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Residue Sequence and Structure in the Re evaluation the Categorization of HIV Progression in Subjects Based on CD4 T cell Decline Rates Angela Garibaldi & Ryan Willhite Loyola Marymount University BIOL 398-01 March 23, 2010 Outline • Review of previous experiment using CD4 decline rates • Structure based hypothesis • Methods and programs used • Results • Comparison to More Recent Studies • References Recap of past experiment • Evaluated the categorization of progressors based on CD4 decline rates • Analyzed two moderate progressors (6,7) with rates comparable to non-progressor 13 and rapid progressor 10. • Based on divergence and diversity subject 6 did not act as non-progressor • Subject 7 acted like a rapid progressor. Hypothesis • Subject 7 will be more similar to Methods • Create phylogenetic trees based on amino acid sequence • Use ProtPram to analyze residue composition in subjects 6,7,5,10 • Select 7 and 10 for time point analysis – First clone for selected visits used • Use Cn3d to analyze differences in 3d structure Phylogenetics based on amino acid sequence 10 vs 5 10 vs 7 5 vs 7 Overall residue composition •All clones available were used in this analysis per individual •Rapid Progressor Subject 10 is the only one with Asn as its most prevalent residue Residue composition over time Residue composition over time • All clones from selected visits were used. • Subject 10, Rapid Progressor shows Asn as its prevalent residue over time. • Subject 7, Moderate Progressor begins with Asn as prevalent residue • Subject 10 showed sudden jump in Arg %. This may be an artifact. 3d structure of gp120 Resulting 3d structures Conclusions • Amino acid sequence is a secondary way to further categorize subjects into progressor groups • Subject 7, while being more phylogenetically similar, still is best fit as a moderate A more recent study • Structure of HIV-1 gp120 with gp41interactive region reveals layered envelope architecture and basis of conformational mobility gp120, gp41-interactive region structure References