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|Title:||Towards further understanding of protein crystallization : phase diagram, protein interactions, nucleation kinetics and growth kinetics||Authors:||Liu, Yingxin||Keywords:||DRNTU::Engineering::Chemical engineering::Biotechnology||Issue Date:||2010||Source:||Liu, Y. X. (2010). Towards further understanding of protein crystallization : phase diagram, protein interactions, nucleation kinetics and growth kinetics. Doctoral thesis, Nanyang Technological University, Singapore.||Abstract:||Protein crystallization has been well recognized to be of great importance in several applications. Crystallization of protein crystals is the necessary first step in these applications. Given the lack of fundamental understanding of protein crystallization mechanism, protein crystals are usually obtained by the trial-and-error method. Screening for optimal crystallization conditions always requires a large amount of time and protein. Thus, knowledge of phase behavior, crystal nucleation and growth kinetics and the interactions that govern them is crucial for the understanding of protein crystallization mechanism and the design of optimal crystallization conditions. In this dissertation, a full-picture investigation of protein crystallization has been presented. The phase diagram was obtained by measuring solubility and cloud-point temperature of lysozyme in solutions of various conditions. Protein interactions were characterized by measuring the second viral coefficient. It was found that there was a systematic variation between the solubility and the second virial coefficient; the solubility decreased with the increasing of protein attractive interactions, and the liquid-liquid phase separation was also driven by the net attractive interactions between protein molecules. The experimental data were also compared with the theoretical predictions. A good agreement was exhibited between the experimental results and theoretical predictions. In addition, a quantitative description of the liquid-liquid co-existence curve was achieved by modifying random phase approximation.||URI:||https://hdl.handle.net/10356/38586||DOI:||10.32657/10356/38586||Fulltext Permission:||open||Fulltext Availability:||With Fulltext|
|Appears in Collections:||SCBE Theses|
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Updated on Jun 17, 2021
Updated on Jun 17, 2021
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