Tools for in silico target fishing

Ceretó-Massagué, Adrià; Ojeda, María José; Valls, Cristina; Mulero, Miquel; Pujadas, Gerard; Garcı́a-Vallvé, Santiago

doi:10.1016/j.ymeth.2014.09.006

Cited by 126 publications

(111 citation statements)

References 70 publications

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“…Small molecules also interact with proteins involved in cellular signaling as well as other biomacromolecules such as nucleic acids. The interactions between small molecules and biomacromolecules are investigated with the use of software that relies on both bioinformatics and cheminformatics tools [59,60]. Discrimination between areas of interests of cheminformatics reflects tradition.…”

Section: Chemical and Biological Approachmentioning

confidence: 99%

Internet Databases of the Properties, Enzymatic Reactions, and Metabolism of Small Molecules—Search Options and Applications in Food Science

Minkiewicz

Darewicz

Iwaniak

et al. 2016

IJMS

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Internet databases of small molecules, their enzymatic reactions, and metabolism have emerged as useful tools in food science. Database searching is also introduced as part of chemistry or enzymology courses for food technology students. Such resources support the search for information about single compounds and facilitate the introduction of secondary analyses of large datasets. Information can be retrieved from databases by searching for the compound name or structure, annotating with the help of chemical codes or drawn using molecule editing software. Data mining options may be enhanced by navigating through a network of links and cross-links between databases. Exemplary databases reviewed in this article belong to two classes: tools concerning small molecules (including general and specialized databases annotating food components) and tools annotating enzymes and metabolism. Some problems associated with database application are also discussed. Data summarized in computer databases may be used for calculation of daily intake of bioactive compounds, prediction of metabolism of food components, and their biological activity as well as for prediction of interactions between food component and drugs.

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Section: Chemical and Biological Approachmentioning

confidence: 99%

Internet Databases of the Properties, Enzymatic Reactions, and Metabolism of Small Molecules—Search Options and Applications in Food Science

Minkiewicz

Darewicz

Iwaniak

et al. 2016

IJMS

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“…With the explosive increase of the available biologically annotated chemical database, it is now possible to predict the potential targets of query compounds with a relatively high hit rate. Recent published reports [21,23] have employed this method to successfully identify targets in their studies. Lounkine et al adopted a ‘Similarity Ensemble Approach’ to predict the activity of 656 marketed drugs on 73 unintended side-effect targets.…”

Section: Introductionmentioning

confidence: 99%

Discovery of a New Class of Cathepsin K Inhibitors in Rhizoma Drynariae as Potential Candidates for the Treatment of Osteoporosis

Qiu

Dong

Dai

et al. 2016

IJMS

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Rhizoma Drynariae (RD), as one of the most common clinically used folk medicines, has been reported to exert potent anti-osteoporotic activity. The bioactive ingredients and mechanisms that account for its bone protective effects are under active investigation. Here we adopt a novel in silico target fishing method to reveal the target profile of RD. Cathepsin K (Ctsk) is one of the cysteine proteases that is over-expressed in osteoclasts and accounts for the increase in bone resorption in metabolic bone disorders such as postmenopausal osteoporosis. It has been the focus of target based drug discovery in recent years. We have identified two components in RD, Kushennol F and Sophoraflavanone G, that can potentially interact with Ctsk. Biological studies were performed to verify the effects of these compounds on Ctsk and its related bone resorption process, which include the use of in vitro fluorescence-based Ctsk enzyme assay, bone resorption pit formation assay, as well as Receptor Activator of Nuclear factor κB (NF-κB) ligand (RANKL)-induced osteoclastogenesis using murine RAW264.7 cells. Finally, the binding mode and stability of these two compounds that interact with Ctsk were determined by molecular docking and dynamics methods. The results showed that the in silico target fishing method could successfully identify two components from RD that show inhibitory effects on the bone resorption process related to protease Ctsk.

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“…Target Fishing (TF) (Cereto-Massagué et al, 2015;Lavecchia and Cerchia, 2015), also known as Target Prediction or Polypharmacology Prediction, consists in predicting the macromolecular targets of a query molecule. This problem is the reverse of Virtual Screening (VS) (Schneider, 2010;Sukumar and Das, 2011), where the goal is to predict the ligands of a query target.…”

Section: Introductionmentioning

confidence: 99%

How reliable are ligand-centric methods for Target Fishing?

Peón

Dang

Ballester

2015

Preprint

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Computational methods for Target Fishing (TF), also known as Target Prediction or Polypharmacology Prediction, can be used to discover new targets for small-molecule drugs. This may result in repositioning the drug in a new indication or improving our current understanding of its efficacy and side effects. While there is a substantial body of research on TF methods, there is still a need to improve their validation, which is often limited to a small part of the available targets and not easily interpretable by the user. Here we discuss how target-centric TF methods are inherently limited by the number of targets that can possibly predict (this number is by construction much larger in ligand-centric techniques). We also propose a new benchmark to validate TF methods, which is particularly suited to analyse how predictive performance varies with the query molecule. On average over approved drugs, we estimate that only five predicted targets will have to be tested to find two true targets with submicromolar potency (a strong variability in performance is however observed). In addition, we find that an approved drug has currently an average of eight known targets, which reinforces the notion that polypharmacology is a common and strong event. Furthermore, with the assistance of a control group of randomly-selected molecules, we show that the targets of approved drugs are generally harder to predict. The benchmark and a simple target prediction method to use as a performance baseline are available at

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Tools for in silico target fishing

Cited by 126 publications

References 70 publications

Internet Databases of the Properties, Enzymatic Reactions, and Metabolism of Small Molecules—Search Options and Applications in Food Science

Internet Databases of the Properties, Enzymatic Reactions, and Metabolism of Small Molecules—Search Options and Applications in Food Science

Discovery of a New Class of Cathepsin K Inhibitors in Rhizoma Drynariae as Potential Candidates for the Treatment of Osteoporosis

How reliable are ligand-centric methods for Target Fishing?

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