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1.
J Antibiot (Tokyo) ; 75(6): 321-332, 2022 06.
Article in English | MEDLINE | ID: covidwho-1878523

ABSTRACT

Staphylococcus aureus is one of the most dangerous pathogens commonly associated with high levels of morbidity and mortality. Sortase A is considered as a promising molecular target for the development of antistaphylococcal agents. Using hybrid virtual screening approach and FRET analysis, we have identified five compounds able to decrease the activity of sortase A by more than 50% at the concentration of 200 µM. The most promising compound was 2-(2-amino-3-chloro-benzoylamino)-benzoic acid which was able to inhibit S. aureus sortase A at the IC50 value of 59.7 µM. This compound was selective toward sortase A compared to other four cysteine proteases - cathepsin L, cathepsin B, rhodesain, and the SARS-CoV2 main protease. Microscale thermophoresis experiments confirmed that this compound bound sortase A with KD value of 189 µM. Antibacterial and antibiofilm assays also confirmed high specificity of the hit compound against two standard and three wild-type, S. aureus hospital infection isolates. The effect of the compound on biofilms produced by two S. aureus ATCC strains was also observed suggesting that the compound reduced biofilm formation by changing the biofilm structure and thickness.


Subject(s)
COVID-19 , Staphylococcal Infections , Aminoacyltransferases , Anti-Bacterial Agents/chemistry , Anti-Bacterial Agents/pharmacology , Bacterial Proteins/metabolism , Biofilms , Cysteine Endopeptidases , Humans , Microbial Sensitivity Tests , RNA, Viral/pharmacology , SARS-CoV-2 , Staphylococcus aureus
2.
Mol Inform ; 40(1): e2000144, 2021 01.
Article in English | MEDLINE | ID: covidwho-1012199

ABSTRACT

The analysis of B-factor profiles from X-ray protein structures can be utilized for structure-based drug design since protein mobility changes have been associated with the quality of protein-ligand interactions. With the BANΔIT (B'-factor analysis and ΔB' interpretation toolkit), we have developed a JavaScript-based browser application that provides a graphical user interface for the normalization and analysis of B'-factor profiles. To emphasize the usability for rational drug design applications, we have analyzed a selection of crystallographic protein-ligand complexes and have given exemplary conclusions for further drug optimization including the development of a B'-factor-supported pharmacophore model for SARS CoV-2 main protease inhibitors. BANΔIT is available online at https://bandit.uni-mainz.de. The source code can be downloaded from https://github.com/FBarthels/BANDIT.


Subject(s)
Adenosine Monophosphate/analogs & derivatives , COVID-19/drug therapy , Drug Design , Protease Inhibitors/chemistry , SARS-CoV-2/chemistry , Web Browser , Adenosine Monophosphate/chemistry , Adenosine Monophosphate/therapeutic use , Computational Biology , Humans , Protease Inhibitors/therapeutic use
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