Simulation of chemical metabolism for fate and hazard assessment. IV. Computer-based derivation of metabolic simulators from documented metabolism maps

Computer simulation of xenobiotic metabolism and degradation is usually performed proceeding from a set of expert-developed rules modelling the actual enzyme-driven chemical reactions. With the accumulation of extensive metabolic pathway data, the analysis required to derive such chemical reaction patterns has become more objective, but also more convoluted and demanding. Herein we report on our computer-based approach for the analysis of metabolic maps, leading to the construction of reaction rules statistically suitable for simulation purposes. It is based on the set of so-called bare transformations which encompass all unique reaction patterns as obtained by a heuristically enhanced maximum common subgraph algorithm. The bare transformations guarantee that no existing metabolite is missed in simulation at the expense of an enormous amount of false positive predictions. They are rendered more selective by correlating the generated true and false positives to the locations of typical chemical functional groups in the potential reactants. The approach and its results are illustrated for a metabolic map collection of 15 cycloalkanes.     

META 4. Prediction of the metabolism of polycyclic aromatic hydrocarbons

Polycyclic aromatic hydrocarbons (PAHs) are widely distributed in the environment and are often implicated as potential carcinogens. It is generally believed that the carcinogenic potential of polycyclic aromatic hydrocarbons is linked to the formation of ultimate carcinogens generated by metabolic biotransformations. In this paper we propose a methodology that consists of using both quantum chemical properties and structural features of the reaction sites to predict PAH metabolism. Two essential questions have been answered: at which sites will the reaction take place and does the transformation consist of epoxidation or hydroxylation? This methodology has been successfully implemented into an expert system, META, for the evaluation of metabolic transformations of new chemicals. Received: 3 April 1998 / Accepted: 6 July 1998 / Published online: 7 October 1998     

The absorption and metabolism of modified amino acids in processed foods

The chemical reactions involved in the modifications of amino acids in processed food proteins are described. They concern the Maillard reaction, reaction with polyphenols and tannins, formation of lysinoalanine during alkaline and heat treatments, formation of isopeptides, oxidation reaction of the sulfur amino acids, and isomerization of the L-amino acids into their D-form. Information on the digestion, absorption, and urinary excretion of the reaction products obtained by using conventional nutritional tests is given. The studies that have been made on the metabolism of these molecules by using a radioisotopic approach to follow their kinetics in the organism after ingestion are also reviewed. This approach provides unique data on the quantitation of the metabolic pathways and on the kinetics of the metabolic processes involved.     

Simulation of the microdisc problem in spherical co-ordinates. Application to electrochemiluminescence homogeneous analysis.

The chemical transformations of electrogenerated ion-radicals of a number of complex organic compounds may be accompanied by emission of photons. An electrogenerated chemiluminescence (ECL) quantum contains information both on the kinetics of the heterogeneous electrode processes and on the subsequent homogeneous chemical reactions in the solution. Application of ECL to solution analysis provides advantages in comparison to electrochemical methods. We demonstrate a new approach for numerical simulation of the microdisc problem in spherical co-ordinates and apply it to ECL homogeneous analysis under non-steady state electrolysis.     

Simulation of chemical metabolism for fate and hazard assessment. I. Approach for simulating metabolism

Information regarding the metabolism of xenobiotic chemicals plays a central role in regulatory risk assessments. In regulatory programmes where metabolism studies are required, the studies of metabolic pathways are often incomplete and the identification of activated metabolites and important degradation products are limited by analytical methods. Because so many more new chemicals are being produced than can be assessed for potential hazards, setting assessment priorities among the thousands of untested chemicals requires methods for predictive hazard identification which can be derived directly from chemical structure and their likely metabolites. In a series of papers we are sharing our experience in the computerized management of metabolic data and the development of simulators of metabolism for predicting the environmental fate and (eco)toxicity of chemicals. The first paper of the series presents a knowledge-based formalism for the computer simulation of non-intermediary metabolism for untested chemicals, with an emphasis on qualitative and quantitative aspects of modelling metabolism.     

