학술논문

Prediction of enzymatic pathways by integrative pathway mapping.
Document Type
article
Source
Subject
biophysics
computational biology
enzyme function annotation
integrative pathway mapping
l-gulonate catabolic pathway
none
pathway prediction
structural biology
structure based pathway discovery
systems biology
Computational Biology
Enzymes
Haemophilus influenzae
Metabolic Networks and Pathways
Systems Biology
Language
Abstract
The functions of most proteins are yet to be determined. The function of an enzyme is often defined by its interacting partners, including its substrate and product, and its role in larger metabolic networks. Here, we describe a computational method that predicts the functions of orphan enzymes by organizing them into a linear metabolic pathway. Given candidate enzyme and metabolite pathway members, this aim is achieved by finding those pathways that satisfy structural and network restraints implied by varied input information, including that from virtual screening, chemoinformatics, genomic context analysis, and ligand -binding experiments. We demonstrate this integrative pathway mapping method by predicting the L-gulonate catabolic pathway in Haemophilus influenzae Rd KW20. The prediction was subsequently validated experimentally by enzymology, crystallography, and metabolomics. Integrative pathway mapping by satisfaction of structural and network restraints is extensible to molecular networks in general and thus formally bridges the gap between structural biology and systems biology.