Small molecules that target group II introns are potent antifungal agents

Fedorova, Olga; Jagdmann, G. Erik; Adams, Rebecca L.; Yuan, Lin; Zandt, M.C. Van; Pyle, Anna Marie

doi:10.1038/s41589-018-0142-0

Cited by 60 publications

(83 citation statements)

References 53 publications

(61 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This is significant because multi-helix junctions often comprise the core of RNA tertiary structures, like group II self-splicing introns, riboswitches and other regulatory elements. Because these elements are likely to contain well-defined pockets, they often bind specifically to small molecules, and therefore serve as possible drug targets (Warner et al, 2018, Hewitt et al, 2019, Fedorova et al, 2018.…”

Section: Discussionmentioning

confidence: 99%

“…Given the success of antimicrobials targeted against conserved RNA structural elements in other pathogen genomes (Warner et al, 2018, Fedorova et al, 2018, there is an urgent, unmet need to elucidate the genome architecture of SARS-CoV-2.…”

Section: Introductionmentioning

confidence: 99%

“…This is a major gap in our understanding because RNA structural elements in positive strand viruses play central roles in regulating all aspects of replication, translation, packaging and host defense ( McMullan et al, 2007 , Fricke et al, 2015 , Pirakitikulr et al, 2016 , Clyde and Harris, 2006 , MacFadden et al, 2018 ), so an understanding of their location and function is critical for mechanistic understanding and strategies for viral control( Barrows et al, 2018 , Adams et al, 2017 ). Given the success of antimicrobials targeted against conserved RNA structural elements in other pathogen genomes( Warner et al, 2018 , Fedorova et al, 2018 ), there is an urgent, unmet need to elucidate the genome architecture of SARS-CoV-2.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Comprehensive in-vivo secondary structure of the SARS-CoV-2 genome reveals novel regulatory motifs and mechanisms

Huston

Wan

Tavares

et al. 2020

Preprint

Self Cite

119

View full text Add to dashboard Cite

SARS-CoV-2 is the positive-sense RNA virus that causes COVID-19, a disease that has triggered a major human health and economic crisis. The genome of SARS-CoV-2 is unique among viral RNAs in its vast potential to form stable RNA structures and yet, as much as 97% of its 30 kilobases have not been structurally explored in the context of a viral infection. Our limited knowledge of SARS-CoV-2 genomic architecture is a fundamental limitation to both our mechanistic understanding of coronavirus life cycle and the development of COVID-19 RNA-based therapeutics. Here, we apply a novel long amplicon strategy to determine for the first time the secondary structure of the SARS-CoV-2 RNA genome probed in infected cells. In addition to the conserved structural motifs at the viral termini, we report new structural features like a conformationally flexible programmed ribosomal frameshifting pseudoknot, and a host of novel RNA structures, each of which highlights the importance of studying viral structures in their native genomic context. Our in-depth structural analysis reveals extensive networks of well-folded RNA structures throughout Orf1ab and reveals new aspects of SARS-CoV-2 genome architecture that distinguish it from other single-stranded, positive-sense RNA viruses. Evolutionary analysis of RNA structures in SARS-CoV-2 shows that several features of its genomic structure are conserved across beta coronaviruses and we pinpoint individual regions of well-folded RNA structure that merit downstream functional analysis. The native, complete secondary structure of SAR-CoV-2 presented here is a roadmap that will facilitate focused studies on mechanisms of replication, translation and packaging, and guide the identification of new RNA drug targets against COVID-19.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Comprehensive in-vivo secondary structure of the SARS-CoV-2 genome reveals novel regulatory motifs and mechanisms

Huston

Wan

Tavares

et al. 2020

Preprint

Self Cite

119

View full text Add to dashboard Cite

show abstract

“…The linear mitochondrial genome and/or the corresponding DNA replication machinery seems to be responsible for the tolerance of C. parapsilosis to high doses of intercalating agents, such as ethidium bromide and acridine orange (85). On the other hand, compounds interfering with the splicing of a group II intron occurring in the mitochondrial cox1 gene inhibit the growth of C. parapsilosis cells and represent potent antifungal drugs (86). Moreover, other mitochondrial functions such as the intricate electron transport pathways consisting of a conventional respiratory chain with all three phosphorylation coupling sites, a parallel respiratory chain, and alternative oxidase were shown to play a role in the susceptibility of C. parapsilosis cells to a range of drugs (87)(88)(89).…”

