Evaluation of SARs for the prediction of skin irritation/corrosion potential: structural inclusion rules in the BfR decision support system

The German Federal Institute for Risk Assessment (BfR) has developed a Decision Support System (DSS) to assess certain hazardous properties of pure chemicals, including skin and eye irritation/corrosion. The BfR-DSS is a rule-based system that could be used for the regulatory classification of chemicals in the European Union. The system is based on the combined use of two predictive approaches: exclusion rules based on physicochemical cut-off values to identify chemicals that do not exhibit a certain hazard (e.g., skin irritation/corrosion), and inclusion rules based on structural alerts to identify chemicals that do show a particular toxic potential. The aim of the present study was to evaluate the structural inclusion rules implemented in the BfR-DSS for the prediction of skin irritation and corrosion. The following assessments were performed: (a) a confirmation of the structural rules by rederiving them from the original training set (1358 substances), and (b) an external validation by using a test set of 200 chemicals not used in the derivation of the rules. It was found as a result that the test data set did not match the training set relative to the inclusion of structural alerts associated with skin irritation/corrosion, albeit some skin irritants were in the test set.     

An evaluation of selected global (Q)SARs/expert systems for the prediction of skin sensitisation potential

Skin sensitisation potential is an endpoint that needs to be assessed within the framework of existing and forthcoming legislation. At present, skin sensitisation hazard is normally identified using in vivo test methods, the favoured approach being the local lymph node assay (LLNA). This method can also provide a measure of relative skin sensitising potency which is essential for assessing and managing human health risks. One potential alternative approach to skin sensitisation hazard identification is the use of (Quantitative) structure activity relationships ((Q)SARs) coupled with appropriate documentation and performance characteristics. This represents a major challenge. Current thinking is that (Q)SARs might best be employed as part of a battery of approaches that collectively provide information on skin sensitisation hazard. A number of (Q)SARs and expert systems have been developed and are described in the literature. Here we focus on three models (TOPKAT, Derek for Windows and TOPS-MODE), and evaluate their performance against a recently published dataset of 211 chemicals. The current strengths and limitations of one of these models is highlighted, together with modifications that could be made to improve its performance. Of the models/expert systems evaluated, none performed sufficiently well to act as a standalone tool for hazard identification.     

An evaluation of selected global (Q)SARs/expert systems for the prediction of skin sensitisation potential

Skin sensitisation potential is an endpoint that needs to be assessed within the framework of existing and forthcoming legislation. At present, skin sensitisation hazard is normally identified using in vivo test methods, the favoured approach being the local lymph node assay (LLNA). This method can also provide a measure of relative skin sensitising potency which is essential for assessing and managing human health risks. One potential alternative approach to skin sensitisation hazard identification is the use of (Quantitative) structure activity relationships ((Q)SARs) coupled with appropriate documentation and performance characteristics. This represents a major challenge. Current thinking is that (Q)SARs might best be employed as part of a battery of approaches that collectively provide information on skin sensitisation hazard. A number of (Q)SARs and expert systems have been developed and are described in the literature. Here we focus on three models (TOPKAT, Derek for Windows and TOPS-MODE), and evaluate their performance against a recently published dataset of 211 chemicals. The current strengths and limitations of one of these models is highlighted, together with modifications that could be made to improve its performance. Of the models/expert systems evaluated, none performed sufficiently well to act as a standalone tool for hazard identification.     

Automated derivation of reaction rules for the EROS 6.0 system for reaction prediction

The purpose of the EROS 6.0 system is to predict the products of chemical reactions and to model reaction mechanisms. This is accomplished by elementary reaction steps that are selected through the rules that constitute the knowledge base of the EROS 6.0 system. These rules are derived by methods of machine learning. The learning process is based on reaction in data bases. An overview of the EROS 6.0 system is given and the structure of the knowledge as well as the generation of reaction rules are described.     

