In Silico Binding Free Energy Predictability by Using the Linear Interaction Energy (LIE) Method:  Bromobenzimidazole CK2 Inhibitors as a Case Study

2007 ◽  
Vol 47 (2) ◽  
pp. 572-582 ◽  
Author(s):  
A. Bortolato ◽  
S. Moro
2012 ◽  
Vol 12 (6) ◽  
pp. 551-561 ◽  
Author(s):  
O. Nicolotti ◽  
M. Convertino ◽  
F. Leonetti ◽  
M. Catto ◽  
S. Cellamare ◽  
...  

Molecules ◽  
2020 ◽  
Vol 25 (24) ◽  
pp. 5808
Author(s):  
Marko Jukič ◽  
Dušanka Janežič ◽  
Urban Bren

SARS-CoV-2, or severe acute respiratory syndrome coronavirus 2, represents a new strain of Coronaviridae. In the closing 2019 to early 2020 months, the virus caused a global pandemic of COVID-19 disease. We performed a virtual screening study in order to identify potential inhibitors of the SARS-CoV-2 main viral protease (3CLpro or Mpro). For this purpose, we developed a novel approach using ensemble docking high-throughput virtual screening directly coupled with subsequent Linear Interaction Energy (LIE) calculations to maximize the conformational space sampling and to assess the binding affinity of identified inhibitors. A large database of small commercial compounds was prepared, and top-scoring hits were identified with two compounds singled out, namely 1-[(R)-2-(1,3-benzimidazol-2-yl)-1-pyrrolidinyl]-2-(4-methyl-1,4-diazepan-1-yl)-1-ethanone and [({(S)-1-[(1H-indol-2-yl)methyl]-3-pyrrolidinyl}methyl)amino](5-methyl-2H-pyrazol-3-yl)formaldehyde. Moreover, we obtained a favorable binding free energy of the identified compounds, and using contact analysis we confirmed their stable binding modes in the 3CLpro active site. These compounds will facilitate further 3CLpro inhibitor design.


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