A Python toolkit for experimental and computational studies of water transport through channels.A Python toolkit for experimental and computational studies of water transport through channels

ZERBETTO DE PALMA, GERARDO; CANESSA FORTUNA, AGUSTINA; RAMOA, ÚRSULA; ESPELT, MARÍA VICTORIA; ALLEVA, KARINA

Rosario

Congreso; L Reunión Anual de la Sociedad Argentina de Biofísica; 2022

Water transport through membrane proteins has been traditionally studied byexperimental methods and, lately, the increasing accessibility to computational power hasenabled the study of such phenomena through the glass of molecular dynamicssimulations (MDS).Several experimental approaches involve the measurement of a signal that is related to avolume change of a spherical membrane-delimited compartment, which has embeddedwater channels. When cells are used in swelling experiments, volume changes can beobtained by tracking the projected area on a series of pictures taken over time. Thesetechniques can be quite time consuming and hard to standardize if the image processingis made by hand one picture at a time. On the other hand, computational methods toassess water transport mechanisms include the analysis of trajectories obtained from MDS.The theory of these analyses is well documented but implementations of such calculationsare not widely distributed making it difficult to share and compare data obtained with theexact same implementation. To solve these problems and to provide a unified tool to studywater permeation, we have developed an open source Python-based toolkit to assistanalysis in both fronts, experimental and computational. For data acquisition and analysisof swelling experiments, this toolkit provides a time adjustable automatic camerastreaming and capture with on the fly thresholding, which also keeps track and recordsarea measurements in real time. A posteriori automatic thresholding analysis dramaticallydecreases processing times (~150 fold change). Output is structured and can be rapidlyprocessed to compute relative volume change and osmotic permeability (Pf) from bothpictures or area record at the time of the experiment. For MDS trajectory analysis weprovide implementations for intrinsic osmotic permeability coefficient (pf) calculationobtained from equilibrium simulations, potential of mean force and permeation eventscounter.