SAR Approach Research Articles

SAR modeling of genotoxic phenomena: the consequence on predictive performance of deviation from a unity ratio of genotoxicants/non-genotoxicants

SAR approaches to the study of genotoxic phenomena are finding increased applications. However, the data being modeled are frequently not considered optimal due to the small size of the dataset and an uneven distribution of genotoxicants and non-genotoxicants in the dataset. The effects of such imbalances on the performance of one SAR approach were investigated with respect to the modeling of the induction of unscheduled DNA synthesis in rat hepotocytes and of sister chromatid exchanges and chromosomal aberrations in cultural CHO cells.The analyses indicate that if genotoxicants exceed non-genotoxicants, the performance of the SAR model can be improved if the dataset is supplemented with physiological chemicals which are assumed to be non-genotoxicants. On the other hand, if non-genotoxicants exceed genotoxicants, it was found that the predictive performance of the resulting SAR model is not improved by removal of genotoxicants from the dataset to achieve a ratio of genotoxicants/genotoxicants of unity.Overall, the present analyses did not result in the development of SAR models of greatly increased predictivity. Conceivably, for the particular datasets and SAR paradigm the limit of predictivity has been reached. The possibility of investigating the use of a “battery” of SAR paradigms should be considered.

What makes epothilones stick?

The potent epothilone tubulin polymerization promoters have been studied extensively by synthetic and SAR approaches. The paper by Buey et al. (, this issue of Chemistry & Biology) adds a new depth of mechanistic understanding by a careful analysis of the tubulin polymerization mechanism of the epothilones.

Kinetics of the radical scavenging activity of β-carotene-related compounds

To clarify the non-enzymatic radical-scavenging activity of β-carotene-related compounds and other polyenes, we used differential scanning calorimetry to study the kinetics of radical polymerization of methyl methacrylate (MMA) by 2,2′-azobisisobutyronitrile (AIBN) or benzoyl peroxide (BPO) in the absence or presence of polyenes under nearly anaerobic conditions at 70°C, and analyzed the results with an SAR approach. The polyenes studied were all-trans retinol, retinol palmitate, calciferol, β-carotene and lycopene. Polyenes produced a small induction period. The stoichiometric factor (n) (i.e. the number of radicals trapped by each inhibitor molecule) of polyenes was close to 0. Tetraterpenes (β-carotene, lycopene) suppressed significantly more of the initial rate of polymerization (R inh) than did diterpenes (retinol, retinol palmitate). The inhibition rate constants (k inh) for the reaction of β-carotene with AIBN-or BPO-derived radicals were determined to be 1.2–1.6 × 105 l / mol s, similar to published values. A linear relationship between k inh and the kinetic chain length (KCL) for polyenes was observed; as k inh increased, KCL decreased. KCL also decreased significantly as the number of conjugated double bonds in the polyenes increased. Polyenes, particularly β-carotene and lycopene, acted as interceptors of growing poly-MMA radicals.

An Overall Strategy for the Testing of Chemicals for Human Hazard and Risk Assessment under the EU REACH System

In its White Paper, "Strategy for a Future Chemicals Policy," published in 2001, the European Commission (EC) proposed the REACH (Registration, Evaluation and Authorisation of CHemicals) system to deal with both existing and new chemical substances. This system is based on a top-down approach to toxicity testing, in which the degree of toxicity information required is dictated primarily by production volume (tonnage). If testing is to be based on traditional methods, very large numbers of laboratory animals could be needed in response to the REACH system, causing ethical, scientific and logistical problems that would be incompatible with the time-schedule envisaged for testing. The EC has emphasised the need to minimise animal use, but has failed to produce a comprehensive strategy for doing so. The present document provides an overall scheme for predictive toxicity testing, whereby the non-animal methods identified and discussed in a recent and comprehensive ECVAM document, could be used in a tiered approach to provide a rapid and scientifically justified basis for the risk assessment of chemicals for their toxic effects in humans. The scheme starts with a preliminary risk assessment process (involving available information on hazard and exposure), followed by testing, based on physicochemical properties and (Q)SAR approaches. (Q)SAR analyses are used in conjunction with expert system and biokinetic modelling, and information on metabolism and identification of the principal metabolites in humans. The resulting information is then combined with production levels and patterns of use to assess potential human exposure. The nature and extent of any further testing should be based strictly on the need to fill essential information gaps in order to generate adequate risk assessments, and should rely on non-animal methods, as far as possible. The scheme also includes a feedback loop, so that new information is used to improve the predictivity of computational expert systems. Several recommendations are made, the most important of which is that the European Union (EU) should actively promote the improvement and validation of (Q)SAR models and expert systems, and computer-based methods for biokinetic modelling, since these offer the most realistic and most economical solution to the need to test large numbers of chemicals.

