10 research outputs found

    Identification of a novel DNA repair inhibitor using an in silico driven approach shows effective combinatorial activity with genotoxic agents against multidrug-resistant Escherichia coli

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    Increasing antimicrobial drug resistance represents a global existential threat. Infection is a particular problem in immunocompromised individuals, such as patients undergoing cancer chemotherapy, due to the targeting of rapidly dividing cells by antineoplastic agents. We recently developed a strategy that targets bacterial nucleotide excision DNA repair (NER) to identify compounds that act as antimicrobial sensitizers specific for patients undergoing cancer chemotherapy. Building on this, we performed a virtual drug screening of a ~120,000 compound library against the key NER protein UvrA. From this, numerous target compounds were identified and of those a candidate compound, Bemcentinib (R428), showed a strong affinity toward UvrA. This NER protein possesses four ATPase sites in its dimeric state, and we found that Bemcentinib could inhibit UvrA's ATPase activity by ~90% and also impair its ability to bind DNA. As a result, Bemcentinib strongly diminishes NER's ability to repair DNA in vitro. To provide a measure of in vivo activity we discovered that the growth of Escherichia coli MG1655 was significantly inhibited when Bemcentinib was combined with the DNA damaging agent 4-NQO, which is analogous to UV. Using the clinically relevant DNA-damaging antineoplastic cisplatin in combination with Bemcentinib against the urological sepsis-causing E. coli strain EC958 caused complete growth inhibition. This study offers a novel approach for the potential development of new compounds for use as adjuvants in antineoplastic therapy

    Aprotinin Inhibits SARS-CoV-2 Replication

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    Severe acute respiratory syndrome virus 2 (SARS-CoV-2) is the cause of the current coronavirus disease 19 (COVID-19) pandemic. Protease inhibitors are under consideration as virus entry inhibitors that prevent the cleavage of the coronavirus spike (S) protein by cellular proteases. Herein, we showed that the protease inhibitor aprotinin (but not the protease inhibitor SERPINA1/alpha-1 antitrypsin) inhibited SARS-CoV-2 replication in therapeutically achievable concentrations. An analysis of proteomics and translatome data indicated that SARS-CoV-2 replication is associated with a downregulation of host cell protease inhibitors. Hence, aprotinin may compensate for downregulated host cell proteases during later virus replication cycles. Aprotinin displayed anti-SARS-CoV-2 activity in different cell types (Caco2, Calu-3, and primary bronchial epithelial cell air–liquid interface cultures) and against four virus isolates. In conclusion, therapeutic aprotinin concentrations exert anti-SARS-CoV-2 activity. An approved aprotinin aerosol may have potential for the early local control of SARS-CoV-2 replication and the prevention of COVID-19 progression to a severe, systemic disease

    PDBe-KB: a community-driven resource for structural and functional annotations.

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    The Protein Data Bank in Europe-Knowledge Base (PDBe-KB, https://pdbe-kb.org) is a community-driven, collaborative resource for literature-derived, manually curated and computationally predicted structural and functional annotations of macromolecular structure data, contained in the Protein Data Bank (PDB). The goal of PDBe-KB is two-fold: (i) to increase the visibility and reduce the fragmentation of annotations contributed by specialist data resources, and to make these data more findable, accessible, interoperable and reusable (FAIR) and (ii) to place macromolecular structure data in their biological context, thus facilitating their use by the broader scientific community in fundamental and applied research. Here, we describe the guidelines of this collaborative effort, the current status of contributed data, and the PDBe-KB infrastructure, which includes the data exchange format, the deposition system for added value annotations, the distributable database containing the assembled data, and programmatic access endpoints. We also describe a series of novel web-pages-the PDBe-KB aggregated views of structure data-which combine information on macromolecular structures from many PDB entries. We have recently released the first set of pages in this series, which provide an overview of available structural and functional information for a protein of interest, referenced by a UniProtKB accession

    Aprotinin Inhibits SARS-CoV-2 Replication

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    Severe acute respiratory syndrome virus 2 (SARS-CoV-2) is the cause of the current coronavirus disease 19 (COVID-19) pandemic. Protease inhibitors are under consideration as virus entry inhibitors that prevent the cleavage of the coronavirus spike (S) protein by cellular proteases. Herein, we showed that the protease inhibitor aprotinin (but not the protease inhibitor SERPINA1/alpha-1 antitrypsin) inhibited SARS-CoV-2 replication in therapeutically achievable concentrations. An analysis of proteomics and translatome data indicated that SARS-CoV-2 replication is associated with a downregulation of host cell protease inhibitors. Hence, aprotinin may compensate for downregulated host cell proteases during later virus replication cycles. Aprotinin displayed anti-SARS-CoV-2 activity in different cell types (Caco2, Calu-3, and primary bronchial epithelial cell air–liquid interface cultures) and against four virus isolates. In conclusion, therapeutic aprotinin concentrations exert anti-SARS-CoV-2 activity. An approved aprotinin aerosol may have potential for the early local control of SARS-CoV-2 replication and the prevention of COVID-19 progression to a severe, systemic disease

