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Ph.D Dissertation Defense
"Conformational Rheostats in Protein Folding and Binding: A Computational Study"
Department of Bioengineering
University of California, Merced
Intrinsically disordered proteins (IDPs), which are centrally involved in many biological processes, fold upon binding to various biological partners. However, how IDPs leverage their intrinsic disorder to select among multiple partners via folding upon binding mechanism and mediate protein functions remains elusive. Previously, we observed a close connection between IDPs and gradual transitions of downhill folders, leading to the hypothesis that many IDPs work as conformational rheostats. Here we investigate the biological and technological implications of gradual morphing transitions using protein engineering, Molecular Dynamics (MD) simulations, and comparative analyses with experiments. We first demonstrate the design principles for protein-based scaffolds to develop rheostatic conformational transducers for biosensing applications. Next, inspired by the LEGO toy, we devised a novel modular approach to dissect the conformational landscapes of IDPs and rationalize their functional mechanisms. One particularly interesting IDP is NCBD, which binds to multiple structurally diverse partners in recruiting the basal transcription machinery. Using extensive all-atom MD simulations of NCBD and its biological partners in their free and bound forms, we decipher the hidden conformational biases in the dynamics of the heterogeneous ensemble of NCBD, undergoing gradual morphing transitions hinting at a working molecular rheostat in transcription.
Suhani Nagpal is a Ph.D. candidate in the Department of Bioengineering. She joined the Muñoz Lab in 2016. Prior to her Ph.D., she worked as a senior research fellow at the CSIR-Institute of Genomics and Integrative Biology, India, and obtained her Master’s and Bachelor’s in Biotechnology from Jaypee University of Information Technology. Her primary research interests focus on developing new approaches to characterize morphing transitions in proteins and engineer molecular scaffolds for biosensing applications using biomolecular simulations and protein engineering.
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