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.
Nazarov
Petr V
PV
Laboratory of Biophysics, Wageningen University, Dreijenlaan 3, 6703 HA, Wageningen, The Netherlands. petr.nazarov@wur.nl
Apanasovich
Vladimir V
VV
Lutkovski
Vladimir M
VM
Yatskou
Mikalai M
MM
Koehorst
Rob B M
RB
Hemminga
Marcus A
MA
D000465:Algorithms; D001185:Artificial Intelligence; D017104:Bacteriophage M13 / Q000737:chemistry; D055592:Biophysical Phenomena; D001703:Biophysics; D036022:Capsid Proteins / Q000737:chemistry; D003198:Computer Simulation; D031541:Fluorescence Resonance Energy Transfer; D005456:Fluorescent Dyes; D008051:Lipid Bilayers; D008055:Lipids / Q000737:chemistry*; D008956:Models, Chemical; D016571:Neural Networks, Computer; D009474:Neurons; D011506:Proteins / Q000737:chemistry*; D013329:Structure-Activity Relationship; D013816:Thermodynamics
D036022:Capsid Proteins; D005456:Fluorescent Dyes; D008051:Lipid Bilayers; D008055:Lipids; D011506:Proteins