The microcomputer OASIS system for predicting the biological activity of chemical compounds

Mold(2), molecular descriptors from 2D structures for chemoinformatics and toxicoinformatics

Research applications in chemoinformatics and toxicoinformatics increasingly use representations of molecules in the form of numerical descriptors that capture the structural characteristics and properties of molecules. These representations are useful for ADME/toxicity prediction, diversity analysis, library design, QSAR/QSPR, virtual screening, and other purposes. Molecular descriptors have ranged from relatively simple forms calculated from simple two-dimensional (2D) chemical structures to more complex forms representing three-dimensional (3D) chemical structures or complex molecular fingerprints consisting of numerous bit positions to represent specific chemical information. The Mold (2) software was developed to enable the rapid calculation of a large and diverse set of descriptors encoding two-dimensional chemical structure information. Comparative analysis of Mold (2) descriptors with those calculated by Cerius (2), Dragon, and Molconn-Z on several data sets using Shannon entropy analysis demonstrated that Mold (2) descriptors convey a similar amount of information. In addition, using the same classification method, slightly better models were generated using Mold (2) descriptors compared to those generated using descriptors from the compared commercial software packages. The low computing cost for Mold (2) makes it suitable not only for small data sets, such as in QSAR, but also for large databases in virtual screening. High reproducibility and reliability are expected because Mold (2) does not require 3D structures. Mold (2) is freely available to the public ( http://www.fda.gov/nctr/science/centers/toxicoinformatics/index.htm).

Quantitative prediction of biodegradability, metabolite distribution and toxicity of stable metabolites

An evaluation of the capability of organic chemicals to mineralize is an important factor to consider when assessing their fate in the environment. Microbial degradation can convert a toxic chemical into an innocuous one, and vice versa, or alter the toxicity of a chemical. Moreover, primary biodegradation can convert chemicals into stable products that can be difficult to mineralize. In this paper, we present some new results obtained on the basis of a recently developed probabilistic approach to modeling biodegradation based on microbial transformation pathways. The metabolic transformations and their hierarchy were calibrated by making use of the ready biodegradability data from the MITI-I test and expert knowledge for the most probable transformation pathways. A model was developed and integrated into an expert software system named CATABOL that is able to predict the probability of biodegradation of organic chemicals directly from their structure. CATABOL simulates the effects of microbial enzyme systems, generates the most plausible transformation pathways, and quantitatively predicts the persistence and toxicity of the biodegradation products. A subset of 300 organic chemicals were selected from Canada's Domestic Substances List and subjected to CATABOL to compare predicted properties of the parent chemicals with their respective first stable metabolite. The results show that most of the stable metabolites have a lower acute toxicity to fish and a lower bioaccumulation potential compared to the parent chemicals. In contrast, the metabolites appear to be generally more estrogenic than the parent chemicals.

Non-linear modeling of bioconcentration using partition coefficients for narcotic chemicals

Bioconcentration factors (BCFs) have traditionally been used to describe the tendency of chemicals to concentrate in aquatic organisms. A reexamination of the log-log QSAR between the BCF and Kow for non-congener narcotic chemicals is presented on the basis of recommended data for fish. The model is extended to give a simple correlation between BCF and the toxicity of highly, moderately and weakly hydrophilic chemicals. For the first time, in this study an equation for calculating BCF was applied in a QSAR model for predicting the acute toxicity of chemicals to aquatic organisms.

The overall Wiener index--a new tool for characterization of molecular topology

Recently, the concept of overall connectivity of a graph G, TC(G), was introduced as the sum of vertex degrees of all subgraphs of G. The approach of more detailed characterization of molecular topology by accounting for all substructures is extended here to the concept of overall distance OW(G) of a graph G, defined as the sum of distances in all subgraphs of G, as well as the sum of eth-order terms, (e)OW(G), with e being the number of edges in the subgraph. Analytical expressions are presented for OW(G) of several basic classes of graphs. The overall distance is analyzed as a measure of topological complexity in acyclic and cyclic structures. The potential usefulness of the components of this generalized Wiener index in QSPR/QSAR is evaluated by its correlation with a number of properties of C3-C8 alkanes and by a favorable comparison with models based on molecular connectivity indices.

