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McSweeney, S.

Publications and source records attributed to McSweeney, S..

6 recordsLinked to original sources

AlphaFold Protein Structure Database for Sequence-Independent Molecular Replacement

Crystallographic phasing recovers the phase information that is lost during a diffraction experiment. Molecular replacement is a dominant phasing method for the crystal structures in the protein data bank. In one form it uses a protein sequence to search a structure database for finding suitable templates for phasing. However, such sequence information is not always available such as when proteins are crystallized with unknown binding partner proteins or when the crystal is that of a contaminant. The recent development of AlphaFold has resulted in the availability of predicted protein structures for all proteins from twenty species. In this work, we tested whether AlphaFold-predicted E. coli protein structures were accurate enough for sequence-independent phasing of diffraction data from two crystallization contaminants for which we had not identified the protein. Using each of more than 4000 predicted structures as a search model, robust molecular replacement solutions were obtained which allowed the identification and structure determination of both structures, YncE and YadF. Our results advocate a general utility of AlphaFold-predicted structure database with respect to crystallographic phasing.

biochemistry↗

CREB5 reprograms nuclear interactions to promote resistance to androgen receptor targeting therapies

Metastatic castration resistant prostate cancers (mCRPC) are treated with therapies that antagonize the androgen receptor (AR). Nearly all patients develop resistance to AR-targeted therapies (ART). Our previous work identified CREB5 as an upregulated target gene in human mCRPC that promoted resistance to all clinically-approved ART. The mechanisms by which CREB5 promotes progression of mCRPC or other cancers remains elusive. Integrating ChIP-seq and rapid immunoprecipitation and mass spectroscopy of endogenous proteins (RIME), we report that cells overexpressing CREB5 demonstrate extensive reprogramming of nuclear protein-protein interactions in response to the ART agent enzalutamide. Specifically, CREB5 physically interacts with AR, the pioneering actor FOXA1, and other known co-factors of AR and FOXA1 at transcription regulatory elements recently found to be active in mCRPC patients. We identified a subset of CREB5/FOXA1 co-interacting nuclear factors that have critical functions for AR transcription (GRHL2, HOXB13) while others (TBX3, NFIC) regulated cell viability and ART resistance and were amplified or overexpressed in mCRPC. Upon examining the nuclear protein interactions and the impact of CREB5 expression on the mCRPC patient transcriptome, we found CREB5 was associated with TGF{beta} and Wnt signaling and epithelial to mesenchymal transitions, implicating these pathways in ART resistance. Overall, these observations define the molecular interactions among CREB5, FOXA1, and pathways that promote ART resistance.

cancer biology↗

The temperature-dependent conformational ensemble of SARS-CoV-2 main protease (Mpro)

The COVID-19 pandemic, instigated by the SARS-CoV-2 coronavirus, continues to plague the globe. The SARS-CoV-2 main protease, or Mpro, is a promising target for development of novel antiviral therapeutics. Previous X-ray crystal structures of Mpro were obtained at cryogenic temperature or room temperature only. Here we report a series of high-resolution crystal structures of unliganded Mpro across multiple temperatures from cryogenic to physiological, and another at high humidity. We interrogate these datasets with parsimonious multiconformer models, multi-copy ensemble models, and isomorphous difference density maps. Our analysis reveals a temperature-dependent conformational landscape for Mpro, including mobile solvent interleaved between the catalytic dyad, mercurial conformational heterogeneity in a key substrate-binding loop, and a far-reaching intramolecular network bridging the active site and dimer interface. Our results may inspire new strategies for antiviral drug development to counter-punch COVID-19 and combat future coronavirus pandemics. SynopsisX-ray crystallography at variable temperature for SARS-CoV-2 Mpro reveals a complex conformational landscape, including mobile solvent at the catalytic dyad, mercurial conformational heterogeneity in a key substrate-binding loop, and an intramolecular network bridging the active site and dimer interface.

