Dinâmica não linear na análise de séries temporais resultantes do bloqueio na corrente iônica através do nanoporo individual da alfatoxina do Staphylococcus aureus

Abstract

Statistical tools of nonlinear dynamics are widely used in the analysis and proper description of phenomena in the areas of chemistry, physics and biology. The increase in computational processing capacity, together with the development of programming languages and algorithms, enabled the availability of programs capable of simulation and prediction in phenomena that for some years would be impracticable. In this work, we used: Detrended Flutuation Analysis (DFA), Markov Modeling, Approximate Entropy (ApEn), Lempel Ziv Complexity (CLZ) and Recurrence Plot (RP) in the analysis of time series resulting from the blocking or unlocking in the chain Ionization through the individual nanopore of the alpha-hemolysin of Staphylococcus aureus (alpha-hemolysin), caused by the entry or translocation of monodisperse polyethylene glycol (PEG1294). All experiments were performed on lipid bilayers formed by diftanyl phosphatidylcholine at room temperature (25°C) and voltage clamping conditions employing a patch clamp amplifier. The aqueous solution was 4M KCl, pH 7.5, with the PEG at the concentrations of 400, 1000 or 2000M and the time series with a duration of at least 30 seconds were obtained for each of the PEG concentrations and in the potential transmembrane: 20, 40, 60, 80 and 100 mV. Each of the time series was segmented originating the series called TP's and TA's. The TP's and TA's series were composed respectively by the residence times or absence of PEG within the nanopore. . These events did not present correlation (αDFA = 0.5), followed a Markovian stochastic pattern, modeled by a two state process, presented high complexity (CLZ ~ 1 and ApEn ~ 2) and randomness as showed through RP (DET <100) and RQA. These theoretical results corroborate with the literature that affirm to be the kinetics of the analyte-nanopore interaction a stochastic phenomenon.