Structural Studies of Nascent Chain-Mediated Translational Arrest
My research at Yale focuses on several aspects of ribosome function. Most notably, I have been studying the way in which certain nascent peptide sequences have the ability to stall the process of translation in cis, thereby regulating a variety of cellular processes. In order to carry out structural studies on this process, stalled ribosome-nascent chain (RNC) complexes carrying a nascent peptide of defined length and sequence must be obtained in pure form and in milligram quantities. As a result, I have optimized an in vitro translation system that is able to fulfil such requirements. This resulted in the preparation of highly purified RNC complexes in quantities suitable for structural work.
My goal is to obtain structures of stalled ribosome nascent chain complexes at subnanometer or atomic resolution using cryo-EM and X-ray crystallography. Nascent chains of interest include TnaC, which controls the expression of the E.coli tryptophanase operon, and ermCL, an arresting peptide that leads to ribosome stalling in the presence of the antibiotic erythromycin. By studying how these and other peptides are capable of interacting with the walls of the ribosomal exit tunnel and alter translation, I hope to better understand how the ribosome can be modulated by small peptides in cis. This knowledge may then be used as a base for the design of novel antibiotics capable of targeting the 50S ribosomal subunit.
Predicting the Location of Functional Sites in Proteins
During my stay at the National Centre for Biological Sciences in Bangalore (India), I developed a computational method, referred to as Conserved Functional Group (CFG) analysis, for the identification of functionally important sites in proteins. This method relies on a simplified representation of the chemical groups found in amino acid side-chains to identify functional sites from a single protein structure and a number of its sequence homologues. Extensive benchmarking showed that CFG analysis can fully or partially predict the location of functional sites in approximately 96% of the 470 cases tested and that, unlike some of the other methods available, it is able to tolerate wide variations in sequence identity. As a result, this method is of considerable use in a structural genomics context, where automation, scalability and efficiency are critical, and an increasing number of protein structures are determined with no prior knowledge of function.
Since moving to Yale, I have developed and subsequently maintained an online tool to make CFG analysis available to the scientific community. The resulting siteFiNDER|3D Server may be used to predict the location of functionally important regions in proteins of known structure. It requires, at a minimum, the atomic coordinates of a query protein in PDB format.
Seidelt, B.*, Innis, C.A.*, Wilson, D.N., Gartmann, M., Armache, J.P., Villa, E., Trabuco, L.G., Becker, T., Mielke, T., Schulten, K., Steitz, T.A., Beckmann, R. (2009). Structural insight into nascent polypeptide chain-mediated translational stalling. Science 326, 1412-1415 (PubMed).
Innis, C.A. (2007). siteFiNDER|3D: a web-based tool for predicting the location of functional sites in proteins. Nucl. Acids Res. 35 (Web Server Issue), W489-494 (PubMed).
Innis, C.A., Anand, A.P., Sowdhamini, R. (2004). Prediction of functional sites in proteins using Conserved Functional Group analysis. J. Mol. Biol. 337, 1053-1068 (PubMed).
* These authors contributed equally to this work