Ayoun Cho

Prediction of novel synthetic pathways for the production of desired chemicals

BackgroundThere have been several methods developed for the prediction of synthetic metabolic pathways leading to the production of desired chemicals. In these approaches, novel pathways were predicted based on chemical structure changes, enzymatic information, and/or reaction mechanisms, but the approaches generating a huge number of predicted results are difficult to be applied to real experiments. Also, some of these methods focus on specific pathways, and thus are limited to expansion to the whole metabolism.ResultsIn the present study, we propose a system framework employing a retrosynthesis model with a prioritization scoring algorithm. This new strategy allows deducing the novel promising pathways for the synthesis of a desired chemical together with information on enzymes involved based on structural changes and reaction mechanisms present in the system database. The prioritization scoring algorithm employing Tanimoto coefficient and group contribution method allows examination of structurally qualified pathways to recognize which pathway is more appropriate. In addition, new concepts of binding site covalence, estimation of pathway distance and organism specificity were taken into account to identify the best synthetic pathway. Parameters of these factors can be evolutionarily optimized when a newly proven synthetic pathway is registered. As the proofs of concept, the novel synthetic pathways for the production of isobutanol, 3-hydroxypropionate, and butyryl-CoA were predicted. The prediction shows a high reliability, in which experimentally verified synthetic pathways were listed within the top 0.089% of the identified pathway candidates.ConclusionsIt is expected that the system framework developed in this study would be useful for the in silico design of novel metabolic pathways to be employed for the efficient production of chemicals, fuels and materials.

WebCell: An Integrated Environment For Modeling and Simulation of Cellular Networks Online

Various softwares and computational environments have been developed as listed in the systems biology community (http://sbml.org). Nevertheless, only a handful of projects adopt the platform-independent Web-based approach which is a desirable direction for simulation research and development. To this end, we developed WebCell which is an integrated simulation environment for managing information on cellular networks, and for interactively exploring their steady-state and dynamic behaviors over the Web. A user friendly Web interface allows users to efficiently create, visualize, simulate and store their reaction network models, thereby facilitating kinetic modeling and simulation of biological systems of interest. Supported analysis methods for such models include structural pathway analysis, metabolic control analysis, conservation analysis and time-course simulation. In addition, a variety of model collections publicly available have been compiled to provide comprehensive implications for cellular dynamics of the models. Thus, this comprehensive, Web-accessible and integrative system not only serves the educational demonstration site of publicly available kinetic models but also provides the customized modeling environment for quantitatively and qualitatively analyzing the cellular system

WebCell-script: A web-based script for managing quantitative and qualitative information of cellular networks

WebCell, the integrative program for modeling and simulation of cellular networks, is based on the user-friendly Web environment. It is available at anytime, anywhere. This environment, however, has some constraints. For instance, the data format is limited. In addition, the user-interface is not really flexible. These problems can be solved with simple object access protocol (SOAP). It offers many useful functions - especially extensibility and fast response. We have been developing the WebCell-script, an add-in module for WebCell, using this technology. This also can handle many user-defined analyses independently. It is expected to contribute to developing models and analyzing pathway networks under various conditions through the advanced in silico experiments

Quantitative Analysis of Biological Models under the Internet Environment

The computational modeling and simulation of complex biological systems are indispensable for new knowledge extraction from huge experimental data and ever growing vast amount of information in systems biology. Moreover, gathering and sharing of the existing information and newly-generated knowledge can speed up this research process. In this regard, several modeling projects have been undertaken for quantitatively analyzing the biological systems via the internet. They include Virtual Cell, JWS and OBIYagns. We also develop an integrated web-based environment, which facilitate investigation of dynamic behavior of cellular systems.