Chemical equation balancer science tools

#Chemical equation balancer science tools manual
#Chemical equation balancer science tools software

The best performing algorithm was used to predict atom mappings for the latest version of the human metabolic reconstruction, Recon 3D. Of the manually curated atom mappings, 340 were obtained from the BioPath database and 172 additional reactions were manually curated to ensure that we could compare predictions with representative reaction types from all six top level EC numbers (see Additional file 1: Table 1S). We also compared these predictions with manually curated atom mappings for a set of 512 human metabolic reactions. We compare their predictions for more than five thousand metabolic reactions in the latest human metabolic reconstruction, Recon 3D.

It is fortunate that many atom mapping algorithms have been developed, but which is most suited to predict atom mappings for a genome-scale metabolic network reconstruction? Here, we evaluate six recently published atom mapping algorithms. It is envisaged that this reconstruction and the models derived from it will drive deeper understanding how biochemical processes relate to mechanisms at the atomic scale. Recon 3D is the latest human metabolic reconstruction, that adds three dimensional metabolite and protein structures to a genome-scale reconstruction for the first time.

#Chemical equation balancer science tools software

This situation has driven the development of a range of software tools that seek to automate parts of the process to generate reconstruction content, e.g.

#Chemical equation balancer science tools manual

Manual curation reconstructions involves extensive literature review and sometimes sufficient experimental literature is not in existence. These models are then used in a wide range of biological, biotechnological and biomedical research scenarios. Such reconstructions form the basis for the development of condition-specific metabolic models whose functions are simulated and validated by comparison with experimental results.

Other metabolic databases such as EC-BLAST MetaCyc and MetRxn include predicted atom mappings.ДЄ genome-scale metabolic reconstruction is a structured knowledge-base that abstracts pertinent information on the biochemical transformations taking place within an organism. To our knowledge, only the BioPath and KEGG RPAIR databases disseminate manually curated atom mappings. In addition to prediction accuracy, we found that software accessibility and advanced features were fundamental to the selection of an atom mapping algorithm in practice.Дue to the time consuming nature of manual curation of atom mapping, it is of great importance to have reliable algorithms to predict atom mappings, especially for large sets of reactions found in metabolic databases and genome-scale metabolic network reconstructions. In addition to prediction accuracy, the algorithms were evaluated on their accessibility, their advanced features, such as the ability to identify equivalent atoms, and their ability to map hydrogen atoms. On average, the accuracy of the prediction was highest for reactions catalysed by oxidoreductases and lowest for reactions catalysed by ligases. Five of the evaluated algorithms had similarly high prediction accuracy of over 91% when compared to manually curated atom mapped reactions. We also compared these predictions to those obtained by manual curation of atom mappings for over five hundred reactions distributed among all top level Enzyme Commission number classes. How do their predictions compare to each other and to manually curated atom mappings? For more than four thousand metabolic reactions in the latest human metabolic reconstruction, Recon 3D, we compared the atom mappings predicted by six atom mapping algorithms. However, many algorithms exist to predict atom mappings. Complete manual acquisition of atom mapping data for a genome-scale metabolic network is a laborious process. However, a more detailed representation at the underlying level of atom mappings opens the possibility for a broader range of biological, biomedical and biotechnological applications than with stoichiometry alone. Genome-scale metabolic network reconstructions typically represent biochemistry at the level of reaction stoichiometry.

The mechanism of each chemical reaction in a metabolic network can be represented as a set of atom mappings, each of which relates an atom in a substrate metabolite to an atom of the same element in a product metabolite.