Table · dataset · 2026
Supplementary file 1_High-throughput screening to identify inhibitors of the MTB CARD•RNA polymerase protein-protein interaction.docx
Listed in figshare and Loughborough Research Repository and GRANTS Data and UP Research Data Repository — shown once because both records carry DOI 10.3389/ftubr.2026.1937953.s001
<p>In 2023, tuberculosis (TB) once again became the world's deadliest infectious disease, overtaking COVID-19 as the leading cause of death from a single infectious agent, Mycobacterium tuberculosis (MTB).
Description
The World Health Organization (WHO) reports that the COVID-19 pandemic has reversed years of progress in providing essential TB services and reducing TB disease burden. In 2025, TB was responsible for an estimated 1.23 million deaths globally (95% uncertainty interval: 1.13–1.33 million), and there were 400 K cases of rifamycin resistant/multidrug resistant TB (RR, RIFR, MDR).
While treatment success for drug susceptible TB remains high (88%), outcomes for MDR/RR-TB are lower but improving, reaching 71% globally. Clearly, there is a critical unmet need for novel antibiotics against MTB, exacerbated now due to COVID-19. The limited success in pursuing novel targets underscores the urgent need to revisit and reevaluate the mechanisms of action behind existing and once effective drugs, a strategy that may hold untapped potential in the fight against growing antibiotic-resistant TB.
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The MTB RNA polymerase (RNAP) is a proven target for TB treatment by rifampin (RMP), which kills both active and latent MTB. However, RMP suffers from several drawbacks including: long treatment times, activation of hPXR (inducing Cyp3A4 which is problematic for HIV-TB coinfection), and resistant mutations within RNAP. Two newer treatments with novel mechanisms of action include bedaquiline and delamanid, the former has been approved by the FDA for the treatment of multiple-drug resistant tuberculosis (MDR-MTB); however, even these new drugs already have incidences of acquired resistance.
Our goal is to develop novel drug candidates for TB treatment that: target RNAP, have the potential to shorten treatment times, and have activity against RIF<sup>R</sup> mutants. Our approach, orthogonal to the rifamycins, is to target the interaction of MTB RNAP with the required transcription factor CarD. We have previously labeled CarD with the BODIPY-FL fluorophore via engineered cysteine mutations and developed a fluorescence polarization assay to monitor its interaction with RNAP and promoter DNA.
Leveraging this target, we screened a 24 K small molecule library against CarD binding to MTB RNAP. We have now extended this screening to∼88,000 additional molecules.</p>
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Where it is published
- DOI doi.org/10.3389/ftubr.2026.1937953.s001 ↗
DOI / persistent id · from figshare com
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from figshare com
Topics
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- Inferred from text
- Disease 75%
Provenance · 4 source records, 45 field assertions
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|---|---|---|---|
| figshare | oai:figshare.com:article/34053594 | 11 d ago | JSON v1 |
| Loughborough Research Repository | oai:figshare.com:article/34053594 | 11 d ago | JSON v1 |
| GRANTS Data | oai:figshare.com:article/34053594 | 11 d ago | JSON v1 |
| UP Research Data Repository | oai:figshare.com:article/34053594 | 11 d ago | JSON v1 |
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| concepts[field].anzsrc:field:320211 | mapping · figshare com | vocabulary-mapper@1.0.0 | keywords['Infectious Diseases'] |
| concepts[field].anzsrc:field:320211 | mapping · grantsdata jst go jp | vocabulary-mapper@1.0.0 | keywords['Infectious Diseases'] |
| concepts[field].anzsrc:field:320211 | mapping · researchdata up ac za | vocabulary-mapper@1.0.0 | keywords['Infectious Diseases'] |
| concepts[field].anzsrc:field:320211 | mapping · repository lboro ac uk | vocabulary-mapper@1.0.0 | keywords['Infectious Diseases'] |
| concepts[field].local:field:astronomy | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:chemistry | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:chemistry | mapping · repository lboro ac uk | connector:repository_lboro_ac_uk@1.0.0 | |
| concepts[field].local:field:computer-science-ai | mapping · repository lboro ac uk | connector:repository_lboro_ac_uk@1.0.0 | |
| concepts[field].local:field:computer-science-ai | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · repository lboro ac uk | connector:repository_lboro_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · grantsdata jst go jp | connector:grantsdata_jst_go_jp@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata up ac za | connector:researchdata_up_ac_za@1.0.0 | |
| concepts[field].local:field:economics-finance | mapping · repository lboro ac uk | connector:repository_lboro_ac_uk@1.0.0 | |
| concepts[field].local:field:economics-finance | mapping · figshare com | connector:figshare_com@1.0.0 | |
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| concepts[field].local:field:life-sciences | mapping · figshare com | connector:figshare_com@1.0.0 | |
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| concepts[field].local:field:mathematics-statistics | mapping · repository lboro ac uk | connector:repository_lboro_ac_uk@1.0.0 | |
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| concepts[field].local:field:medicine-health | mapping · grantsdata jst go jp | connector:grantsdata_jst_go_jp@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · figshare com | connector:figshare_com@1.0.0 | |
| concepts[field].local:field:medicine-health | mapping · repository lboro ac uk | connector:repository_lboro_ac_uk@1.0.0 | |
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| concepts[field].local:field:social-science | mapping · repository lboro ac uk | connector:repository_lboro_ac_uk@1.0.0 | |
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| title | source · figshare com | connector:figshare_com@1.0.0 | /metadata/dc/title |