Some Remarks on Prediction of Drug-Target Interaction with Network Models

Author(s):  
Shao-Wu Zhang ◽  
Xiao-Ying Yan
2020 ◽  
Vol 21 (10) ◽  
pp. 1011-1026
Author(s):  
Bruna O. Costa ◽  
Marlon H. Cardoso ◽  
Octávio L. Franco

: Aminoglycosides and β-lactams are the most commonly used antimicrobial agents in clinical practice. This occurs because they are capable of acting in the treatment of acute bacterial infections. However, the effectiveness of antibiotics has been constantly threatened due to bacterial pathogens producing resistance enzymes. Among them, the aminoglycoside-modifying enzymes (AMEs) and β-lactamase enzymes are the most frequently reported resistance mechanisms. AMEs can inactivate aminoglycosides by adding specific chemical molecules in the compound, whereas β-lactamases hydrolyze the β-lactams ring, preventing drug-target interaction. Thus, these enzymes provide a scenario of multidrug-resistance and a significant threat to public health at a global level. In response to this challenge, in recent decades, several studies have focused on the development of inhibitors that can restore aminoglycosides and β-lactams activity. In this context, peptides appear as a promising approach in the field of inhibitors for future antibacterial therapies, as multiresistant bacteria may be susceptible to these molecules. Therefore, this review focused on the most recent findings related to peptide-based inhibitors that act on AMEs and β-lactamases, and how these molecules could be used for future treatment strategies.


2013 ◽  
Vol 13 (14) ◽  
pp. 1636-1649 ◽  
Author(s):  
Esvieta Tenorio-Borroto ◽  
Xerardo Garcia-Mera ◽  
Claudia Penuelas-Rivas ◽  
Juan Vasquez-Chagoyan ◽  
Francisco Prado-Prado ◽  
...  

Author(s):  
Ali Ezzat ◽  
Peilin Zhao ◽  
Min Wu ◽  
Xiao-Li Li ◽  
Chee-Keong Kwoh

2016 ◽  
Vol 12 (2) ◽  
pp. 520-531 ◽  
Author(s):  
Xiao-Ying Yan ◽  
Shao-Wu Zhang ◽  
Song-Yao Zhang

By implementing label propagation on drug/target similarity network with mutual interaction information derived from drug–target heterogeneous network, LPMIHN algorithm identifies potential drug–target interactions.


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