Browse
Submit Data
Databases
API
Help

Dataset Information

17 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Predicting mechanism of action of novel compounds using compound structure and transcriptomic signature coembedding.

ABSTRACT:

Motivation

Identifying mechanism of actions (MoA) of novel compounds is crucial in drug discovery. Careful understanding of MoA can avoid potential side effects of drug candidates. Efforts have been made to identify MoA using the transcriptomic signatures induced by compounds. However, these approaches fail to reveal MoAs in the absence of actual compound signatures.

Results

We present MoAble, which predicts MoAs without requiring compound signatures. We train a deep learning-based coembedding model to map compound signatures and compound structure into the same embedding space. The model generates low-dimensional compound signature representation from the compound structures. To predict MoAs, pathway enrichment analysis is performed based on the connectivity between embedding vectors of compounds and those of genetic perturbation. Results show that MoAble is comparable to the methods that use actual compound signatures. We demonstrate that MoAble can be used to reveal MoAs of novel compounds without measuring compound signatures with the same prediction accuracy as that with measuring them.

Availability and implementation

MoAble is available at https://github.com/dmis-lab/moable.

Supplementary information

Supplementary data are available at Bioinformatics online.

SUBMITTER: Jang G

PROVIDER: S-EPMC8275331 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

MAVEN: compound mechanism of action analysis and visualisation using transcriptomics and compound structure data in R/Shiny.

Project description:BackgroundUnderstanding the Mechanism of Action (MoA) of a compound is an often challenging but equally crucial aspect of drug discovery that can help improve both its efficacy and safety. Computational methods to aid MoA elucidation usually either aim to predict direct drug targets, or attempt to understand modulated downstream pathways or signalling proteins. Such methods usually require extensive coding experience and results are often optimised for further computational processing, making them difficult for wet-lab scientists to perform, interpret and draw hypotheses from.ResultsTo address this issue, we in this work present MAVEN (Mechanism of Action Visualisation and Enrichment), an R/Shiny app which allows for GUI-based prediction of drug targets based on chemical structure, combined with causal reasoning based on causal protein-protein interactions and transcriptomic perturbation signatures. The app computes a systems-level view of the mechanism of action of the input compound. This is visualised as a sub-network linking predicted or known targets to modulated transcription factors via inferred signalling proteins. The tool includes a selection of MSigDB gene set collections to perform pathway enrichment on the resulting network, and also allows for custom gene sets to be uploaded by the researcher. MAVEN is hence a user-friendly, flexible tool for researchers without extensive bioinformatics or cheminformatics knowledge to generate interpretable hypotheses of compound Mechanism of Action.ConclusionsMAVEN is available as a fully open-source tool at https://github.com/laylagerami/MAVEN with options to install in a Docker or Singularity container. Full documentation, including a tutorial on example data, is available at https://laylagerami.github.io/MAVEN .

| S-EPMC10502988 | biostudies-literature

Antibacterial activity and mechanism of action of a novel anilinouracil-fluoroquinolone hybrid compound.

Project description:The anilinouracils (AUs) such as 6-(3-ethyl-4-methylanilino)uracil (EMAU) are a novel class of gram-positive, selective, bactericidal antibacterials which inhibit pol IIIC, the gram-positive-specific replicative DNA polymerase. We have linked various fluoroquinolones (FQs) to the N-3 position of EMAU to generate a variety of AU-FQ "hybrids" offering the potential for targeting two distinct steps in DNA replication. In this study, the properties of a hybrid, "251D," were compared with those of representative AUs and FQs in a variety of in vitro assays, including pol IIIC and topoisomerase/gyrase enzyme assays, antibacterial, bactericidal, and mammalian cytotoxicity assays. Compound 251D potently inhibited pol IIIC and topoisomerase/gyrase, displayed gram-positive antibacterial potency at least 15 times that of the corresponding AU compound, and as expected, acted selectively on bacterial DNA synthesis. Compound 251D was active against a broad panel of antibiotic-resistant gram-positive pathogens as well as several gram-negative organisms and was also active against both AU- and FQ-resistant gram-positive organisms, demonstrating its capacity for attacking both of its potential targets in the bacterium. 251D also was bactericidal for gram-positive organisms and lacked toxicity in vitro. Although we obtained strains of Staphylococcus aureus resistant to the individual parent compounds, spontaneous resistance to 251D was not observed. We obtained 251D resistance in multiple-passage experiments, but resistance developed at a pace comparable to those for the parent compounds. This class of AU-FQ hybrids provides a promising new pharmacophore with an unusual dual mechanism of action and potent activity against antibiotic-sensitive and -resistant gram-positive pathogens.

| S-EPMC1797695 | biostudies-literature

Mechanism of action of a pestivirus antiviral compound.

