Open MoA: Revealing the Mechanism of Action (MoA) Based on Network Topology and Hierarchy

Overview

Journal Bioinformatics

Publisher Oxford University Press

Specialty Biology

Date 2023 Nov 6

PMID 37930015

Authors

Xinmeng Liao

Mehmet Ozcan

Mengnan Shi

Woonghee Kim

Han Jin

Xiangyu Li

Hasan Turkez

Adnane Achour

Mathias Uhlen

Adil Mardinoglu

Cheng Zhang

Affiliations

Soon will be listed here.

Abstract

Motivation: Many approaches in systems biology have been applied in drug repositioning due to the increased availability of the omics data and computational biology tools. Using a multi-omics integrated network, which contains information of various biological interactions, could offer a more comprehensive inspective and interpretation for the drug mechanism of action (MoA).

Results: We developed a computational pipeline for dissecting the hidden MoAs of drugs (Open MoA). Our pipeline computes confidence scores to edges that represent connections between genes/proteins in the integrated network. The interactions showing the highest confidence score could indicate potential drug targets and infer the underlying molecular MoAs. Open MoA was also validated by testing some well-established targets. Additionally, we applied Open MoA to reveal the MoA of a repositioned drug (JNK-IN-5A) that modulates the PKLR expression in HepG2 cells and found STAT1 is the key transcription factor. Overall, Open MoA represents a first-generation tool that could be utilized for predicting the potential MoA of repurposed drugs and dissecting de novo targets for developing effective treatments.

Availability And Implementation: Source code is available at https://github.com/XinmengLiao/Open_MoA.

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