=Paper=
{{Paper
|id=Vol-1795/paper38
|storemode=property
|title=Finding Drugs with Common Downstream Effects, Using Direction Information in Biological Pathways
|pdfUrl=https://ceur-ws.org/Vol-1795/paper38.pdf
|volume=Vol-1795
|authors=Ryan Miller,Jonathan Melius,Nuno Nunes,Egon Willighagen,Peter Woollard,Chris Evelo
|dblpUrl=https://dblp.org/rec/conf/swat4ls/MillerMNWWE16
}}
==Finding Drugs with Common Downstream Effects, Using Direction Information in Biological Pathways==
Finding drugs with common downstream effects,
using direction information in biological
pathways
Ryan A. Miller1 , Jonathan Melius1 , Nuno Nunes1 , Egon L. Willighagen1 , Peter
Woollard2 , and Chris T. Evelo1,3
1
Department of Bioinformatics - BiGCaT, NUTRIM,
Maastricht University, The Netherlands
2
Computational Biology, GlaxoSmithKline, Stevenage, UK.
3
Maastricht Centre for Systems Biology (MaCSBio),
Maastricht University, The Netherlands
Abstract. Drugs aim at compensating for a biological process or pro-
cesses that are not behaving as desired. Drugs frequently do this by bind-
ing to proteins in pathways, causing immediate or downstream changes in
the pathway affecting the biological process. WikiPathways is an open re-
source for curating biological pathways. Interactions in the pathway, cap-
ture information that connects biological entities. WikiPathways RDF
representation captures the participants of a specific interaction, the type
of interaction (inhibition, stimulation, catalysis, etc.), and also the direc-
tion of the interaction. The increasing availability of this directionality
enables answering a new class of research questions programmatically.
For instance, this knowledge can be used to show how a combination of
two drugs affects common downstream processes. This list of drug com-
binations with common downstream effects is important because drug
combination therapies may be used to minimize the side effects of single
drug treatments where higher doses need to be administered.
We will present work that answers this question by combining data from
WikiPathways, ChEMBL, and Uniprot. ChEMBL is used to extend the
knowledge base with drug data annotations linking drugs to protein tar-
gets in the pathway. While Uniprots endpoint is used to map ChEMBL
target information to Uniprot IDs. The interaction directional informa-
tion defines what is upstream and downstream in the pathway of the
protein targets. Analysis of the combined data results in a list of drug
combinations that share common downstream effects. The analysis was
implemented as a series of queries against the SPARQL endpoints of
ChEMBL, Uniprot, and WikiPathways.
Keywords: Semantic Web, biological pathways, network extension