Project description:We report here the discovery of a small molecule inhibitor of pestivirus replication. The compound, designated VP32947, inhibits the replication of bovine viral diarrhea virus (BVDV) in cell culture at a 50% inhibitory concentration of approximately 20 nM. VP32947 inhibits both cytopathic and noncytopathic pestiviruses, including isolates of BVDV-1, BVDV-2, border disease virus, and classical swine fever virus. However, the compound shows no activity against viruses from unrelated virus groups. Time of drug addition studies indicated that VP32947 acts after virus adsorption and penetration and before virus assembly and release. Analysis of viral macromolecular synthesis showed VP32947 had no effect on viral protein synthesis or polyprotein processing but did inhibit viral RNA synthesis. To identify the molecular target of VP32947, we isolated drug-resistant (DR) variants of BVDV-1 in cell culture. Sequence analysis of the complete genomic RNA of two DR variants revealed a single common amino acid change located within the coding region of the NS5B protein, the viral RNA-dependent RNA polymerase. When this single amino acid change was introduced into an infectious clone of drug-sensitive wild-type (WT) BVDV-1, replication of the resulting virus was resistant to VP32947. The RNA-dependent RNA polymerase activity of the NS5B proteins derived from WT and DR viruses expressed and purified from recombinant baculovirus-infected insect cells confirmed the drug sensitivity of the WT enzyme and the drug resistance of the DR enzyme. This work formally validates NS5B as a target for antiviral drug discovery and development. The utility of VP32947 and similar compounds for the control of pestivirus diseases, and for hepatitis C virus drug discovery efforts, is discussed.

| S-EPMC16656 | biostudies-literature

Predicting the in vivo mechanism of action for drug leads using NMR metabolomics.

Project description:New strategies are needed to circumvent increasing outbreaks of resistant strains of pathogens and to expand the dwindling supply of effective antimicrobials. A common impediment to drug development is the lack of an easy approach to determine the in vivo mechanism of action and efficacy of novel drug leads. Toward this end, we describe an unbiased approach to predict in vivo mechanisms of action from NMR metabolomics data. Mycobacterium smegmatis, a non-pathogenic model organism for Mycobacterium tuberculosis, was treated with 12 known drugs and 3 chemical leads identified from a cell-based assay. NMR analysis of drug-induced changes to the M. smegmatis metabolome resulted in distinct clustering patterns correlating with in vivo drug activity. The clustering of novel chemical leads relative to known drugs provides a mean to identify a protein target or predict in vivo activity.

| S-EPMC3262886 | biostudies-literature

Elucidating Compound Mechanism of Action by Network Perturbation Analysis.

Project description:Genome-wide identification of the mechanism of action (MoA) of small-molecule compounds characterizing their targets, effectors, and activity modulators represents a highly relevant yet elusive goal, with critical implications for assessment of compound efficacy and toxicity. Current approaches are labor intensive and mostly limited to elucidating high-affinity binding target proteins. We introduce a regulatory network-based approach that elucidates genome-wide MoA proteins based on the assessment of the global dysregulation of their molecular interactions following compound perturbation. Analysis of cellular perturbation profiles identified established MoA proteins for 70% of the tested compounds and elucidated novel proteins that were experimentally validated. Finally, unknown-MoA compound analysis revealed altretamine, an anticancer drug, as an inhibitor of glutathione peroxidase 4 lipid repair activity, which was experimentally confirmed, thus revealing unexpected similarity to the activity of sulfasalazine. This suggests that regulatory network analysis can provide valuable mechanistic insight into the elucidation of small-molecule MoA and compound similarity.

| S-EPMC4506491 | biostudies-literature

In vivo analysis of compound activity and mechanism of action using epistasis in Drosophila.

