Comparison of prediction models for blood brain barrier permeability and analysis of the molecular descriptors

Pharmazie. 2012 Jul;67(7):628-34.

Abstract

To develop an in silico model for predicting blood brain barrier (BBB) permeability, and evaluate whether incorporation of two new biological descriptors, high affinity P-glycoprotein substrate probability (HAPSP) and plasma protein binding ratio (PPBR), could result in a better model, four different multiple linear regression (MLR) models have been constructed and compared with each other. The optimized model demonstrated predictive ability and simplicity, not only suitable for passive but also for active transport. Moreover, the molecular descriptors used here are discussed.

Publication types

  • Comparative Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • ATP Binding Cassette Transporter, Subfamily B, Member 1 / chemistry
  • Algorithms
  • Biological Transport, Active
  • Blood Proteins / chemistry
  • Blood Proteins / metabolism
  • Blood-Brain Barrier / metabolism*
  • Databases, Factual
  • Forecasting
  • Humans
  • Linear Models
  • Models, Chemical
  • Molecular Weight
  • Octanols
  • Permeability
  • Protein Binding
  • Quantitative Structure-Activity Relationship
  • Solubility
  • Water

Substances

  • ATP Binding Cassette Transporter, Subfamily B, Member 1
  • Blood Proteins
  • Octanols
  • Water