Fast 3D molecular superposition and similarity search in databases of flexible molecules

We present a new method (fFLASH) for the virtual screening of compound databases that is based on explicit three-dimensional molecular superpositions. fFLASH takes the torsional flexibility of the database molecules fully into account, and can deal with an arbitrary number of conformation-dependent molecular features. The method utilizes a fragmentation-reassembly approach which allows for an efficient sampling of the conformational space. A fast clique-based pattern matching algorithm generates alignments of pairs of adjacent molecular fragments on the rigid query molecule that are subsequently reassembled to complete database molecules. Using conventional molecular features (hydrogen bond donors and acceptors, charges, and hydrophobic groups) we show that fFLASH is able to rapidly produce accurate alignments of medium-sized drug-like molecules. Experiments with a test database containing a diverse set of 1780 drug-like molecules (including all conformers) have shown that average query processing times of the order of 0.1 seconds per molecule can be achieved on a PC.     

Effectiveness of graph-based and fingerprint-based similarity measures for virtual screening of 2D chemical structure databases

This paper reports an evaluation of both graph-based and fingerprint-based measures of structural similarity, when used for virtual screening of sets of 2D molecules drawn from the MDDR and ID Alert databases. The graph-based measures employ a new maximum common edge subgraph isomorphism algorithm, called RASCAL, with several similarity coefficients described previously for quantifying the similarity between pairs of graphs. The effectiveness of these graph-based searches is compared with that resulting from similarity searches using BCI, Daylight and Unity 2D fingerprints. Our results suggest that graph-based approaches provide an effective complement to existing fingerprint-based approaches to virtual screening.     

Advanced exact structure searching in large databases of chemical compounds

Efficient recognition of tautomeric compound forms in large corporate or commercially available compound databases is a difficult and labor intensive task. Our data indicate that up to 0.5% of commercially available compound collections for bioscreening contain tautomers. Though in the large registry databases, such as Beilstein and CAS, the tautomers are found in an automated fashion using high-performance computational technologies, their real-time recognition in the nonregistry corporate databases, as a rule, remains problematic. We have developed an effective algorithm for tautomer searching based on the proprietary chemoinformatics platform. This algorithm reduces the compound to a canonical structure. This feature enables rapid, automated computer searching of most of the known tautomeric transformations that occur in databases of organic compounds. Another useful extension of this methodology is related to the ability to effectively search for different forms of compounds that contain ionic and semipolar bonds. The computations are performed in the Windows environment on a standard personal computer, a very useful feature. The practical application of the proposed methodology is illustrated by several examples of successful recovery of tautomers and different forms of ionic compounds from real commercially available nonregistry databases.     

Performance evaluation of 2D fingerprint and 3D shape similarity methods in virtual screening

Virtual screening (VS) can be accomplished in either ligand- or structure-based methods. In recent times, an increasing number of 2D fingerprint and 3D shape similarity methods have been used in ligand-based VS. To evaluate the performance of these ligand-based methods, retrospective VS was performed on a tailored directory of useful decoys (DUD). The VS performances of 14 2D fingerprints and four 3D shape similarity methods were compared. The results revealed that 2D fingerprints ECFP_2 and FCFP_4 yielded better performance than the 3D Phase Shape methods. These ligand-based methods were also compared with structure-based methods, such as Glide docking and Prime molecular mechanics generalized Born surface area rescoring, which demonstrated that both 2D fingerprint and 3D shape similarity methods could yield higher enrichment during early retrieval of active compounds. The results demonstrated the superiority of ligand-based methods over the docking-based screening in terms of both speed and hit enrichment. Therefore, considering ligand-based methods first in any VS workflow would be a wise option.     

