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One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation01:24

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Identification of Kinase-substrate Pairs Using High Throughput Screening
11:13

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Published on: August 29, 2015

High-throughput pKa screening and prediction amenable for ADME profiling.

Hong Wan1, Johan Ulander

  • 1AstraZeneca R&D Mölndal, DMPK & Bioanalytical Chemistry, Mölndal, Sweden. hong.wan@astrazeneca.com

Expert Opinion on Drug Metabolism & Toxicology
|July 26, 2006
PubMed
Summary

New pKa assays aid drug screening by evaluating drug properties like absorption and metabolism. This review compares experimental and computational methods for pKa prediction and profiling in drug discovery.

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Area of Science:

  • Pharmacology
  • Analytical Chemistry
  • Computational Chemistry

Background:

  • Technological advancements enable novel pKa assays for drug screening.
  • pKa determination is crucial for Absorption, Distribution, Metabolism, and Excretion (ADME) profiling and Quantitative Structure-Activity Relationship (QSAR) modeling.

Purpose of the Study:

  • To provide a critical overview of new methodologies for high-throughput screening and prediction of pKa.
  • To compare experimental and computational approaches for pKa determination and profiling.
  • To guide drug discovery companies in integrating experimental and computational methods.

Main Methods:

  • High-throughput screening of pKa using multiplexed capillary electrophoresis with UV detection.
  • Capillary Electrophoresis and Mass Spectrometry (CEMS) based on sample pooling.
  • pKa determination via pH gradient High-Performance Liquid Chromatography (HPLC).
  • pKa measurement using a mixed-buffer linear pH gradient system.
  • Computational approaches including fragment-based methods and quantum mechanical calculations.

Main Results:

  • Comparison of various experimental pKa assays, with emphasis on the CEMS method.
  • Discussion of the accuracy limits of computational pKa prediction methods.
  • Demonstration of pKa prediction for drug candidates and commercial drugs.

Conclusions:

  • New pKa assays offer valuable tools for high-throughput drug screening.
  • Integration of experimental and computational pKa determination enhances ADME profiling.
  • Accurate pKa prediction is essential for effective drug discovery and development.