Selection of appropriate training and validation set chemicals for modelling dermal permeability by U-optimal design

Details

• Personal Author:
  Baynes RE ; Brooks JD ; Hughes-Oliver JM ; Xu G ; Yeatts JL
• Description:
  Quantitative structure-activity relationship (QSAR) models are being used increasingly in skin permeation studies. The main idea of QSAR modelling is to quantify the relationship between biological activities and chemical properties, and thus to predict the activity of chemical solutes. As a key step, the selection of a representative and structurally diverse training set is critical to the prediction power of a QSAR model. Early QSAR models selected training sets in a subjective way and solutes in the training set were relatively homogenous. More recently, statistical methods such as D-optimal design or space-filling design have been applied but such methods are not always ideal. This paper describes a comprehensive procedure to select training sets from a large candidate set of 4534 solutes. A newly proposed 'Baynes' rule', which is a modification of Lipinski's 'rule of five', was used to screen out solutes that were not qualified for the study. U-optimality was used as the selection criterion. A principal component analysis showed that the selected training set was representative of the chemical space. Gas chromatograph amenability was verified. A model built using the training set was shown to have greater predictive power than a model built using a previous dataset [1]. [Description provided by NIOSH]
• Subjects:
  Chemistry Chemistry, Analytic Metals Occupational Health Safety Skin Skin Absorption Solvents Staff Development
• Keywords:
  Analytical-chemistry Analytical-models Analytical-processes Applicability Domain (AD) Author Keywords: QSAR Model Baynes' Rule Biocides Biological-effects Chemical-analysis Chemical-kinetics Chemical-properties Chemical-reactions Chemical-structure Gas-chromatography Metalworking-fluids Models Molecular-structure Pharmacodynamics Principal Component Analysis (PCA) Quantitative-analysis Skin-absorption Skin-exposure Structural-analysis Training Training Set Selection U-optimal Design

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• ISSN:
  1062-936X
• Document Type:
  Text
• Funding:
  Grant
• Genre:
  Journal Article
• Place as Subject:
  North Carolina ; OSHA Region 3 ; OSHA Region 4 ; Virginia
• CIO:
  National Institute for Occupational Safety and Health (NIOSH)
• Topic:
  Workplace Safety & Health
• Location:
  North America
• Pages in Document:
  135-156
• Volume:
  24
• Issue:
  2
• NIOSHTIC Number:
  nn:20042645
• Citation:
  SAR QSAR Environ Res 2013 Feb; 24(2):135-156
• Contact Point Address:
  R.E.Baynes, Center for Chemical Toxicology Research and Pharmacokinetics, North Carolina State University, College of Veterinary Medicine, Raleigh, NC 27606, USA
• Email:
  rebaynes@ncsu.edu
• Federal Fiscal Year:
  2013
• NORA Priority Area:
  Manufacturing ; Disease and Injury: Allergic and Irritant Dermatitis
• Performing Organization:
  North Carolina State University, Raleigh, North Carolina
• Peer Reviewed:
  True
• Start Date:
  20000801
• Source Full Name:
  SAR and QSAR in Environmental Research
• End Date:
  20150731
• Collection(s):
  National Institute for Occupational Safety and Health
• Main Document Checksum:
  urn:sha-512:360de96916829e8c3df2155d69d68530f43074febe7b11d64431b7e746a7cdb4f89d35efeaca2539f0b3f6b9dfa30b4f61b8810c6b3f64e784daba629f5df1c7
• Download URL:
  https://stacks.cdc.gov/view/cdc/194806/cdc_194806_DS1.pdf
• File Type:
  [PDF - 775.70 KB ]