Learning from the data: mining of large high-throughput screening databases

High-throughput screening (HTS) campaigns in pharmaceutical companies have accumulated a large amount of data for several million compounds over a couple of hundred assays. Despite the general awareness that rich information is hidden inside the vast amount of data, little has been reported for a systematic data mining method that can reliably extract relevant knowledge of interest for chemists and biologists. We developed a data mining approach based on an algorithm called ontology-based pattern identification (OPI) and applied it to our in-house HTS database. We identified nearly 1500 scaffold families with statistically significant structure-HTS activity profile relationships. Among them, dozens of scaffolds were characterized as leading to artifactual results stemming from the screening technology employed, such as assay format and/or readout. Four types of compound scaffolds can be characterized based on this data mining effort: tumor cytotoxic, general toxic, potential reporter gene assay artifact, and target family specific. The OPI-based data mining approach can reliably identify compounds that are not only structurally similar but also share statistically significant biological activity profiles. Statistical tests such as Kruskal-Wallis test and analysis of variance (ANOVA) can then be applied to the discovered scaffolds for effective assignment of relevant biological information. The scaffolds identified by our HTS data mining efforts are an invaluable resource for designing SAR-robust diversity libraries, generating in silico biological annotations of compounds on a scaffold basis, and providing novel target family specific scaffolds for focused compound library design.     

A novel search engine for virtual screening of very large databases

Virtual screening of large chemical databases using the structure of the receptor can be computationally very demanding. We present a novel strategy that combines exhaustive similarity searches directly in SMILES format with the docking of flexible ligands, whose 3D structure is generated on the fly from the SMILES representation. Our strategy makes use of the recently developed LINGO tools to extract implicit chemical information from SMILES strings and integrates LINGO similarities into a pseudo-evolutionary algorithm. The algorithm represents a combination of a fast target-independent similarity method with a slower but information richer target-focused method. A virtual search of FactorXa ligands provided 62% of the potential hits after docking only 6.5% of a database of nearly 1 million molecules. The set of solutions showed good diversity, indicating that the method shows good scaffold hopping capabilities.     

Discovery of chemical reactions through multidimensional screening

Multidimensional reaction screening of ortho-alkynyl benzaldehydes with a variety of catalysts and reaction partners was conducted in an effort to identify new chemical reactions. Reactions affording unique products were selected for investigation of preliminary scope and limitations.     

Comparison of the NCI open database with seven large chemical structural databases.

Eight large chemical databases have been analyzed and compared to each other. Central to this comparison is the open National Cancer Institute (NCI) database, consisting of approximately 250 000 structures. The other databases analyzed are the Available Chemicals Directory ("ACD," from MDL, release 1.99, 3D-version); the ChemACX ("ACX," from CamSoft, Version 4.5); the Maybridge Catalog and the Asinex database (both as distributed by CamSoft as part of ChemInfo 4.5); the Sigma-Aldrich Catalog (CD-ROM, 1999 Version); the World Drug Index ("WDI," Derwent, version 1999.03); and the organic part of the Cambridge Crystallographic Database ("CSD," from Cambridge Crystallographic Data Center, 1999 Version 5.18). The database properties analyzed are internal duplication rates; compounds unique to each database; cumulative occurrence of compounds in an increasing number of databases; overlap of identical compounds between two databases; similarity overlap; diversity; and others. The crystallographic database CSD and the WDI show somewhat less overlap with the other databases than those with each other. In particular the collections of commercial compounds and compilations of vendor catalogs have a substantial degree of overlap among each other. Still, no database is completely a subset of any other, and each appears to have its own niche and thus "raison d'être". The NCI database has by far the highest number of compounds that are unique to it. Approximately 200 000 of the NCI structures were not found in any of the other analyzed databases.     

New approach to molecular docking and its application to virtual screening of chemical databases

This paper describes the validation of a molecular docking method and its application to virtual database screening. The code flexibly docks ligand molecules into rigid receptor structures using a tabu search methodology driven by an empirically derived function for estimating the binding affinity of a protein-ligand complex. The docking method has been tested on 70 ligand-receptor complexes for which the experimental binding affinity and binding geometry are known. The lowest energy geometry produced by the docking protocol is within 2.0 A root mean square of the experimental binding mode for 79% of the complexes. The method has been applied to the problem of virtual database screening to identify known ligands for thrombin, factor Xa, and the estrogen receptor. A database of 10,000 randomly chosen "druglike" molecules has been docked into the three receptor structures. In each case known receptor ligands were included in the study. The results showed good separation between the predicted binding affinities of the known ligand set and the database subset.     

