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Sökning: onr:"swepub:oai:DiVA.org:kth-290066" > Toward a Computatio...

Toward a Computational Ecotoxicity Assay

Kamerlin, Natasha (författare)
Uppsala universitet,Science for Life Laboratory, SciLifeLab,Institutionen för cell- och molekylärbiologi
Delcey, Mickaël G (författare)
Uppsala universitet,Teoretisk kemi
Manzetti, Sergio (författare)
Fjordforsk A/S,David van der Spoel
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Van der Spoel, David (författare)
Uppsala universitet,Science for Life Laboratory, SciLifeLab,Beräkningsbiologi och bioinformatik
visa färre...
 (creator_code:org_t)
2020-07-10
2020
Engelska.
Ingår i: Journal of Chemical Information and Modeling. - : American Chemical Society (ACS). - 1549-9596 .- 1549-960X. ; 60:8, s. 3792-3803
  • Tidskriftsartikel (refereegranskat)
Abstract Ämnesord
Stäng  
  • Thousands of anthropogenic chemicals are released into the environment each year, posing potential hazards to human and environmental health. Toxic chemicals may cause a variety of adverse health effects, triggering immediate symptoms or delayed effects over longer periods of time. It is thus crucial to develop methods that can rapidly screen and predict the toxicity of chemicals to limit the potential harmful impacts of chemical pollutants. Computational methods are being increasingly used in toxicity predictions. Here, the method of molecular docking is assessed for screening potential toxicity of a variety of xenobiotic compounds, including pesticides, pharmaceuticals, pollutants, and toxins derived from the chemical industry. The method predicts the binding energy of pollutants to a set of carefully selected receptors under the assumption that toxicity in many cases is related to interference with biochemical pathways. The strength of the applied method lies in its rapid generation of interaction maps between potential toxins and the targeted enzymes, which could quickly yield molecular-level information and insight into potential perturbation pathways, aiding in the prioritization of chemicals for further tests. Two scoring functions are compared: Autodock Vina and the machine-learning scoring function RF-Score-VS. The results are promising, although hampered by the accuracy of the scoring functions. The strengths and weaknesses of the docking protocol are discussed, as well as future directions for improving the accuracy for the purpose of toxicity predictions.

Ämnesord

NATURVETENSKAP  -- Kemi -- Teoretisk kemi (hsv//swe)
NATURAL SCIENCES  -- Chemical Sciences -- Theoretical Chemistry (hsv//eng)
NATURVETENSKAP  -- Geovetenskap och miljövetenskap -- Miljövetenskap (hsv//swe)
NATURAL SCIENCES  -- Earth and Related Environmental Sciences -- Environmental Sciences (hsv//eng)

Nyckelord

xenobiotic
docking
pollutant
assay
computational

Publikations- och innehållstyp

ref (ämneskategori)
art (ämneskategori)

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