Kavraki, Lydia E.2019-05-162019-05-162019-052019-03-06May 2019Kim, Sarah Michelle. "Precomputation and Visualization of Metabolic Pathways." (2019) Diss., Rice University. <a href="https://hdl.handle.net/1911/105385">https://hdl.handle.net/1911/105385</a>.https://hdl.handle.net/1911/105385Advances in metabolic engineering have led to the development of alternative, renewable methods for producing chemicals that are traditionally challenging to obtain. The rapid growth of available knowledge on metabolic processes across thousands of species continues to expand the possibilities of chemicals that can be produced with metabolic engineering. However, manually searching through the tens of thousands of possible enzymatic reactions for promising metabolic pathways has become increasingly difficult. Over the past two decades, several computational search algorithms have been developed for automating the identification of novel metabolic pathways. Even so, these searches may return thousands of pathway results presented in a way that is tedious to sift through. Although there are a large number of possible compounds and reactions to include in metabolic pathways, a smaller subset of core reaction “modules” may be repeatedly incorporated into pathways across multiple searches. To reduce the resources spent on searching the same metabolic space, a new meta-algorithm for metabolic pathfinding, Hub Pathway Search with Atom Tracking (HPAT), was developed as a first step to take advantage of a precomputed network of subpath modules. The result pathways are visualized as a single interactive graph, allowing the users to filter pathways based on a collection of pathway features. The modularity of pathways is also exploited in visualization to organize pathways in a more concise way. A test set of nineteen known pathways taken from literature and metabolic databases was used to evaluate if HPAT was capable of identifying known pathways. HPAT found the exact pathway for eleven of the nineteen test cases using a diverse set of precomputed subpaths, whereas a comparable pathfinding search algorithm that does not use precomputed subpaths found only seven of the nineteen test cases. The capability of HPAT to find novel pathways was demonstrated by its ability to identify novel 3-hydroxypropanoate (3-HP) synthesis pathways. As for pathway visualization, the new interactive pathway filters enable a reduction of the number of displayed pathways from hundreds down to less than ten pathways in several test cases, illustrating the utility of these filters in reducing the amount of displayed information. This work presents the first step in incorporating a precomputed subpath network into metabolic pathfinding and providing a concise, interactive visualization of pathway results. The modular nature of metabolic pathways is exploited to facilitate efficient discovery of alternate pathways.application/pdfengCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.Metabolic pathfindingprecomputationmetabolic engineeringgraph searchatom trackingmetabolic pathwaysThesis2019-05-16