    Differentially conserved amino acid positions may reflect differences in SARS-CoV-2 and SARS-CoV behaviour

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    Motivation: SARS-CoV-2 is a novel coronavirus currently causing a pandemic. Here, we per-formed a combined in-silico and cell culture comparison of SARS-CoV-2 and the closely related SARS-CoV.Results: Many amino acid positions are differentially conserved between SARS-CoV-2 and SARS-CoV, which reflects the discrepancies in virus behaviour, i.e. more effective human-to-human transmission of SARS-CoV-2 and higher mortality associated with SARS-CoV. Variations in the S protein (mediates virus entry) were associated with differences in its interaction with ACE2 (cellular S receptor) and sensitivity to TMPRSS2 (enables virus entry via S cleavage) inhi-bition. Anti-ACE2 antibodies more strongly inhibited SARS-CoV than SARS-CoV-2 infection, probably due to a stronger SARS-CoV-2 S-ACE2 affinity relative to SARS-CoV S. Moreover, SARS-CoV-2 and SARS-CoV displayed differences in cell tropism. Cellular ACE2 and TMPRSS2 levels did not indicate susceptibility to SARS-CoV-2. In conclusion, we identified genomic varia-tion between SARS-CoV-2 and SARS-CoV that may reflect the differences in their clinical and biological behaviour

    SARS-CoV-2 and SARS-CoV differ in their cell tropism and drug sensitivity profiles

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    SARS-CoV-2 is a novel coronavirus currently causing a pandemic. We show that the majority of amino acid positions, which differ between SARS-CoV-2 and the closely related SARS-CoV, are differentially conserved suggesting differences in biological behaviour. In agreement, novel cell culture models revealed differences between the tropism of SARS-CoV-2 and SARS-CoV. Moreover, cellular ACE2 (SARS-CoV-2 receptor) and TMPRSS2 (enables virus entry via S protein cleavage) levels did not reliably indicate cell susceptibility to SARS-CoV-2. SARS-CoV-2 and SARS-CoV further differed in their drug sensitivity profiles. Thus, only drug testing using SARS-CoV-2 reliably identifies therapy candidates. Therapeutic concentrations of the approved protease inhibitor aprotinin displayed anti-SARS-CoV-2 activity. The efficacy of aprotinin and of remdesivir (currently under clinical investigation against SARS-CoV-2) were further enhanced by therapeutic concentrations of the proton pump inhibitor omeprazole (aprotinin 2.7-fold, remdesivir 10-fold). Hence, our study has also identified anti-SARS-CoV-2 therapy candidates that can be readily tested in patients

    Steroid drugs inhibit bacterial respiratory oxidases and are lethal towards methicillin-resistant Staphylococcus aureus

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    Background: Cytochrome bd complexes are respiratory oxidases found exclusively in prokaryotes that are important during infection for numerous bacterial pathogens. Methods: In silico docking was employed to screen approved drugs for their ability to bind to the quinol site of Escherichia coli cytochrome bd-I. Respiratory inhibition was assessed with oxygen electrodes using membranes isolated from E. coli and Methicillin-resistant Staphylococcus aureus strains expressing single respiratory oxidases (i.e., cytochromes bd, bo or aa3). Growth/viability assays were used to measure bacteriostatic and bactericidal effects. Results: The steroid drugs ethinylestradiol and quinestrol inhibited E. coli bd-I activity with IC50 values of 47 ± 28.9 µg/mL (158 ± 97.2 µM) and 0.2 ± 0.04 µg/mL (0.5 ± 0.1 µM), respectively. Quinestrol inhibited growth of an E. coli ‘bd-I only’ strain with an IC50 of 0.06 ± 0.02 µg/mL (0.2 ± 0.07 µM). Growth of a S. aureus ‘bd only’ strain was inhibited by quinestrol with an IC50 of 2.2 ± 0.43 µg/mL (6.0 ± 1.2 µM). Quinestrol exhibited potent bactericidal effects against S. aureus but not E. coli. Conclusions: Quinestrol inhibits cytochrome bd in E. coli and S. aureus membranes and inhibits the growth of both species yet is only bactericidal towards S. aureus

