Biotransformations database

One of the earliest attempts to model chemical transformations in a living system was carried out in 1987. This system consists of a biotransformation database and one or more logic-based prediction tools.This system and other knowledge-based systems provide a branching tree of possible metabolites but provide no information on likelihood or quantitative rates of production. 

Based on the biotransformation database of Kroutil and Faber (2010) 14,000 entries. 

Knowledge-based methods are those based on the application of certain rules to describe the metabolism. These rules could be defined as chemical reactions relating structure and biotransformations to predict the metabolic fate of a query chemical structure, as in the Meteor approach [26], or alternatively they could be obtained by fragment analysis of a metabolic database as performed in the SPORCalc (Substrate Product Occurrence Ratio Calculator) system [27]. 

As with chemical synthesis, the first step when prospecting for a particular biotransformation is to perform a literature search to check whether a suitable precedent has been described. Extensive technical literature resources in the public domain provide both examples of specific enzyme-catalysed reactions and descriptions of transformations where enzyme activity is inferred if not explicitly described. Currently, searches of online databases such as PubMed reveal over 2000 new publications per annum in the subject of enzyme catalysis (excluding reviews). 

In this section, enzymes in the EC 2.4. class are presented that catalyze valuable and interesting reactions in the field of polymer chemistry. The Enzyme Commission (EC) classification scheme organizes enzymes according to their biochemical function in living systems. Enzymes can, however, also catalyze the reverse reaction, which is very often used in biocatalytic synthesis. Therefore, newer classification systems were developed based on the three-dimensional structure and function of the enzyme, the property of the enzyme, the biotransformation the enzyme catalyzes etc. [88-93]. The Carbohydrate-Active enZYmes Database (CAZy), which is currently the best database/classification system for carbohydrate-active enzymes uses an amino-acid-sequence-based classification and would classify some of the enzymes presented in the following as hydrolases rather than transferases (e.g. branching enzyme, sucrases, and amylomaltase) [91]. Nevertheless, we present these enzymes here because they are transferases according to the EC classification. 

Several databases of published biotransformations are commercially available, such as Molecular Design Ltd s Metabolite and the Accelerys Metabolism Database (formerly produced by Synopsis). The former is quite extensive, and contains in vivo and in vitro biotransformation summaries from the literature, while the latter has as its core information based on the U.K. Royal Society of Chemistry s Biotransformations series (Hawkins, 1988-1996) supplemented by additional data from the literature. Both systems are searchable by reaction type. The intelligent use of such databases provides much valuable information on likely metabolic profile. 

Many publications dealing with TLC-HPTLC steroid analysis have appeared every year. The publications can be summarized into categories as follows analytical control of steroid formulations (drug preparations), determination of steroids in biological media and natural resources, and analytical control of the production of steroids (including raw material, syntheses, and biotransformation). A cumulative database of thousands of TLC methods (including steroids) is provided in compact-disk (CD) format by Camag [6]. 

Metabolism databases and several predictive software packages also have been reviewed.A knowledge-based expert system for the prediction of phase I and II biotransformations called META was developed on the VAX/VMS platform,META contains over 750 biotransformations based on substrnctnres and qnantnm mechanical calculations that gave excellent predictions on test data and have been optimized using a genetic algorithm to perform better than human experts.However, when used to predict the metabolism of 42 polycyclic aromatic hydrocarbons (PAHs), META overpredicted 29 and missed 8 of 72 experimentally observed epoxidations, and missed 27 of 49 experimentally observed hydroxylations. ... 

Once the structure of the PBPK model is formulated, the next step is specifying the model parameters. These can be classified into a chemical-independent set of parameters (such as physiological characteristics, tissue volumes, and blood flow rates) and a chemical-specific set (such as blood/tissue partition coefficients, and metabolic biotransformation parameters). Values for the chemical-independent parameters are usually obtained from the scientific literature and databases of physiological parameters. Specification of chemical-specific parameter values is generally more challenging. Values for one or more chemical-specific parameters may also be available in the literature and databases of biochemical and metabolic data. Values for parameters that are not expected to have substantial interspecies differences (e.g., tissue/blood partition coefficients) can be imputed based on parameter values in animals. Parameter values can also be estimated by conducting in vitro experiments with human tissue. Partitioning of a chemical between tissues can be obtained by vial equilibration or equilibrium dialysis studies, and metabolic parameters can be estimated from in vitro metabolic systems such as microsomal and isolated hepatocyte syterns. Parameters not available from the aforementioned sources can be estimated directly from in vivo data, as discussed in Section 43.4.5. 

Saving a biotransformation in the system stores all relevant data in the main database (administrative data, connectivity information) and in the chemistry databases (strnctnre, spectra, other instrnmental data and metadata). Optionally, the biotransformation system may be integrated with an electronic notebook solntion. When started from the notebook, the biotransformation system creates a graphical representation of the metabolic pathway and sends it together with administrative data and metadata to an electronic scientific docnment. 

The state of the art is described in many excellent and comprehensive books [4-29] and general review articles [30-70], The reference list gives only the most prominent and best known reviews. Additional and highly recommendable information sources for the synthetic chemist are the Warwick Biotransformation Abstracts and the associated electronic database. Contact address H.G. Crout, Warwick Biotransformation Club Database, Organic Chemical Institute, University of Warwick, UK (service for members only). The two CD-ROMs Biotransformation (K. Kieslich and the Warwick Biotransformation Club) and BioCatalysis (H.L. Holland and B. Jones) are available from Chapman Hall (London, 1996). Practical examples for preparative biotransformations (with checked procedures)... 

According to the Warwick Biotransformation Club Database in 1987/88 [60], approximately 65% of all applications reported fell into the classes of esterolytic reactions (ester hydrolysis, synthesis or transesterification) (40%) and dehydrogenase reactions (25%). Next in importance were oxygenase-mediated reactions, peptide and oligosaccharide synthesis, which together comprise 24% of the total. Reports of enzymatic procedures for carbon-carbon bond formation were very few in number (2%). All other reaction types comprised less than 10% of the total. 

The exposure-related physico-chemical properties of phenol were estimated according to the methods in Chapter 4. The estimates were mostly obtained from general models, except for soil sorption and biotransformation for which QSARs for polar non-reactive aromatics were applied. Overall, there is good agreement between the calculated data and the experimental data taken from databases (Table 9.1). 

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