z-logo
open-access-imgOpen Access
SVD-aided pseudo principal-component analysis: A new method to speed up and improve determination of the optimum kinetic model from time-resolved data
Author(s) -
Key Young Oang,
Cheolhee Yang,
Srinivasan Muniyappan,
Jeongho Kim,
Hyotcherl Ihee
Publication year - 2017
Publication title -
structural dynamics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.415
H-Index - 29
ISSN - 2329-7778
DOI - 10.1063/1.4979854
Subject(s) - principal component analysis , kinetic energy , singular value decomposition , biological system , spectroscopy , chromophore , component (thermodynamics) , chemistry , computer science , algorithm , physics , thermodynamics , artificial intelligence , quantum mechanics , biology , organic chemistry
Determination of the optimum kinetic model is an essential prerequisite for characterizing dynamics and mechanism of a reaction. Here, we propose a simple method, termed as singular value decomposition-aided pseudo principal-component analysis (SAPPA), to facilitate determination of the optimum kinetic model from time-resolved data by bypassing any need to examine candidate kinetic models. We demonstrate the wide applicability of SAPPA by examining three different sets of experimental time-resolved data and show that SAPPA can efficiently determine the optimum kinetic model. In addition, the results of SAPPA for both time-resolved X-ray solution scattering (TRXSS) and transient absorption (TA) data of the same protein reveal that global structural changes of protein, which is probed by TRXSS, may occur more slowly than local structural changes around the chromophore, which is probed by TA spectroscopy.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom