Biomedical subjects

Vladimir V Apanasovich

Publications and source records attributed to Vladimir V Apanasovich.

5 recordsLinked to original sources

PubMed2006

FRET study of membrane proteins: determination of the tilt and orientation of the N-terminal domain of M13 major coat protein.

A formalism for membrane protein structure determination was developed. This method is based on steady-state FRET data and information about the position of the fluorescence maxima on site-directed fluorescent labeled proteins in combination with global data analysis utilizing simulation-based fitting. The methodology was applied to determine the structural properties of the N-terminal domain of the major coat protein from bacteriophage M13 reconstituted into unilamellar DOPC/DOPG (4:1 mol/mol) vesicles. For our purpose, the cysteine mutants A7C, A9C, N12C, S13C, Q15C, A16C, S17C, and A18C in the N-terminal domain of this protein were produced and specifically labeled with the fluorescence probe AEDANS. The energy transfer data from the natural Trp-26 to AEDANS were analyzed assuming a two-helix protein model. Furthermore, the polarity Stokes shift of the AEDANS fluorescence maxima is taken into account. As a result the orientation and tilt of the N-terminal protein domain with respect to the bilayer interface were obtained, showing for the first time, to our knowledge, an overall alpha-helical protein conformation from amino acid residues 12-46, close to the protein conformation in the intact phage.

Bacteriophage M13↗

PubMed2006

FRET study of membrane proteins: simulation-based fitting for analysis of membrane protein embedment and association.

A new formalism for the simultaneous determination of the membrane embedment and aggregation of membrane proteins is developed. This method is based on steady-state Förster (or fluorescence) resonance energy transfer (FRET) experiments on site-directed fluorescence labeled proteins in combination with global data analysis utilizing simulation-based fitting. The simulation of FRET was validated by a comparison with a known analytical solution for energy transfer in idealized membrane systems. The applicability of the simulation-based fitting approach was verified on simulated FRET data and then applied to determine the structural properties of the well-known major coat protein from bacteriophage M13 reconstituted into unilamellar DOPC/DOPG (4:1 mol/mol) vesicles. For our purpose, the cysteine mutants Y24C, G38C, and T46C of this protein were produced and specifically labeled with the fluorescence label AEDANS. The energy transfer data from the natural tryptophan at position 26, which is used as a donor, to AEDANS were analyzed assuming a helix model for the transmembrane domain of the protein. As a result of the FRET data analysis, the topology and bilayer embedment of this domain were quantitatively characterized. The resulting tilt of the transmembrane helix of the protein is 18 +/- 2 degrees. The tryptophan is located at a distance of 8.5 +/- 0.5 A from the membrane center. No specific aggregation of the protein was found. The methodology developed here is not limited to M13 major coat protein and can be used in principle to study the bilayer embedment of any small protein with a single transmembrane domain.

Amino Acids↗

PubMed2006

Initial guesses generation for Fluorescence Intensity Distribution Analysis.

The growing number of applications of Fluorescence Intensity Distribution Analysis (FIDA) demands for new approaches in data processing, aiming at increased speed and robustness. Iterative algorithms of parameter estimation, although proven to be universal and accurate, require some initial guesses (IG) of the unknown parameters. An essential component of any data processing technology, IG become especially important in case of FIDA, since even with apparently reasonable, and physically admissible but randomly chosen IG, the iterative procedure may converge to situations where the FIDA model cannot be evaluated correctly. In the present work we introduce an approach for IG generation in FIDA experiments based on the method of moments. IG are generated for the sample parameters: brightness, concentration, and for the parameters related to experimental set-up: background, observation volume profile. A number of analytical simplifications were introduced in order to increase the accuracy and robustness of the numerical algorithms. The performance of the developed method has been tested on number of simulations and experimental data. Iterative fitting with generated IG proved to be more robust and at least five times faster than with an arbitrarily chosen IG. Applicability of the proposed method for quick estimation of brightness and concentrations is discussed.

Algorithms↗

PubMed2005

Global analysis of fluorescence fluctuation data.

Over the last decade the number of applications of fluorescence correlation spectroscopy (FCS) has grown rapidly. Here we describe the development and application of a software package, FCS Data Processor, to analyse the acquired correlation curves. The algorithms combine strong analytical power with flexibility in use. It is possible to generate initial guesses, link and constrain fit parameters to improve the accuracy and speed of analysis. A global analysis approach, which is most effective in analysing autocorrelation curves determined from fluorescence fluctuations of complex biophysical systems, can also be implemented. The software contains a library of frequently used models that can be easily extended to include user-defined models. The use of the software is illustrated by analysis of different experimental fluorescence fluctuation data sets obtained with Rhodamine Green in aqueous solution and enhanced green fluorescent protein in vitro and in vivo.

Algorithms↗

PubMedDate not supplied

Artificial neural network modification of simulation-based fitting: application to a protein-lipid system.

Simulation-based fitting has been applied to data analysis and parameter determination of complex experimental systems in many areas of chemistry and biophysics. However, this method is limited because of the time costs of the calculations. In this paper it is proposed to approximate and substitute a simulation model by an artificial neural network during the fitting procedure. Such a substitution significantly speeds up the parameter determination. This approach is tested on a model of fluorescence resonance energy transfer (FRET) within a system of site-directed fluorescence labeled M13 major coat protein mutants incorporated into a lipid bilayer. It is demonstrated that in our case the application of a trained artificial neural network for the substitution of the simulation model results in a significant gain in computing time by a factor of 5 x 10(4). Moreover, an artificial neural network produces a smooth approximation of the noisy results of a stochastic simulation.

Algorithms↗