The rise in multidrug-resistant bacteria highlights the critical need for novel antibiotics. This study explores clovibactin-like compounds as potential therapeutic agents targeting lipid II, a crucial component in bacterial cell wall synthesis, using in silico techniques. A total of 2624 clovibactin analogs were sourced from the PubChem database and screened using ProTox 3.0 software based on their ADME-Tox properties, prioritizing candidates with favorable pharmacokinetic profiles and minimal toxicity. Molecular docking protocols were then employed to assess the binding interactions of the selected compounds with lipid II. Our analysis identified Compound 22 as a particularly promising candidate, exhibiting strong binding affinity, stable complex formation, and high selectivity for the target. Binding energy analysis, conducted via molecular dynamics simulations, revealed a highly negative value of −25.50 kcal/mol for Compound 22, surpassing that of clovibactin and underscoring its potential efficacy. In addition, Compound 22 was prioritized due to its exceptional binding affinity to lipid II and its favorable ADME-Tox properties, suggesting a lower likelihood of adverse effects. These characteristics position Compound 22 as a promising candidate for further pharmacological development. While our computational results are encouraging, experimental validation is essential to confirm the efficacy and safety of these compounds. This study not only advances our understanding of clovibactin analogs but also contributes to the ongoing efforts to combat antimicrobial resistance through innovative antibiotic development.

The growing prevalence of multidrug-resistant Gram-negative pathogens highlights the urgent need for therapeutic strategies that complement traditional antibiotics by targeting essential virulence pathways. Glycosyltransferase LgtC, a key enzyme in lipooligosaccharide (LOS) biosynthesis, represents an attractive target for antivirulence approaches because of its essential role in bacterial immune evasion and pathogenicity. In this work, we employed an integrated in silico pipeline to identify thioglycoside analogs structurally related to the metabolic decoys FucSBn and BacSBn, evaluating their potential to hit the UDP-galactose donor pocket of LgtC. A similarity-based screening in PubChem, followed by ADME-Tox filtering yield 18 candidate analogs. Molecular docking using AutoDock-GPU revealed several candidates, most notably C-5 (- 8.36 kcal/mol) and C-18 (- 8.13 kcal/mol), to bind favorably within the donor site, showing more negative mean scoring values than natural donor UDP-α-D-galactose (- 6.74 kcal/mol). Redocking of the natural ligand reproduced the crystallographic pose, supporting the reliability of the docking protocol. To assess dynamic behavior, 100 ns molecular dynamics simulations (AMBER14) were performed for each complex. The top-scoring analogs maintained stable binding poses, with RMSD values of ~ 2.0-3.0 Å and preserved donor-like hydrogen-bond networks complemented by π-stacking and sulfur-mediated contacts. These interaction patterns suggest that the thioglycoside analogs may occupy the donor site in a manner compatible with competitive binding. While docking and MD describe different aspects of ligand recognition, several trends observed in docking, such as the favorable binding scores of C-5 and C-18, are broadly consistent with their ability to maintain stable poses during MD. Based on this consistency and scoring, the thioglycoside scaffolds C-5, C-14, and C-18 emerge as computationally prioritized candidates for subsequent biochemical testing against LgtC. Furthermore, these scaffolds offer a mechanistic basis and putative starting points for future structure-based optimization of thioglycoside analogs aimed at disrupting LOS biosynthesis in multidrug-resistant Gram-negative bacteria.

Nipah virus (NiV) is a highly lethal zoonotic pathogen with significant pandemic potential, for which no approved antiviral therapies are currently available. Viral entry is mediated by the interaction between the NiV attachment glycoprotein (NiV-G) and host ephrin receptors, particularly ephrin-B2 (EFNB2) and ephrin-B3 (EFNB3), making this interface an attractive therapeutic target. In this study, we evaluated a set of structurally related flavonoids, apigenin, cynaroside, and lonicerin, as potential modulators of the EFNB2–NiV-G and EFNB3–NiV-G interactions. These compounds were selected based on their structural similarity, reported antiviral activity, chemical diversity, and favorable drug-like properties. Apigenin was employed as a reference scaffold due to its well-characterized pharmacological profile and its suitability for guiding analog-based compound selection. Apigenin served as a reference scaffold for selecting structurally related flavonoids, which were analyzed through density functional theory optimization, molecular docking, pharmacokinetic and toxicity predictions, molecular dynamics simulations, and binding free energy calculations. These flavonoids demonstrated high predicted affinity for both the EFNB2–NiV-G and EFNB3–NiV-G interfaces. According to results, these compounds consistently interacted with residues known to play a critical role in receptor recognition, with special emphasis on leucine and tryptophan residues within the G–H loop. These residues are well established as key determinants in the entry process of Nipah virus (NiV) into host cells, highlighting the potential relevance of these flavonoid–protein interactions. Molecular dynamics analyses indicated that flavonoid binding reduced the affinity and the conformational flexibility at the receptor–glycoprotein interfaces and decreased the stability of the complexes. Pharmacokinetic and toxicity predictions suggested favorable drug-like properties for the flavonoids, with apigenin displaying the most balanced profile. Collectively, these results support the potential of selected flavonoids as modulators of EFNB2–NiV-G and EFNB3–NiV-G interactions and provide a rationale for their prioritization in experimental studies aimed at developing scaffolds for the modulation of viral entry against Nipah virus.

The rapid spread of antibiotic resistance through plasmid-mediated conjugation remains a primary global health concern. Despite its critical role in horizontal gene transfer, no approved drugs currently target this process, leaving a critical therapeutic gap. Integration Host Factor (IHF), a DNA-binding protein essential for plasmid replication and mobilization, emerges as a promising yet underexplored target for anti-conjugation strategies. This work aimed to develop a predictive computational model and identify small molecules that disrupt IHF function, thereby reducing plasmid transfer and limiting resistance gene dissemination. A curated dataset of 65 compounds with reported anti-plasmid activity was analyzed using a 3D-QSAR model based on algebraic descriptors computed with QuBiLS-MIDAS. The model was validated through leave-one-out cross-validation (Q² = 0.82), Tropsha’s criteria, and Y-scrambling. Representative compounds were selected via pharmacophore clustering and evaluated through molecular docking at both the DNA-binding site and a predicted allosteric pocket of IHF. The most promising complexes underwent 200 ns molecular dynamics simulations to assess stability and interaction patterns. The QSAR model demonstrated strong predictive performance (R² = 0.90). Docking simulations revealed more favorable binding energies at the allosteric site (up to −12.15 kcal/mol) compared to the DNA-binding site. Molecular dynamics confirmed the stability of these interactions, with allosteric complexes showing lower RMSD fluctuations and consistent binding energy profiles. Dynamic cross-correlation analysis revealed that allosteric ligand binding induces conformational changes in key catalytic residues, including Pro65, Pro61, and Leu66. These alterations may compromise DNA recognition and disrupt the initiation of replication. To our knowledge, this is the first computational study proposing allosteric inhibition of IHF as an anti-conjugation strategy. These findings provide a foundation for experimental validation and the development of novel agents to prevent horizontal gene transfer, offering a promising approach to restoring antibiotic efficacy against multidrug-resistant pathogens.