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Updated: Sep 21, 2025

High-throughput Identification of Synergistic Drug Combinations by the Overlap2 Method
Published on: May 21, 2018
A Combination of Pharmacophore-Based Virtual Screening, Structure-Based Lead Optimization, and DFT Study for the
Srimai Vuppala1, Jaeyoung Kim1, Bo-Sun Joo2
1Department of Nanoenergy Engineering, Pusan National University, Busan 46241, Korea.
Abstract:
The transcriptional regulator (TcaR) enzyme plays an important role in biofilm formation. Prevention of TcaR-DNA complex formation leads to inhibit the biofilm formation is likely to reveal therapeutic ways for the treatment of bacterial infections. To identify the novel ligands for TcaR and to provide a new idea for drug design, two efficient drug design methods, such as pharmacophore modeling and structure-based drug design, were used for virtual screening of database and lead optimization, respectively. Gemifloxacin (FDA-approved drug) was considered to generate the pharmacophore model for virtual screening of the ZINC database, and five hits, namely ZINC77906236, ZINC09550296, ZINC77906466, ZINC09751390, and ZINC01269201, were identified as novel inhibitors of TcaR with better binding energies. Using structure-based drug design, a set of 7a-7p inhibitors of S. epidermidis were considered, and Mol34 was identified with good binding energy and high fitness score with improved pharmacological properties. The active site residues ARG110, ASN20, HIS42, ASN45, ALA38, VAL63, VAL68, ALA24, VAL43, ILE57, and ARG71 are playing a promising role in inhibition process. In addition, we performed DFT simulations of final hits to understand the electronic properties and their significant role in driving the inhibitor to adopt apposite bioactive conformations in the active site. Conclusively, the newly identified and designed hits from both the methods are promising inhibitors of TcaR, which can hinder biofilm formation.
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