Data shaving: a focused screening approach

The number of compounds available for evaluation as part of the drug discovery process continues to increase. These compounds may exist physically or be stored electronically allowing screening by either actual or virtual means. This growing number of compounds has generated an increasing need for effective strategies to direct screening efforts. Initial efforts toward this goal led to the development of methods to select diverse sets of compounds for screening, methods to cluster actives into related groups of compounds, and tools to select compounds similar to actives of interest for further screening. In this work we extend these earlier efforts to exploit information about inactive compounds to help make rational decisions about which sets of compounds to include as part of a continuing screening campaign, or as part of a focused follow-up effort. This method uses the information from inactive compounds to "shave" off or deprioritize compounds similar to inactives from further consideration. This methodology can be used in two ways: first, to provide a rational means of deciding when sufficient compounds containing certain structural features have been tested and second as a tool to enhance similarity searching around known actives. Similarity searching is improved by deprioritizing compounds predicted to be inactive, due to the presence of structural features associated with inactivity.     

2,5-噻吩齐聚物链结构的表征

本文合成、分离和纯化了一系列2,5-噻吩齐聚物(n=2-5),作为聚噻吩的模型化合物.首次系统报道了这类化合物的质谱、^1H、^1^3C核磁共振谱和红外光谱,以对其结构进行表征,所得结果与用电化学方法制备的中性聚噻吩的相应结果进行比较,表面聚噻也具有α-α'连结的结构.     

Sequential optimisation of the separation of a complex mixture of plastics additives by HPLC with a quaternary gradient and a dual detection system

Summary The separation of two families of plastics additives (phenolic antioxidants and UV absorbers) has been achieved by high performance liquid chromatography with a quaternary gradient. A methodology of separation based on a sequential optimization is described. After a preliminary study of the effects of solvents on retention of compounds, the mobile phase is first chosen for each class of additives (Irganox and Tinuvin), then for the mixture of all the compounds and the separation is finally optimized. The importance of the column phase ratio is also reported. The use of two detectors, UV absorbance and light-scattering, enables all the compounds to be detected. The performance of the detectors has been compared and the effects of the nebulization temperature on the detection of low molecular mass compounds is reported.     

High-throughput prediction of blood-brain partitioning: a thermodynamic approach

A high-throughput in silico screening tool for potentially CNS active compounds was developed on the basis of the correlation of solvation free energies and blood-brain partitioning (log(cbrain/cblood) = log BB) data available from experimental sources. Utilizing a thermodynamic approach, solvation free energies were calculated by the fast and efficient generalized Born/surface area continuum solvation model, which enabled us to evaluate more than 10 compounds/min. Our training set involved a structurally diverse set of 55 compounds and yielded a function of log BB = 0.035Gsolv + 0.2592 (r = 0.85, standard error 0.37). Calculation of solvation free energies for 8700 CNS active compounds (CIPSLINE database) revealed that Gsolv is higher than -50 kJ/mol for the 96% of these compounds which can be used as suitable criteria for the identification of compounds preferable for CNS penetration.     

Silatrane as a reducing agent

Silatrane has been shown to have potential as a reducing agent for some organic compounds, including halides, carbonyl compounds, and azoxybenzene.     

Hidden active information in a random compound library: extraction using a pseudo-structure-activity relationship model

We propose a hypothesis that "a model of active compound can be provided by integrating information of compounds high-ranked by docking simulation of a random compound library". In our hypothesis, the inclusion of true active compounds in the high-ranked compound is not necessary. We regard the high-ranked compounds as being pseudo-active compounds. As a method to embody our hypothesis, we introduce a pseudo-structure-activity relationship (PSAR) model. Although the PSAR model is the same as a quantitative structure activity relationship (QSAR) model, in terms of statistical methodology, the implications of the training data are different. Known active compounds (ligands) are used as training data in the QSAR model, whereas the pseudo-active compounds are used in the PSAR model. In this study, Random Forest was used as a machine-learning algorithm. From tests for four functionally different targets, estrogen receptor antagonist (ER), thymidine kinase (TK), thrombin, and acetylcholine esterase (AChE), using five scoring functions, we obtained three conclusions: (1) the PSAR models significantly gave higher percentages of known ligands found than random sampling, and these results are sufficient to support our hypothesis; (2) the PSAR models gave higher percentages of known ligands found than normal scoring by scoring function, and these results demonstrate the practical usefulness of the PSAR model; and (3) the PSAR model can assess compounds failed in the docking simulation. Note that PSAR and QSAR models are used in different situations; the advantage of the PSAR model emerges when no ligand is available as training data or when one wants to find novel types of ligands, whereas the QSAR model is effective for finding compounds similar to known ligands when the ligands are already known.     

