Biology subjects

Dai, S. A.

Publications and source records attributed to Dai, S. A..

5 recordsLinked to original sources

bioRxiv2026

Computational design of a versatile, zero-radius proximity labeling enzyme

The ability to map protein interactomes and organelle proteomes is foundational for achieving a molecular understanding of living cells. Proximity labeling (PL) provides a powerful strategy for this, but existing enzymes and photocatalysts are limited by their spatial resolution, reliance on biotin, and/or in vivo compatibility. Here we report FlexID, an engineered promiscuous ligase that catalyzes the rapid attachment of diverse small-molecule probes to proximal endogenous proteins. Critically, FlexID operates through a zero-radius, direct-contact mechanism, offering superior spatial precision compared to existing PL tools. We engineered FlexID by combining the strengths of sequence- and structure-trained computational models to enhance its catalytic activity and structural stability. Biophysical analysis revealed that specific conformational changes in FlexID improve its ability to recognize diverse target proteins while simultaneously preventing the premature release of the reactive intermediate. We demonstrate FlexID's versatility through in vivo proximity labeling, comprehensive organelle proteome mapping, and a high-throughput, fluorescence-based screen for molecular glues. Our work shows that computational methods can be harnessed to create mechanistically distinct PL enzymes and establishes FlexID as a flexible, high-resolution tool for mapping protein interactions and proteomes in living cells.

bioengineering↗

bioRxiv2021

Evolutionarily divergent mTOR remodels the translatome to drive rapid wound closure and regeneration

An outstanding mystery in biology is why some species, such as the axolotl, can scarlessly heal and regenerate tissues while most mammals cannot. Here, we demonstrate that rapid activation of protein synthesis is a unique, and previously uncharacterized, feature of the injury response critical for limb regeneration in the axolotl (A. mexicanum). By applying polysome sequencing, we identify hundreds of transcripts, including antioxidants and ribosome components, which do not change in their overall mRNA abundance but are selectively activated at the level of translation from pre-existing mRNAs in response to injury. In contrast, we show that protein synthesis is not activated in response to digit amputation in the non-regenerative mouse. We further identify the mTORC1 pathway as a key upstream signal that mediates this regenerative translation response in the axolotl. Inhibition of this pathway is sufficient to suppress translation and axolotl regeneration. Surprisingly, although mTOR is highly evolutionarily conserved, we discover unappreciated expansions in mTOR protein sequence among urodele amphibians. By engineering an axolotl mTOR in human cells, we demonstrate that this change creates a hypersensitive kinase that may allow axolotls to maintain this pathway in a highly labile state primed for rapid activation. This may underlie metabolic differences and nutrient sensing between regenerative and non-regenerative species that are key to regeneration. Together, these findings highlight the unanticipated impact of the translatome on orchestrating the early steps of wound healing in highly regenerative species and provide a missing link in our understanding of vertebrate regenerative potential.

developmental biology↗

bioRxiv2020

A GTP-state specific cyclic peptide inhibitor of the GTPase Gαs

The G protein-coupled receptor (GPCR) cascade leading to production of the second messenger cAMP is replete with pharmacologically targetable receptors and enzymes with the exception of the G subunit, Gs. GTPases remain largely undruggable given the difficulty of displacing high-affinity guanine nucleotides and the lack of other drug binding sites. We explored a chemical library of 1012 cyclic peptides in order to expand the chemical search for inhibitors of this enzyme class. We identified two macrocyclic peptides, GN13 and GD20, that antagonize the active and inactive states of Gs, respectively. Both macrocyclic peptides fine-tune Gs activity with high nucleotide-binding-state selectivity and G protein class-specificity. Co-crystal structures reveal that GN13 and GD20 distinguish the conformational differences within the switch II/3 pocket and block effector interactions. The Gs inhibitors showed strong activity in cellular contexts through binding to crystallographically defined pockets. The discovery of cyclic peptide inhibitors targeting Gs provides a path for further development of state-dependent GTPase inhibitors.

biochemistry↗

bioRxiv2020

A SARS-CoV-2-Human Protein-Protein Interaction Map Reveals Drug Targets and Potential Drug-Repurposing

An outbreak of the novel coronavirus SARS-CoV-2, the causative agent of COVID-19 respiratory disease, has infected over 290,000 people since the end of 2019, killed over 12,000, and caused worldwide social and economic disruption1,2. There are currently no antiviral drugs with proven efficacy nor are there vaccines for its prevention. Unfortunately, the scientific community has little knowledge of the molecular details of SARS-CoV-2 infection. To illuminate this, we cloned, tagged and expressed 26 of the 29 viral proteins in human cells and identified the human proteins physically associated with each using affinity-purification mass spectrometry (AP-MS), which identified 332 high confidence SARS-CoV-2-human protein-protein interactions (PPIs). Among these, we identify 66 druggable human proteins or host factors targeted by 69 existing FDA-approved drugs, drugs in clinical trials and/or preclinical compounds, that we are currently evaluating for efficacy in live SARS-CoV-2 infection assays. The identification of host dependency factors mediating virus infection may provide key insights into effective molecular targets for developing broadly acting antiviral therapeutics against SARS-CoV-2 and other deadly coronavirus strains.

systems biology↗

bioRxiv2017

Extending Chemical Perturbations Of The Ubiquitin Fitness Landscape In A Classroom Setting

Although the primary protein sequence of ubiquitin (Ub) is extremely stable over evolutionary time, it is highly tolerant to mutation during selection experiments performed in the laboratory. We have proposed that this discrepancy results from the difference between fitness under laboratory culture conditions and the selective pressures in changing environments over evolutionary time scales. Building on our previous work (Mavor et al 2016), we used deep mutational scanning to determine how twelve new chemicals (3-Amino-1,2,4-triazole, 5-fluorocytosine, Amphotericin B, CaCl2, Cerulenin, Cobalt Acetate, Menadione, Nickel Chloride, p-fluorophenylalanine, Rapamycin, Tamoxifen, and Tunicamycin) reveal novel mutational sensitivities of ubiquitin residues. We found sensitization of Lys63 in eight new conditions. In total, our experiments have uncovered a sensitizing condition for every position in Ub except Ser57 and Gln62. By determining the Ubiquitin fitness landscape under different chemical constraints, our work helps to resolve the inconsistencies between deep mutational scanning experiments and sequence conservation over evolutionary timescales.\n\nBuilds onMavor D, Barlow KA, Thompson S, Barad BA, Bonny AR, Cario CL, Gaskins G, Liu Z, Deming L, Axen SD, Caceres E, Chen W, Cuesta A, Gate R, Green EM, Hulce KR, Ji W, Kenner LR, Mensa B, Morinishi LS, Moss SM, Mravic M, Muir RK, Niekamp S, Nnadi CI, Palovcak E, Poss EM, Ross TD, Salcedo E, See S, Subramaniam M, Wong AW, Li J, Thorn KS, Conchuir SO, Roscoe BP, Chow ED, DeRisi JL, Kortemme T, Bolon DN, Fraser JS. Determination of Ubiquitin Fitness Landscapes Under Different Chemical Stresses in a Classroom Setting. eLife. 2016.\n\nImpact StatementWe organized a project-based course that used deep mutational scanning in multiple chemical conditions to resolve the inconsistencies between tolerance to mutations in laboratory conditions and sequence conservation over evolutionary timescales.

bioinformatics↗