NetControl4BioMed: a web-based platform for controllability analysis of protein–protein interaction networks

Abstract

Motivation There is an increasing amount of data coming from genome-wide studies identifying disease-specific survivability-essential proteins and host factors critical to a cell becoming infected. Targeting such proteins has a strong potential for targeted, precision therapies. Typically however, too few of them are drug targetable. An alternative approach is to influence them through drug targetable proteins upstream of them. Structural target network controllability is a suitable solution to this problem. It aims to discover suitable source nodes (e.g., drug targetable proteins) in a directed interaction network that can control (through a suitable set of input functions) a desired set of targets. Results We introduce NetControl4BioMed, a free open-source web-based application that allows users to generate or upload directed protein-protein interaction networks and to perform target structural network controllability analyses on them. The analyses can be customized to focus the search on drug targetable source nodes, thus providing drug therapeutic suggestions. The application integrates protein data from HGNC, Ensemble, UniProt, NCBI, and InnateDB, directed interaction data from InnateDB, Omnipath, and SIGNOR, cell-line data from COLT and DepMap, and drug-target data from DrugBank. Availability The application and data are available online at https://netcontrol.combio.org/. The source code is available at https://github.com/Vilksar/NetControl4BioMed under an MIT license.

Network analytics for drug repurposing in COVID-19

“…For each network, we repeated the analysis until three consecutive runs identified no new drugs. The analyses were run on the NetControl4BioMed platform ( [7]).…”

“…We used the NetControl4BioMed web application ( [7]) to apply the target controllability analysis on the two generated networks using the greedy algorithm described in [69]. The analysis setup is the same in both cases: we use the set of host factors in each network as controllability targets and we aim on identifying a minimal set of proteins that control the host factors, while maximizing the number of drugtarget proteins among them.…”

“…We also included the top 200 host factors required for SARS-CoV-2 infection found by [3] for viral loads MOI 0.01 and MOI 0.3, and all protein-protein directed interactions from KEGG, OmniPath and Signor. Using the NetControl4BioMed platform ( [7]) we identified all the control paths of length at most 3 from drug targets to the host factors. We ranked the drugs based on the number of host factors they can control through any of their targets.…”