Probabilistic assessment of biodegradability based on metabolic pathways: catabol system

A novel mechanistic modeling approach has been developed that assesses chemical biodegradability in a quantitative manner. It is an expert system predicting biotransformation pathway working together with a probabilistic model that calculates probabilities of the individual transformations. The expert system contains a library of hierarchically ordered individual transformations and matching substructure engine. The hierarchy in the expert system was set according to the descending order of the individual transformation probabilities. The integrated principal catabolic steps are derived from set of metabolic pathways predicted for each chemical from the training set and encompass more than one real biodegradation step to improve the speed of predictions. In the current work, we modeled O2 yield during OECD 302 C (MITI I) test. MITI-I database of 532 chemicals was used as a training set. To make biodegradability predictions, the model only needs structure of a chemical. The output is given as percentage of theoretical biological oxygen demand (BOD). The model allows for identifying potentially persistent catabolic intermediates and their molar amounts. The data in the training set agreed well with the calculated BODs (r2 = 0.90) in the entire range i.e. a good fit was observed for readily, intermediate and difficult to degrade chemicals. After introducing 60% ThOD as a cut off value the model predicted correctly 98% ready biodegradable structures and 96% not ready biodegradable structures. Crossvalidation by four times leaving 25% of data resulted in Q2 = 0.88 between observed and predicted values. Presented approach and obtained results were used to develop computer software for biodegradability prediction CATABOL.     

Probabilistic assessment of biodegradability based on metabolic pathways: CATABOL System

A novel mechanistic modeling approach has been developed that assesses chemical biodegradability in a quantitative manner. It is an expert system predicting biotransformation pathway working together with a probabilistic model that calculates probabilities of the individual transformations. The expert system contains a library of hierarchically ordered individual transformations and matching substructure engine. The hierarchy in the expert system was set according to the descending order of the individual transformation probabilities. The integrated principal catabolic steps are derived from set of metabolic pathways predicted for each chemical from the training set and encompass more than one real biodegradation step to improve the speed of predictions. In the current work, we modeled O 2 yield during OECD 302 C (MITI I) test. MITI-I database of 532 chemicals was used as a training set. To make biodegradability predictions, the model only needs structure of a chemical. The output is given as percentage of theoretical biological oxygen demand (BOD). The model allows for identifying potentially persistent catabolic intermediates and their molar amounts. The data in the training set agreed well with the calculated BODs ( r 2 =0.90) in the entire range i.e. a good fit was observed for readily, intermediate and difficult to degrade chemicals. After introducing 60% ThOD as a cut off value the model predicted correctly 98% ready biodegradable structures and 96% not ready biodegradable structures. Crossvalidation by four times leaving 25% of data resulted in Q 2 =0.88 between observed and predicted values. Presented approach and obtained results were used to develop computer software for biodegradability prediction CATABOL.     

Accelerated stochastic simulation of the stiff enzyme-substrate reaction

The enzyme-catalyzed conversion of a substrate into a product is a common reaction motif in cellular chemical systems. In the three reactions that comprise this process, the intermediate enzyme-substrate complex is usually much more likely to decay into its original constituents than to produce a product molecule. This condition makes the reaction set mathematically "stiff." We show here how the simulation of this stiff reaction set can be dramatically speeded up relative to the standard stochastic simulation algorithm (SSA) by using a recently introduced procedure called the slow-scale SSA. The speedup occurs because the slow-scale SSA explicitly simulates only the relatively rare conversion reactions, skipping over occurrences of the other two less interesting but much more frequent reactions. We describe, explain, and illustrate this simulation procedure for the isolated enzyme-substrate reaction set, and then we show how the procedure extends to the more typical case in which the enzyme-substrate reactions occur together with other reactions and species. Finally, we explain the connection between this slow-scale SSA approach and the Michaelis-Menten [Biochem. Z. 49, 333 (1913)] formula, which has long been used in deterministic chemical kinetics to describe the enzyme-substrate reaction.     

