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Combinatorial design of a four‐helix bundle protein using high‐throughput thermal scanning
Author(s) -
Magliery Thomas J.,
Lavinder Jason J.,
Hari Sanjay B.,
Nguyen Chau,
Sen Shila
Publication year - 2010
Publication title -
the faseb journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.709
H-Index - 277
eISSN - 1530-6860
pISSN - 0892-6638
DOI - 10.1096/fasebj.24.1_supplement.908.2
Subject(s) - throughput , sorting , bundle , sequence (biology) , computer science , rational design , protein design , stability (learning theory) , helix bundle , sequence space , computational biology , thermal stability , protein structure , chemistry , algorithm , nanotechnology , machine learning , biology , mathematics , biochemistry , materials science , telecommunications , organic chemistry , composite material , pure mathematics , banach space , wireless
Both the prediction and design of protein structure, using computational and rational approaches, remain significant challenges in protein chemistry. A major limitation to developing a comprehensive physicochemical model of the protein structure‐sequence relationship is the vastness of sequence space and the low‐throughput nature of biophysical studies. We are pursuing a combinatorial approach to understand better the sequence structure‐relationship: sorting large libraries of protein variants for structured proteins. We have developed a high‐throughput cell‐based screen for activity of the well‐studied four‐helix bundle protein Rop. To collect quantitative stability data for large numbers of variants, we have developed a method of high‐throughput hydrophobic dye binding called High‐Throughput Thermal Scanning (HTTS) which can be applied using automation and a real‐time PCR machine 96‐wells at a time. This system is being used to directly test the “rules” of protein design, taking those rules as hypotheses and sorting the resulting libraries for structure and stability. Here we will discuss the in‐depth analysis of a library of hydrophobic core variants, as well as initial results from surface libraries and rational design based on library statistics. This work was supported by a grant from the NIH (R01 GM083114) to TJM.