biophysics↗

Structural Basis for SARS-CoV-2 Envelope Protein in Recognition of Human Cell Junction Protein PALS1

The COVID-19 pandemic caused by the SARS-CoV-2 virus has created a global health and economic emergency. SARS-CoV-2 viruses hijack human proteins to promote their spread and virulence including the interactions involving the viral envelope (E) protein and human proteins. To understand the structural basis for SARS-CoV-2 viral-host recognition, we used cryo-electron microscopy to determine a structure for the human cell junction protein PALS1 and SARS-CoV-2 E protein complex. The structure shows that the E protein C-terminal DLLV motif recognizes a pocket formed exclusively by hydrophobic residues from the PDZ and SH3 domains in PALS1. Our structural analysis provides an explanation for the observation that the viral E protein recruits PALS1 from lung epithelial cell junctions resulting in vascular leakage, lung damage, viral spread, and virulence. In addition, our structure provides novel targets for peptide- and small-molecule inhibitors that could block the PALS1-E interactions to reduce the E-mediated damage to vascular structures.

biochemistry↗

Structural Basis for Ca2+-Dependent Activation of a Plant Metacaspase

Plants metacaspases mediate programmed cell death in development 1,2, biotic and abiotic stresses 3, damage-induced immune response 4, and resistance to pathogen attack 5. Most metacaspases require Ca2+ for their activation and substrate processing 6-8. However, the Ca2+-dependent activation mechanism remains elusive 9-11. Here we report the crystal structure of Metacaspase 4 from Arabidopsis thaliana (AtMC4) that modulates Ca2+-dependent, damage-induced plant immune defense. The AtMC4 structure exhibits an inhibitory conformation in which a large linker domain blocks activation and substrate access. In addition, the side chain of Lys225 in the linker domain blocks the active site by sitting directly between two catalytic residues. We show that the activation of AtMC4 and cleavage of its physiological substrate involve multiple cleavages in the linker domain upon activation by Ca2+. Our analysis provides insight into the Ca2+-dependent activation of AtMC4 and lays the basis for tuning its activity in response to stresses that may help engineer more sustainable crops for production of food and biofuel.

biochemistry↗

Serial Crystallography with Multi-stage Merging of 1000’s of Images

KAMO and Blend provide particularly effective tools to manage automatically the merging of large numbers of datasets from serial crystallography. The requirement for manual intervention in the process can be reduced by extending Blend to support additional clustering options such as use of more accurate cell distance metrics and use of reflection-intensity correlation coefficients to infer "distances" among sets of reflec- tions. This increases the sensitivity to differences in unit cell parameters and allows for clustering to assemble nearly complete datasets on the basis of intensity or ampli- tude differences. If datasets are already sufficiently complete to permit it, one applies KAMO once and clusters the data using intensities only. If starting from incomplete datasets, one applies KAMO twice, first using cell parameters. In this step we use either the simple cell vector distance of the original Blend, or we use the more sensi- tive NCDist. This step tends to find clusters of sufficient size so that, when merged, each cluster is sufficiently complete to allow reflection intensities or amplitudes to be compared. One then uses KAMO again using the correlation between the reflections having a common hkl to merge clusters in a way sensitive to structural differences that may not have perturbed the cell parameters sufficiently to make meaningful clusters. Many groups have developed effective clustering algorithms that use a measurable physical parameter from each diffraction still or wedge to cluster the data into cate- gories which then can be merged, one hopes, to yield the electron density from a single protein form. Since these physical parameters are often largely independent from one another, it should be possible to greatly improve the efficacy of data clustering software by using a multi-stage partitioning strategy. Here, we have demonstrated one possible approach to multi-stage data clustering. Our strategy is to use unit-cell clustering until merged data is sufficiently complete then to use intensity-based clustering. We have demonstrated that, using this strategy, we are able to accurately cluster datasets from crystals that have subtle differences.

bioinformatics↗