visualisedin a 3D context. The program runs on Silicon Graphics machinesusing GL graphics libraries and on machines with X servers supportingthe PEX extension: its use is illustrated here by depictingthe location of low-density lipoprotein-binding (LDL) motifsand leucine-rich repeats in a mosaic G-protein-coupled receptor(GPCR).     

PATMAT: a searching and extraction program for sequence, pattern and block queries and databases

A program has been developed that provides molecular biologistswith multiple tools for searching databases, yet uses a verysimple interface. PATMATcan use protein or (translated) DNAsequences, patterns or blocks of aligned proteins as queriesof databases consisting of amino acid or nucleotide sequences,patterns or blocks. The ability to search databases of blocksby ‘on-the-fly’ conversion to scoring matrices providesa new tool for detection and evaluation of distant relationships.PATMAT uses a pull-down, menu-driven interface to carry outits multiple searching, extraction and viewing functions. Eachquery or database type is recognized, reported, and the appropriatesearch carried out, with matches and alignments reported inwindows as they occur. Any of the high scoring matches can beexported to a file, viewed and recalled as a query using onlya few keystrokes or mouse selections. Searches of multiple databasefiles are carried out by user selection within a window. PATMATruns under DOS; the searching engine also runs under UNIX.     

LB3D: a protein three-dimensional substructure search program based on the lower bound of a root mean square deviation value

Searching for protein structure-function relationships using three-dimensional (3D) structural coordinates represents a fundamental approach for determining the function of proteins with unknown functions. Since protein structure databases are rapidly growing in size, the development of a fast search method to find similar protein substructures by comparison of protein 3D structures is essential. In this article, we present a novel protein 3D structure search method to find all substructures with root mean square deviations (RMSDs) to the query structure that are lower than a given threshold value. Our new algorithm runs in O(m + N/m(0.5)) time, after O(N log N) preprocessing, where N is the database size and m is the query length. The new method is 1.8-41.6 times faster than the practically best known O(N) algorithm, according to computational experiments using a huge database (i.e., >20,000,000 C-alpha coordinates).     

FACTA: a text search engine for finding associated biomedical concepts

FACTA is a text search engine for MEDLINE abstracts, which is designed particularly to help users browse biomedical concepts (e.g. genes/proteins, diseases, enzymes and chemical compounds) appearing in the documents retrieved by the query. The concepts are presented to the user in a tabular format and ranked based on the co-occurrence statistics. Unlike existing systems that provide similar functionality, FACTA pre-indexes not only the words but also the concepts mentioned in the documents, which enables the user to issue a flexible query (e.g. free keywords or Boolean combinations of keywords/concepts) and receive the results immediately even when the number of the documents that match the query is very large. The user can also view snippets from MEDLINE to get textual evidence of associations between the query terms and the concepts. The concept IDs and their names/synonyms for building the indexes were collected from several biomedical databases and thesauri, such as UniProt, BioThesaurus, UMLS, KEGG and DrugBank. AVAILABILITY: The system is available at http://www.nactem.ac.uk/software/facta/     

Pharmacophore-based molecular docking to account for ligand flexibility

Rapid computational mining of large 3D molecular databases is central to generating new drug leads. Accurate virtual screening of large 3D molecular databases requires consideration of the conformational flexibility of the ligand molecules. Ligand flexibility can be included without prohibitively increasing the search time by docking ensembles of precomputed conformers from a conformationally expanded database. A pharmacophore-based docking method whereby conformers of the same or different molecules are overlaid by their largest 3D pharmacophore and simultaneously docked by partial matches to that pharmacophore is presented. The method is implemented in DOCK 4.0.     

TPX: Biomedical literature search made easy

TPX is a web-based PubMed search enhancement tool that enables faster article searching using analysis and exploration features. These features include identification of relevant biomedical concepts from search results with linkouts to source databases, concept based article categorization, concept assisted search and filtering, query refinement. A distinguishing feature here is the ability to add user-defined concept names and/or concept types for named entity recognition. The tool allows contextual exploration of knowledge sources by providing concept association maps derived from the MEDLINE repository. It also has a full-text search mode that can be configured on request to access local text repositories, incorporating entity co-occurrence search at sentence/paragraph levels. Local text files can also be analyzed on-the-fly. Availability: http://tpx.atc.tcs.com     

MMDB: 3D structure data in Entrez

Three-dimensional structures are now known for roughly half of all protein families. It is thus quite likely, in searching sequence databases, that one will encounter a homolog with known structure and be able to use this information to infer structure-function properties. The goal of Entrez's 3D structure database is to make this information accessible and useful to molecular biologists. To this end, Entrez's search engine provides three powerful features: (i) Links between databases; one may search by term matching in Medline((R)), for example, and link to 3D structures reported in these articles. (ii) Sequence and structure neighbors; one may select all sequences similar to one of interest, for example, and link to any known 3D structures. (iii) Sequence and structure visualization; identifying a homolog with known structure, one may view a combined molecular-graphic and alignment display, to infer approximate 3D structure. Entrez's MMDB (Molecular Modeling DataBase) may be accessed at: http://www.ncbi.nlm.nih.gov/Entrez/structure.html