Alzheimer's disease (AD) is a neurodegenerative disorder that lacks effective treatment options. Anti-amyloid beta (Aβ) antibodies are the leading drug candidates to treat AD, but the results of clinical trials have been disappointing. Introducing rational mutations into anti-Aβ antibodies to increase their effectiveness is a way forward, but the path to take is unclear. In this study, we demonstrate the use of computational fragment-based docking and MMPBSA binding free energy calculations in the analysis of anti-Aβ antibodies for rational drug design efforts. Our fragment-based docking method successfully predicts the emergence of the common EFRH epitope. MD simulations coupled with MMPBSA binding free energy calculations are used to analyze scenarios described in prior studies, and we computationally introduce rational mutations into PFA1 to predict mutations that can improve its binding affinity toward the pE3-Aβ form of Aβ. Two out of our four proposed mutations are predicted to stabilize binding. Our study demonstrates that a computational approach may lead to an improved drug candidate for AD in the future.

Biologists commonly visualize different features of an organism using distinct sources of illumination. Such multichannel imaging has largely not been applied to behavioral studies because of the challenges posed by a moving subject. We address this challenge with the technique of multichannel stroboscopic videography (MSV), which synchronizes multiple strobe lights with video exposures of a single camera. We illustrate the utility of this approach with kinematic measurements of a walking cockroach (Gromphadorhina portentosa) and calculations of the pressure field around a swimming fish (Danio rerio). In both, transmitted illumination generated high-contrast images of the animal's body in one channel. Other sources of illumination were used to visualize the points of contact for the feet of the cockroach and the water flow around the fish in separate channels. MSV provides an enhanced potential for high-throughput experimentation and the capacity to integrate changes in physiological or environmental conditions in freely-behaving animals.