Science Inventory

A Probablistic Diagram to Guide Chemical Design with Reduced Potency to Incur Cytotoxicity

Citation:

Shen, L., R. Judson, F. Melnikov, J. Roethle, A. Guidanda, J. Zimmerman, AND P. Anastas. A Probablistic Diagram to Guide Chemical Design with Reduced Potency to Incur Cytotoxicity. GREEN CHEMISTRY. Royal Society of Chemistry, Cambridge, Uk, 18:4461-4467, (2016).

Impact/Purpose:

The study uses calculated chemical descriptors to build a predictive model for cytotoxicity using a Näive Bayesian algorithm. Using this model, design rules are provided to help synthetic chemists minimize the chance that a newly synthesized chemical will be cytotoxic.

Description:

Toxicity is a concern with many chemicals currently in commerce, and with new chemicals that are introduced each year. The standard approach to testing chemicals is to run studies in laboratory animals (e.g. rats, mice, dogs), but because of the expense of these studies and concerns for animal welfare, few chemicals besides pharmaceuticals and pesticides are fully tested. Over the last decade there have been significant developments in the field of computational toxicology which combines in vitro tests and computational models. The ultimate goal of this ?field is to test all chemicals in a rapid, cost effective manner with minimal use of animals. One of the simplest measures of toxicity is provided by high-throughput in vitro cytotoxicity assays, which measure the concentration of a chemical that kills particular types of cells. Chemicals that are cytotoxic at low concentrations tend to be more toxic to animals than chemicals that are less cytotoxic. We employed molecular characteristics derived from density functional theory (DFT) and predicted values of log(octanol-water partition coe?fficient) (logP)to construct a design variable space, and built a predictive model for cytotoxicity using a Naive Bayesian algorithm. External evaluation showed that the area under the curve (AUC) for the receiver operating characteristic (ROC) of the model to be 0.81. Using this model, we provide design rules to help synthetic chemists minimize the chance that a newly synthesized chemical will be cytotoxic.

Record Details:

Record Type:DOCUMENT( JOURNAL/ PEER REVIEWED JOURNAL)
Product Published Date:08/21/2016
Record Last Revised:10/17/2016
OMB Category:Other
Record ID: 329408