Prediction of native-state hydrogen exchange from perfectly funneled energy landscapes

Simulations based on perfectly funneled energy landscapes often capture many of the kinetic features of protein folding. We examined whether simulations based on funneled energy functions can also describe fluctuations in native-state protein ensembles. We quantitatively compared the site-specific local stability determined from structure-based folding simulations, with hydrogen exchange protection factors measured experimentally for ubiquitin, chymotrypsin inhibitor 2, and staphylococcal nuclease. Different structural definitions for the open and closed states based on the number of native contacts for each residue, as well as the hydrogen-bonding state, or a combination of both criteria were evaluated. The predicted exchange patterns agree with the experiments under native conditions, indicating that protein topology indeed has a dominant effect on the exchange kinetics. Insights into the simplest mechanistic interpretation of the amide exchange process were thus obtained.Fil: Craig, Patricio Oliver. Fundación Instituto Leloir; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Bioquimicas de Buenos Aires; Argentina. University of California San Diego. Department of Chemistry and Biochemistry; Estados UnidosFil: Lätzer, Joachim. Rutgers University. BioMaPS Institute; Estados UnidosFil: Weinkam, Patrick. University of California at San Francisco. Department of Bioengineering and Therapeutic Sciences; Estados UnidosFil: Hoffman, Ryan M. B.. University Of California At San Diego; Estados UnidosFil: Ferreiro, Diego. Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Química Biológica de la Facultad de Ciencias Exactas y Naturales; ArgentinaFil: Komives, Elizabeth A.. University Of California At San Diego; Estados UnidosFil: Wolynes, Peter G.. University Of California At San Diego; Estados Unido

Computational tools based on energy landscape theory to predict structurally diverse ensembles of transcription factors

The NF-KB/IKB system provides a challenge to the structure -function paradigm since both binding partners are partially disordered in the monomeric form. The experimental study of this system gives rise to many interesting questions. Can one describe the kinetics of coupled folding and binding? Can one faithfully invert the available low resolution data for partially folded ensembles to provide a picture of the underlying molecular details? What happens upon phosphorylation? In this thesis I show how tools to adequately answer these questions can be obtained using energy landscape theory . These tools are validated on test systems of transcription factors where experimental data are available. I demonstrate that replica simulation algorithms based on a strict Bayesian interpretation of the data can successfully invert low resolution data into the correct partially folded ensembles. In order to study the kinetics of the NF-KB/IKB system I also show that simulations with an energy function that yields a funneled but rugged energy landscape can predict the observed binding mode of the crystal structure as well as an alternative binding mode. A method for computing the frustration of partially structured ensembles is also presented. Finally I present an energy function that can predict phosphorylation induced conformational changes for the NtrC transcription facto

Computational tools based on energy landscape theory to predict structurally diverse ensembles of transcription factors

The NF-KB/IKB system provides a challenge to the structure -function paradigm since both binding partners are partially disordered in the monomeric form. The experimental study of this system gives rise to many interesting questions. Can one describe the kinetics of coupled folding and binding? Can one faithfully invert the available low resolution data for partially folded ensembles to provide a picture of the underlying molecular details? What happens upon phosphorylation? In this thesis I show how tools to adequately answer these questions can be obtained using energy landscape theory . These tools are validated on test systems of transcription factors where experimental data are available. I demonstrate that replica simulation algorithms based on a strict Bayesian interpretation of the data can successfully invert low resolution data into the correct partially folded ensembles. In order to study the kinetics of the NF-KB/IKB system I also show that simulations with an energy function that yields a funneled but rugged energy landscape can predict the observed binding mode of the crystal structure as well as an alternative binding mode. A method for computing the frustration of partially structured ensembles is also presented. Finally I present an energy function that can predict phosphorylation induced conformational changes for the NtrC transcription facto