Message-ID: <1847639079.195.1632427510547.JavaMail.bigchem@cpu> Subject: Exported From Confluence MIME-Version: 1.0 Content-Type: multipart/related; boundary="----=_Part_194_907979056.1632427510547" ------=_Part_194_907979056.1632427510547 Content-Type: text/html; charset=UTF-8 Content-Transfer-Encoding: quoted-printable Content-Location: file:///C:/exported.html OpenRiskNet services

OpenRiskNet services

A number of services to access OCHEM using Swagger UI were devel= oped as part of the Implementation Challenge of the https://openrisknet.= org/ project.

They API is accessible at http://rest.ochem.eu

The tools provide an access to several models, namely physico-chemical p= roperties (logP, melting point, water solubility), biological properties (B= CF - bio-concentration factor, the Human Ether-a-go-go-related Gene (hERG) = channel blockage, CYP1A2 inhibition) as well as  toxicity prediction (= multi-learning model), AMES  and  Lowest Effect Level (LOEL) as w= ell as environmental toxicity (T. pyriformis).  All models are part of= the OCHEM platform and for each model there is a link to its reference and= description in the respective publication at the OCHEM platform. The provi= ded model interface allows an interested user to submit a SMILES of the ana= lyzed compounds and retrieve prediction results. The predictions are perfor= med on the OCHEM web site.

When predicting a model, the user has to provide its ID as well as valid= SMILES.

Model ID is an integer value and list of models is accessible as, e.g.

curl -X GET "http://rest.ochem.eu/endpoint"

{
  "AMES toxicity" : 1,
  "CYP450 in= hibition" : 2,
  "Toxicity against T. Pyriformis" = : 3,
  "CYP1A2 inhibition" : 159,
  "LEL= - Lowest effect dose" : 174,
  "BCF - Bioconcentration= factor" : 8,
  "Melting Point" : 501,
 = "logP - ALOGPS2.1" : 535,
  "logS - ALOGPS2.1 sol= ubility in water" : 536,
  "hERG K+ Channel Blocking&qu= ot; : 628,
  "In vivo toxicities" : 635
}

The respective IDS of models are provided after each model. To make pred= ictions, you can use, e.g.

curl -X GET "http://rest.= ochem.eu/predict?MODELID=3D1&SMILES=3DCc1ccccc1

where 1 is the model id for AMES model. The AMES model is also accessibl= e as http://ochem.eu/model/1

The prediction is:

curl -X GET "http://rest.= ochem.eu/predict?MODELID=3D1&SMILES=3DCc1ccccc1"

{
  "MODEL:" : "http://ochem.eu/model/1&q= uot;,
  "SMILES" : "Cc1ccccc1",
  &= quot;AMES" : {
    "property" : "AM= ES",
    "value" : -0.0042,
 &= nbsp;  "PREDICTION" : "inactive",
  = ;  "insideAD" : true
  }
}

contains also information whether it is within the Applicability Domain = of the model.

 

 

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