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ILSC Monthly Seminar: March 2011

2013

January: Michael Taylor
February: Marna Yandeau-Nelson
March: Paul Lockman
April: Martin Gruebele

2012

January: David D. Thomas
February: Elizabeth Austin-Minor
March: Juliette Lecomte
April: David Millar
May: Lukas Tamm
September: David Millar
September: Dongping Zhong
October: Jonathan V. Rocheleau
November: Yevgenya Grinblat
December: Michael Graner

2011

January: Clay Carter
February (a): Anne Kenworthy
February (b): Jennifer Liang
March: Joe Johnson
April: Marco Ciufolini
May: Gary Pielak
October: Matthew Andrews
December: Andrew Skildum

2010

November: Rui Wang
October: Marshall Hampton

Combining Bioinformatics and Proteomics to Identify Potential Biological Substrates for a Family of Membrane-bound Aspartyl Proteases

Speaker: Dr. Joseph Johnson; Assistant Professor, Department of Chemistry and Biochemistry, University of Minnesota Duluth

Time/Place: Thursday, March 31st at 3:00 pm, 130 SMed

Abstract: The deposition of the short peptide beta amyloid (Aβ) in the brain leads to the development of Alzheimer's disease (AD). Aβ is a product of a sequential cleavage of the amyloid precursor protein (APP) by the proteases β-secretase and γ-secretase. BACE1, a type I transmembrane aspartyl protease, has been characterized as the β-secretase and, as such, is a promising therapeutic target for the chronic treatment of AD. However, few substrates have been identified and the physiological function of BACE1 remains elusive. BACE2 is a close homolog of BACE1 with 50% sequence identity and a very similar 3D structure. BACE2 also shows some modest β-secretase activity but no native substrates have been identified other than APP. We hypothesize that BACE1 and BACE2 have similar but distinct functions in biological systems, and that identification of potential substrates for this family of aspartyl proteases will provide valuable insights into their biological functions. This study focuses on identifying putative in vivo protease substrates by combining bioinformatics and proteomics data.

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