Molecular Structure Databases Research Articles

TCM Database@Taiwan: The World's Largest Traditional Chinese Medicine Database for Drug Screening In Silico

Rapid advancing computational technologies have greatly speeded up the development of computer-aided drug design (CADD). Recently, pharmaceutical companies have increasingly shifted their attentions toward traditional Chinese medicine (TCM) for novel lead compounds. Despite the growing number of studies on TCM, there is no free 3D small molecular structure database of TCM available for virtual screening or molecular simulation. To address this shortcoming, we have constructed TCM Database@Taiwan (http://tcm.cmu.edu.tw/) based on information collected from Chinese medical texts and scientific publications. TCM Database@Taiwan is currently the world's largest non-commercial TCM database. This web-based database contains more than 20,000 pure compounds isolated from 453 TCM ingredients. Both cdx (2D) and Tripos mol2 (3D) formats of each pure compound in the database are available for download and virtual screening. The TCM database includes both simple and advanced web-based query options that can specify search clauses, such as molecular properties, substructures, TCM ingredients, and TCM classification, based on intended drug actions. The TCM database can be easily accessed by all researchers conducting CADD. Over the last eight years, numerous volunteers have devoted their time to analyze TCM ingredients from Chinese medical texts as well as to construct structure files for each isolated compound. We believe that TCM Database@Taiwan will be a milestone on the path towards modernizing traditional Chinese medicine.

Pharmacophore Modeling and Virtual Screening of Novel Inhibitors for c‐Kit Kinase

AbstractThe stem cell factor receptor (c‐Kit) has been known to play critical roles in regulating numerous aspects of cellular behavior including cell growth, differentiation, migration and metabolism. In this investigation, a three‐dimensional pharmacophore model of c‐Kit inhibitors has been established by using the HypoGen algorithms implemented in the catalyst software package. The best quantitative pharmacophore model, hypothesis 1, which has the highest correlation coefficient (0.989), consists of one hydrogen bond acceptor, two hydrogen bond donors and one hydrophobic feature. To our knowledge, this is the first report on the pharmacophore modeling study of c‐Kit inhibitors. The best hypothesis, hypothesis 1, was used to screen molecular structural databases, including Specs and China Natural Products Database for potential lead compounds. The hit compounds were subsequently subjected to filtering by Lipinski's rules and docking study to refine the retrieved hits and as a result to reduce the rate of false positive. Finally 28 compounds were purchased or synthesized for further in vitro assay against several human tumour cell lines including A549, MCF‐7, HepG2 and PC‐3, in which c‐Kit is overexpressed. Two compounds show very low micromolar inhibition potency against the PC‐3 and HepG2 cell lines respectively. And they were selected for further modification and testing.

A General Database for Main Group Thermochemistry, Kinetics, and Noncovalent Interactions - Assessment of Common and Reparameterized (meta-)GGA Density Functionals.

We present a quantum chemistry benchmark database for general main group thermochemistry, kinetics, and noncovalent interactions (GMTKN24). It is an unprecedented compilation of 24 different, chemically relevant subsets that either are taken from already existing databases or are presented here for the first time. The complete set involves a total of 1.049 atomic and molecular single point calculations and comprises 731 data points (relative chemical energies) based on accurate theoretical or experimental reference values. The usefulness of the GMTKN24 database is shown by applying common density functionals on the (meta-)generalized gradient approximation (GGA), hybrid-GGA, and double-hybrid-GGA levels to it, including an empirical London dispersion correction. Furthermore, we refitted the functional parameters of four (meta-)GGA functionals based on a fit set containing 143 systems, comprising seven chemically different problems. Validation against the GMTKN24 and the molecular structure (bond lengths) databases shows that the reparameterization does not change bond lengths much, whereas the description of energetic properties is more prone to the parameters' values. The empirical dispersion correction also often improves for conventional thermodynamic problems and makes a functional's performance more uniform over the entire database. The refitted functionals typically have a lower mean absolute deviation for the majority of subsets in the proposed GMTKN24 set. This, however, is also often accompanied at the expense of poor performance for a few other important subsets. Thus, creating a broadly applicable (and overall better) functional by just reparameterizing existing ones seems to be difficult. Nevertheless, this benchmark study reveals that a reoptimized (i.e., empirical) version of the TPSS-D functional (oTPSS-D) performs well for a variety of problems and may meet the standards of an improved functional. We propose validation against this new compilation of benchmark sets as a definitive way to evaluate a new quantum chemical method's true performance.