Structural controls on Neoproterozoic mineralization in the South Eastern Desert, Egypt: an integrated field, Landsat TM, and SIR-C/X SAR approach

The Arabian–Nubian Shield represents a complex amalgam of arcs and microcontinents assembled during Neoproterozoic closure of the Mozambique Ocean. The 750–720 Ma Allaqi suture is an arc/arc collision zone, formed when the Gerf terrane in the north overrode the circa 830–720 Ma Gabgaba terrane in the south, prior to closure of the Mozambique Ocean. Neoproterozoic rocks include ophiolitic ultramafic–mafic rocks, metasediments, intermediate metavolcanic rocks, intrusive gabbro-diorite rocks, granodiorites, biotite granites, and leucocratic granites. High-pressure/low-temperature metamorphism has been documented in rocks of the suture zone. Mineral deposits include nickel–copper–platinum and podiform chromite in ultramafic rocks, marble, gold-bearing quartz-veins in D 2 and D 3 shear zones, and radioactive mineralization associated with late leucocratic granitic rocks. Integrated field mapping and remote sensing techniques are used to distinguish and map the relationships between rock units, structures, and alteration zones associated with mineral deposits along the Allaqi suture of Egypt's SE Desert. Landsat TM images processed using a band ratioing technique show different rock types remarkably well, and are able to distinguish between alteration zones associated with ultramafic rocks (listwaenites) and those associated with leucocratic granitic rocks (greisenization, silicification and albitization). Black and white L-band SIR-C/X SAR images outline foliations, faults and folds that control mineralization at several deposits in the area, whereas color composite multiband Chh-Lhh-Lhv SIR-C/X SAR images reveal some elliptical granitic bodies that host radioactive mineralization. E-trending, tight to isoclinal, gently dipping folds, thrust faults and subvertical shear zones related to the Allaqi suture are overprinted by N-oriented structures related to the Wadi Ungate shear zone, formed during collision of east and west Gondwana during closure of the Mozambique Ocean. The location of the Wadi Ungate shear zone in the Wadi Shellman area was previously unknown due to burial of basement rocks beneath thin dry sands. A new structural map was prepared using Landsat TM ratio images and SIR-C/X SAR imagery. SIR-C/X SAR data conveys considerably more information about rocks and structures beneath the thin sand cover than discernible from aerial photographs or Landsat TM images.

Computational Toxicology and the Generation of Mechanistic Hypotheses: γ-Butyrolactone

In this study, we use SAR approaches in an attempt to elucidate the action of γ-butyrolactone (GBL), an illicit drug and a dietary supplement, that can cause coma and deaths in humans while exhibiting low systemic toxicity towards rodents. The lack of systemic toxicity of GBL and of its metabolite(s) was also predicted by validated SAR models. In fact using diverse SAR models, the only significant SAR prediction was that GBL had the potential for inhibiting human cytochrome P4502D6 (CYP2D6). However, inhibition of that isozyme is not necessarily associated with toxicity. It is suggested that GBL users also abuse other substances. When GBL inhibits CYP2D6 this may prevent the CYP2D6-mediated detoxification of other toxicants simultaneously consumed by the GBL user.

Modulation of P-glycoprotein (PGP) mediated multidrug resistance (MDR) using chemosensitizers: recent advances in the design of selective MDR modulators.

