2015
DOI: 10.1016/j.toxlet.2014.09.004
|View full text |Cite
|
Sign up to set email alerts
|

OpenVirtualToxLab—A platform for generating and exchanging in silico toxicity data

Abstract: The VirtualToxLab is an in silico technology for estimating the toxic potential--endocrine and metabolic disruption, some aspects of carcinogenicity and cardiotoxicity--of drugs, chemicals and natural products. The technology is based on an automated protocol that simulates and quantifies the binding of small molecules towards a series of currently 16 proteins, known or suspected to trigger adverse effects: 10 nuclear receptors (androgen, estrogen α, estrogen β, glucocorticoid, liver X, mineralocorticoid, pero… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1

Citation Types

2
80
0

Year Published

2015
2015
2023
2023

Publication Types

Select...
5
2
1

Relationship

1
7

Authors

Journals

citations
Cited by 103 publications
(82 citation statements)
references
References 52 publications
2
80
0
Order By: Relevance
“…The VirtualToxLab is an in silico technology for estimating the toxic potential-endocrine and metabolic disruption, some aspects of carcinogenicity and cardiotoxicity-of drugs, chemicals, and natural products [ 11 ]. The technology is based on an automated protocol that simulates and quantifi es the binding of small molecules toward a series of currently 16 proteins, known or suspected to trigger adverse effects: ten nuclear receptors (androgen, estrogen α, estrogen β, glucocorticoid, liver X, mineralocorticoid, peroxisome proliferator-activated receptor γ, progesterone, thyroid α, thyroid β), four members of the cytochrome P450 enzyme family (1A2, 2C9, 2D6, 3A4), a cytosolic transcription factor (aryl hydrocarbon receptor) and a potassium ion channel (hERG).…”
Section: Scoring Posesmentioning
confidence: 99%
“…The VirtualToxLab is an in silico technology for estimating the toxic potential-endocrine and metabolic disruption, some aspects of carcinogenicity and cardiotoxicity-of drugs, chemicals, and natural products [ 11 ]. The technology is based on an automated protocol that simulates and quantifi es the binding of small molecules toward a series of currently 16 proteins, known or suspected to trigger adverse effects: ten nuclear receptors (androgen, estrogen α, estrogen β, glucocorticoid, liver X, mineralocorticoid, peroxisome proliferator-activated receptor γ, progesterone, thyroid α, thyroid β), four members of the cytochrome P450 enzyme family (1A2, 2C9, 2D6, 3A4), a cytosolic transcription factor (aryl hydrocarbon receptor) and a potassium ion channel (hERG).…”
Section: Scoring Posesmentioning
confidence: 99%
“…Some of these limitations can be overcome by developing models for which the starting point is not the ligand but the receptor. An understanding of the receptor conformation and the molecular interactions required for a ligand to bind with the receptor can allow the development of flexible docking approaches which can better describe the subtleties of the MIE (D'Ursi et al, 2005;Vedani et al, 2014). Although more complex than traditional QSAR and pharmacophore models, these approaches do hold promise for generating data which are more biologically relevant.…”
Section: Develop High Content In Vitro Assays In Human Cells and Modementioning
confidence: 99%
“…biograf.ch/index.php?id=projects&subid=virtualtoxlab), which uses an automated protocol that simulates and quantifies the binding of molecules with 16 target proteins, comprising 10 nuclear receptors (AR, oestrogen receptor (ER)α, ERβ, glucocorticoid, liver X, mineralocorticoid, peroxisome proliferator-activated receptor γ, progesterone, thyroid α, and thyroid β), four cytochrome P450 enzymes (1A2, 2C9, 2D6, and 3A4), the aryl hydrocarbon receptor and the hERG potassium ion channel (Vedani et al, 2014).…”
Section: Develop High Content In Vitro Assays In Human Cells and Modementioning
confidence: 99%
See 1 more Smart Citation
“…For instance, nuclear receptors are common targets for a number of drug molecules and could be, in the same way, affected by the interaction with food or food-like molecules. Thus, key computational medicinal chemistry methods like molecular dynamics can be used to decipher protein flexibility and to obtain stable models for docking and scoring in food-related studies, and virtual screening is increasingly being applied to identify molecules with potential to act as endocrine disruptors, food mycotoxins, and new nutraceuticals [3][4][5]. All of these methods and simulations are based on protein-ligand interaction phenomena, and represent the basis for any subsequent modification of the targeted receptor's or enzyme's physiological activity.…”
mentioning
confidence: 99%