Pharmacophore Modelling and Virtual Screening for Identification of New Aurora‐A Kinase Inhibitors

Aurora-A has been identified as one of the most attractive targets for cancer therapy and a considerable number of Aurora-A inhibitors have been reported recently. In order to clarify the essential structure-activity relationship for the known Aurora-A inhibitors as well as identify new lead compounds against Aurora-A, 3D pharmacophore models were developed based on the known inhibitors. The best hypothesis, Hypo1, was used to screen molecular structural databases, including Specs and China Natural Products Database for potential lead compounds. The hit compounds were subsequently subjected to filtering by Lipinski's rules and docking study to refine the retrieved hits and as a result to reduce the rate of false positive. Finally, 39 compounds were purchased for further in vitro assay against several human tumour cell lines including A549, MCF-7, HepG2 and PC-3, in which Aurora-A is overexpressed. Two compounds show very low micromolar inhibition potency against some of these tumour cells. And they have been selected for further investigation.

Application of the in combo screening approach for the discovery of non-alkaloid acetylcholinesterase inhibitors from Cichorium intybus.

Because of the direct correlation of cholinergic deficit and the severity of dementia, Alzheimer's disease is preferentially treated with acetylcholinesterase (AChE) inhibitors to supplement the acetylcholine level. In this study we focused on non-alkaloid AChE inhibitors from natural sources in order to discover new lead structures. In the course of in vitro extract screening of Tyrolean plants using an enzyme assay with Ellman's reagent, the dichloromethane extract of chicory roots (Cichorium intybus L.) showed a pronounced inhibitory effect on AChE. At a concentration of 1 mg extract/ml an inhibition of 70% was measured. Based on a 3D multi-conformational molecular-structure database consisting of secondary metabolites from C. intybus known from the relevant literature, virtual screening filtering experiments were conducted using both a feature-based pharmacophore model and a docking procedure. Some low molecular weight sesquiterpenoids exhibited distinct interactions with the pharmacophore model. In order to verify the applicability of this computer-aided strategy, an activity-guided fractionation of the chicory root extract was performed, which resulted in the isolation of two sesquiterpene lactones, 8-deoxylactucin and lactucopicrin, showing significant and dose-dependent inhibitory activity on AChE (IC(50) of 308.1 microM [CI(95) 243.9 - 405.3 microM] and 150.3 microM [CI(95) 100.8 - 188.1 microM], respectively). The two isolates were correctly predicted within the virtual screening process which corroborates the potential of the computer-assisted in combo screening approach for the discovery of the anti-cholinesterase compounds from C. intybus.

Chemical function based pharmacophore generation of endothelin-A selective receptor antagonists.

Both quantitative and qualitative chemical function based pharmacophore models of endothelin-A (ET(A)) selective receptor antagonists were generated by using the two algorithms HypoGen and HipHop, respectively, which are implemented in the Catalyst molecular modeling software. The input for HypoGen is a training set of 18 ET(A) antagonists exhibiting IC(50) values ranging between 0.19 nM and 67 microM. The best output hypothesis consists of five features: two hydrophobic (HY), one ring aromatic (RA), one hydrogen bond acceptor (HBA), and one negative ionizable (NI) function. The highest scoring Hip Hop model consists of six features: three hydrophobic (HY), one ring aromatic (RA), one hydrogen bond acceptor (HBA), and one negative ionizable (NI). It is the result of an input of three highly active, selective, and structurally diverse ET(A) antagonists. The predictive power of the quantitative model could be approved by using a test set of 30 compounds, whose activity values spread over 6 orders of magnitude. The two pharmacophores were tested according to their ability to extract known endothelin antagonists from the 3D molecular structure database of Derwent's World Drug Index. Thereby the main part of selective ET(A) antagonistic entries was detected by the two hypotheses. Furthermore, the pharmacophores were used to screen the Maybridge database. Six compounds were chosen from the output hit lists for in vitro testing of their ability to displace endothelin-1 from its receptor. Two of these are new potential lead compounds because they are structurally novel and exhibit satisfactory activity in the binding assay.

Orientation-dependent coarse-grained potentials derived by statistical analysis of molecular structural databases

We present results obtained for anisotropic potentials for protein simulations extracted from the continually growing databases of protein structures. This work is based on the assumption that the detailed information on molecular conformations can be used to derive statistical (a.k.a. ‘knowledge-based’) potentials that can describe on a coarse-grained level the side chain–side chain interactions in peptides and proteins. The complexity of inter-residue interactions is reflected in a high degree of orientational anisotropy for the twenty amino acids. By including in this coarse-grained interaction model the possibility of quantifying the backbone–backbone and backbone–side chain interactions, important improvements are obtained in characterizing the native protein states. Results obtained from tests that involve the identification of native-like conformations from large sets of decoy structures are presented. The method for deriving orientation-dependent statistical potentials is also applied to obtain water–water interactions. Monte Carlo simulations using the new coarse-grained water model show that the locations of the minima and maxima of the oxygen–oxygen radial distribution function correspond well with experimental measurements.

