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Binding affinity in drug design: experimental and computational techniques.
Journal article

Binding affinity in drug design: experimental and computational techniques.

  • Kairys V a Department of Bioinformatics , Institute of Biotechnology, Life Sciences Center, Vilnius University , Vilnius , Lithuania.
  • Baranauskiene L b Department of Biothermodynamics and Drug Design , Institute of Biotechnology, Life Sciences Center, Vilnius University , Vilnius , Lithuania.
  • Kazlauskiene M c Department of Biochemistry , University of Zurich , Zurich , Switzerland.
  • Matulis D b Department of Biothermodynamics and Drug Design , Institute of Biotechnology, Life Sciences Center, Vilnius University , Vilnius , Lithuania.
  • Kazlauskas E b Department of Biothermodynamics and Drug Design , Institute of Biotechnology, Life Sciences Center, Vilnius University , Vilnius , Lithuania.
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  • 2019-06-01
Published in:
  • Expert opinion on drug discovery. - 2019
AUC
BLI
DSC
DSF
Drug design
FTSA
Gibbs energy
ICD
ITC
MM-PBSA
MST
NMR
QM/MM
QSAR
SPR
TSA
affinity
binding
electrophoresis
fluorescence
free energy
inhibitor
ligand
molecular dynamics
thermophoresis
Drug Design
Drug Development
Drug Discovery
Humans
Ligands
Protein Binding
Proteins
English Introduction: In pharmaceutical design where future drugs are developed by targeting a specific chosen protein, the evaluation of ligand affinity is crucial. For this very purpose are a multitude of diverse methods which are continuously being improved, which, in turn, makes it difficult to choose which techniques to use in practice. Areas covered: In this review, the authors discuss both experimental and computational approaches for affinity evaluation. Basic principles, general limitations and advantages, as well as main areas of application in drug discovery, are overviewed for some of the most popular ligand binding assays. The authors further provide a guide to affinity predictions, collectively covering several techniques that are used in the first stages of rational drug design. Expert opinion: All affinity estimation methods have limitations and advantages that partially overlap and complement one another. Some of the suggested best practices include cross-verification of data using at least two different techniques and careful data interpretation.
Language
  • English
Open access status
closed
Identifiers
Persistent URL
https://sonar.ch/global/documents/164731
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