Why relevant chemical information cannot be exchanged without disclosing structures

Both society and industry are interested in increasing the safety of pharmaceuticals. Potentially dangerous compounds could be filtered out at early stages of R&D by computer prediction of biological activity and ADMET characteristics. Accuracy of such predictions strongly depends on the quality & quantity of information contained in a training set. Suggestion that some relevant chemical information can be added to such training sets without disclosing chemical structures was generated at the recent ACS Symposium. We presented arguments that such safety exchange of relevant chemical information is impossible. Any relevant information about chemical structures can be used for search of either a particular compound itself or its close analogues. Risk of identifying such structures is enough to prevent pharma industry from relevant chemical information exchange.     

A data base of data banks for toxicological information

The procedures necessary to find the appropriate data banks in seeking particular information or data are much less systematic than the way in which the information is stored at some data banks. Based on the information taken from several hundred direct-mailed questionnaires, a conceptual design is proposed for a data base of toxicological data banks relating to other areas such as medicine, pharmacology, biology, chemistry and environmental science. The system (not yet implemented) contains nearly 150 data banks (both computerized and manual) all over the world with data on the type of information, the way to obtain it, its cost, etc.     

Leach data vs total: which is relevant for SRMs?

This paper presents an overview of the available leach data for NIST SRMs currently in distribution or to be released in the near future. These include coal fly ash, soil, sediment and sludge matrices, each leached with only one of several potential acid mixtures as specified in the Toxicity Characteristics Leaching Protocol, Method 3050, or Method 3051. These leach values are method-specific and that specificity applies individually to each of several potential leach media which may be used. Therefore leach values cannot be confirmed by the agreement of results obtained by two or more independent methods or techniques, as is NIST practice for certified values. Additionally, the certified values, which have historically been total concentration values, do not provide the necessary quality assurance for environmental studies based on leach data. The information leach values provide this level of quality control for environmental studies.     

Biologically relevant phosphoranes: structural characterization of a nucleotidyl phosphorane

The first successful crystal structures of biorelevant nucleoside and carbohydrate-based phosphoranes are reported. Employing thymidine, a nucleotidyl phosphorane was synthesized in 90% yield and was shown by X-ray analysis to possess a trigonal bipyramidal geometry. With the use of 1,2-O-isopropylidene-alpha-d-glucofuranose, a carbohydrate-based phosphorane was formed and similarly found to have a trigonal bipyramidal geometry. NMR studies demonstrated the existence of isomerism in solution associated with the nucleotidyl phosphorane and rapid exchange for the carbohydrate-based phosphorane. The geometrical representations reported here are expected to have significant applications associated with active site mechanisms of phosphoryl transfer enzymes, for example, in DNA, RNA, c-AMP, and others.     

Reduction of the information space for data collections

Reduction of infrared spectra representation by using fast Fourier and fast Hadamard transforms is discussed. It is shown that the information content for different truncations varies in the same way for both transformations, while the execution of FHT is about 8 times faster than that of FFT. The reduction of the information content is illustrated by comparing the hierarchical ordering of clusters of the same set of infrared spectra using representations of different lengths. The same basic pattern of three clusters was obtained even when the representations were reduced by more than 96% of the original representations.     

Accentuated selective population transfer difference spectroscopy: a new method for revealing hidden NMR resonances.

Block difference FID accumulation with an initial selective decoupler pulse alternately placed at the high and low frequency lines of a multiples provides, upon transform, a difference spectrum that shows only those other multiplets that are scalar coupled to the probed resonance with full retention of all splittings for the multiplets so revealed.     

Possibilities of powder X-ray diffraction methods in determining structural characteristics of carbon materials

The possibilities of using powder X-ray diffraction methods in the study of carbon materials are discussed. To determine the phase composition of the crystalline materials the X-ray phase analysis is employed; the real structure is established by the harmonic analysis of diffraction profiles; the structural features and phase composition of the nanomaterials are found by the radial electron density distribution function.     

