Dynamic alpha-helices: conformations that do not conform.
Structural transitions are important for the stability and function of proteins, but these phenomena are poorly understood. An extensive analysis of Protein Data Bank entries reveals 103 regions in proteins with a tendency to transform from helical to nonhelical conformation and vice versa. We find that these dynamic helices, unlike other helices, are depleted in hydrophobic residues. Furthermore, the dynamic helices have higher surface accessibility and conformational mobility (P-value = 3.35e-07) than the rigid helices. Contact analyses show that these transitions result from protein-ligand, protein-nucleic acid, and crystal-contacts. The immediate structural environment differs quantitatively (P-value = 0.003) as well as qualitatively in the two alternate conformations. Often, dynamic helix experiences more contacts in its helical conformation than in the nonhelical counterpart (P-value = 0.001). There is differential preference for the type of short contacts observed in two conformational states. We also demonstrate that the regions in protein that can undergo such large conformational transitions can be predicted with a reasonable accuracy using logistic regression model of supervised learning. Our findings have implications in understanding the molecular basis of structural transitions that are coupled with binding and are important for the function and stability of the protein. Based on our observations, we propose that several functionally relevant regions on the protein surface can switch over their conformation from coil to helix and vice-versa, to regulate the recognition and binding of their partner and hence these may work as "molecular switches" in the proteins to regulate certain biological process. Our results supports the idea that protein structure-function paradigm should transform from static to a highly dynamic one.
Sandhu
Kuljeet Singh
KS
GN Ramachandran Knowledge Center for Genome Informatics, Institute of Genomics and Integrative Biology, CSIR, Delhi 110007, India.
Dash
Debasis
D
D000595:Amino Acid Sequence; D019295:Computational Biology; D030562:Databases, Protein; D016015:Logistic Models; D008958:Models, Molecular; D017433:Protein Structure, Secondary; D011506:Proteins / Q000737:chemistry*
D011506:Proteins