Bayesian regression and model selection for isothermal titration calorimetry with enantiomeric mixtures

Bayesian regression and model selection for isothermal titration calorimetry with enantiomeric mixtures

Bayesian regression is performed to infer parameters of thermodynamic binding models from isothermal titration calorimetry measurements in which the titrant is an enantiomeric mixture. For some measurements the posterior density is multimodal, indicating that additional data with a different protoco...

Full description

Saved in:
Bibliographic Details
Published in:PloS one Vol. 17; no. 9; p. e0273656
Main Authors: Trung Hai Nguyen, Van N T La, Kyle Burke, David D L Minh
Format: Journal Article
Language:English
Published: Public Library of Science (PLoS) 29-09-2022
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Bayesian regression is performed to infer parameters of thermodynamic binding models from isothermal titration calorimetry measurements in which the titrant is an enantiomeric mixture. For some measurements the posterior density is multimodal, indicating that additional data with a different protocol are required to uniquely determine the parameters. Models of increasing complexity-two-component binding, racemic mixture, and enantiomeric mixture-are compared using model selection criteria. To precisely estimate one of these criteria, the Bayes factor, a variation of bridge sampling is developed.
ISSN:1932-6203
DOI:10.1371/journal.pone.0273656