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Virtual screening identification of novel severe acute respiratory syndrome 3C-like protease inhibitors and in vitro confirmation |
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| Authors: | Nguyen Thi Thanh Hanh Ryu Hwa-Ja Lee Se-Hoon Hwang Soonwook Breton Vincent Rhee Joon Haeng Kim Doman |
| Institution: | a School of Biological Sciences and Technology, Chonnam National University, Gwangju, Republic of Korea b School of Biological Sciences and Technology and The Research Institute for Catalysis, Chonnam National University, Gwangju, Republic of Korea c Korea Institute of Science and Technology Information, Daejeon, Republic of Korea d LPC Clermont-Ferrand, Campus des Cézeaux, 63177 Aubière Cedex, France e Chonnam National University Medical School and Clinical Vaccine R&D Institute, Hwa-Sun, Republic of Korea |
| Abstract: | The 3C-like protease (3CLpro) of severe acute respiratory syndrome associated coronavirus (SARS-CoV) is vital for SARS-CoV replication and is a promising drug target. Structure based virtual screening of 308 307 chemical compounds was performed using the computation tool Autodock 3.0.5 on a WISDOM Production Environment. The top 1468 ranked compounds with free binding energy ranging from −14.0 to −17.09 kcal mol−1 were selected to check the hydrogen bond interaction with amino acid residues in the active site of 3CLpro. Fifty-three compounds from 35 main groups were tested in an in vitro assay for inhibition of 3CLpro expressed by Escherichia coli. Seven of the 53 compounds were selected; their IC50 ranged from 38.57 ± 2.41 to 101.38 ± 3.27 μM. Two strong 3CLpro inhibitors were further identified as competitive inhibitors of 3CLpro with Ki values of 9.11 ± 1.6 and 9.93 ± 0.44 μM. Hydrophobic and hydrogen bond interactions of compound with amino acid residues in the active site of 3CLpro were also identified. |
| Keywords: | 3CL Protease Severe acute respiratory syndrome SARS Coronavirus FRET-based assays Autodock Virtual screening Grid |
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