Computer simulation of ecdysone metabolism and of the HPLC analysis of the metabolites

Summary Computer simulation of ecdysone metabolism in insects has been done by the a software called HPLC-Metabolexpert®, that served to generate the metabolic pathways of ecdysone in a retrospective manner. Some of the generated metabolites have already been detected, others are to be confirmed. Lists of the applied metabolic transformations, the predicted metabolites and their HPLC elution times are also given.     

Automatic polarographic elucidation of electrode mechanisms by means of a knowledge-based system : Part 1. Sampled d.c. polarography

A knowledge-based system has been developed for the automatic elucidation of electrochemical mechanisms. The system is based on sampled direct current (or Tast) polarography at a dropping mercury electrode as a technique for collecting experimental information and consists of a general expert system shell for the reasoning process, the specific set of rules and experimental modules. The set of rules allows the elucidation of eight relatively simple electrode reaction mechanisms fully atomatically. The computer system has been validated with chemical systems the electrochemical behaviour of which is well established. All parts of the program are written in FORTH language for Apple II microcomputers. This expert system has an open character and new rules can be added to extend the set of mechanisms that can be determined.     

Kinetics and mechanism of the catalytic reaction between alcohols and dimethyl carbonate

The mechanism of the reaction between alcohols and dimethyl carbonate, catalyzed by dicobalt octacarbonyl Co₂(CO)₈, is studied by means of mathematical modeling. Kinetic models for possible schemes of chemical transformations are constructed at different initial concentrations of the catalyst. Based on a comparative analysis of activation energies of possible stages of chemical transformations, possible reaction pathways are determined and an appropriate mechanism is selected.     

Simulation of chemical metabolism for fate and hazard assessment. V. Mammalian hazard assessment

Animals and humans are exposed to a wide array of xenobiotics and have developed complex enzymatic mechanisms to detoxify these chemicals. Detoxification pathways involve a number of biotransformations, such as oxidation, reduction, hydrolysis and conjugation reactions. The intermediate substances created during the detoxification process can be extremely toxic compared with the original toxins, hence metabolism should be accounted for when hazard effects of chemicals are assessed. Alternatively, metabolic transformations could detoxify chemicals that are toxic as parents. The aim of the present paper is to describe specificity of eukaryotic metabolism and its simulation and incorporation in models for predicting skin sensitization, mutagenicity, chromosomal aberration, micronuclei formation and estrogen receptor binding affinity implemented in the TIMES software platform. The current progress in model refinement, data used to parameterize models, logic of simulating metabolism, applicability domain and interpretation of predictions are discussed. Examples illustrating the model predictions are also provided.     

The application of the CSB to the prediction of single step reactions and reaction pathways

Applications of the CSB (Common-Sense Builder) system for the logic-oriented and knowledge-assisted simulation of chemical reaction courses are described. We present the possibility of using the CSB for two ways of reaction simulation, i.e., as a multi-step process or as single step procedure. Results of the first simulation type are given to predict the course, and to model reaction mechanism. The second one is capable of complex chemical transformations such as multi-component and cascade reactions to generate structurally diverse products for combinatorial chemistry. In several experiments performed, we analyze the capabilities and limitations of the CSB modules and controlling tools for the examination and selective generation of solutions.     

Simulation of chemical metabolism for fate and hazard assessment. V. Mammalian hazard assessment

Animals and humans are exposed to a wide array of xenobiotics and have developed complex enzymatic mechanisms to detoxify these chemicals. Detoxification pathways involve a number of biotransformations, such as oxidation, reduction, hydrolysis and conjugation reactions. The intermediate substances created during the detoxification process can be extremely toxic compared with the original toxins, hence metabolism should be accounted for when hazard effects of chemicals are assessed. Alternatively, metabolic transformations could detoxify chemicals that are toxic as parents. The aim of the present paper is to describe specificity of eukaryotic metabolism and its simulation and incorporation in models for predicting skin sensitization, mutagenicity, chromosomal aberration, micronuclei formation and estrogen receptor binding affinity implemented in the TIMES software platform. The current progress in model refinement, data used to parameterize models, logic of simulating metabolism, applicability domain and interpretation of predictions are discussed. Examples illustrating the model predictions are also provided.     