Coarse-grained potential models for structural prediction of carbon dioxide (CO2) in confined environments

In this paper, we propose coarse-grained single-site (CGSS), wall-CO(2), and CO(2)-CO(2) interaction potential models to study the structure of carbon dioxide under confinement. The CGSS potentials are used in an empirical potential based quasi-continuum theory, EQT, to compute the center-of-mass density and potential profiles of CO(2) confined inside different size graphite slit pores. Results obtained from EQT are compared with those obtained from all-atom molecular dynamics (AA-MD) simulations, and are found to be in good agreement with each other. Though these CGSS interaction potentials are primarily developed and parameterized for EQT, they are also used to perform coarse-grained molecular dynamics (CG-MD) simulations. The results obtained from CG-MD simulations are also found to be in reasonable agreement with AA-MD simulation results.     

Evaluation of the potential of Raman microspectroscopy for prediction of chemotherapeutic response to cisplatin in lung adenocarcinoma

The study of the interaction of anticancer drugs with mammalian cells in vitro is important to elucidate the mechanisms of action of the drug on its biological targets. In this context, Raman spectroscopy is a potential candidate for high throughput, non-invasive analysis. To explore this potential, the interaction of cis-diamminedichloroplatinum(II) (cisplatin) with a human lung adenocarcinoma cell line (A549) was investigated using Raman microspectroscopy. The results were correlated with parallel measurements from the MTT cytotoxicity assay, which yielded an IC(50) value of 1.2 ± 0.2 μM. To further confirm the spectral results, Raman spectra were also acquired from DNA extracted from A549 cells exposed to cisplatin and from unexposed controls. Partial least squares (PLS) multivariate regression and PLS Jackknifing were employed to highlight spectral regions which varied in a statistically significant manner with exposure to cisplatin and with the resultant changes in cellular physiology measured by the MTT assay. The results demonstrate the potential of the cellular Raman spectrum to non-invasively elucidate spectral changes that have their origin either in the biochemical interaction of external agents with the cell or its physiological response, allowing the prediction of the cellular response and the identification of the origin of the chemotherapeutic response at a molecular level in the cell.     

Exploring the use of a structural alphabet for structural prediction of protein loops

 The prediction of loop conformations is one of the challenging problems of homology modeling, owing to the large sequence variability associated with these parts of protein structures. In the present study, we introduce a search procedure that evolves in a structural alphabet space deduced from a hidden Markov model to simplify the structural information. It uses a Bayesian criterion to predict, from the amino acid sequence of a loop region, its corresponding word in the structural alphabet space. The results show that our approach ranks 30% of the target words with the best score, 50% within the five best scores. Interestingly, our approach is also suited to accept or not the prediction performed. This allows the ranking of 57% of the target words with the best score, 67% within the five best scores, accepting 16% of learned words and rejecting 93% of unknown words. Received: 17 July 2000 / Accepted: 5 January 2001 / Published online: 3 April 2001     

Characterization of structural transitions in the SLS/decanol/water system

The ternary system sodium-dodecylsulphate (SLS)/decanol/water has been investigated at three different water contents and varying ratios of cosurfactant to surfactant by means of polarized optical microscopy,²H-NMR quadrupole splittings and small angle x-ray scattering. Upon addition of decanol a hexagonal phase transforms into a lamellar phase. For the highest water content of 0.65 no intermediate two-phase regions are detected but nematic phases are formed between. The lamellar phase at low cosurfactant content is very sensitive to changes of temperature and seems to be a so-called defective one with curved interfaces. From the scaling behavior it is concluded that the building units seem to be ribbons of increasing width on addition of cosurfactant or amphiphilic substance. By reaching a decanol mole fraction of 0.4 a classical lamellar phase with well-known behavior is formed. During these transformations the position of the first diffraction maximum changes gradually irrespective of phase transitions. The maximum mole fraction of cosurfactant the lamellar phase of our system can incorporate is 0.77.     