Over the past two decades, a number of chemical entities have been investigated in the continuing quest to reverse P-glycoprotein (PGP) mediated multidrug resistance (MDR) in cancer. The complexity of interactions between these agents and the proteins responsible for MDR in conjunction with the challenges associated with developing SAR/QSAR relationships for MDR modulators has hampered our ability to develop agents that modulate MDR with enhanced specificity of target, increased efficacy, and minimized toxicity when coadministered with anticancer drugs. With an increased understanding of the molecular interaction, target-mediated SAR and combinatorial chemistry approaches, newer more selective inhibitors have been recently reported. These agents have shown remarkable promise in preclinical trials; although their ultimate clinical therapeutic utility remains to be established. The emphasis of this review is placed on the current understanding of modulator-drug transport protein interactions and to review the advances in the structure-based design, synthetic efforts and the cellular pharmacology of MDR modulating activity of a number of known PGP inhibitors.

Sar modeling of unbalanced data sets

The increased acceptance of SAR approaches to hazard identification has led us to investigate methods to improve the predictive performance of SAR models. In the present study we demonstrate that although on theoretical grounds the ratio of active to inactive chemicals in the learning set should be unity, SAR models can ‚tolerate’ an unbalanced range in ratios from 3 : 1 (i.e., 75% actives) to 1 : 2 (i.e., 33% actives) and still perform adequately. On the other hand SAR models derived from learning sets with ratios in excess of 4 : 1 (80% actives), even when corrected for the initial ratio do not perform satisfactorily.

Chemical Categories for Health Hazard Identification: A Feasibility Study

The use of chemical categories has been suggested in order to lower the number of chemicals tested in the High Production Volume (HPV) Chemical Challenge Program. In this investigation we examined the reliability of using organic chemical categories to classify chemicals as either toxic or nontoxic for individual toxicological effects as well as for panels of such endpoints. The analyses indicate that chemical categories are unable to consistently identify groups of chemicals with similar toxic responses either for a multiplicity of endpoints or for single effects. Our analyses suggest that if chemical categories are to be used to identify health hazards, that computer-based SAR approaches appear to be superior to arbitrary chemical categories for predicting specific toxicological effects but they are not, at this time, useful for defining the overall toxicity.

Synthesis and evaluation of a series of novel 2-[(4-chlorophenoxy)methyl]benzimidazoles as selective neuropeptide Y Y1 receptor antagonists.

A series of novel benzimidazoles (BI) derived from the indole 2 was synthesized and evaluated as selective neuropeptide Y (NPY) Y1 receptor antagonists with the aim of developing antiobesity drugs. In our SAR approach, the (4-chlorophenoxy)methyl group at C-2 was kept constant and a series of BIs substituted with various piperidinylalkyl groups at N-1 was synthesized to identify the optimal spacing and orientation of the piperidine ring nitrogen relative to the benzimidazole. The 3-(3-piperidinyl)propyl in 33 was found to maximize affinity for the Y1 receptor. Because of the critical importance of Arg33 and Arg35 of NPY binding to the Y1 receptor, the incorporation of an additional aminoalkyl functionality to the structure of 33 was explored. Methyl substitution was used to probe where substitution on the aromatic ring was best tolerated. In this fashion, the C-4 was chosen for the substitution of the second aminoalkyl functionality. Synthesis of such compounds with a phenoxy tether using the 4-hydroxybenzimidazole 11 was pursued because of their relative ease of synthesis. Functionalization of the hydroxy group of 45 with a series of piperidinylalkyl groups provided the dibasic benzimidazoles 55-62. Among them, BI 56 demonstrated a Ki of 0.0017 microM, which was 400-fold more potent than 33. To evaluate if there was a stereoselective effect on affinity for these BIs, the four constituent stereoisomers (69-72) of the BI 60 were prepared using the S- and R-isomers of bromide 17. Antagonist activity of these BIs was confirmed by measuring the ability of selected compounds to reverse NPY-induced forskolin-stimulated cyclic AMP. The high selectivity of several BI antagonists for the Y1 versus Y2, Y4, and Y5 receptors was also shown.