Application of computer simulation free-energy methods to compute the free energy of micellization as a function of micelle composition. 2. Implementation

In this paper, the implementation of the CS-FE/MT model introduced in article 1 is discussed, and computer simulations are performed to evaluate the feasibility of the new theoretical approach. As discussed in article 1, making predictions of surfactant/solubilizate aqueous solution behavior using the CS-FE/MT model requires evaluation of DeltaDeltaG for multiple surfactant-to-solubilizate or surfactant-to-cosurfactant transformations. The central goal of this article is to evaluate the quantitative accuracy of the alchemical computer simulation method used in the CS-FE/MT modeling approach to predict DeltaDeltaG for a single surfactant-to-solubilizate or for a single surfactant-to-cosurfactant transformation. A hybrid single/dual topology approach was used to morph the ionic surfactant sodium dodecyl sulfate (SDS) into the ionic solubilizate ibuprofen (IBU), and a dual topology approach was used to morph the nonionic surfactant octyl glucoside (OG) into the nonionic solubilizate p-aminobenzoate (PAB). In addition, a single topology approach was used to morph the nonionic surfactant n-decyl dimethylphosphine oxide (C10PO) into the nonionic cosurfactant n-decyl methyl sulfoxide (C10SO), the nonionic surfactant octylsulfinyl ethanol (C8SE) into the nonionic cosurfactant decylsulfinyl ethanol (C10SE), and the nonionic surfactant n-decyl methyl sulfoxide (C10SO) into the nonionic cosurfactant n-octyl methyl sulfoxide (C8SO). Each DeltaDeltaG value was computed by using thermodynamic integration to determine the difference in free energy associated with (i) transforming a surfactant molecule of type A into a cosurfactant/solubilizate molecule of type B in a micellar environment (referred to as DeltaG2) and (ii) transforming a surfactant molecule of type A into a cosurfactant/solubilizate molecule of type B in aqueous solution (referred to as DeltaG1). CS-FE/MT model predictions of DeltaDeltaG for each alchemical transformation were made at a number of simulation conditions, including (i) different equilibration times at each value of the coupling parameter lambda, (ii) different data-gathering times at each lambda value, and (iii) simulation at a different number of lambda values. For the three surfactant-to-cosurfactant transformations considered here, the DeltaDeltaG values predicted by the CS-FE/MT model were compared with DeltaDeltaG values predicted by an accurate molecular thermodynamic (MT) model developed by fitting to experimental CMC data. Even after performing lengthy equilibration and data gathering at each lambda value, physically unrealistic values of DeltaDeltaG were predicted by the CS-FE/MT model for the transformations of SDS into IBU and of OG into PAB. However, more physically realistic DeltaDeltaG values were predicted for the transformation of C10PO into C10SO, and reasonable free-energy predictions were obtained for the transformations of C8SE into C10SE and C10SO into C8SO. Each of the surfactant-to-cosurfactant transformations considered here involved less extensive structural changes than the surfactant-to-solubilizate transformations. As computer power increases and as improvements are made to alchemical free-energy methods, it may become possible to apply the CS-FE/MT model to make accurate predictions of the free-energy changes associated with forming multicomponent surfactant and solubilizate micelles in aqueous solution where the chemical structures of the surfactants, cosurfactants, and solubilizates differ significantly.     

An oligomer-based approach to skeletal diversity in small-molecule synthesis

Access to small molecules of widely varying molecular shapes has been identified as an enabling step in the discovery of biologically active materials. In this communication we introduce an approach to the systematic development of architecturally distinct chemical compounds based upon the assembly of reactive monomers into linear oligomers, each of which encodes a unique molecular framework under a common set of reaction conditions. Certain products of the initial chemical transformation (Ru-catalyzed metathesis reaction) encode additional skeletons upon treatment with a second common set of reagents (Diels-Alder dienophiles). Application of this oligomerization approach has led to the discovery of a previously unreported tandem ene-yne-yne metathesis-6pi-electrocyclization-1,5-hydride migration that converts a linear substrate into a complex tricyclic 1,3-diene in a single step. Thus, the reported strategy might serve not only as a generator of skeletally diverse small molecules but also as a discovery platform for the identification of novel chemical transformations.     