QSAR for acetylcholinesterase inhibition and toxicity of two classes of phosphoramidothioates

Methamidophos (Met) is a weak inhibitor of housefly head AChE but at the same time it is highly toxic to the common housefly. The lethality of Met is believed to be due to AChE inhibition. An extensive QSAR study may help in determining the mode of action of Met in vivo and in vitro and provide a rational for its high insecticidal toxicity. Acephate (Ace), like Met, is a poor inhibitor of AChE in vitro and has a comparable to Met insect toxicity in vivo. Contrary to Met, though, Ace has much lower mammalian toxicity. Understanding the structural properties which make insecticides toxic to insects but not to mammals is of great importance, since mammals (including humans) are inadvertently exposed to these compounds. Our results were consistent with the model in which both the in vitro and in vivo toxicity of Met depends on the inhibition of the active center of AChE by the unchanged Met. An optimal susceptibility to hydrolysis is needed for Met and its analogs to have high insecticidal activity since in order to phosphorylate AChE they need to be hydrolyzed and at the same time their stability is of great importance in vivo for accumulating at the site of action. The insecticidal activity of Ace analogs may be due to direct interaction with the active center of the AChE. The mammalian toxicity of Ace analogs may be due to interaction with an 'allosteric' reaction center in the AChE.

Evaluation in quantitative structure--property relationship models of structural descriptors derived from information-theory operators

During the search for new structural descriptors we have defined the information-theory operators U(M), V(M), X(M), and Y(M), that are computed from atomic invariants and measure the information content of the elements of molecular matrices. Structural descriptors computed with these four information-theory operators are used to develop structure-property models for the boiling temperature, molar heat capacity, standard Gibbs energy of formation, vaporization enthalpy, refractive index, and density of alkanes. The information-theory operators were applied to six molecular matrices, namely, the distance D, the reciprocal distance RD, the distance-path Dp, the reciprocal distance-path RDp, the path Szeged Sz(p), and the reciprocal path Szeged RSz(p) matrices. In combination with other topological indices, the information-theory indices offer good structure-property models for all six alkane properties investigated in this study.

Quantitative analysis of polychlorinated biphenyls, organochlorine insecticides, polycyclic aromatic hydrocarbons, polychlorinated hydrocarbons and polynitrohydrocarbons in spiked samples of soil, water and plasma by selected-ion monitoring gas chromatography-mass spectrometry

A broad range of pollutants such as polycyclic aromatic hydrocarbons (PAHs), polychlorinated hydrocarbons (PCHs), polynitrohydrocarbons (PNHs), polychlorinated biphenyls (PCBs) and organochlorine (OCs) insecticides were simultaneously analyzed in spiked soil, water or plasma samples by using gas chromatography-mass spectrometry (GC-MS). Water and plasma samples containing the pollutants were extracted by a solid-phase extraction (SPE) method using florisil columns. The soil samples, fortified with the toxicants, were extracted with water, methanol or dichloromethane (DCM). The water extract was processed by the SPE method. The methanol and DCM samples were dried, dissolved in acetonitrile and subjected to the SPE extraction. The extracted samples were analyzed by GC-MS programmed to monitor selected ions. The deuterium labelled compounds were used as the internal standards. The chromatographic profile of total ions indicated complete separation of some compounds such as isophorone, naphthalene, all PCBs, most OC insecticides and PNHs; high Mr PAHs and some PCHs were partially or incompletely separated. The chromatographic profile of individual ion indicated good separation of each ion. The minimum detection limit ranged from 1 to 4 pg injected when 1 or 2 ions were monitored or from 20 to 200 pg injected when 20 ions were monitored. The SPE method that provided 60-105% recovery of pollutants from water samples, provided only 2-60% recovery from plasma samples. This may be due to the binding of pollutants to plasma proteins. Water recovered 1-30%, while methanol or DCM recovered 65-100% of the pollutants added to the soil samples. The use of internal standards corrected for the loss of pollutants from plasma or soil.

