Christopher C. Williams's research while affiliated with The Scripps Research Institute and other places

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Publications (3)


Systematically Studying the Effect of Small Molecules Interacting with RNA in Cellular and Preclinical Models
  • Literature Review

June 2021

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48 Reads

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11 Citations

ACS Chemical Biology

Jessica A. Bush

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Christopher C. Williams

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Samantha M. Meyer

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[...]

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Figure 1. In silico ScanFold-Fold predicted secondary structure for the SARS-CoV-2 frameshift stimulatory element (FSE) spanning nts 13422-13547. Average z-scores are overlaid on each nt via a heat map ranging from -2.34 (red) to 0.00 (blue). Top 10% of reactivities are shown for Manfredoina et al. (squares, pentagons and diamonds), Huston et al. (circles), Sun et al. (stars) and Lan et al. (triangles) at their corresponding nt positions (17-20). The attenuator hairpin and UU internal loop, recently targeted with small molecule inhibitors of -1 PRF (16), are depicted in blue shaded boxes and the slippery sequence in a gold shaded box. The interactions of the pseudoknot proposed by other groups (17-20) are shown with solid and dashed gray lines and the specific base pairing pattering are also shown in an inset. The smaller pseudoknot structure as determined by cyro-EM (14,73) is highlighted in lavender (dashed line and inset). The two orange colored pairs at the top of Stem 1 were not detected by Bhatt et al. (73) in their cryo-EM and the two red pairs at the base of stem 3 were not detected by either Bhatt et al. or Zhang et al. (14,73). All significantly covarying bps (R-scape APC corrected G-test; E < 0.05) have been highlighted with a green box.
Figure 3. Comparisons of ScanFold vs. experimental data. Receiveroperating characteristic (ROC) analysis of the in silico (at a 120 nt analysis window) ScanFold-Fold predicted base pair structure of SARS-CoV-2 against SHAPE and DMS reactivity data sets generated from SARS-CoV-2 probing experiments. Reactivities are progressively evaluated from the lowest reactivity values to the highest, at intervals of 1% of the total number of reactivity values (see Materials and Methods) and compared to the ScanFold predicted secondary structure yielding a true positive rate (y axis) and a false positive rate (x axis). Progressively increasing reactivity thresholds have their respective TPR and FPR plotted from 0% (coordinate (0,0)) to 100% (coordinate (1,1)) and each respective dataset is indicated by a line with a unique marker (see figure legend). The area under the curve (AUC) is calculated for each curve (listed in the figure legend and Supplementary Table S6) and is an indication of how well the reactivity datasets agree with the in silico ScanFold-Fold predicted structure.
Figure 5. Full analysis of the 5 UTR of SARS-CoV-2. (A) The results of the full ScanFold pipeline are shown. ScanFold metrics and base pairs have been loaded into the IGV desktop browser (91). Metric type and ranges are shown on the left side of the panel (metric descriptions can be found in Material and Methods). Here the start codon has been highlighted with a green bar and structures which correspond to previously named elements have been annotated. (B) ScanFold RNA 2D structures are shown for the 5 UTR. All base pairs shown are consistent between SARS-CoV and SARS-CoV-2, and nucleotide variations which are present within structures have been highlighted with green circles. Structures have been visualized here using VARNA (92). Top 10% of reactivities are shown for Manfredoina et al. (squares, pentagons and diamonds), Huston et al. (circles), Sun et al. (stars) and Lan et al. (triangles) at their corresponding nt positions (17-20).
A map of the SARS-CoV-2 RNA structurome
  • Article
  • Full-text available

April 2021

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209 Reads

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63 Citations

NAR Genomics and Bioinformatics

SARS-CoV-2 has exploded throughout the human population. To facilitate efforts to gain insights into SARS-CoV-2 biology and to target the virus therapeutically, it is essential to have a roadmap of likely functional regions embedded in its RNA genome. In this report, we used a bioinformatics approach, ScanFold, to deduce the local RNA structural landscape of the SARS-CoV-2 genome with the highest likelihood of being functional. We recapitulate previously-known elements of RNA structure and provide a model for the folding of an essential frameshift signal. Our results find that SARS-CoV-2 is greatly enriched in unusually stable and likely evolutionarily ordered RNA structure, which provides a large reservoir of potential drug targets for RNA-binding small molecules. Results are enhanced via the re-analyses of publicly-available genome-wide biochemical structure probing datasets that are broadly in agreement with our models. Additionally, ScanFold was updated to incorporate experimental data as constraints in the analysis to facilitate comparisons between ScanFold and other RNA modelling approaches. Ultimately, ScanFold was able to identify eight highly structured/conserved motifs in SARS-CoV-2 that agree with experimental data, without explicitly using these data. All results are made available via a public database (the RNAStructuromeDB: https://structurome.bb.iastate.edu/sars-cov-2) and model comparisons are readily viewable at https://structurome.bb.iastate.edu/sars-cov-2-global-model-comparisons.

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Small molecule recognition of disease-relevant RNA structures

September 2020

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127 Reads

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108 Citations

Chemical Society Reviews

Targeting RNAs with small molecules represents a new frontier in drug discovery and development. The rich structural diversity of folded RNAs offers a nearly unlimited reservoir of targets for small molecules to bind, similar to small molecule occupancy of protein binding pockets, thus creating the potential to modulate human biology. Although the bacterial ribosome has historically been the most well exploited RNA target, advances in RNA sequencing technologies and a growing understanding of RNA structure have led to an explosion of interest in the direct targeting of human pathological RNAs. This review highlights recent advances in this area, with a focus on the design of small molecule probes that selectively engage structures within disease-causing RNAs, with micromolar to nanomolar affinity. Additionally, we explore emerging RNA-target strategies, such as bleomycin A5 conjugates and ribonuclease targeting chimeras (RIBOTACs), that allow for the targeted degradation of RNAs with impressive potency and selectivity. The compounds discussed in this review have proven efficacious in human cell lines, patient-derived cells, and pre-clinical animal models, with one compound currently undergoing a Phase II clinical trial and another that recently garnerd FDA-approval, indicating a bright future for targeted small molecule therapeutics that affect RNA function.

Citations (3)


... Further, R-BIND (SM) was curated based on biological activity, and few ligands were extensively tested by the scientists for in vitro selectivity. 22,49,50 Increasing the number of bioactive RNA ligands, particularly with demonstrated in vitro selectivity for structurally similar RNAs and with on-target effects in biological systems, will further refine the boundaries of RNA-privileged chemical space and provide critical benchmarks for RNA-targeted probe design. ...

Reference:

Probing Bioactive Chemical Space to Discover RNA-Targeted Small Molecules
Systematically Studying the Effect of Small Molecules Interacting with RNA in Cellular and Preclinical Models
  • Citing Article
  • June 2021

ACS Chemical Biology

... Similarly, a number of computational biology studies have been undertaken for this problem. The Moss laboratory published their findings in early 2021, describing eight highly likely structures predicted with their ScanFold-based computational pipeline [35,36]. The Pyle laboratory, at nearly the same time, described their findings using the SuperFold RNA secondary structure prediction utility, identifying 61% of the genome as being base paired [37]. ...

A map of the SARS-CoV-2 RNA structurome

NAR Genomics and Bioinformatics

... Campagne et al. 2019;Kelly et al. 2021;Meyer et al. 2020;Umuhire Juru & Hargrove 2021;Warner et al. 2018). Considering the regulatory roles of the UTRs of viruses, it is interesting to explore the druggability of these regions. ...

Small molecule recognition of disease-relevant RNA structures

Chemical Society Reviews