Unveiling Berberine analogues as potential inhibitors of Escherichia coli FtsZ through machine learning molecular docking and molecular dynamics approach
Abstract The bacterial cell division protein FtsZ, a crucial GTPase, plays a vital role in the formation of the contractile Z-ring, which is essential for bacterial cytokinesis. Consequently, inhibiting FtsZ could prevent the formation of proto-filaments and interfere with the cell division machiner...
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Nature Portfolio
2025-04-01
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| Online Access: | https://doi.org/10.1038/s41598-025-98835-x |
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| author | Aditi Roy Anand Anbarasu |
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| description | Abstract The bacterial cell division protein FtsZ, a crucial GTPase, plays a vital role in the formation of the contractile Z-ring, which is essential for bacterial cytokinesis. Consequently, inhibiting FtsZ could prevent the formation of proto-filaments and interfere with the cell division machinery. The remarkable conservation of FtsZ across diverse bacterial species makes it a promising drug target for combating drug resistance. In the present study, 1072 berberine analogues were screened for favorable pharmacokinetic properties. A total of 60 compounds that fulfilled the drug-likeliness criteria and were found to be non-toxic were selected for virtual screening against Escherichia coli FtsZ protein (PDB ID: 8GZY). Molecular docking revealed a strong binding affinity of ZINC000524729297 (− 8.73 kcal/mol) and ZINC000604405393 (and − 8.55 kcal/mol) with FtsZ by strong intermolecular hydrogen bonds and hydrophobic interactions. Subsequently, the docking profiles were validated through a 500 ns MD simulation and MMPBSA analysis of the FtsZ-ligand complexes. The analysis revealed the FtsZ- ZINC524729297 and FtsZ-ZINC000604405393 complexes had the lowest root-mean-square deviation with lowest binding energy and enhanced conformational stability in a dynamic environment. These findings suggest that ZINC524729297 and ZINC000604405393 are the potent lead compound that targets FtsZ and requires further experimental validation. |
| format | Article |
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| institution | DOAJ |
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| publishDate | 2025-04-01 |
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| spelling | doaj-art-0e2f3e3fd5dc4e69822377c62eb1776b2025-08-20T03:14:10ZengNature PortfolioScientific Reports2045-23222025-04-0115111810.1038/s41598-025-98835-xUnveiling Berberine analogues as potential inhibitors of Escherichia coli FtsZ through machine learning molecular docking and molecular dynamics approachAditi Roy0Anand Anbarasu1Medical and Biological Computing Laboratory, School of Bio-Sciences and Technology (SBST), Vellore Institute of Technology (VIT)Medical and Biological Computing Laboratory, School of Bio-Sciences and Technology (SBST), Vellore Institute of Technology (VIT)Abstract The bacterial cell division protein FtsZ, a crucial GTPase, plays a vital role in the formation of the contractile Z-ring, which is essential for bacterial cytokinesis. Consequently, inhibiting FtsZ could prevent the formation of proto-filaments and interfere with the cell division machinery. The remarkable conservation of FtsZ across diverse bacterial species makes it a promising drug target for combating drug resistance. In the present study, 1072 berberine analogues were screened for favorable pharmacokinetic properties. A total of 60 compounds that fulfilled the drug-likeliness criteria and were found to be non-toxic were selected for virtual screening against Escherichia coli FtsZ protein (PDB ID: 8GZY). Molecular docking revealed a strong binding affinity of ZINC000524729297 (− 8.73 kcal/mol) and ZINC000604405393 (and − 8.55 kcal/mol) with FtsZ by strong intermolecular hydrogen bonds and hydrophobic interactions. Subsequently, the docking profiles were validated through a 500 ns MD simulation and MMPBSA analysis of the FtsZ-ligand complexes. The analysis revealed the FtsZ- ZINC524729297 and FtsZ-ZINC000604405393 complexes had the lowest root-mean-square deviation with lowest binding energy and enhanced conformational stability in a dynamic environment. These findings suggest that ZINC524729297 and ZINC000604405393 are the potent lead compound that targets FtsZ and requires further experimental validation.https://doi.org/10.1038/s41598-025-98835-xAntimicrobial resistanceEscherichia coliFtsZMolecular dockingMolecular dynamics simulationMachine learning |
| spellingShingle | Aditi Roy Anand Anbarasu Unveiling Berberine analogues as potential inhibitors of Escherichia coli FtsZ through machine learning molecular docking and molecular dynamics approach Scientific Reports Antimicrobial resistance Escherichia coli FtsZ Molecular docking Molecular dynamics simulation Machine learning |
| title | Unveiling Berberine analogues as potential inhibitors of Escherichia coli FtsZ through machine learning molecular docking and molecular dynamics approach |
| title_full | Unveiling Berberine analogues as potential inhibitors of Escherichia coli FtsZ through machine learning molecular docking and molecular dynamics approach |
| title_fullStr | Unveiling Berberine analogues as potential inhibitors of Escherichia coli FtsZ through machine learning molecular docking and molecular dynamics approach |
| title_full_unstemmed | Unveiling Berberine analogues as potential inhibitors of Escherichia coli FtsZ through machine learning molecular docking and molecular dynamics approach |
| title_short | Unveiling Berberine analogues as potential inhibitors of Escherichia coli FtsZ through machine learning molecular docking and molecular dynamics approach |
| title_sort | unveiling berberine analogues as potential inhibitors of escherichia coli ftsz through machine learning molecular docking and molecular dynamics approach |
| topic | Antimicrobial resistance Escherichia coli FtsZ Molecular docking Molecular dynamics simulation Machine learning |
| url | https://doi.org/10.1038/s41598-025-98835-x |
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