Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States
Daniel J Wichelecki
Institute for Genomic Biology, University of Illinois, Urbana, United States; Department of Biochemistry, University of Illinois, Urbana, United States; Department of Chemistry, University of Illinois, Urbana, United States
Brian San Francisco
Institute for Genomic Biology, University of Illinois, Urbana, United States
Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States
Dmitry A Rodionov
Sanford Burnham Prebys Medical Discovery Institute, La Jolla, United States; A.A. Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, Russia
Matthew W Vetting
Department of Biochemistry, Albert Einstein College of Medicine, New York, United States
Nawar F Al-Obaidi
Department of Biochemistry, Albert Einstein College of Medicine, New York, United States
Henry Lin
Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States
Matthew J O'Meara
Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States
David A Scott
Sanford Burnham Prebys Medical Discovery Institute, La Jolla, United States
John H Morris
Resource for Biocomputing, Visualization and Informatics, Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States
Daniel Russel
Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, United States
Steven C Almo
Department of Biochemistry, Albert Einstein College of Medicine, New York, United States
Andrei L Osterman
Sanford Burnham Prebys Medical Discovery Institute, La Jolla, United States
John A Gerlt
Institute for Genomic Biology, University of Illinois, Urbana, United States; Department of Biochemistry, University of Illinois, Urbana, United States; Department of Chemistry, University of Illinois, Urbana, United States
Matthew P Jacobson
Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States
Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, United States; Department of Pharmaceutical Chemistry, University of California, San Francisco, San Francisco, United States; California Institute for Quantitative Biosciences, University of California, San Francisco, San Francisco, United States
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.
