Tautomerism in chemical information management systems

Tautomerism has an impact on many of the processes in chemical information management systems including novelty checking during registration into chemical structure databases; storage of structures; exact and substructure searching in chemical structure databases; and depiction of structures retrieved by a search. The approaches taken by 27 different software vendors and database producers are compared. It is hoped that this comparison will act as a discussion document that could ultimately improve databases and software for researchers in the future.     

Representation of the molecular topology of cyclical structures by means of cycle graphs. 2. Application to clustering of chemical databases

The great size of chemical databases and the high computational cost required in the atom-atom comparison of molecular structures for the calculation of the similarity between two chemical compounds necessitate the proposal of new clustering models with the aim of reducing the time of recovery of a set of molecules from a database that satisfies a range of similarities with regard to a given molecule pattern. In this paper we make use of the information corresponding to the cycles existing in the structure of molecules as an approach for the classification of chemical databases. The clustering method here proposed is based on the representation of the topological structure of molecules stored in chemical databases through its corresponding cycle graph. This method presents a more appropriate behavior for others described in the bibliography in which the information corresponding to the cyclicity of the molecules is also used.     

Identification and selection of "privileged fragments" suitable for primary screening

The use of small molecule libraries for fragment-based primary screening (FBS) is a well-known approach to identify protein binders in the low affinity range. However, the search, analysis, and selection of suitable screening fragments can be a lengthy process, because of the large number of compounds that must be analyzed for different levels of ring/substituents identification and submitted to selection/exclusion criteria based on their physicochemical properties. The purpose of the present work is to propose a strategy to identify substructures from databases of known drugs, which can be used as templates for the generation of libraries of "privileged fragments" that are able to provide high-quality hits. The entire process has been developed integrating Pipeline Pilot (Accelrys Inc., San Diego, CA; http://www.accelrys.com ) native components and user-defined molecular files containing ISIS-like substructure query features (Symyx, San Ramon, CA; http://www.symyx.com ). The method is effortless, easy to put in place, and fast enough to be iteratively applied to different sources of druglike compounds.     

Quantum probability ranking principle for ligand-based virtual screening

Chemical libraries contain thousands of compounds that need screening, which increases the need for computational methods that can rank or prioritize compounds. The tools of virtual screening are widely exploited to enhance the cost effectiveness of lead drug discovery programs by ranking chemical compounds databases in decreasing probability of biological activity based upon probability ranking principle (PRP). In this paper, we developed a novel ranking approach for molecular compounds inspired by quantum mechanics, called quantum probability ranking principle (QPRP). The QPRP ranking criteria would make an attempt to draw an analogy between the physical experiment and molecular structure ranking process for 2D fingerprints in ligand based virtual screening (LBVS). The development of QPRP criteria in LBVS has employed the concepts of quantum at three different levels, firstly at representation level, this model makes an effort to develop a new framework of molecular representation by connecting the molecular compounds with mathematical quantum space. Secondly, estimate the similarity between chemical libraries and references based on quantum-based similarity searching method. Finally, rank the molecules using QPRP approach. Simulated virtual screening experiments with MDL drug data report (MDDR) data sets showed that QPRP outperformed the classical ranking principle (PRP) for molecular chemical compounds.     

Substructure isomorphism matrix

A substructure isomorphism matrix n x p contains binary elements describing which of the given p query structures (substructures) are part of the given n target structures (molecular structures). Such a matrix can be used to investigate the diversity of the target structures and allows the characterization and comparison of structural libraries. A quadratic substructure isomorphism matrix n x n is obtained if the same structures are used as molecular structures and as substructures; this matrix contains full information about the topological hierarchy of the n structures. A hierarchical arrangement of chemical structures is useful for the evaluation of results obtained from searches in structure databases.     

A system for encoding and searching markush structures

The encoding and searching of generic chemical structures, so-called Markush structures, have received little attention in the literature of late. The ability to encode and search these complex entities is of use in various branches of chemoinformatics. We describe a general language for encoding Markush structures and algorithms for searching them and give three examples of the utility of such a system: development of general Free-Wilson analyses of chemical series, detection of controlled substances within a large database of molecular structures, and searching of large databases of virtual compounds.     

Is nontarget screening of emerging contaminants by LC-HRMS successful? A plea for compound libraries and computer tools

This review focuses on the possibilities and limits of nontarget screening of emerging contaminants, with emphasis on recent applications and developments in data evaluation and compound identification by liquid chromatography-high-resolution mass spectrometry (HRMS). The general workflow includes determination of the elemental composition from accurate mass, a further search for the molecular formula in compound libraries or general chemical databases, and a ranking of the proposed structures using further information, e.g., from mass spectrometry (MS) fragmentation and retention times. The success of nontarget screening is in some way limited to the preselection of relevant compounds from a large data set. Recently developed approaches show that statistical analysis in combination with suspect and nontarget screening are useful methods to preselect relevant compounds. Currently, the unequivocal identification of unknowns still requires information from an authentic standard which has to be measured or is already available in user-defined MS/MS reference databases or libraries containing HRMS spectral information and retention times. In this context, we discuss the advantages and future needs of publicly available MS and MS/MS reference databases and libraries which have mostly been created for the metabolomic field. A big step forward has been achieved with computer-based tools when no MS library or MS database entry is found for a compound. The numerous search results from a large chemical database can be condensed to only a few by in silico fragmentation. This has been demonstrated for selected compounds and metabolites in recent publications. Still, only very few compounds have been identified or tentatively identified in environmental samples by nontarget screening. The availability of comprehensive MS libraries with a focus on environmental contaminants would tremendously improve the situation.     

A graph theory data base for storage of chemical structures organized by the block-cutpoint tree technique

The method presented for organizing a data base according to graph theory, is based on representation of chemical structures in terms of BCT (block-cutpoint tree). It is useful for quick substructure searches and is convenient for structure generation. The data base consists of four files: a master file, a bit sequence file of fixed length records which gives block components of compounds, a BCT file which gives the BCT structures of compounds, and a block file which specifies the blocks. These files are organized recursively and hierarchally, which simplifies the processing of structural information on compounds.     

A computer search system for chemical structure elucidation based on low-resolution mass spectra

A computerized search system which employs the data on the masses and relative abundances of spectral peaks and primary neutral losses is designed for computer elucidation of chemical structures. Recognition of structural fragments is based on analysis of the structures of reference compounds selected as best matches to the mass spectrum of the compound under investigation. Tests of the system on 67 “unknowns” show that the probability of recognizing a large structural fragment lies in the interval 60–80%, depending on the fragment size (100–50% of molecular weight), and that the reliability of the corresponding structural conclusion is 98%. An approach to automatic selection of the substructure common to all or several of the selected compounds is discussed.     

Algorithm for naming molecular equivalence classes represented by labeled pseudographs

The emergence of large chemical databases imposes a need for organizing the compounds in these databases. Mapping the chemical graph in particular, and a molecular equivalence class represented by a labeled pseudograph in general, to a unique number or string facilitates high-throughput browsing, grouping, and searching of the chemical database. Computing this number using a naming adaptation of the Morgan algorithm, we observed a large classification noise in which nonisomorphic graphs were mapped to the same number. Our extensions to that algorithm greatly reduced the classification noise.