SARs for the Antiparasitic Plant Metabolite Pulchrol. 3. Combinations of New Substituents in A/B-Rings and A/C-Rings

The natural products pulchrol and pulchral, isolated from the roots of the Mexican plant Bourreria pulchra, have previously been shown to possess antiparasitic activity towards Trypanosoma cruzi, Leishmania braziliensis and L. amazonensis, which are protozoa responsible for Chagas disease and leishmaniasis. These infections have been classified as neglected diseases, and still require the development of safer and more efficient alternatives to their current treatments. Recent SARs studies, based on the pulchrol scaffold, showed which effects exchanges of its substituents have on the antileishmanial and antitrypanosomal activity. Many of the analogues prepared were shown to be more potent than pulchrol and the current drugs used to treat leishmaniasis and Chagas disease (miltefosine and benznidazole, respectively), in vitro. Moreover, indications of some of the possible interactions that may take place in the binding sites were also identified. In this study, 12 analogues with modifications at two or three different positions in two of the three rings were prepared by synthetic and semi-synthetic procedures. The molecules were assayed in vitro towards T. cruzi epimastigotes, L. braziliensis promastigotes, and L. amazonensis promastigotes. Some compounds had higher antiparasitic activity than the parental compound pulchrol, and in some cases even benznidazole and miltefosine. The best combinations in this subset are with carbonyl functionalities in the A-ring and isopropyl groups in the C-ring, as well as with alkyl substituents in both the A- and C-rings combined with a hydroxyl group in position 1 (C-ring). The latter corresponds to cannabinol, which indeed was shown to be potent towards all the parasites.     

An in silico expert system for the identification of eye irritants

This report describes development of an in silico, expert rule-based method for the classification of chemicals into irritants or non-irritants to eye, as defined by the Draize test. This method was developed to screen data-poor cosmetic ingredient chemicals for eye irritancy potential, which is based upon exclusion rules of five physicochemical properties – molecular weight (MW), hydrophobicity (log P), number of hydrogen bond donors (HBD), number of hydrogen bond acceptors (HBA) and polarizability (Pol). These rules were developed using the ADMET Predictor software and a dataset of 917 eye irritant chemicals. The dataset was divided into 826 (90%) chemicals used for training set and 91 (10%) chemicals used for external validation set (every 10th chemical sorted by molecular weight). The sensitivity of these rules for the training and validation sets was 72.3% and 71.4%, respectively. These rules were also validated for their specificity using an external validation set of 2011 non-irritant chemicals to the eye. The specificity for this validation set was revealed as 77.3%. This method facilitates rapid screening and prioritization of data poor chemicals that are unlikely to be tested for eye irritancy in the Draize test.     

Peculiarities of inclusion complex formation in the 1,4-benzodiazepine-benzene system

5-Phenyl-1-methyl-7-bromo-3-hydroxy-1,2-dihydro-3H-1,4-benzodiazepin-2-one and its 5-(o-chloro)-phenyl analog form 2:1 (host:guest) inclusion compounds with benzene. The crystal structures of the compounds were studied by the single-crystal XRD method and were interpreted as host (H) (benzodiazepine) — guest (G) (benzene solvent molecule) complexes. The studied structures, revealing H-H and H-G interactions as both typical hydrogen bonds and π-π, C-H?π weak interactions, may serve as models for ligand-receptor binding.     

Liquid chromatographic methods for the therapeutic drug monitoring of methotrexate as clinical decision support for personalized medicine: A brief review

Methotrexate (MTX) is an antifolate drug used for several diseases. Depending on the disease, MTX can be administered at low dose (LDMTX) in some autoimmune diseases, like rheumatoid arthritis, or at high dose (HDMTX) in some cancers, such as acute lymphoblastic leukemia. After absorption, MTX is metabolized in the liver to 7‐hydroxymethotrexate and in the intestine to 2,4‐diamino‐N10‐methylpteroic acid (DAMPA). Moreover, inside red blood cells, MTX is converted to active metabolites, MTX polyglutamates (MTXPGs), contributing to its pharmacodynamics. Owing to its narrow therapeutic range, and inter‐ and intra‐patient variability, either noneffectiveness and/or toxicity may occur. Because of the existence of a relationship between drug therapeutic outcome and its systemic concentration, therapeutic drug monitoring (TDM) may ensure the effectiveness and safety of MTX use. In order to monitor the optimization of patient clinical response profile, several analytical methods have been described for TDM in biological samples. These include liquid chromatography (LC) coupled with ultraviolet detection, fluorescence detection or mass spectrometry, each one presenting advantages and drawbacks. This paper reviews the most commonly used techniques for sample preparation and critically discusses the current LC methods applied for the TDM of MTX in biological samples, at LDMTX and HDMTX.     