Triple a

Many biological compounds exhibit irreversible redox behavior as a result of slow heterogeneous electron transfer at electrode surfaces. In order to study the electrochemical behavior of these biocomponents, redox mediators are used to facilitate the electron transfer process. In this review the characteristics of ideal mediators are discussed and structural information on previously reported mediator compounds is provided. The electrochemical literature has been extensively surveyed to provide an up-to-date compilation of mediators suitable for use in potentiometric and coulometric titrations and in various types of voltammetric studies of biological redox systems. The compilation provides information on the formal potentials of the mediators as well as their previous applications and references. This review is intended to provide a current survey of compounds having suitable redox mediation characteristics.     

Evaluation of a hypercrosslinked polystyrene, MN-200, as a sorbent for the preconcentration of volatile organic compounds in air

Breakthrough volumes, average percentage recoveries, and storage stabilities were obtained for vapors of 8 volatile organic compounds (pentane, octane, undecane, isooctane, cyclohexane, toluene, methanol, and dichloromethane) on a new adsorbent material, Hypersol-Macronet, MN-200. Breakthrough volumes were estimated as half of the gas chromatographic specific retention volumes at 20 degrees C for the compounds. Recoveries of the adsorbates were determined by both solvent extraction and thermal desorption methods. The results obtained compare favorably with those for Tenax GR (values reported in the published literature and others obtained in our laboratory). Results of storage stability studies on MN-200 meet the criterion for acceptability (<10% loss). High adsorption capacity for very volatile and polar compounds, combined with ease of desorption of less volatile compounds, render MN-200 a highly promising adsorbent for sampling volatile organic compounds in indoor and outdoor air.     

Chemics—ube,a modified system of chemics

Two kinds of contraint have been added to the CHEMICS program system for structure elucidation of organic compounds. One is a limitation on the construction of small ring structures; the other is the introduction of a facility for input of appropriate information at the discretion of the user during the automated analyses of spectral data of unknown compounds. The computation processes for a couple of compounds by the new system are described.     

Theory of docking scores and its application to a customizable scoring function

In general, the docking scoring tends to have a size dependence related to the ranking of compounds. In this paper, we describe a novel method of parameter optimization for docking scores which reduce the size dependence and can efficiently discriminate active compounds from chemical databases. This method is based on a simplified theoretical model of docking scores which enables us to utilize large amounts of data of known active and inactive compounds for a particular target without requiring large computational resources or a complicated procedure. This method is useful for making scoring functions for the identification of novel scaffolds using the knowledge of active compounds for a particular target or a customized scoring function for an interesting family of drug targets.     

Construction of a Meroterpenoid-Like Compounds Library Based on Diversity-Enhanced Extracts

The structural diversity of natural products and their derivatives have long contributed to the development of new drugs. However, the difficulty in obtaining compounds bearing skeletally novel structures has recently led to a decline of pharmaceutical research into natural products. This paper reports the construction of a meroterpenoid-like library containing 25 compounds with diverse molecular scaffolds obtained from diversity-enhanced extracts. This method constitutes an approach for increasing the chemical diversity of natural-product-like compounds by combining natural product chemistry and diversity-oriented synthesis. Extensive pharmacological screening of the library revealed promising compounds for anti-osteoporotic and anti-lymphoma/leukemia drugs. This result indicates that the use of diversity-enhanced extracts is an effective methodology for producing chemical libraries for the purpose of drug discovery.     

Developing an antituberculosis compounds database and data mining in the search of a motif responsible for the activity of a diverse class of antituberculosis agents

A novel data mining procedure to look for new antitubercular agents and targets as well as to find a minimum common bioactive substructure (MCBS), has been reported here. The methodology extracts MCBS, both across the diverse chemical classes and within the particular chemical class, known to be present in the various marketed drugs alongside antimycobacterial compounds with known MICs. For this purpose a small in-house database of compounds has been created, for which MICs against Mycobacterium are known. The compounds have been collected from literature available on the synthetic compounds, having known MICs against Mycobacterium tuberculosis. An elaborate HQSAR (Hologram QSAR) study has been attempted to extract active fragment from a diverse class of compounds, in combination with the clustering technique to select a homogeneous group of compounds having good a profile toward the activity. The 2D pharmacophore (the 2D fragments extracted from HQSAR) has been validated searching the database. It has been found further that this validated 2D pharmacophore could be used for searching the orphan target in Mycobacterium effectively.     

Designing antibacterial compounds through a topological substructural approach

A novel application of TOPological Substructural MOlecular DEsign (TOPS-MODE) was carried out in antibacterial drugs using computer-aided molecular design. Two series of compounds, one containing antibacterial and the other containing non-antibacterial compounds, were processed by a k-means cluster analysis in order to design training and predicting series. All clusters had a p-level < 0.005. Afterward, a linear classification function has been derived toward discrimination between antibacterial and non-antibacterial compounds. The model correctly classifies 94% of active and 86% of inactive compounds in the training series. More specifically, the model showed a global good classification of 91%, i.e., 263 cases out of 289. In predicting series, the model has shown overall predictabilities of 91 and 83% for active and inactive compounds, respectively. Thereby, the model has a global percentage of good classification of 89%. The TOPS-MODE approach, also, similarly compares with respect to one of the most useful models for antimicrobials selection reported to date.     