Measuring splitting and overlapping in molecular systems. A fuzzy set estimation of reaction hazards

An algorithm for assessments of fuzzy molecular structural characteristics has been presented, and its chemical relevance is approved for numerous evidences of reaction mechanisms. Empirical rules pervading the results of chemical synthesis are continuously the source of information efficiently used by experimental chemists and technologists. Approaching them theoretically to broaden areas of applicability and to make them more precise for better prediction is of great importance to reach progress in the chemical information recognition and to steer and control technological processes. Fuzzy sets called splitting and overlapping have been applied for assessments of the reaction hazards. The mathematically grounded properties turned out to underlie well-known empirical rules for preliminary estimations of organic reaction tendencies. Informative quantitative data shown are revealing new ways of understanding basic chemical reaction mechanisms.     

Application of chemical graph theory for automated mechanism generation

We present an application of the chemical graph theory approach for generating elementary reactions of complex systems. Molecular species are naturally represented by graphs, which are identified by their vertices and edges where vertices are atom types and edges are bonds. The mechanism is generated using a set of reaction patterns (sub-graphs). These subgraphs are the internal representations for a given class of reaction thus allowing for the possibility of eliminating unimportant product species a priori. Furthermore, each molecule is canonically represented by a set of topological indices (Connectivity Index, Balaban Index, Schulz TI Index, WID Index, etc.) and thus eliminates the probability for regenerating the same species twice. Theoretical background and test cases on combustion of hydrocarbons are presented.     

Coupled molecular dynamics-Monte Carlo model to study the role of chemical processes during laser ablation of polymeric materials

The coarse grained chemical reaction model is enhanced to build a molecular dynamics (MD) simulation framework with an embedded Monte Carlo (MC) based reaction scheme. The MC scheme utilizes predetermined reaction chemistry, energetics, and rate kinetics of materials to incorporate chemical reactions occurring in a substrate into the MD simulation. The kinetics information is utilized to set the probabilities for the types of reactions to perform based on radical survival times and reaction rates. Implementing a reaction involves changing the reactants species types which alters their interaction potentials and thus produces the required energy change. We discuss the application of this method to study the initiation of ultraviolet laser ablation in poly(methyl methacrylate). The use of this scheme enables the modeling of all possible photoexcitation pathways in the polymer. It also permits a direct study of the role of thermal, mechanical, and chemical processes that can set off ablation. We demonstrate that the role of laser induced heating, thermomechanical stresses, pressure wave formation and relaxation, and thermochemical decomposition of the polymer substrate can be investigated directly by suitably choosing the potential energy and chemical reaction energy landscape. The results highlight the usefulness of such a modeling approach by showing that various processes in polymer ablation are intricately linked leading to the transformation of the substrate and its ejection. The method, in principle, can be utilized to study systems where chemical reactions are expected to play a dominant role or interact strongly with other physical processes.     

Kinetic analysis of sequential multistep reactions

Many processes in biology and chemistry involve multistep reactions or transitions. The kinetic data associated with these reactions are manifested by superpositions of exponential decays that are often difficult to dissect. Two major challenges have hampered the kinetic analysis of multistep chemical reactions: (1) reliable and unbiased determination of the number of reaction steps, and (2) stable reconstruction of the distribution of kinetic rate constants. Here, we introduce two numerically stable integral transformations to solve these two challenges. The first transformation enables us to deduce the number of rate-limiting steps from kinetic measurements, even when each step has arbitrarily distributed rate constants. The second transformation allows us to reconstruct the distribution of rate constants in the multistep reaction using the phase function approach, without fitting the data. We demonstrate the stability of the two integral transformations by both analytic proofs and numerical tests. These new methods will help provide robust and unbiased kinetic analysis for many complex chemical and biochemical reactions.