Fast 2D NMR ligand screening using Hadamard spectroscopy

Fast 2D NMR-based screening can be achieved using Hadamard encoded spectroscopy to focus on the signals of interest (e.g., enzyme active or ligand recognition sites). By recording a set of Hadamard spectra (a "Hadamard constellation") with relative offsets comparable to the excitation bandwidth, quantitative ligand-induced shifts can be obtained from peak intensities.     

Review of chemical signature databases

This review assesses the current state of chemical signature databases, the primary characteristics that determine their applicability, characterization of their capability to support spectral identifications, and the target audience to which they are directed. Database file formats, spectrometer operating conditions, and spectral matching tools are found to be primary characteristics that determine the applicability of databases and their ability to support spectral identifications. Chemical signature databases have evolved in two very different directions. One movement offers a single portal for chemical signature determinations by multiple analytical techniques. The other movement is toward highly specialized databases that address narrow scientific disciplines. Both movements are necessary, and serve distinctly different needs in the analytical community.     

Representation of the molecular topology of cyclical structures by means of cycle graphs. 3. Hierarchical model of screening of chemical databases

The increase in the size and complexity of chemical databases necessitates the proposal and development of efficient methods of classification and recovery of information, which supposes proposal of a model of classification of database records and the use of a compatible model of screening for inspection of clusters and recovery of the molecules that satisfy the search criterion. The cycle graphs model based on consideration of all the cycles and chains (and equivalent cycles and chains) present in the molecular structure has been proven appropriate for classification of chemical databases, giving rise to a generation of different classification levels depending on the structural elements (cycles and chains) that are considered. In this paper we propose a screening model, compatible with the cycle graphs model, based on a hierarchy of levels of abstraction. The set of molecules that satisfies a screening model (or selection criterion) diminishes as we advance in the hierarchy of levels of the model, which allows filtering of records and, therefore, an increase in the efficiency of the screening process. In the following work of this series we describe and validate the screening tool developed.     

CLIP: similarity searching of 3D databases using clique detection

This paper describes a program for 3D similarity searching, called CLIP (for Candidate Ligand Identification Program), that uses the Bron-Kerbosch clique detection algorithm to find those structures in a file that have large structures in common with a target structure. Structures are characterized by the geometric arrangement of pharmacophore points and the similarity between two structures calculated using modifications of the Simpson and Tanimoto association coefficients. This modification takes into account the fact that a distance tolerance is required to ensure that pairs of interatomic distances can be regarded as equivalent during the clique-construction stage of the matching algorithm. Experiments with HIV assay data demonstrate the effectiveness and the efficiency of this approach to virtual screening.     

Fast and efficient in silico 3D screening: toward maximum computational efficiency of pharmacophore-based and shape-based approaches

In continuation of our recent studies on the quality of conformational models generated with CATALYST and OMEGA we present a large-scale survey focusing on the impact of conformational model quality and several screening parameters on pharmacophore-based and shape-based virtual high throughput screening (vHTS). Therefore, we collected known active compounds of CDK2, p38 MAPK, PPAR-gamma, and factor Xa and built a set of druglike decoys using ilib:diverse. Subsequently, we generated 3D structures using CORINA and also calculated conformational models for all compounds using CAESAR, CATALYST FAST, and OMEGA. A widespread set of 103 structure-based pharmacophore models was developed with LigandScout for virtual screening with CATALYST. The performance of both database search modes (FAST and BEST flexible database search) as well as the fit value calculation procedures (FAST and BEST fit) available in CATALYST were analyzed in terms of their ability to discriminate between active and inactive compounds and in terms of efficiency. Moreover, these results are put in direct comparison to the performance of the shape-based virtual screening platform ROCS. Our results prove that high enrichment rates are not necessarily in conflict with efficient vHTS settings: In most of the experiments, we obtained the highest yield of actives in the hit list when parameter sets for the fastest search algorithm were used.