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Full-Text Articles in Physical Sciences and Mathematics
Prediction And Confirmation Of A Switch-Like Region Within The N-Terminal Domain Of Hsirt1, Angelina T. Huynh, Thi-Tina N. Nguyen, Carina A. Villegas, Saira Montemorso, Benjamin Strauss, Richard A. Pearson, Jason G. Graham, Jonathan Oribello, Rohit Suresh, Brooke Lustig, Ningkun Wang
Prediction And Confirmation Of A Switch-Like Region Within The N-Terminal Domain Of Hsirt1, Angelina T. Huynh, Thi-Tina N. Nguyen, Carina A. Villegas, Saira Montemorso, Benjamin Strauss, Richard A. Pearson, Jason G. Graham, Jonathan Oribello, Rohit Suresh, Brooke Lustig, Ningkun Wang
Faculty Research, Scholarly, and Creative Activity
Many proteins display conformational changes resulting from allosteric regulation. Often only a few residues are crucial in conveying these structural and functional allosteric changes. These regions that undergo a significant change in structure upon receiving an input signal, such as molecular recognition, are defined as switch- like regions. Identifying these key residues within switch-like regions can help elucidate the mechanism of allosteric regulation and provide guidance for synthetic regulation. In this study, we combine a novel computational workflow with biochemical methods to identify a switch-like region in the N-terminal domain of human SIRT1 (hSIRT1), a lysine deacetylase that plays important …
Statistical Potentials For Rna-Protein Interactions Optimized By Cma-Es, Takayuki Kimura, Nobuaki Yasuo, Masakazu Sekijima, Brooke Lustig
Statistical Potentials For Rna-Protein Interactions Optimized By Cma-Es, Takayuki Kimura, Nobuaki Yasuo, Masakazu Sekijima, Brooke Lustig
Faculty Research, Scholarly, and Creative Activity
Characterizing RNA-protein interactions remains an important endeavor, complicated by the difficulty in obtaining the relevant structures. Evaluating model structures via statistical potentials is in principle straight-forward and effective. However, given the relatively small size of the existing learning set of RNA-protein complexes optimization of such potentials continues to be problematic. Notably, interaction-based statistical potentials have problems in addressing large RNA-protein complexes. In this study, we adopted a novel strategy with covariance matrix adaptation (CMA-ES) to calculate statistical potentials, successfully identifying native docking poses.