scholarly journals Molecular Mechanism of the Flavonoid Natural Product Dryocrassin ABBA against Staphylococcus aureus Sortase A

Molecules ◽  
2016 ◽  
Vol 21 (11) ◽  
pp. 1428 ◽  
Author(s):  
Bing Zhang ◽  
Xiyan Wang ◽  
Lin Wang ◽  
Shuiye Chen ◽  
Dongxue Shi ◽  
...  
2016 ◽  
Vol 13 (7) ◽  
pp. 668-675
Author(s):  
Saba Farooq ◽  
. Atia-tul-Wahab ◽  
Ali Azarpira ◽  
. Atta-ur-Rahman ◽  
M. Iqbal Choudhary

2016 ◽  
Vol 7 (1) ◽  
Author(s):  
Hyun Ok Ham ◽  
Zheng Qu ◽  
Carolyn A. Haller ◽  
Brent M. Dorr ◽  
Erbin Dai ◽  
...  

ChemMedChem ◽  
2020 ◽  
Vol 15 (10) ◽  
pp. 839-850 ◽  
Author(s):  
Fabian Barthels ◽  
Gabriella Marincola ◽  
Tessa Marciniak ◽  
Matthias Konhäuser ◽  
Stefan Hammerschmidt ◽  
...  

2021 ◽  
Author(s):  
Xiang-Na Guan ◽  
Tao Zhang ◽  
Teng Yang ◽  
Ze Dong ◽  
Song Yang ◽  
...  

The housekeeping sortase A (SrtA), a membrane-associated cysteine transpeptidase, is responsible for anchoring surface proteins to the cell wall peptidoglycan in Gram-positive bacteria. This process is essential for the regulation...


2019 ◽  
Vol 80 (8) ◽  
pp. 1136-1145 ◽  
Author(s):  
Georgiana Nitulescu ◽  
Dragos P. Mihai ◽  
Isabela M. Nicorescu ◽  
Octavian T. Olaru ◽  
Anca Ungurianu ◽  
...  

2019 ◽  
Vol 32 (12) ◽  
pp. 555-564
Author(s):  
Magdalena Wójcik ◽  
Susana Vázquez Torres ◽  
Wim J Quax ◽  
Ykelien L Boersma

Abstract Staphylococcus aureus sortase A (SaSrtA) is an enzyme that anchors proteins to the cell surface of Gram-positive bacteria. During the transpeptidation reaction performed by SaSrtA, proteins containing an N-terminal glycine can be covalently linked to another protein with a C-terminal LPXTG motif (X being any amino acid). Since the sortase reaction can be performed in vitro as well, it has found many applications in biotechnology. Although sortase-mediated ligation has many advantages, SaSrtA is limited by its low enzymatic activity and dependence on Ca2+. In our study, we evaluated the thermodynamic stability of the SaSrtA wild type and found the enzyme to be stable. We applied consensus analysis to further improve the enzyme’s stability while at the same time enhancing the enzyme’s activity. As a result, we found thermodynamically improved, more active and Ca2+-independent mutants. We envision that these new variants can be applied in conjugation reactions in low Ca2+ environments.


Marine Drugs ◽  
2018 ◽  
Vol 17 (1) ◽  
pp. 16 ◽  
Author(s):  
Tiago Dias ◽  
Susana Gaudêncio ◽  
Florbela Pereira

The risk of methicillin-resistant Staphylococcus aureus (MRSA) infection is increasing in both the developed and developing countries. New approaches to overcome this problem are in need. A ligand-based strategy to discover new inhibiting agents against MRSA infection was built through exploration of machine learning techniques. This strategy is based in two quantitative structure–activity relationship (QSAR) studies, one using molecular descriptors (approach A) and the other using descriptors (approach B). In the approach A, regression models were developed using a total of 6645 molecules that were extracted from the ChEMBL, PubChem and ZINC databases, and recent literature. The performance of the regression models was successfully evaluated by internal and external validation, the best model achieved R2 of 0.68 and RMSE of 0.59 for the test set. In general natural product (NP) drug discovery is a time-consuming process and several strategies for dereplication have been developed to overcome this inherent limitation. In the approach B, we developed a new NP drug discovery methodology that consists in frontloading samples with 1D NMR descriptors to predict compounds with antibacterial activity prior to bioactivity screening for NPs discovery. The NMR QSAR classification models were built using 1D NMR data (1H and 13C) as descriptors, from crude extracts, fractions and pure compounds obtained from actinobacteria isolated from marine sediments collected off the Madeira Archipelago. The overall predictability accuracies of the best model exceeded 77% for both training and test sets.


2019 ◽  
Vol 27 (19) ◽  
pp. 115043 ◽  
Author(s):  
Patrick M. Wehrli ◽  
Ivana Uzelac ◽  
Thomas Olsson ◽  
Tomas Jacso ◽  
Daniel Tietze ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document