TY - JOUR
T1 - Complex networks govern coiled-coil oligomerization - Predicting and profiling by means of a machine learning approach
AU - Mahrenholz, Carsten C.
AU - Abfalter, Ingrid G.
AU - Bodenhofer, Ulrich
AU - Volkmer, Rudolf
AU - Hochreiter, Sepp
PY - 2011/5
Y1 - 2011/5
N2 - Understanding the relationship between protein sequence and structure is one of the great challenges in biology. In the case of the ubiquitous coiled-coil motif, structure and occurrence have been described in extensive detail, but there is a lack of insight into the rules that govern oligomerization, i.e. how many α-helices form a given coiled coil. To shed new light on the formation of two- and three-stranded coiled coils, we developed a machine learning approach to identify rules in the form of weighted amino acid patterns. These rules form the basis of our classification tool, PrOCoil, which also visualizes the contribution of each individual amino acid to the overall oligomeric tendency of a given coiled-coil sequence. We discovered that sequence positions previously thought irrelevant to direct coiled-coil interaction have an undeniable impact on stoichiometry. Our rules also demystify the oligomerization behavior of the yeast transcription factor GCN4, which can now be described as a hybrid - part dimer and part trimer - with both theoretical and experimental justification.
AB - Understanding the relationship between protein sequence and structure is one of the great challenges in biology. In the case of the ubiquitous coiled-coil motif, structure and occurrence have been described in extensive detail, but there is a lack of insight into the rules that govern oligomerization, i.e. how many α-helices form a given coiled coil. To shed new light on the formation of two- and three-stranded coiled coils, we developed a machine learning approach to identify rules in the form of weighted amino acid patterns. These rules form the basis of our classification tool, PrOCoil, which also visualizes the contribution of each individual amino acid to the overall oligomeric tendency of a given coiled-coil sequence. We discovered that sequence positions previously thought irrelevant to direct coiled-coil interaction have an undeniable impact on stoichiometry. Our rules also demystify the oligomerization behavior of the yeast transcription factor GCN4, which can now be described as a hybrid - part dimer and part trimer - with both theoretical and experimental justification.
KW - Algorithms
KW - Amino Acid Motifs
KW - Area Under Curve
KW - Artificial Intelligence
KW - Basic-Leucine Zipper Transcription Factors/chemistry
KW - Computer Simulation
KW - Models, Molecular
KW - Molecular Sequence Annotation
KW - Mutant Proteins/chemistry
KW - Protein Multimerization
KW - ROC Curve
KW - Saccharomyces cerevisiae Proteins/chemistry
UR - http://www.scopus.com/inward/record.url?scp=79955766198&partnerID=8YFLogxK
U2 - 10.1074/mcp.M110.004994
DO - 10.1074/mcp.M110.004994
M3 - Article
C2 - 21311038
AN - SCOPUS:79955766198
SN - 1535-9476
VL - 10
JO - Molecular and Cellular Proteomics
JF - Molecular and Cellular Proteomics
IS - 5
ER -