On The Use of Genetic Algorithms for Parameter Identification in Anaerobic Digestion Modelling

Anaerobic digestion (AD) of wastewater is a very interesting option for waste valorization, energy production and environment protection. It is a complex, naturally occurring process that can take place inside bioreactors. The capability of predicting the operation of such bioreactors is important to optimize the design and the operation conditions of the reactors, which, in part, justifies the numerous AD models presently available. The existing AD models are not universal, have to be inferred from prior knowledge and rely on existing experimental data. Among the tasks involved in the process of developing a dynamical model for AD, the estimation of parameters is one of the most challenging. This paper presents the identifiability analysis of a nonlinear dynamical model for a batch reactor. Particular attention is given to the structural identifiability of the model, which considers the uniqueness of the estimated parameters. To perform this analysis, the GenSSI toolbox was used. The estimation of the model parameters is achieved with genetic algorithms (GA) which have already been used in the context of AD modelling, although not commonly. The paper discusses its advantages and disadvantages.

Insights into (S)-rivastigmine inhibition of butyrylcholinesterase (BuChE): Molecular docking and saturation transfer difference NMR (STD-NMR)

Rivastigmine is a very important drug prescribed for the treatment of Alzheimer's disease (AD) symptoms. It is a dual inhibitor, in that it inhibits both acetylcholinesterase (AChE) and butyrylcholinesterase (BuChE). For our screening program on the discovery of new rivastigmine analogue hits for human butyrylcholinesterase (hBuChE) inhibition, we investigated the interaction of this inhibitor with BuChE using the complimentary approach of the biophysical method, saturation transfer difference (STD)-NMR and molecular docking. This allowed us to obtain essential information on the key binding interactions between the inhibitor and the enzyme to be used for screening of hit compounds. The main conclusions obtained from this integrated study was that the most dominant interactions were (a) H-bonding between the carbamate carbonyl of the inhibitor and the NH group of the imidazole unit of H434, (b) stacking of the aromatic unit of the inhibitor and the W82 aromatic unit in the choline binding pocket via pi-pi interactions and (c) possible CH/pi interactions between the benzylic methyl group and the N-methyl groups of the inhibitor and W82 of the enzyme.