Translator Disclaimer
Presentation + Paper
24 April 2017 SAW based micro- and acousto-fluidics in biomedicine
Author Affiliations +
Protein association starts with random collisions of individual proteins. Multiple collisions and rotational diffusion brings the molecules to a state of orientation. Majority of the protein associations are influenced by electrostatic interactions. To introduce: electrostatic rate enhancement, Brownian dynamics and transient complex theory has been traditionally used. Due to the recent advances in interdisciplinary sciences, an array of molecular assembly methods is being studied. Protein nanostructural assembly and macromolecular crowding are derived from the subsets of biochemistry to study protein-protein interactions and protein self-assembly. This paper tries to investigate the issue of enhancing the protein self-association rate, and bridging the gap between the simulations and experimental results. The methods proposed here include: electrostatic rate enhancement, macromolecular crowing, nanostructural protein assembly, microfluidics based approaches and magnetic force based approaches. Despite the suggestions of several methods, microfluidic and magnetic force based approaches seem to serve the need of protein assembly in a wider scale. Congruence of these approaches may also yield better results. Even though, these methods prove to be conceptually strong, to prevent the disagreement of theory and practice, a wide range of experiments is required. This proposal intends to study theoretical and experimental methods to successfully implement the aforementioned assembly strategies, and conclude with an extensive analysis of experimental data to address practical feasibility.
Conference Presentation
© (2017) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Mouli Ramasamy and Vijay K. Varadan "SAW based micro- and acousto-fluidics in biomedicine", Proc. SPIE 10167, Nanosensors, Biosensors, Info-Tech Sensors and 3D Systems 2017, 101671D (24 April 2017);

Back to Top