Section: Introductionmentioning

confidence: 99%

Candida parapsilosis: from Genes to the Bedside

et al. 2019

View full text Add to dashboard Cite

SUMMARY Patients with suppressed immunity are at the highest risk for hospital-acquired infections. Among these, invasive candidiasis is the most prevalent systemic fungal nosocomial infection. Over recent decades, the combined prevalence of non-albicans Candida species outranked Candida albicans infections in several geographical regions worldwide, highlighting the need to understand their pathobiology in order to develop effective treatment and to prevent future outbreaks. Candida parapsilosis is the second or third most frequently isolated Candida species from patients. Besides being highly prevalent, its biology differs markedly from that of C. albicans, which may be associated with C. parapsilosis’ increased incidence. Differences in virulence, regulatory and antifungal drug resistance mechanisms, and the patient groups at risk indicate that conclusions drawn from C. albicans pathobiology cannot be simply extrapolated to C. parapsilosis. Such species-specific characteristics may also influence their recognition and elimination by the host and the efficacy of antifungal drugs. Due to the availability of high-throughput, state-of-the-art experimental tools and molecular genetic methods adapted to C. parapsilosis, genome and transcriptome studies are now available that greatly contribute to our understanding of what makes this species a threat. In this review, we summarize 10 years of findings on C. parapsilosis pathogenesis, including the species’ genetic properties, transcriptome studies, host responses, and molecular mechanisms of virulence. Antifungal susceptibility studies and clinician perspectives are discussed. We also present regional incidence reports in order to provide an updated worldwide epidemiology summary.

show abstract

“…Indeed, many classes of "functional" RNAs are implicated in diseases 8 and are now considered viable drug targets [9][10][11][12] . Moreover, targeting RNAs with small molecules has garnered keen interest over the last decade [13][14][15][16] .…”

Section: Introductionmentioning

confidence: 99%

RNAPosers: Machine Learning Classifiers For RNA-Ligand Poses

Chhabra

Xie

Frank

2019

Preprint

View full text Add to dashboard Cite

Determining the 3-dimensional (3D) structures of ribonucleic acid (RNA)-small molecule complexes is critical to understanding molecular recognition in RNA. Computer docking can, in principle, be used to predict the 3D structure of RNA-small molecule complexes. Unfortunately, retrospective analysis has shown that the scoring functions that are typically used to rank poses tend to misclassify non-native poses as native, and vice versa. This misclassification of non-native poses severely limits the utility of computer docking in the context pose prediction, as well as in virtual screening. Here, we use machine learning to train a set of pose classifiers that estimate the relative "nativeness" of a set of RNA-ligand poses. At the heart of our approach is the use of a pose "fingerprint" that is a composite of a set of atomic fingerprints, which individually encode the local "RNA environment" around ligand atoms. We found that by ranking poses based on the classification scores from our machine learning classifiers, we were able to recover native-like poses better than when we ranked poses based on their docking scores. With a leave-one-out training and testing approach, we found that one of our classifiers could recover poses that were within 2.5 Å of the native poses in ∼80% of the 88 cases we examined, and similarly, on a separate validation set, we could recover such poses in ∼70% of the cases. Our set of classifiers, which we refer to as RNAPosers, should find utility as a tool to aid in RNA-ligand pose prediction and so we make RNAPosers open to the academic community via https://github.com/atfrank/RNAPosers.

show abstract

Small molecules that target group II introns are potent antifungal agents

Cited by 60 publications

References 53 publications

Comprehensive in-vivo secondary structure of the SARS-CoV-2 genome reveals novel regulatory motifs and mechanisms

Comprehensive in-vivo secondary structure of the SARS-CoV-2 genome reveals novel regulatory motifs and mechanisms

Candida parapsilosis: from Genes to the Bedside

RNAPosers: Machine Learning Classifiers For RNA-Ligand Poses

Contact Info

Product

Resources

About