Gas chromatography retention data of environmentally relevant polybrominated compounds

Polybrominated organic compounds are ubiquitous throughout the environment. This generic term comprises several classes of brominated flame retardants (e.g., polybrominated diphenyl ethers, polybrominated biphenyls, hexabromocyclododecane, dibromopropyltribromophenyl ether, 1,2-bis(2,4,6-tribromophenoxy)ethane) as well as a range of marine halogenated natural products (HNPs). Here we present gas chromatography retention times and elution orders (on DB-5) of 122 polybrominated compounds that may be found in food and environmental samples. Organobromine compounds in fish samples determined with gas chromatography interfaced to electron-capture negative ion mass spectrometry (GC/ECNI-MS) are discussed. The environmental relevance and important mass spectrometric features of the compounds are described as well. Our database aims to support the closer inspection and identification of peaks in gas chromatograms and to initiate dedicated screening for less frequently studied organobromines in samples.     

A performance criterion for information theoretic data analysis

A previously unobserved electronic state in fluorobenzene appears as a two-photon resonance in the multiphoton resonance ionization spectrum. The band system is assigned to the 3s Rydberg ← b₂(π) HOMO transition with a quantum defect of 0.83 and an origin at 50 914 ± 15 cm^?1. Its correspondence to the benzene state characterized by Johnson in the same region assigns that state to E_1g 3s Rydberg.     

Biologically relevant phosphoranes: structural characterization of glucofuranose- and xylofuranose-based phosphoranes

Carbohydrate-based phosphoranes were synthesized by reacting 2,2'-ethylidenebis(4,6-di-tert-butylphenyl)fluorophosphite with 1,2-O-isopropylidene-alpha-D-glucofuranose, beta-chloralose, and 1,2-isopropylidene-alpha-D-xylofuranose to form the monocyclic biophosphoranes 1-3, respectively, in the presence of N-chlorodiisopropylamine. Synthesis of the monocyclic biophosphorane 4 was achieved by reacting tris(2,6-di-isopropylphenyl)phosphite with 1,2-O-isopropylidene-alpha-D-glucofuranose in the presence of N-chlorodiisopropylamine. X-ray analysis of 1-4 revealed trigonal bipyramidal structures with the carbohydrate components occupying axial-equatorial sites. An eight-membered ring in 1-3 occupied diequatorial sites of the trigonal bipyramid. Solution and solid state 31P and solution 19F, 1H, and 13C NMR measurements including variable temperature and correlation spectroscopy studies established retention of the solid state structure in solution. A dynamic equilibrium exists among two isomeric forms. These biophosphoranes serve as models for active sites of phosphoryl transfer enzymes. The rapid exchange process reorients the carbohydrate component of the trigonal bipyramidal phosphorane. At an active site, this type of pseudorotational behavior provides a mechanism that could bring another active site residue into play and account for a means by which some phosphoryl transfer enzymes express promiscuous behavior.     

Exploiting structural information in patent specifications for key compound prediction

Patent specifications are one of many information sources needed to progress drug discovery projects. Understanding compound prior art and novelty checking, validation of biological assays, and identification of new starting points for chemical explorations are a few areas where patent analysis is an important component. Cheminformatics methods can be used to facilitate the identification of so-called key compounds in patent specifications. Such methods, relying on structural information extracted from documents by expert curation or text mining, can complement or in some cases replace the traditional manual approach of searching for clues in the text. This paper describes and compares three different methods for the automatic prediction of key compounds in patent specifications using structural information alone. For this data set, the cluster seed analysis described by Hattori et al. (Hattori, K.; Wakabayashi, H.; Tamaki, K. Predicting key example compounds in competitors' patent applications using structural information alone. J. Chem. Inf. Model.2008, 48, 135-142) is superior in terms of prediction accuracy with 26 out of 48 drugs (54%) correctly predicted from their corresponding patents. Nevertheless, the two new methods, based on frequency of R-groups (FOG) and maximum common substructure (MCS) similarity measures, show significant advantages due to their inherent ability to visualize relevant structural features. The results of the FOG method can be enhanced by manual selection of the scaffolds used in the analysis. Finally, a successful example of applying FOG analysis for designing potent ATP-competitive AXL kinase inhibitors with improved properties is described.     