Validation of a laboratory-constructed automated gas chromatograph for the measurement of ozone precursors through comparison with a commercial analogy

An automated gas chromatographic (auto-GC) system aiming at performing unattended hourly measurement of ozone precursors was developed in the laboratory. To encompass volatile organic compounds (VOCs) of a wide range of volatility within each analysis, the system uses dual-traps and dual-columns to simultaneously analyze both low and high-boiling compounds with each injection. Since sorbents with sufficient retention of C2 compounds at room temperature, namely ethane, ethene, and ethyne are not yet available, cooling with a thermoelectrical device was built around the low-boiling trap to facilitate quantitative enrichment of C2 compounds. The effectiveness of using micro-trap with low dead volume plumbing was manifested in reducing peak width and increasing peak height for particularly the lower-boiling compounds. The increase in sensitivity allowed sufficient detector response with a small amount of air sample, e.g. 200 ml in our routine operation, which in term eliminate the need for remove water prior to sampling trapping. The performance and applicability of this laboratory-built auto-GC system was validated by comparison with a commercial analog, i.e. the ATD-400 system made by Perkin-Elmer, in the field sharing a common air intake. During more than 3 weeks of synchronized monitoring of ambient volatile organic compounds both systems showed highly consistent results on almost every monitored compound, clearly demonstrating the robustness of this self-built system.     

Sensing and formation of a stable gel in the presence of picric acid by a low-molecular-weight-gelator

In this work, a set of amide-based compounds, L1-L3, have been studied. These compounds are decorated with various H-bonding functional groups while the presence of aromatic rings not only promote π?π stacking but also made these molecules electron-rich. All three compounds were utilized for the sensing of electron-deficient nitro-explosives. These compounds were found to be highly selective for the nanomolar sensing of picric acid (PA). Out of three compounds, L3 acted as a low-molecular-weight-gelator and formed a more stable and stronger gel in the presence of PA. The resultant [email protected]L3?gel was studied by the SEM, powder XRD and rheological techniques while further supported by the molecular docking studies. These results illustrate that doping of L3 with PA not only enhances several noteworthy interaction avenues but also the stability of the resultant [email protected]L3?gel when compared to L3?gel.     

β-Cyclodextrin epichlorohydrin copolymer as a solid-phase extraction adsorbent for aromatic compounds in water samples

A novel solid-phase extraction (SPE) procedure for trace aromatic compounds in water samples has been developed using 12 aromatic compounds as model compounds and GC-MS and UV spectrophotometry for detection. The method is based on the fact that β-cyclodextrin (β-CD) epichlorohydrin (ECH) copolymer (β-CDEP) can extract non-ionized aromatic compounds quantitatively from aqueous samples. The polymer used is a colorless, transparent and insoluble solid with a maximum capacity of 0.82 μmol aromatic compounds per gram. It was synthesized by co-polymerization of β-CD and ECH and characterized by FT-IR and UV. β-CDEP does not contain double bonds, and therefore it does not have appreciable absorbance in the UV region. The optimum pH range for the extraction of aromatic compounds is 2.5-5.0. The method has high extraction efficiency with the recoveries between 90 and 101% for aromatic compounds at 0.02-1.67 ppm levels, and the analytes can be easily eluted by methanol washing after preconcentration.     

Quantitative gas chromatographic analysis of perhalogenated compounds using a flame lonization detector

Summary In the determination of several perhalogenated compounds after gas chromatographic separation on an Apiezon L column, using a flame ionization detector, all the compounds tested gave linear area-mass plots although the coefficients observed do not lead to extrapolations which would permit quantitation of perhalogenated compounds for which no standard is available. Of the compounds tested, dibromodichloromethane, tetrachloroethene and tetrabromoethene gave good linear correlations of area ratio-mass ratio (using n-decane as the internal standard). Bromotrichloromethane and tetrabromomethane gave continuously curving area ratio-mass ratio plots which were very reproducible and could be used for graphical interpolation.     

Exact-mass library for pesticides using a molecular-feature database

An automated molecular-feature database (MFD) consisting of the exact monoisotopic mass of 100 compounds, at least one exact mass product ion for each compound, and chromatographic retention time were used to identify pesticides in food and water samples. The MFD software compiles a list of accurate mass ions, excludes noise, and compares them with the monoisotopic exact masses in the database. The screening criteria consisted of +/-5 ppm accurate mass window, +/-0.2 min retention time window, and a minimum 1000 counts (signal-to-noise (S/N) ratio of approximately 10:1). The limit of detection for 100 tested compounds varied from <0.01 mg/kg for 72% of the compounds to <0.1 mg/kg for 95% of the compounds. The MFD search was useful for rapid screening and identification of pesticides in food and water, as shown in actual samples. The combined use of accurate mass and chromatographic retention time eliminated false positives in the automated analysis. The major weakness of the MFD is matrix interferences and loss of mass accuracy. Strengths of the MFD include rapid screening of 100 compounds at sensitive levels compared with a manual approach and the ease of use of the library for any accurate mass spectrometer instrumentation capable of routine sub-5-ppm mass accuracy.