Project description:The recent establishment of high-throughput methods for culturing Drosophila provided a unique ability to screen compound libraries against complex disease phenotypes in the context of whole animals. However, as compound studies in Drosophila have been limited so far, the degree of conservation of compound activity between Drosophila and vertebrates or the effectiveness of feeding as a compound delivery system is not well known. Our comprehensive in vivo analysis of 27 small molecules targeting seven signaling pathways in Drosophila revealed a high degree of conservation of compound activity between Drosophila and vertebrates. We also investigated the mechanism of action of AY9944, one of the Hh pathway antagonists that we identified in our compound feeding experiments. Our epistasis analysis of AY9944 provided novel insights into AY9944's mechanism of action and revealed a novel role for cholesterol transport in Hh signal transduction.The online version of this article (doi:10.1007/s12154-010-0051-5) contains supplementary material, which is available to authorized users.

| S-EPMC3077214 | biostudies-other

Structure and mechanism of action of a novel phosphoglycerate mutase from Bacillus stearothermophilus.

Project description:Bacillus stearothermophilus phosphoglycerate mutase (PGM), which interconverts 2- and 3-phosphoglyceric acid (PGA), does not require 2,3-diphosphoglyceric acid for activity. However, this enzyme does have an absolute and specific requirement for Mn(2+) ions for catalysis. Here we report the crystal structure of this enzyme complexed with 3PGA and manganese ions to 1.9 A resolution; this is the first crystal structure of a diphosphoglycerate-independent PGM to be determined. This information, plus the location of the two bound Mn(2+) ions and the 3PGA have allowed formulation of a possible catalytic mechanism for this PGM. In this mechanism Mn(2+) ions facilitate the transfer of the substrate's phosphate group to Ser62 to form a phosphoserine intermediate. In the subsequent phosphotransferase part of the reaction, the phosphate group is transferred from Ser62 to the O2 or O3 positions of the reoriented glycerate to yield the PGA product. Site-directed mutagenesis studies were used to confirm our mechanism and the involvement of specific enzyme residues in Mn(2+) binding and catalysis.

| S-EPMC313928 | biostudies-literature

Mechanism of Action of the Sesquiterpene Compound Helenalin in Rhabdomyosarcoma Cells.

Project description:Rhabdomyosarcoma (RMS) is the most frequent soft tissue sarcoma in paediatric patients. Relapsed or refractory RMS shows very low 5-year survival rates, which urgently necessitates new chemotherapy agents. Herein, the sesquiterpene lactone, helenalin, was investigated as a new potential therapeutic agent against the embryonal RMS (eRMS) and alveolar RMS (aRMS) cells. We have evaluated in vitro antiproliferative efficacy of helenalin on RMS cells by the MTT and wound healing assay, and estimated several cell death pathways by flow cytometry, confocal microscopy and immunoblotting. It was shown that helenalin was able to increase reactive oxygen species levels, decrease mitochondrial membrane potential, trigger endoplasmic reticulum stress and deactivate the NF-κB pathway. Confirmation was obtained through the use of antagonistic compounds which alleviated the effects of helenalin in the corresponding pathways. Our findings demonstrate that oxidative stress is the pivotal mechanism of action of helenalin in promoting RMS cell death in vitro.

| S-EPMC8703838 | biostudies-literature

Deciphering the mechanism of action of antitubercular compounds with metabolomics.

Project description:Tuberculosis (TB), one of the oldest and deadliest bacterial diseases, continues to cause serious global economic, health, and social problems. Current TB treatments are lengthy, expensive, and routinely ineffective against emerging drug resistant strains. Thus, there is an urgent need for the identification and development of novel TB drugs possessing comprehensive and specific mechanisms of action (MoAs). Metabolomics is a valuable approach to elucidating the MoA, toxicity, and potency of promising chemical leads, which is a critical step of the drug discovery process. Recent advances in metabolomics methodologies for deciphering MoAs include high-throughput screening techniques, the integration of multiple omics methods, mass spectrometry imaging, and software for automated analysis. This review describes recently introduced metabolomics methodologies and techniques for drug discovery, highlighting specific applications to the discovery of new antitubercular drugs and the elucidation of their MoAs.

| S-EPMC8358470 | biostudies-literature

Unveiling the mechanism of action of nature-inspired anti-cancer compounds using a multi-Omics approach

Project description:MCF-7 breast cancer cells were treated with two novel anti-cancer compounds, SIMR_3058 and SIMR_3066, and the metabolome and proteome analysed by LC-MS/MS using a timsTOF.

2023-01-17 | PXD033257 | Pride

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data