Bioactive glasses as potential radioisotope vectors for in situ cancer therapy: investigating the structural effects of yttrium

The incorporation of yttrium in bioactive glasses (BGs) could lead to a new generation of radionuclide vectors for cancer therapy, with high biocompatibility, controlled biodegradability and the ability to enhance the growth of new healthy tissues after the treatment with radionuclides. It is essential to assess whether and to what extent yttrium incorporation affects the favourable properties of the BG matrix: ideally, one would like to combine the high surface reactivity typical of BGs with a slow release of radioactive yttrium. Molecular Dynamics simulations show that, compared to a BG composition with the same silica fraction, incorporation of yttrium results in two opposing effects on the glass durability: a more fragmented silicate network (leading to lower durability) and a stronger yttrium-mediated association between separate silicate fragments (leading to higher durability). The simulations also highlight a high site-selectivity and some clustering of yttrium cations, which are likely linked to the observed slow rate of yttrium released from related Y-BG compositions. Optimisation of yttrium BG compositions for radiotherapy applications thus depends on the delicate balance between these effects.     

Digital simulation of the effect of dispatching rules on the performance of a routine laboratory for structural analysis

Several output characteristics of a laboratory for structural analysis are shown to be identical with the output of a model of that laboratory, e.g. the histograms of the input and output density (samples/day), the histograms of the number of samples present in the laboratory, the histograms of the delays and several cross-correlations. The effect of various strategies concerning priorities between various groups of samples is forecast, e.g. samples with a different expected analysis time, samples from various sources, samples with a different history in the laboratory. The effects of the introduction of an adaptable routing procedure, several technician assignment decisions and strategies on the termination of the analysis are simulated.     

Knowledge-based scoring functions in drug design: 3. A two-dimensional knowledge-based hydrogen-bonding potential for the prediction of protein-ligand interactions

Hydrogen bonding is a key contributor to the molecular recognition between ligands and their host molecules in biological systems. Here we develop a novel orientation-dependent hydrogen bonding potential based on the geometric characteristics of hydrogen bonds observed in 44,585 protein-ligand complexes. We find a close correspondence between the empirical knowledge and the energy landscape inferred from the distribution of HBs. A scoring function based on the resultant hydrogen-bonding potentials discriminates native protein-ligand structures from incorrectly docked decoys with remarkable predictive power.     

Thermodynamics and structural chemistry of compounds in the system MgOTiO2

Thermochemical and crystallographic properties of MgTi₂O₅, MgTiO₃, and Mg₂TiO₄ have been studied to characterize stability relations, structural variations, and order-disorder phenomena. Enthalpies of formation, decomposition, and order-disorder transitions were determined by high-temperature solution calorimetry and transposed-temperature-drop calorimetry on synthetic powders. X-Ray lattice parameter measurements and Rietveld refinements of neutron diffraction data were used to evaluate intracrystalline cation distributions and their variation with quenching temperature. MgTiO₃ is the most stable phase and apparently retains a fully ordered MgTi distribution to at least 1673 K. Both MgTi₂O₅ and Mg₂TiO₄ are stable only at high temperature because of the configurational entropy arising from cation disorder. The disorder in MgTi₂O₅ appears to vary continuously throughout the range 773–1373 K and is accompanied by changes in lattice parameters. Mg₂TiO₄ undergoes a cubictetragonal transition at 933 ± 20 K involving the appearance of long-range order on octahedral sites. However, thermochemical evidence suggests that MgTi octahedral short-range order changes gradually, perhaps over an interval of several hundred degrees. Models for describing the order-disorder and accompanying enthalpy changes are discussed.