NLM DIR Seminar Schedule
UPCOMING SEMINARS
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Feb. 18, 2025 Samuel Lee
Efficient predictions of alternative protein conformations by AlphaFold2-based sequence association -
Feb. 25, 2025 Zhizheng Wang
GeneAgent: Self-verification Language Agent for Gene Set Analysis using Domain Databases -
March 4, 2025 Sofya Garushyants
TBD -
March 11, 2025 Sanasar Babajanyan
TBD -
March 18, 2025 MG Hirsch
TBD
RECENT SEMINARS
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Feb. 11, 2025 Po-Ting Lai
Enhancing Biomedical Relation Extraction with Directionality -
Feb. 4, 2025 Victor Tobiasson
On the dominance of Asgard contributions to Eukaryogenesis -
Jan. 28, 2025 Kaleb Abram
Leveraging metagenomics to investigate the co-occurrence of virome and defensome elements at large scale -
Jan. 21, 2025 Qiao Jin
Artificial Intelligence for Evidence-based Medicine -
Jan. 17, 2025 Xuegong Zhang
Using Large Cellular Models to Understand Cell Transcriptomics Language
Scheduled Seminars on Feb. 8, 2024
Contact NLMDIRSeminarScheduling@mail.nih.gov with questions about this seminar.
Abstract:
Although most proteins adopt a single energetically favorable fold, some proteins have been evolutionarily selected to reversibly interconvert between distinct folds that regulate biological processes or perform different functions. One such fold-switching protein is Escherichia coli RfaH, a member of the only known family of universally conserved transcription factors. RfaH is composed of an N-terminal NGN domain and a C-terminal KOW domain expected to fold into a beta-roll structure. Strikingly, RfaH’s KOW domain adopts an alpha-helical fold bound to the NGN domain in its apo form, but upon binding its target DNA sequence and RNA polymerase, RfaH KOW dissociates from the NGN domain and reversibly switches to the expected beta-roll topology. Previous biophysical measurements indicate that RfaH’s KOW domain is marginally stable and interconverts with a sparsely populated unfolded state with alpha-helical propensity. Although these factors may poise RfaH’s KOW domain to switch folds, the transition between the two distinctly folded states has not been observed. One possible explanation is RfaH’s poor solubility, particularly of its NGN domain, which aggregates at concentrations above 2 uM and hampers biophysical characterization. To circumvent this problem, we used the deep learning tool ProteinMPNN, to design an RfaH-like protein sequence with a soluble NGN domain. We then fine-tuned this sequence to switch folds. In this work, we use circular dichroism and nuclear magnetic resonance to characterize the unique folds assumed by the designed KOW domain. This structural characterization paves the way to biophysically characterize the fold-switching behavior of an RfaH-like protein.