Pad�-Laplace method for the analysis of time-resolved fluorescence decay curves

Abstract

The interpretation of fluorescence intensity decay times in terms of protein structure and dynamics depends on the accuracy and sensitivity of the methods used for data analysis. The are many methods available for the analysis of fluorescence decay data, but justification for choosing any one of them is unclear. In this paper we generalize the recently proposed Padé-Laplace method to include deconvolution with respect to the instrument response function. In this form the method can be readily applied to the analysis of time-correlated single photon counting data. By extensive simulations we have shown that the Padé-Laplace method provides more accurate results than the standard least squares method with iterative reconvolution under the condition of closely spaced lifetimes. The application of the Padé-Laplace method to several experimental data sets yielded results consistent with those obtained by use of the least squares analysis.

Analysis of the phosphorescence of thianthren crystals

“…The existence of three different lifetimes in the radiative deactivation of the thianthren has been also confu-med analysing the phosphorescence intensity, taken as the area under the emission curves recorded at different time delays, by using the Kinetic Fit Subroutine (KINFIT [29]) and by using a novel approach for the analysis of the multiexponential functions, the PadS-Laplace (PL) method [30][31][32]. The results of the KINFIT routine indicate that acceptable values of the standard deviation and of the Durbin-Watson factor can be obtained if one fits the experimental data to a combination of three exponential functions rather than to a mono-or a doubleexponential decay.…”

A model for multiexponential tryptophan fluorescence intensity decay in proteins

“…Time-correlated photon-counting measurements were performed at pH 8.0 under conditions of 10 ps channel widths and 20,000 counts at the peak. The intensity profile comprising 1900 channels was analyzed by use of the generalized Pade-Laplace method (GPL) (Bajzer et al, 1990), the maximum likelihood (ML) (Bajzer et al, 1991; Bajzer and Prendergast 1992) and the maximum entropy methods (MEM) (Livesey and Brochon, 1987;Vincent et al, 1988) assuming multiexponential function of the general form (Eq. 6).…”

“…4) with a favorable run test statistic z (Bajzer and Prendergast, 1992). Separability and detectability indexes (Bajzer et al, 1991; t The errors in parameters (second line) were estimated as described in (Bajzer et al, 1990). § D = 1932, Dlv = 1.036, Z = 1.12, Q = 0.135, z = 1.0.…”

Analysis of fluorescence induction in thylakoids with the method of moments reveals two different active Photosystem II centres

“…Therefore, arranging for smaller excitation and fluorescence moments produced smaller corrections and smaller numerical errors in the computation of the reduced moments. This had the further advantage that the results (amplitudes and rate constants) were directly applicable to the area growth curve with no further computations, whereas a further analytical integration as reported by Bajzer et al (1990) would have been otherwise necessary.…”

“…Although both methods give in theory the same result, singular value decomposition is technically superior (Press et al 1989). Deconvolution errors depend on how close exponentials are, and can be estimated by doing tests with simulated data (Small et al 1989, Bajzer et al 1990). From tests with simulated data (three exponentials with rate constants of 150, 30 and 10s -1, with amplitudes inversely proportional to the rate constants) rounded to 8 bit precision before integration of the area growth (and no added noise), we found errors of about 5% for the fastest exponential and about 25% (relative to the original value) for the two slowest ones (these errors go down to 1% without rounding).…”