Borrowing information from relevant microarray studies for sample classification using weighted partial least squares

With an increasing number of publicly available microarray datasets, it becomes attractive to borrow information from other relevant studies to have more reliable and powerful analysis of a given dataset. We do not assume that subjects in the current study and other relevant studies are drawn from the same population as assumed by meta-analysis. In particular, the set of parameters in the current study may be different from that of the other studies. We consider sample classification based on gene expression profiles in this context. We propose two new methods, a weighted partial least squares (WPLS) method and a weighted penalized partial least squares (WPPLS) method, to build a classifier by a combined use of multiple datasets. The methods can weight the individual datasets depending on their relevance to the current study. A more standard approach is first to build a classifier using each of the individual datasets, then to combine the outputs of the multiple classifiers using a weighted voting. Using two quite different datasets on human heart failure, we show first that WPLS/WPPLS, by borrowing information from the other dataset, can improve the performance of PLS/PPLS built on only a single dataset. Second, WPLS/WPPLS performs better than the standard approach of combining multiple classifiers. Third, WPPLS can improve over WPLS, just as PPLS does over PLS for a single dataset.     

Molecular shape and electrostatics in the encoding of relevant chemical information

We propose a molecule's chemistry can be hidden by representations of its shape and electrostatic field while retaining crucial, pharmaceutically relevant, information. Necessary, but not sufficient, to this proposition are the importance of shape and electrostatics to activity, the facility to easily represent, store and compare field properties, and knowledge of the density of possible drug-like molecules within a given radius of physical similarity. We provide methods and evidence to support the conclusion that a useful encoding is practical and propose tests for falsification.     

A constant heat-flux calorimeter for measuring heat transfer data

A new isothermal calorimeter, designed especially for simultaneously measuring the heat of reaction and the heat transfer data in a reaction solution, is described. The system, called a Constant Heat-Flux Calorimeter, is similar to a differential scanning calorimeter in terms of direct calorimetric measurement of the energies of reaction, but differs from the conventional calorimeters described in the literature. With this device, one recorded output in a temperature control circuit is a linear function of change in energies of reaction, and second in a differential temperature control circuit is found to be proportional to a resistance to heat transfer in a solution. The performance of the calorimeter was evaluated on the basis of some results on heat transfer data of aqueous solution of polyethylene glycol and on solution polymerization of styrene at constant temperatures.     

Exploiting scale-free information from expression data for cancer classification

Most studies concerning expression data analyses usually exploit information on the variability of gene intensity across samples. This information is sensitive to initial data processing, which affects the final conclusions. However expression data contains scale-free information, which is directly comparable between different samples. We propose to use the pairwise ratio of gene expression values rather than their absolute intensities for a classification of expression data. This information is stable to data processing and thus more attractive for classification analyses. In proposed schema of data analyses only information on relative gene expression levels in each sample is exploited. Testing on publicly available datasets leads to superior classification results.     

Automatic extraction of relevant peaks and reconstruction of mass spectra for low signal-to-noise GC-MS data

A method for the automatic extraction of spectra from GC-MS data is described. The program localizes chromatographic peaks and provides a reconstructed spectrum of each compound. It is particularly designed for low-sampling conditions frequently encountered with efficient GC columns, requiring threshold methods rather than methods based on peak shape; automatic threshold adjustments on the mass chromatograms are thus performed at different stages of the process. A test of the program on two sets of experimental data revealed better performances than manual data treatment, particularly in the case of low signal-to-noise ratios.