Parallelization Techniques for Sparse Matrix Applications

Sparse matrix problems are difficult to parallelize efficiently on distributed memory machines since data is often accessed indirectly. Inspector–executor strategies, which are typically used to parallelize loops with indirect references, incur substantial runtime preprocessing overheads when references with multiple levels of indirection are encountered—a frequent occurrence in sparse matrix algorithms. Thesparse-array rolling(SAR) technique, introduced in [M. Ujaldón and E. L. Zapata,Proc. 9th ACM Int'l. Conf. on Supercomputing,Barcelona, July 1995, pp. 117–126], significantly reduces these preprocessing overheads. This paper outlines the SAR approach and describes its runtime support accompanied by a detailed performance evaluation. The results demonstrate that SAR yields significant reduction in preprocessing overheads compared to standard inspector–executor techniques.

Molecular fragments associated with non-genotoxic carcinogens, as detected using a software program based on graph theory: their usefulness to predict carcinogenicity

We assembled 390 chemicals with a structure non-alerting to DNA-reactivity (145 carcinogens and 245 non-carcinogens) for which rodent carcinogenicity data were available. These non-alerting chemicals were defined by the absence in their molecules of DNA-reactive (directly or after metabolic activation) alerting structures, as described by Ashby and coworkers (Mutat. Res., 204 (1988) 17–115; Mutat. Res., 223 (1989) 73–103; Mutat. Res., 257 (1991) 209–227; Mutat. Res., 286 (1993) 3–74). Using our software program based on graph theory we analyzed the compounds in order to estimate the program's ability to predict nonalerting carcinogens. Our software fragmented the structural formula of the chemicals into all possible fragments of contiguous atoms with size between 2 and 8 (non-hydrogen) atoms and learned about statistically significant fragments from a training set of chemicals. These fragments were used to predict carcinogenicity or lack thereof in a verification set of compounds. For 390 runs of the software program we used ( n − 1) of the chemicals as a training set, to predict the excluded chemical at each run (as a test set). Using two different probability thresholds to select significant fragments ( P = 0.05 and P = 0.125 1-tailed according to binomial distribution), we performed two analyses: in the better one ( P = 0.05) 19% of the molecules tested lacked significant fragments, for the remaining 81% the observed level of accuracy of the prediction was 66.0% against an expected level of accuracy of 51.7%. The difference was highly significant ( P < 0.0001). We also examined the more significant activating fragments (biophores) and discussed at length both their biological plausibility and the working hypothesis that additional alerting structures for carcinogenicity (not only those related to genotoxicity) can be detected using this type of SAR approach. This new class of alerting structures could identify subfamilies of congeneric analogs active through mechanisms of receptor mediated carcinogenesis.

Potential histamine H2-receptor antagonists: analogues of classical antagonists containing 4-substituted-3-aminofurazan moieties.

AbstractAnalogues of classical H2‐receptor antagonists containing aminofurazan moieties as polar groups were synthesized and tested “in vitro” for their activities. Compounds containing 3‐amino‐4‐methylfurazan and 4‐amino‐3‐methylfuroxan substructures show good antagonistic properties. The compound containing the 3‐amino‐4‐phenylfurazan moiety is inactive. An SAR approach is discussed.

Computer-assisted structure-activity relationships of nitrogenous cyclic compounds tested in Salmonella assays for mutagenicity

Study of the relationship between mutagenicity and molecular structure for a data set of nitrogenous cyclic compounds is reported. A computerized SAR system (ADAPT) was utilized to classify a data set of 114 nitrogenous cyclic compounds with 19 molecular descriptors. All of the descriptors represented at least 10% of the compounds in the data sets. The average correct predictability of the data base was calculated to be 89% after evaluating 100 training/prediction subsets. The actual predictive ability of the discriminants generated by the ADAPT system was demonstrated by predicting the mutagenicity of structurally similar compounds not in the data set. Weight vectors generated in the pattern recognition programs were used to predict the bacterial mutagenicity of 10 compounds which were not included in the data set. All of the compounds were predicted correctly which was actually better than the 89% calculated by the system. This displayed the ability of the system of classify compounds as mutagenic or nonmutagenic by using molecular descriptors and to predict the biological activity of untested chemicals with a high degree of confidence. This paper presents the uses of this type of SAR approach in a research laboratory.