Electrostatic Modeling of Protein Aggregation

dc.contributor.advisorDubin, Paul L.
dc.contributor.authorVanam, Ram
dc.date.accessioned2005-10-03T15:41:02Z
dc.date.available2005-10-03T15:41:02Z
dc.date.issued2004-12
dc.degree.disciplineBioinformatics
dc.degree.levelMaster of Science
dc.degree.nameMaster of Science
dc.descriptionSubmitted to the faculty of Indiana University in partial fulfillment of the requirements for the degree Master of Science in the Department of Bioinformatics in the School of Informatics of, Indiana University December, 2004en
dc.description.abstractElectrostatic modeling was done with Delphi of insight II to explain and predict protein aggregation, measured here for β-lactoglobulin and insulin using turbidimetry and stopped flow spectrophotometry. The initial rate of aggregation of β-Lactoglobulin was studied between pH 3.8 and 5.2 in 4.5mM NaCl; and for ionic strengths from 4.5 to 500mM NaCl at pH 5.0. The initial slope of the turbidity vs. time curve was used to define the initial rate of aggregation. The highest initial rate was observed near pH < pI i.e., 4.6 (< 5.2). The decrease in aggregation rate when the pH was increased from 4.8 to 5.0 was large compared to its decrease when the pH was reduced from 4.4 to 4.2; i.e., the dependence of initial rate on pH was highly asymmetric. The initial rate of aggregation at pH 5.0 increased linearly with the reciprocal of ionic strength in the range I = 0.5 to 0.0045M. Protein electrostatic potential distributions are used to understand the pH and ionic strength dependence of the initial rate of aggregation. Similar studies were done with insulin. In contrast to BLG, the highest initial aggregation rate for insulin was observed at pH = pI. Electrostatic computer modeling shows that these differences arise from the distinctly different surface charge distributions of insulin and BLG.en
dc.format.extent1703247 bytes
dc.format.mimetypeapplication/pdf
dc.identifier.urihttps://hdl.handle.net/1805/400
dc.identifier.urihttp://dx.doi.org/10.7912/C2/808
dc.language.isoen_US
dc.subjectelectrostatic modelingen
dc.subjectprotein aggregationen
dc.titleElectrostatic Modeling of Protein Aggregationen
dc.typeThesisen
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