Combining ethnopharmacology and virtual screening for lead structure discovery: COX-inhibitors as application example

Virtual screening of large libraries of organic compounds combined with pharmacological high throughput screening is widely used for drug discovery in the pharmaceutical industry. Our aim was to explore the efficiency of using a biased 3D database comprising secondary metabolites from antiinflammatory medicinal plants as a source for the virtual screening. For this study pharmacophore models of cyclooxygenase I and II (COX-1, COX-2), key enzymes in the inflammation process, were generated with structure-based as well as common feature based modeling, resulting in three COX hypotheses. Four different multiconfomational 3D databases limited in molecular weight between 300 and 700 Da were applied to the screening in order to compare and analyze the obtained hit rates. Two of them were created in-house (DIOS, NPD). The database DIOS consists of 2752 compounds from phytochemical reports of antiinflammatory medicinal plants described by the ethnopharmacological source 'De material medica' of Pedanius Dioscorides, whereas NPD contains almost 80,000 compounds gathered arbitrarily from natural sources. In addition, two available multiconformational 3D libraries comprising marketed and development drug substances (DWI and NCI), mainly originating from synthesis, were used for comparison. As a test of the pharmacophore models' capability in natural sources, the models were used to search for known COX inhibitory natural products. This was achieved with some exceptions, which are discussed in the paper. Depending on the hypothesis used, DWI and NCI library searches produced hit rates in the range of 6.6% to 13.7%. A slight increase of the number of molecules assessed for binding was achieved with the database of natural products (NPD). Using the biased 3D database DIOS, however, the average increase of efficiency reached 77% to 133% compared to the hit rates resulting from WDI and NCI. The statistical benefit of a combination of an ethnopharmacological approach with the potential of computer aided drug discovery by in silico screening was demonstrated exemplified on the applied targets COX-1 and COX-2.     

The Cambridge Structural Database in Retrospect and Prospect

The Cambridge Crystallographic Data Centre (CCDC) was established in 1965 to record numerical, chemical and bibliographic data relating to published organic and metal–organic crystal structures. The Cambridge Structural Database (CSD) now stores data for nearly 700 000 structures and is a comprehensive and fully retrospective historical archive of small‐molecule crystallography. Nearly 40 000 new structures are added each year. As X‐ray crystallography celebrates its centenary as a subject, and the CCDC approaches its own 50th year, this article traces the origins of the CCDC as a publicly funded organization and its onward development into a self‐financing charitable institution. Principally, however, we describe the growth of the CSD and its extensive associated software system, and summarize its impact and value as a basis for research in structural chemistry, materials science and the life sciences, including drug discovery and drug development. Finally, the article considers the CCDC’s funding model in relation to open access and open data paradigms.     

Chemometric analysis of skeletal data from non-fused and non-pi-complexed pentafulvenes

A broad chemometric study was made on structural data from non-fused and non-pi-complexed pentafulvenes obtained both from the Cambridge structural database (CSD) and from several studies to synthesise new fulvene compounds. Three main differentiated pentafulvene groups can be established considering bond distances extracted from the CSD database. Structural data for the new 1-mono and 1,4-disubstituted 2,3,6-trioxypentafulvenes and 1,4-disubstituted-6-amino-2, 3-dioxypentafulvenes reveal different structural behaviours due to their high functionality. The chemometric techniques employed comprise principal component analysis, cluster analysis, selection of essential variables (Procrustes rotation) and isoprobability curves, all of them giving essentially the same general chemical conclusions.     

Tautomerism in large databases

We have used the Chemical Structure DataBase (CSDB) of the NCI CADD Group, an aggregated collection of over 150 small-molecule databases totaling 103.5 million structure records, to conduct tautomerism analyses on one of the largest currently existing sets of real (i.e. not computer-generated) compounds. This analysis was carried out using calculable chemical structure identifiers developed by the NCI CADD Group, based on hash codes available in the chemoinformatics toolkit CACTVS and a newly developed scoring scheme to define a canonical tautomer for any encountered structure. CACTVS’s tautomerism definition, a set of 21 transform rules expressed in SMIRKS line notation, was used, which takes a comprehensive stance as to the possible types of tautomeric interconversion included. Tautomerism was found to be possible for more than 2/3 of the unique structures in the CSDB. A total of 680 million tautomers were calculated from, and including, the original structure records. Tautomerism overlap within the same individual database (i.e. at least one other entry was present that was really only a different tautomeric representation of the same compound) was found at an average rate of 0.3% of the original structure records, with values as high as nearly 2% for some of the databases in CSDB. Projected onto the set of unique structures (by FICuS identifier), this still occurred in about 1.5% of the cases. Tautomeric overlap across all constituent databases in CSDB was found for nearly 10% of the records in the collection.     

