Multidimensional Criteria for Virtual Screening of PqsR Inhibitors Based on Pharmacophore, Docking, and Molecular Dynamics
Pseudomonas aeruginosa is a clinically challenging pathogen due to its high resistance to antibiotics. Quorum sensing inhibitors (QSIs) have been proposed as a promising strategy to overcome this resistance by interfering with the bacterial communication system. Among the potential targets of QSIs, PqsR is a key regulator of quorum sensing in Pseudomonas aeruginosa. However, the current research on PqsR inhibitors is limited by the lack of diversity in the chemical structures and the screening methods. Therefore, this study aims to develop a multidimensional screening model for PqsR inhibitors based on both ligand- and receptor-based approaches. First, a pharmacophore model was constructed from a training set of PqsR inhibitors to identify the essential features and spatial arrangement for the activity. Then, molecular docking and dynamics simulations were performed to explore the core interactions between PqsR inhibitors and their receptor. The results indicate that an effective PqsR inhibitor should possess two aromatic rings, one hydrogen bond acceptor, and two hydrophobic groups and should form strong interactions with the following four amino acid residues: TYR_258, ILE_236, LEU_208, and GLN_194. Moreover, the docking score and the binding free energy should be lower than -8 kcal/mol and -40 kcal/mol, respectively. Finally, the validity of the multidimensional screening model was confirmed by a test set of PqsR inhibitors, which showed a higher accuracy than the existing screening methods based on single characteristics. This multidimensional screening model would be a useful tool for the discovery and optimization of PqsR inhibitors in the future.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:25 |
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| Enthalten in: |
International journal of molecular sciences - 25(2024), 3 vom: 03. Feb. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Xiao, Haichuan [VerfasserIn] |
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| Links: |
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| Themen: |
Anti-Bacterial Agents |
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| Anmerkungen: |
Date Completed 14.02.2024 Date Revised 14.02.2024 published: Electronic Citation Status MEDLINE |
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| doi: |
10.3390/ijms25031869 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM368286428 |
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| 500 | |a published: Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a Pseudomonas aeruginosa is a clinically challenging pathogen due to its high resistance to antibiotics. Quorum sensing inhibitors (QSIs) have been proposed as a promising strategy to overcome this resistance by interfering with the bacterial communication system. Among the potential targets of QSIs, PqsR is a key regulator of quorum sensing in Pseudomonas aeruginosa. However, the current research on PqsR inhibitors is limited by the lack of diversity in the chemical structures and the screening methods. Therefore, this study aims to develop a multidimensional screening model for PqsR inhibitors based on both ligand- and receptor-based approaches. First, a pharmacophore model was constructed from a training set of PqsR inhibitors to identify the essential features and spatial arrangement for the activity. Then, molecular docking and dynamics simulations were performed to explore the core interactions between PqsR inhibitors and their receptor. The results indicate that an effective PqsR inhibitor should possess two aromatic rings, one hydrogen bond acceptor, and two hydrophobic groups and should form strong interactions with the following four amino acid residues: TYR_258, ILE_236, LEU_208, and GLN_194. Moreover, the docking score and the binding free energy should be lower than -8 kcal/mol and -40 kcal/mol, respectively. Finally, the validity of the multidimensional screening model was confirmed by a test set of PqsR inhibitors, which showed a higher accuracy than the existing screening methods based on single characteristics. This multidimensional screening model would be a useful tool for the discovery and optimization of PqsR inhibitors in the future | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a PqsR | |
| 650 | 4 | |a Pseudomonas aeruginosa | |
| 650 | 4 | |a molecular docking | |
| 650 | 4 | |a molecular dynamics | |
| 650 | 4 | |a pharmacophore modeling | |
| 650 | 4 | |a virtual screening | |
| 650 | 7 | |a Anti-Bacterial Agents |2 NLM | |
| 700 | 1 | |a Li, Jiahao |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Dongdong |e verfasserin |4 aut | |
| 700 | 1 | |a Du, Jiarui |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Jie |e verfasserin |4 aut | |
| 700 | 1 | |a Lin, Shuqi |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, Haibo |e verfasserin |4 aut | |
| 700 | 1 | |a Sun, Pinghua |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Jun |e verfasserin |4 aut | |
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