    PDBe-KB: collaboratively defining the biological context of structural data

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    none71: The Protein Data Bank in Europe - Knowledge Base (PDBe-KB, https://pdbe-kb.org) is an open collaboration between world-leading specialist data resources contributing functional and biophysical annotations derived from or relevant to the Protein Data Bank (PDB). The goal of PDBe-KB is to place macromolecular structure data in their biological context by developing standardised data exchange formats and integrating functional annotations from the contributing partner resources into a knowledge graph that can provide valuable biological insights. Since we described PDBe-KB in 2019, there have been significant improvements in the variety of available annotation data sets and user functionality. Here, we provide an overview of the consortium, highlighting the addition of annotations such as predicted covalent binders, phosphorylation sites, effects of mutations on the protein structure and energetic local frustration. In addition, we describe a library of reusable web-based visualisation components and introduce new features such as a bulk download data service and a novel superposition service that generates clusters of superposed protein chains weekly for the whole PDB archive.noneVaradi, Mihaly; Anyango, Stephen; Armstrong, David; Berrisford, John; Choudhary, Preeti; Deshpande, Mandar; Nadzirin, Nurul; Nair, Sreenath S; Pravda, Lukas; Tanweer, Ahsan; Al-Lazikani, Bissan; Andreini, Claudia; Barton, Geoffrey J; Bednar, David; Berka, Karel; Blundell, Tom; Brock, Kelly P; Carazo, Jose Maria; Damborsky, Jiri; David, Alessia; Dey, Sucharita; Dunbrack, Roland; Recio, Juan Fernandez; Fraternali, Franca; Gibson, Toby; Helmer-Citterich, Manuela; Hoksza, David; Hopf, Thomas; Jakubec, David; Kannan, Natarajan; Krivak, Radoslav; Kumar, Manjeet; Levy, Emmanuel D; London, Nir; Macias, Jose Ramon; Srivatsan, Madhusudhan M; Marks, Debora S; Martens, Lennart; McGowan, Stuart A; McGreig, Jake E; Modi, Vivek; Parra, R Gonzalo; Pepe, Gerardo; Piovesan, Damiano; Prilusky, Jaime; Putignano, Valeria; Radusky, Leandro G; Ramasamy, Pathmanaban; Rausch, Atilio O; Reuter, Nathalie; Rodriguez, Luis A; Rollins, Nathan J; Rosato, Antonio; Rubach, Paweł; Serrano, Luis; Singh, Gulzar; Skoda, Petr; Sorzano, Carlos Oscar S; Stourac, Jan; Sulkowska, Joanna I; Svobodova, Radka; Tichshenko, Natalia; Tosatto, Silvio C E; Vranken, Wim; Wass, Mark N; Xue, Dandan; Zaidman, Daniel; Thornton, Janet; Sternberg, Michael; Orengo, Christine; Velankar, SameerVaradi, Mihaly; Anyango, Stephen; Armstrong, David; Berrisford, John; Choudhary, Preeti; Deshpande, Mandar; Nadzirin, Nurul; Nair, Sreenath S; Pravda, Lukas; Tanweer, Ahsan; Al-Lazikani, Bissan; Andreini, Claudia; Barton, Geoffrey J; Bednar, David; Berka, Karel; Blundell, Tom; Brock, Kelly P; Carazo, Jose Maria; Damborsky, Jiri; David, Alessia; Dey, Sucharita; Dunbrack, Roland; Recio, Juan Fernandez; Fraternali, Franca; Gibson, Toby; Helmer-Citterich, Manuela; Hoksza, David; Hopf, Thomas; Jakubec, David; Kannan, Natarajan; Krivak, Radoslav; Kumar, Manjeet; Levy, Emmanuel D; London, Nir; Macias, Jose Ramon; Srivatsan, Madhusudhan M; Marks, Debora S; Martens, Lennart; Mcgowan, Stuart A; Mcgreig, Jake E; Modi, Vivek; Parra, R Gonzalo; Pepe, Gerardo; Piovesan, Damiano; Prilusky, Jaime; Putignano, Valeria; Radusky, Leandro G; Ramasamy, Pathmanaban; Rausch, Atilio O; Reuter, Nathalie; Rodriguez, Luis A; Rollins, Nathan J; Rosato, Antonio; Rubach, Paweł; Serrano, Luis; Singh, Gulzar; Skoda, Petr; Sorzano, Carlos Oscar S; Stourac, Jan; Sulkowska, Joanna I; Svobodova, Radka; Tichshenko, Natalia; Tosatto, Silvio C E; Vranken, Wim; Wass, Mark N; Xue, Dandan; Zaidman, Daniel; Thornton, Janet; Sternberg, Michael; Orengo, Christine; Velankar, Samee
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