From data to knowledge—Use of the Cambridge Structural Database for studying molecular interactions

Abstract

The ordered arrangement of molecules and ions in crystal structures is the result of non-bonded interactions, albeit modulated in the crystalline state by random crystal packing forces. Each individual crystal structure gives but a snapshot of these interactions. It is only by examining a large number of structures containing similar molecules or functional groups that we can gain any generalized knowledge about the rules governing molecular interactions. Indeed if we knew these rules it should be possible to predict crystal structures likely to be formed by specific molecules, whereas at present each new crystal structure requires a de novo experimental solution. We would also be able to evaluate the relative contribution of non-bonded and crystal packing forces and extrapolate to the interactive behaviour of molecules in solution and, most importantly, in the environments encountered in biological systems. A key to these studies is the Cambridge Structural Database (CSD) system where experimental results from over 100,000 individual structure determinations are stored in computer readable form. The system also provides the computational tools needed to locate the relevant structures and analyse the numerical data using a variety of statistical techniques. This paper describes the latest Version of the CSD system (Version 5) released Autumn 1992. The use of the system is illustrated by several examples, such as the preferential interaction of certain functional groups, the study of the C—H…O bond and drug-DNA interactions.     

Large-scale annotation of small-molecule libraries using public databases

While many large publicly accessible databases provide excellent annotation for biological macromolecules, the same is not true for small chemical compounds. Commercial data sources also fail to encompass an annotation interface for large numbers of compounds and tend to be cost prohibitive to be widely available to biomedical researchers. Therefore, using annotation information for the selection of lead compounds from a modern day high-throughput screening (HTS) campaign presently occurs only under a very limited scale. The recent rapid expansion of the NIH PubChem database provides an opportunity to link existing biological databases with compound catalogs and provides relevant information that potentially could improve the information garnered from large-scale screening efforts. Using the 2.5 million compound collection at the Genomics Institute of the Novartis Research Foundation (GNF) as a model, we determined that approximately 4% of the library contained compounds with potential annotation in such databases as PubChem and the World Drug Index (WDI) as well as related databases such as the Kyoto Encyclopedia of Genes and Genomes (KEGG) and ChemIDplus. Furthermore, the exact structure match analysis showed 32% of GNF compounds can be linked to third party databases via PubChem. We also showed annotations such as MeSH (medical subject headings) terms can be applied to in-house HTS databases in identifying signature biological inhibition profiles of interest as well as expediting the assay validation process. The automated annotation of thousands of screening hits in batch is becoming feasible and has the potential to play an essential role in the hit-to-lead decision making process.     

Correlation between DFT calculated and X-ray structures from CSD,for Cu(II) and Cu(I) coordination spheres when coordinated to four acyclic amine ligands. A reconsideration of copper(II) planarity

The Cambridge Crystallographic Database (CSD) shows [Cu^IIL₄]²⁺ complexes, L = acyclic amine, fitting well with theoretically calculated structures to describe a planar-to-flat tetrahedral transformation pathway. Statistically, the Cu^II “planar” coordination sphere shows two distinct sets of trans N–Cu–N bond angles, 180° and near 150°, with the latter somewhat energetically favored according to DFT results. The planar structure is not confirmed theoretically when an example of these molecules in the CSD is geometrically minimized, suggesting that crystallographic or packing forces help to generate the planar structure in the crystal. Results of energy calculations from DFT seem to explain this feature. Less planar and more tetrahedral examples in the CSD are also found and compare well with theoretically converged related molecules. Trans N–Cu–N bond angles near 130° seem feasible for both Cu^I and Cu^II coordination spheres. These copper complexes having the copper coordination sphere in a less tetrahedral geometry are suggested as potential alternative models for blue proteins, and they deserve further exploration.     

Use of vector processing to search the Cambridge Structural Database

The Cambridge Structural Database (CSD) is a vast numerical resource of crystallographic data. The January 1989 release contains over 70,000 entries, and the data acquisition rate currently increases about 15% per annum. To be able to provide adequate response times for interactive data retrieval, using the new (1988) CSD file format, a vectorized search procedure has been developed as a modification of the CSD program QUEST. This procedure employs the pipelined vector facilities of the CONVEX C120 system to perform bitscreen logic, resulting in response times for arbitrary queries in the order of seconds, almost independent of the size of the database.     