Circular effects in representations of an RNA nucleotides data set in relation with principal components analysis

During the last few years, the main reason for using molecular structure databases has changed. Instead of using databases as a storage medium, databases now are also used as a source for data-mining applications. The large number of objects and variables in these databases induced that besides univariate techniques, multivariate techniques are also applied to search for knowledge hidden in the data. A popular multivariate technique that is used to explore the underlying structure in data is called principal component analysis (PCA). Because structure data are often represented as torsion angles and PCA is not originally designed to deal with this kind of circular data, the outcome of PCA experiments can be misleading. This article describes several alternative representations of circular data and its effect on the outcome of PCA experiments. A worked example is given using a database of RNA nucleotides.

Resources at EBI.

AbstractThe European Bioinformatics Institute (EBI) is an EMBL Outstation located at the Wellcome Trust Genome Campus in Hinxton (UK). The EBI maintains and distributes the EMBL Nucleotide Sequence database, Europe’s primary nucleotide sequence data resource, the SwissProt Protein Sequence database, in collaboration with Amos Bairoch of the Swiss Institute for Bioinformatics (SIB), TrEMBL a SwissProt complement consisting of translations from EMBL database coding sequences, MSD, the Molecular Structure Database in collaboration with the Protein Data Bank (PDB) in Brookhaven National Laboratory (Brookhaven, NY), the Radiation Hybrid database (RHdb), and other additional molecular biology databases produced in collaboration with other groups. The EBI also provides network services that allow access to the most up-to-date data collections via the Internet through its World Wide Web interfaces and ftp services, also providing database and sequence similarity searches facilities.KeywordsProtein Data BankEuropean Bioinformatics InstituteEMBL DatabaseData SubmissionGenome Survey SequenceThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

CyberMol-A Molecular Graphics Program System on the World Wide Web Using the Common Gateway Interface.

CyberMol, an interactive molecular graphics program system on the World Wide Web (WWW) using the Common Gateway Interface (CGI) is presented. The molecular coordinates which are inputted from the WWW browser can be transferred to the Virtual Reality Modeling Language (VRML) format file and viewed as a molecular model by using a VRML viewer on the WWW. The vibrational modes calculated by the ab initio molecular orbital program GAUSSIAN 94 can be visualized. The organic molecular structure database and the search engine for displaying molecular models by using the VRML viewer are also provided.

Adventures in Information Space

Since the mid-1970s, DNA and protein sequence data has led to remarkable discoveries that are revealing the fundamental causes of cancer and genetic disease. By the year 2005, the Human Genome Project will produce a complete blueprint of human biology. Scientists and physicians access these data in GenBank®, a NIH database developed, maintained and distributed by the NCBI. These sequences are linked directly to molecular structure databases and to the biomedical journal literature through bibliographic databases like MEDLINE®. This new knowledge management system functions with the use of e-mail, CD-ROM products, and Internet client-server applications, and blends the world of print publishing with primary source data residing in globally accessible databanks. Current systems require that human beings initiate specific search, analysis, and retrieval requests. However, software robots already maintain and update these data, and «intelligent agents» will soon be available for the automated and targeted dissemination of new research findings. This paper discusses the development of this new working model and speculates about the impact of future technological advances, the effect on how researchers and physicians work, and possible applicability to other research disciplines

PROPHET--a national computing resource for life science research.

PROPHET is a national computing resource tailored to meet the data management and analysis needs of life scientists working in a wide variety of disciplines, ranging from pharmacology to molecular biology. The PROPHET system offers a fully integrated graphics-oriented environment designed for the manipulation and analysis of tabular data, graphs, molecular structures, biological simulation models, and protein and nucleic acid sequences, and it includes access to molecular structure and sequence databases.

PROPHET, a national computing resource for life science research.

PROPHET is a national computing resource tailored to meet the data management and analysis needs of life scientists working in a wide variety of disciplines, ranging from pharmacology to molecular biology. The PROPHET system offers a fully integrated graphics-oriented environment designed to aid research scientists in the manipulation and analysis of scientific spreadsheets of data, graphs, molecular structures, biological simulation models, and protein and nucleic acid sequences, and it includes access to a range of molecular structure and sequence databases. This paper briefly describes the PROPHET system, some of its current capabilities, and plans for a new fully distributed version of the system now under development.