Physicochemical, molecular-orbital and electronic properties of acephate and methamidophos

Methamidophos (Me) and its N-acetylated derivative, acephate (Ac), are water soluble insecticides that have similar insecticidal potency, but different mammalian toxicity. Me is a potent inhibitor, while Ac is a poor inhibitor of mammalian AChE (mAChE). At physiological pH, both insecticides exhibit similar accumulation in RBC, while Ac exhibits greater binding to plasma proteins than Me. These differential effects of Ac and Me are attributed to the differences in their physicochemical, molecular-orbital and electronic properties. Ac and Me are freely soluble in aqueous solution, moderately soluble in ethyl-acetate (EtAct) and insoluble in n-hexane. The solubility of these insecticides in aqueous solution and the partitioning of these insecticides from aqueous solution into EtAct are independent of the pH of the aqueous solution. At pH 8, Me did not react with o-phthalaldehyde (a NH2 selective dye), but gamma-amino-butyric acid (pKa 10) did. Thus, despite the presence of an amino group, Ac and Me do not exhibit pH dependent solubility in aqueous and in organic solvents. Ac has two O atoms with non-bonding electrons (P = O delta- and C = O delta-) where P = O and C = O point in opposite directions. Me has only one O atom with non-bonding electrons (P = O delta-). However, because of charge translocation, the C = O group of Ac exists as C = O- and the P-NH3+ group of Me exists as P = NH2+ at a pH lower than their pKa. The P-N bond of Me, but not of Ac, is hydrolyzed at pH 2. Thus, the presence of an electron rich domain stabilizes Ac's P-N bond. The CH3S-P bond of both insecticides is similarly hydrolyzed at pH 11. This indicates that the two compounds are considerably similar except that Ac has an additional electron rich domain. At physiological pH, therefore, the functional differences between these insecticides may be due to the differences in their electronic structure. We propose that, similar to a previous model for cationic inhibitors of AChE (13), the P = O delta- group of Me forms hydrogen bonds within the oxyanion-hole causing the leaving group (-SCH3) to orient towards the "gorge" opening. This orientation allows the P atom of Me to interact with Ser200, resulting in the phosphorylation of the enzyme. For acephate, either P = O or C = O, but not both, interact within the oxyanion-hole. This destabilizes the binding of Ac to the active center, resulting in reduced AChE phosphorylation.

Effects of hexamethonium, phenothiazines, propranolol and ephedrine on acetylcholinesterase carbamylation by physostigmine, aldicarb and carbaryl: interaction between the active site and the functionally distinct peripheral sites in acetylcholinesterase