Computational validation of the importance of absolute stereochemistry in virtual screening

Consideration of stereochemistry early in the identification and optimization of lead compounds can improve the efficiency and efficacy of the drug discovery process and reduce the time spent on subsequent drug development. These improvements can result by focusing on specific enantiomers that have the desired potential therapeutic effect (eutomers), while removing from consideration enantiomers that may have no, or even undesirable, effects (distomers). A virtual screening campaign that correctly takes stereochemical information into account can, in theory, be utilized to provide information about the relative binding affinities of enantiomers. Thus, the proper enumeration of the relevant stereoisomers in general, and enantiomeric pairs in particular, of chiral compounds is crucial if one is to use virtual screening as an effective drug discovery tool. As is obvious, in cases where no stereochemical information is provided for chiral compounds in a 2D chemical database, then each possible stereoisomer should be generated for construction of the subsequent 3D database to be used for virtual screening. However, acute problems can arise in 3D database construction when relative stereochemistry is encoded in a 2D database for a chiral compound containing multiple stereogenic atoms but absolute stereochemistry is not implied. In this case, we report that generation of enantiomeric pairs is imperative in database development if one is to obtain accurate docking results. A study is described on the impact of the neglect of enantiomeric pairs on virtual screening using the human homolog of murine double minute 2 (MDM2) protein, the product of a proto-oncogene, as the target. Docking in MDM2 with GLIDE 4.0 was performed using the NCI Diversity Set 3D database and, for comparison, a set of enantiomers we created corresponding to mirror image structures of the single enantiomers of chiral compounds present in the NCI Diversity Set. Our results demonstrate that potential lead candidates may be overlooked when databases contain 3D structures representing only a single enantiomer of racemic chiral compounds.     

Enrichment of ligands for the serotonin receptor using the Shape Signatures approach

Shape Signatures, a new 3-dimensional molecular comparison method, has been adapted to rank ligands of the serotonin receptors. A set of 825 agonists and 400 antagonists together with approximately 10,000 randomly chosen compounds from the NCI database were used in this study. Both 1D and 2D Shape Signature databases were created, and enrichment studies were carried out. Results from these studies reveal that the 1D Shape Signature approach is highly efficient in separating agonists from a mixture of molecules which includes compounds randomly selected from the NCI database taken as inactives. It is also equally effective at separating agonists and antagonists from a pool of active ligands for the serotonin receptor. Parallel enrichment studies using 2D shape signatures showed high selectivity with more restricted coverage due to the high specificity of 2D signatures. The influence of conformational variation of the shape signature on enrichment was explored by docking a subset of ligands into the crystal structure of serotonin N-acetyltransferase. Enrichment studies on the resulting "docked" conformations produced only slightly improved results compared with the CORINA-generated conformations.     

Librarians, crystal structures and drug design

There are now 355,000 published crystal structures of organic and metal-organic compounds, all of which have been acquired, validated, chemically annotated and organised for searching in the Cambridge Structural Database (CSD). The CSD is used in rational drug design and is beginning to answer important questions relevant to the formulation of pharmaceutical active ingredients. The value and credibility of this research are ultimately dependent on the accuracy and completeness of the underlying crystal-structure data.     

The NCI Drug Information System. 4. Inventory and Shipping Modules

The Inventory/Shipping package of the NCI Drug Information System (DIS) is designed to support all inventory and shipping operations associated with the testing by the NCI of large numbers of chemicals for anticancer activity. Two major databases, an Inventory database and a Shipping History database, contain all of the data associated with these operations. Software that supports the operations in an online interactive manner also provides for the accessing and updating of these databases as necessary. Special hardware in the form of barcode reader/printers and digital balances is also interfaced to the system to improve the efficiency of the operations.     

Internet resources integrating many small-molecule databases

()New data, tools and services recently made available on the web server (http://cactus.nci.nih.gov) of the Computer-Aided Drug Design (CADD) Group, NCI, NIH, developed in the context of chemoinformatics and drug development work, are presented. These tools are designed for searching for structures in very large databases of small molecules. One of them is a web service-the Chemical Structure Look-up Service (CSLS)-for very rapid structure look-up in an aggregated collection of more than 80 databases comprising more than 27 million unique structures at the time of this writing. CSLS contains pointers to the entries in toxicology-related databases, catalogues of commercially available samples, drugs, assay results data sets, and databases in several other categories. CSLS allows the user to find out very rapidly in which one(s) of all these databases a given structure occurs independent of the representation of the input structure, by making use of InChIs as well as new CACTVS hashcode-based identifiers. These latter, calculable, identifiers are designed to take into account tautomerism, different resonance structures drawn for charged species, and presence of additional fragments. They make possible fine-tunable yet rapid compound identification and database overlap analyses in very large compound collections.     

