Publications
2019
Pineiro A, Munoz E, Sabin J, Costas M, Bastos M, Velazquez-Campoy A, Garrido P F, Dumas P, Ennifar E, Garcia-Rio L, Rial J, Pérez D, Fraga P, Rodriguez A, Cotelo C
AFFINImeter: A software to analyze molecular recognition processes from experimental data Journal Article
In: Anal Biochem, vol. 5, no. 577, pp. 117-134, 2019, ISBN: 30849378.
Abstract | Links | BibTeX | Tags: Affinity Analysis software Isothermal titration calorimetry Kinetics Molecular recognition Thermodynamics, ENNIFAR, Unité ARN
@article{,
title = {AFFINImeter: A software to analyze molecular recognition processes from experimental data},
author = {A Pineiro and E Munoz and J Sabin and M Costas and M Bastos and A Velazquez-Campoy and P F Garrido and P Dumas and E Ennifar and L Garcia-Rio and J Rial and D Pérez and P Fraga and A Rodriguez and C Cotelo},
url = {https://www.ncbi.nlm.nih.gov/pubmed/30849378?dopt=Abstract},
doi = {10.1016/j.ab.2019.02.031},
isbn = {30849378},
year = {2019},
date = {2019-01-01},
journal = {Anal Biochem},
volume = {5},
number = {577},
pages = {117-134},
abstract = {The comprehension of molecular recognition phenomena demands the understanding of the energetic and kinetic processes involved. General equations valid for the thermodynamic analysis of any observable that is assessed as a function of the concentration of the involved compounds are described, together with their implementation in the AFFINImeter software. Here, a maximum of three different molecular species that can interact with each other to form an enormous variety of surpramolecular complexes are considered. The corrections currently employed to take into account the effects of dilution, volume displacement, concentration errors and those due to external factors, especially in the case of ITC measurements, are included. The methods used to fit the model parameters to the experimental data, and to generate the uncertainties are described in detail. A simulation tool and the so called kinITC analysis to get kinetic information from calorimetric experiments are also presented. An example of how to take advantage of the AFFINImeter software for the global multi-temperature analysis of a system exhibiting cooperative 1:2 interactions is presented and the results are compared with data previously published. Some useful recommendations for the analysis of experiments aimed at studying molecular interactions are provided.},
keywords = {Affinity Analysis software Isothermal titration calorimetry Kinetics Molecular recognition Thermodynamics, ENNIFAR, Unité ARN},
pubstate = {published},
tppubtype = {article}
}
The comprehension of molecular recognition phenomena demands the understanding of the energetic and kinetic processes involved. General equations valid for the thermodynamic analysis of any observable that is assessed as a function of the concentration of the involved compounds are described, together with their implementation in the AFFINImeter software. Here, a maximum of three different molecular species that can interact with each other to form an enormous variety of surpramolecular complexes are considered. The corrections currently employed to take into account the effects of dilution, volume displacement, concentration errors and those due to external factors, especially in the case of ITC measurements, are included. The methods used to fit the model parameters to the experimental data, and to generate the uncertainties are described in detail. A simulation tool and the so called kinITC analysis to get kinetic information from calorimetric experiments are also presented. An example of how to take advantage of the AFFINImeter software for the global multi-temperature analysis of a system exhibiting cooperative 1:2 interactions is presented and the results are compared with data previously published. Some useful recommendations for the analysis of experiments aimed at studying molecular interactions are provided.