Physostigmine, aldicarb and carbaryl were potent inhibitors of acetylcholinesterase (AChE). The physostigmine-inhibited AChE fluoresced at 300 nm excitation and 500 nm emission wavelengths, but the aldicarb and carbaryl inhibited enzyme did not. This suggests that the carbamylated active center is not the fluorescing site in AChE. The fluorescence intensity of physostigmine-inhibited AChE decreased with increasing the substrate (acetylthiocholine) concentration, thus indicating that physostigmine binding to the active site is essential for the development of fluorescence. Thus, the physostigmine-inhibited AChE fluoresces due to the binding of trimethylpyrrolo[2,3-b]indol (TMPI) moiety, formed by the hydrolysis of physostigmine, to a peripheral site in AChE. The fluorescence intensity of the physostigmine-inhibited enzyme decreased when the inhibited-enzyme was dialyzed for either 30 min that poorly reactivated the enzyme or 180 min that fully reactivated the enzyme. This suggests that dialysis dissociates the AChE-TMPI complex much faster than it reactivates the carbamylated AChE. Ephedrine, propranolol and phenothiazines including trifluoparazine (TPZ) caused non-competitive inhibition, while hexamethonium caused an uncompetitive inhibition of AChE activity. TPZ, upon binding with AChE, formed a fluorescent TPZ-enzyme complex. The fluorescence intensity of TPZ-AChE complex was effectively decreased by ephedrine, but not by propranolol or hexamethonium. This indicates that TPZ and ephedrine bind to the same site in AChE which is different from the site/or sites to which propranolol or hexamethonium bind. Hexamethonium protected AChE from inhibition by carbamates and decreased the fluorescence intensity of the physostigmine-inhibited AChE. Phenothiazines and ephedrine did not modulate the enzyme inhibition or the fluorescence intensity of the physostigmine-inhibited AChE. Propranolol and TPZ potentiated the enzyme inhibition and increased the fluorescence intensity in the presence of physostigmine. These compounds, however, did not affect the inhibition of AChE by carbaryl or aldicarb. Ephedrine blocked the effects of TPZ, but did not alter the effects of propranolol on physostigmine-inhibited AChE. AChE, therefore, contains multiple peripheral binding sites which, upon binding to specific ligands, transduce differential signals to the active center.

The use of computer based structure-activity relationships in the risk assessment of industrial chemicals

The concept of a two-step approach toward the assessment of toxicity endpoints for a chemical is proposed. The first step involves the selection of chemical analogues for which toxicity data is available in a noncongeneric database. The next step is the derivation of a Quantitative Structure-Activity Relationship (QSAR) for the chemical domain, predetermined by the selection rules. The software tools needed for the computer implementation of such an approach are summarized. By making use of them, we have derived aquatic toxicity QSARs, of which two are given as example. The latter pertain to chemicals that have been automatically extracted from noncongeneric databases, after defining the substructure recognition rules implied by the putative mechanism of toxicity.

The conformational flexibility of aromatic retinoids

AM1 and PM3 complete geometry optimizations were performed on 19 arotinoids congeneric with (E)-4-[2-(5,6,7,8-tetrahydro-5,5,8,8-tetramethyl-2- naphthalenyl)-1-propenyl] benzoic acid (TTNPB), a very potent agent in carcinoprevention and carcinotherapy. Sixteen TTNPB conformations with close energy were obtained and characterized; four representative conformations were then studied for 14 derivative compounds, for which we found a substantial non-planarity of the two aromatic moieties. Large rotational flexibility of the arotinoid ring fragments was predicted by both methods. Very low barriers (0.4-3.9 kcal/mol) were found for the tetralenyl ring rotation. The two methods also agreed in predicting benzoic acid moiety rotation in a wide range of torsion angle values except those close to 0 or 180 degrees for which the PM3 rotational barriers were found to be considerably lower than the AM1 ones. This high conformational flexibility of arotinoid molecules may facilitate their favorable orientation in the process of fitting to the receptor sites.

The electronic factor in QSAR: MO-parameters, competing interactions, reactivity and toxicity

Reactive chemicals pose unique problems in the development of SAR and QSAR in environmental chemistry and toxicology. Models of the stereoelectronic interactions of reactive toxicants with biological systems require formulation of parameters that quantify the electronic structure of the chemicals. A review of early approaches to modeling reactivity is presented in this work, with emphasis on the generalized polyelectronic perturbation theory. Applications of GPPT are demonstrated with QSARs for predicting toxicity of soft electrophiles and proelectrophiles using superdelocalizability and the charges on frontier orbitals. Prediction of toxicity for hard electrophiles such as organophosphates require atomic charges and bond orders in the QSAR. Special considerations for the orthogonality of factors and for the classification of reactive chemicals are reviewed.