MolTarPred: A web tool for comprehensive target prediction with reliability estimation

Peón, Antonio; Li, Hongjian; Ghislat, Ghita; Leung, Kwong‐Sak; Wong, Man‐Hon; Lü, Gang; Ballester, Pedro J.

doi:10.1111/cbdd.13516

Cited by 33 publications

(23 citation statements)

References 46 publications

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“…Computational methods are now being actively investigated as tools for identifying new therapeutic targets for repurposed drugs. Here, we used a data‐driven predictive tool called moltarpred [27]. Briefly, moltarpred (http://moltarpred.marseille.inserm.fr/) is a freely available web tool for predicting protein targets of small organic molecules.…”

Section: Resultsmentioning

confidence: 99%

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In silico molecular target prediction unveils mebendazole as a potent MAPK14 inhibitor

et al. 2020

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Section: Resultsmentioning

confidence: 99%

“… moltarpred ligand‐centric target prediction workflow. The most similar database molecules to the query molecule (mebendazole) are identified as previously detailed [27]. Known targets for these molecules are retrieved from the ChEMBL database.…”

Section: Resultsmentioning

confidence: 99%

In silico molecular target prediction unveils mebendazole as a potent MAPK14 inhibitor

et al. 2020

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“…The second group of potential targets of compound 7 was selected based on a consensus target fishing approach. For this, the potential targets of the compound were predicted with five publicly available target fishing services: MolTarPred [33], SwissTargetPrediction [34], Target-Net [35], SuperPred [36], and Similarity Ensemble Approach (SEA) [37]. Any Candida albicans protein predicted as a potential target by any target fishing method was selected for modeling studies.…”

Section: Molecular Dockingmentioning

confidence: 99%

Bioactivity and Molecular Docking Studies of Derivatives from Cinnamic and Benzoic Acids

Pérez-Castillo

Lima

Ferreira

et al. 2020

BioMed Research International

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Over the last decade, there has been a dramatic increase in the prevalence and gravity of systemic fungal diseases. This study aimed therefore at evaluating the antifungal potential of ester derivatives of benzoic and cinnamic acids from three Candida species. The compounds were prepared via Fischer esterification, and the antifungal assay was performed by the microdilution method in 96-well microplates for determining the minimal inhibitory concentrations (MICs). The findings of the antifungal tests revealed that the analogue compound methyl ferulate, methyl o-coumarate, and methyl biphenyl-3-carboxylate displayed an interesting antifungal activity against all Candida strains tested, with MIC values of 31.25-62.5, 62.5-125, and 62.5 μg/ml, respectively. A preliminary Structure-Activity Relationship study of benzoic and cinnamic acid derivatives has led to the recognition of some important structural requirements for antifungal activity. The results of molecular docking indicate that the presence of the enoate moiety along with hydroxyl and one methoxy substitution in the phenyl ring has a positive effect on the bioactivity of compound 7 against Candida albicans. These observations further support the hypothesis that the antifungal activity of compound 7 could be due to its binding to multiple targets, specifically to QR, TS, and ST-PK. Additional experiments are required in the future to test this hypothesis and to propose novel compounds with improved antifungal activity.

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“…To identify new therapeutic targets for MBZ, we used a data-driven predictive tool called MolTarPred [20]. Briefly, MolTarPred (http://moltarpred.marseille.inserm.fr/) is a freelyavailable web tool for predicting protein targets of small organic molecules.…”

Section: In Silico Target Prediction Suggests Multiple Novel Moleculamentioning

confidence: 99%

In silicomolecular target prediction unveils mebendazole as a potent MAPK14 inhibitor

Ariey-Bonnet

Carrasco

Grand

et al. 2020

Preprint

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The concept of polypharmacology involves the interaction of drug molecules with multiple molecular targets. It provides a unique opportunity for the repurposing of already-approved drugs to target key factors involved in human diseases. Herein, we used an in silico target prediction algorithm to investigate the mechanism of action of mebendazole, an antihelminthic drug, currently repurposed in the treatment of brain tumors. First, we confirmed that mebendazole decreased the viability of glioblastoma cells in vitro. Our in silico approach unveiled 21 putative molecular targets for mebendazole, including 12 proteins significantly up-regulated at the gene level in glioblastoma as compared to normal brain tissue. Validation experiments were performed on three major kinases involved in cancer biology: ABL1, MAPK1/ERK2 and MAPK14/p38α. Mebendazole could inhibit the activity of these kinases in vitro in a dose-dependent manner, with a high potency against MAPK14. Its direct binding to MAPK14 was further validated in vitro and inhibition of MAPK14 kinase activity was confirmed in live glioblastoma cells. Consistent with biophysical data, molecular modeling suggested that mebendazole was able to bind to the catalytic site of MAPK14. Finally, gene silencing demonstrated that MAPK14 is involved in glioblastoma tumor spheroid growth and response to mebendazole treatment. This study thus highlighted the role of MAPK14 in the anticancer mechanism of action of mebendazole and provides further rationale for the pharmacological targeting of MAPK14 in brain tumors. It also opens new avenues for the development of novel MAPK14/p38α inhibitors to treat human diseases. Significance StatementThis study provides a framework to investigate drug polypharmacology by rapidly identifying novel molecular targets of already-approved drugs. It unveils a new mechanism involved in the anticancer activity of anti-helminthic drug, mebendazole, which is currently being repurposed for the treatment of brain tumors. By helping to decipher the mechanism(s) of action of repurposed drugs in their new indications, this approach could contribute to the development of safer and more effective therapeutic strategies in oncology and beyond.

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MolTarPred: A web tool for comprehensive target prediction with reliability estimation

Cited by 33 publications

References 46 publications

In silico molecular target prediction unveils mebendazole as a potent MAPK14 inhibitor

In silico molecular target prediction unveils mebendazole as a potent MAPK14 inhibitor

Bioactivity and Molecular Docking Studies of Derivatives from Cinnamic and Benzoic Acids

In silicomolecular target prediction unveils mebendazole as a potent MAPK14 inhibitor

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