{"title":"综合机器学习、分子动力学和基于dft的方法阐明环丙沙星类似物对氟喹诺酮耐药伤寒沙门氏菌的抑制作用","authors":"Romita Guchhait, Sudha Ramaiah","doi":"10.1007/s00203-025-04452-7","DOIUrl":null,"url":null,"abstract":"<div><p><i>Salmonella enterica</i> serovar Typhi, the etiological agent of Typhoid fever, remains a critical public health concern associated with high morbidity in many developing countries. The widespread emergence of multidrug-resistant (MDR) <i>Salmonella</i> Typhi strains against the fluoroquinolone group of antibiotics, particularly ciprofloxacin, poses a significant global therapeutic challenge with underlying resistance due to mutations in quinolone-resistance determining region (QRDR) of <i>gyrA</i> gene, encoding DNA gyrase subunit A (GyrA). In pursuit of alternative therapeutic candidates, the present study was designed to evaluate ciprofloxacin analogues against prevalent GyrA mutations (S83F, D87G, and D87N) to overcome fluoroquinolone resistance through machine learning (ML)-based approach. Based on Decision table algorithm with 78% predictive accuracy, 354 potential active ciprofloxacin analogues were identified from a dataset of 400 compounds. Following molecular docking against each mutant variant, top 10 analogues were screened out based on their higher binding affinity than the reference compound, from which 8 compounds revealed acceptable drug-likeness and ADMET properties. Notably, two analogue compounds (C1) and (C5) exhibited highest average binding affinities of −34.17 kJ/mol and −33.61 kJ/mol, respectively. These compounds further yielded validatory results in molecular dynamics (MD) simulation and binding-free energy analysis using Molecular mechanics/Poisson–Boltzmann surface area. Density functional theory (DFT) study of both the compounds indicated least HOMO–LUMO energy gaps, implying enhanced chemical reactivity. Additionally, MEP (Molecular electrostatic potential) surface mapping and Fukui function analysis revealed key reactive regions, supporting favourable binding orientations. Overall, the findings identify promising ciprofloxacin analogues as lead compounds against GyrA mutations, supporting the development of structurally optimised antimicrobial therapeutics.</p></div>","PeriodicalId":8279,"journal":{"name":"Archives of Microbiology","volume":"207 10","pages":""},"PeriodicalIF":2.6000,"publicationDate":"2025-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrated machine learning, molecular dynamics, and DFT-based approach to elucidate the inhibitory effect of Ciprofloxacin analogues against fluoroquinolone-resistant Salmonella Typhi\",\"authors\":\"Romita Guchhait, Sudha Ramaiah\",\"doi\":\"10.1007/s00203-025-04452-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p><i>Salmonella enterica</i> serovar Typhi, the etiological agent of Typhoid fever, remains a critical public health concern associated with high morbidity in many developing countries. The widespread emergence of multidrug-resistant (MDR) <i>Salmonella</i> Typhi strains against the fluoroquinolone group of antibiotics, particularly ciprofloxacin, poses a significant global therapeutic challenge with underlying resistance due to mutations in quinolone-resistance determining region (QRDR) of <i>gyrA</i> gene, encoding DNA gyrase subunit A (GyrA). In pursuit of alternative therapeutic candidates, the present study was designed to evaluate ciprofloxacin analogues against prevalent GyrA mutations (S83F, D87G, and D87N) to overcome fluoroquinolone resistance through machine learning (ML)-based approach. Based on Decision table algorithm with 78% predictive accuracy, 354 potential active ciprofloxacin analogues were identified from a dataset of 400 compounds. Following molecular docking against each mutant variant, top 10 analogues were screened out based on their higher binding affinity than the reference compound, from which 8 compounds revealed acceptable drug-likeness and ADMET properties. Notably, two analogue compounds (C1) and (C5) exhibited highest average binding affinities of −34.17 kJ/mol and −33.61 kJ/mol, respectively. These compounds further yielded validatory results in molecular dynamics (MD) simulation and binding-free energy analysis using Molecular mechanics/Poisson–Boltzmann surface area. Density functional theory (DFT) study of both the compounds indicated least HOMO–LUMO energy gaps, implying enhanced chemical reactivity. Additionally, MEP (Molecular electrostatic potential) surface mapping and Fukui function analysis revealed key reactive regions, supporting favourable binding orientations. Overall, the findings identify promising ciprofloxacin analogues as lead compounds against GyrA mutations, supporting the development of structurally optimised antimicrobial therapeutics.</p></div>\",\"PeriodicalId\":8279,\"journal\":{\"name\":\"Archives of Microbiology\",\"volume\":\"207 10\",\"pages\":\"\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2025-09-08\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Archives of Microbiology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://link.springer.com/article/10.1007/s00203-025-04452-7\",\"RegionNum\":3,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"MICROBIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archives of Microbiology","FirstCategoryId":"99","ListUrlMain":"https://link.springer.com/article/10.1007/s00203-025-04452-7","RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"MICROBIOLOGY","Score":null,"Total":0}
Integrated machine learning, molecular dynamics, and DFT-based approach to elucidate the inhibitory effect of Ciprofloxacin analogues against fluoroquinolone-resistant Salmonella Typhi
Salmonella enterica serovar Typhi, the etiological agent of Typhoid fever, remains a critical public health concern associated with high morbidity in many developing countries. The widespread emergence of multidrug-resistant (MDR) Salmonella Typhi strains against the fluoroquinolone group of antibiotics, particularly ciprofloxacin, poses a significant global therapeutic challenge with underlying resistance due to mutations in quinolone-resistance determining region (QRDR) of gyrA gene, encoding DNA gyrase subunit A (GyrA). In pursuit of alternative therapeutic candidates, the present study was designed to evaluate ciprofloxacin analogues against prevalent GyrA mutations (S83F, D87G, and D87N) to overcome fluoroquinolone resistance through machine learning (ML)-based approach. Based on Decision table algorithm with 78% predictive accuracy, 354 potential active ciprofloxacin analogues were identified from a dataset of 400 compounds. Following molecular docking against each mutant variant, top 10 analogues were screened out based on their higher binding affinity than the reference compound, from which 8 compounds revealed acceptable drug-likeness and ADMET properties. Notably, two analogue compounds (C1) and (C5) exhibited highest average binding affinities of −34.17 kJ/mol and −33.61 kJ/mol, respectively. These compounds further yielded validatory results in molecular dynamics (MD) simulation and binding-free energy analysis using Molecular mechanics/Poisson–Boltzmann surface area. Density functional theory (DFT) study of both the compounds indicated least HOMO–LUMO energy gaps, implying enhanced chemical reactivity. Additionally, MEP (Molecular electrostatic potential) surface mapping and Fukui function analysis revealed key reactive regions, supporting favourable binding orientations. Overall, the findings identify promising ciprofloxacin analogues as lead compounds against GyrA mutations, supporting the development of structurally optimised antimicrobial therapeutics.
期刊介绍:
Research papers must make a significant and original contribution to
microbiology and be of interest to a broad readership. The results of any
experimental approach that meets these objectives are welcome, particularly
biochemical, molecular genetic, physiological, and/or physical investigations into
microbial cells and their interactions with their environments, including their eukaryotic hosts.
Mini-reviews in areas of special topical interest and papers on medical microbiology, ecology and systematics, including description of novel taxa, are also published.
Theoretical papers and those that report on the analysis or ''mining'' of data are
acceptable in principle if new information, interpretations, or hypotheses
emerge.