Web-based tools for mining the NCI databases for anticancer drug discovery

In this paper, we describe the development of a set of integrated Web-based tools for mining the National Cancer Institute's (NCI) anticancer databases for anticancer drug discovery. For data mining, three different correlation algorithms were implemented, which included the commonly used Pearson's correlation algorithm available from the NCI's COMPARE program, the Spearman's and Kendall's correlation algorithms. In addition, we implemented the p-value test to evaluate the significance of the correlation results. These Web-based data mining tools allow robust analysis of the correlation between the in vitro anticancer activity of the drugs in the NCI anticancer database, the protein levels and mRNA levels of molecular targets (genes) in the NCI 60 human cancer cell lines for identification of potential lead compounds for a specific molecular target and for study of the molecular mechanism action of a drug. Examples were provided to identify PKC ligands using a lead compound and to identify potential ErbB-2 inhibitors using the mRNA levels of ErbB-2 in the NCI 60 tumor cell lines.     

In silico drug repositioning of FDA-approved drugs to predict new inhibitors for alpha-synuclein aggregation

One of the hallmarks of Parkinson’s disease (PD), a long-term neurodegenerative syndrome, is the accumulation of alpha-synuclein (α-syn) fibrils. Despite numerous studies and efforts, inhibition of α-syn protein aggregation is still a challenge. To overcome this issue, we propose an in silico pharmacophore-based repositioning strategy, to find a pharmaceutical drug that, in addition to their defined role, can be used to prevent aggregation of the α-syn protein. Ligand-based pharmacophore modeling was developed and the best model was selected with validation parameters including 72 % sensitivity, 98 % specificity and goodness score about 0.7. The optimal model has three groups of hydrogen bond donor (HBD), three groups of hydrogen bond acceptor (HBA), and two aromatic rings (AR). The FDA-Approved reports in the ZINC15 database were screened with the pharmacophore model taken from inhibitor compounds. The model identified 22 hits, as promising candidate drugs for Parkinson's therapy. It is noteworthy that among these, 10 drugs have been reported to inhibition of α-syn aggregation or treat/reduce Parkinson's pathogenesis. This model was used to virtual screen ZINC, NCI databases, and natural products from the pomegranate. The results of this screen were filtered for their inability to cross the blood-brain barrier, poor oral bioavailability, etc. Finally, the selected compounds of two ZINC and NCI databases were combined and structurally clustered. Remained compounds were clustered in 28 different clusters, and the 17 compounds were introduced as final candidates.     

MIMUMBA revisited: torsion angle rules for conformer generation derived from X-ray structures

A method has been developed which automatically generates SMARTS patterns for four-atomic torsional fragments, searches experimental structures in the Cambridge Crystallographic Database, and obtains rules for preferred torsion angles in drug-size molecules. These rules can be used for exhaustive conformational analysis using the popular conformer generator OMEGA. This approach results in an overall improvement of quality and coverage of conformational space when comparing conformer ensembles generated by this method with results obtained by using the default OMEGA setup. In particular, the percentage of structures with at least one conformation closer than 0.5 A to the X-ray structure improves from 84% to 92% in a test set of 11 027 experimental structures from the CSD. Moreover, the average RMS distance of the closest conformation to the X-ray structure improves from 0.30 to 0.22 A.     

Parallel Water/Aromatic Interactions of Non‐Coordinated and Coordinated Water

The parallel interactions of non‐coordinated and coordinated water molecules with an aromatic ring were studied by analyzing data in the Cambridge structural database (CSD) and by using quantum chemical calculations. The CSD data show that water/aromatic contacts prefer parallel to OH/π interactions, which indicates the importance of parallel interactions. The results reveal the influence of water coordination to a metal ion; the interactions of aqua complexes are stronger. Coordinated water molecules prefer a parallel‐down orientation in which one O?H bond is parallel to the aromatic ring, whereas the other O?H bond points to the plane of the ring. The interactions of aqua complexes with parallel‐down water/benzene orientation are as strong as the much better known OH/π orientations. The strongest calculated interaction energy is ?14.89 kcal mol^?1. The large number of parallel contacts in crystal structures and the quite strong interactions indicate the importance of parallel orientation in water/benzene interactions.     

Conformational analysis of 14- and 16-membered unsaturated oxa, thia, and selena macrocyclic ligands

Crystallographic results retrieved from the Cambridge Structural Database (CSD) have been used to perform systematic conformational analyses of the free and metal-coordinated ligands 1,4,8,11-tetraoxa/thia/selenacyclotetradecane, 1,5,9,13-tetraoxa/thia/selenacyclohexadecane, and their derivatives. Conformational classifications established using symmetry-modified Jarvis-Patrick cluster analysis have been displayed in torsional space by principal component analysis (PCA) plots. Relative molecular mechanics energies of free macrocycles in the observed conformations are compared with the cluster populations and the effect of metal coordination investigated. While the conformations of the free macrocycles in the solid state are those with low molecular mechanics energies, substantial reorganization is required to produce tetradentate chelating conformers, particularly with S donors. With the latter, several such conformers occur, while one predominates with O donors for both macrocycles, in agreement with molecular mechanics predictions. Factors influencing the conformations adopted are discussed.