With the progressive and ever-increasing antibacterial resistance pathway, the need for novel antibiotic design becomes critical. Sulfonamides are one of the more effective antibiotics against bacteria. In this work, several novel sulfonamide hybrids including coumarin and isoxazole group were synthesized in five steps starting from coumarin-3-carboxylic acid and 3-amino-5-methyl isoxazole and assayed for antibacterial activity. The samples were obtained in good to high yield and characterized by FT-IR,¹³C-NMR,¹H-NMR, CHN and melting point techniques. 3D-QSAR is a fast, easy, cost-effective, and high throughput screening method to predict the effect of the compound's efficacy, which notably decreases the needed price for experimental drug assay. The 3D-QSAR model displayed acceptable predictive and descriptive capability to find r2 and q2 the pMIC of the designed compound. Key descriptors, which robustly depend on antibacterial activity, perhaps were explained by this method. According to this model, among the synthesized sulfonamide hybrids,9band9fhad the highest effect on the gram-negative and gram-positive bacteria based on the pMIC. The 3D-QSAR results were confirmed in the experimental assays, demonstrating that our model is useful for developing new antibacterial agents. The work proposes a computationally-driven strategy for designing and discovering new sulfonamide scaffold for bacterial inhibition.

In this study, eleven novel chromene sulfonamide hybrids were synthesized by a convenient method in accordance with green chemistry. At first, chromene derivatives (1–9a) were prepared through the multi-component reaction between aryl aldehydes, malononitrile, and 3-aminophenol. Then, synthesized chromenes were reacted with appropriate sulfonyl chlorides by grinding method to give the corresponding chromene sulfonamide hybrids (1–11b). Synthesized hybrids were obtained in good to high yield and characterized by IR, ¹HNMR, ¹³CNMR, CHN and melting point techniques. In addition, the broth microdilution assay was used to determine the minimal inhibitory concentration of newly synthesized chromene-sulfonamide hybrids. The MTT test was used to determine the cytotoxicity and apoptotic activity of the newly synthesized compounds against fibroblast L929 cells. The 3D‑QSAR analysis confirmed the experimental assays, demonstrating that our predictive model is useful for developing new antibacterial inhibitors. Consequently, molecular docking studies were performed to validate the findings of the 3D-QSAR analysis, confirming the potential binding interactions of the synthesized chromene-sulfonamide hybrids with the target enzymes. Molecular docking studies were employed to support the 3D-QSAR predictions, providing insights into the binding interactions between the newly synthesized chromene-sulfonamide hybrids and their target bacterial enzymes, thereby reinforcing the potential efficacy of these compounds as antibacterial agents. Also, some of the experimental outcomes supported or conflicted with the pharmacokinetic prediction (especially about compound carcinogenicity). The performance of ADMET predictor results was assessed. The work presented here proposes a computationally driven strategy for designing and discovering a new sulfonamide scaffold for bacterial inhibition.

Resistance-nodulation-cell devision (RND) efflux pump variants have attracted a great deal of attention for efflux of many antibiotic classes, which leads to multidrug-resistant bacteria. The present study aimed to discover the interaction between the RND efflux pumps and antibiotics, find the conserved and hot spot residues, and use this information to target the most frequent RND efflux pumps. Protein sequence and 3D conformational alignments, pharmacophore modeling, molecular docking, and molecular dynamics simulation were used in the first level for discovering the function of the residues in interaction with antibiotics. In the second level, pharmacophore-based screening, structural-based screening, multistep docking, GRID MIF, pharmacokinetic modeling, fragment molecular orbital, and MD simulation were utilized alongside the former level information to find the most proper inhibitors. Five conserved residues, containing Ala209, Tyr404, Leu415, Asp416, and Ala417, as well as their counterparts in other OMPs were evaluated as the crucial conserved residues. MD simulation confirmed that a number of these residues had a key role in the performance of the efflux antibiotics; therefore, some of them were hot spot residues. Fourteen ligands were selected, four of which interacted with all the crucial conserved residues. NPC100251 was the fittest OMP inhibitor after pharmacokinetic computations. The second-level MD simulation and FMO supported the efficacy of the NPC100251. It was exhibited that perhaps OMPs worked as the intelligent and programable protein. NPC100251 was the strongest OMPs inhibitor, and may be a potential therapeutic candidate for MDR infections.

Background: The SARS-CoV-2 virus is a new highly contagious Coronavirus with a positive-sense RNA encoding 16 non-structural proteins (nsps16, nsp15, nsp3). In this study, the coronavirus pathogenicity and the losartan functional ligand for inhibiting TRPM2 and macrodomain have been molecularly evaluated.Material and method: In this study, the structures of macrodomain binding ADP ribose in CoVs and human Transient Receptor Potential Cation Channel Subfamily M Member 2 (TRPM2) protein were downloaded from protein data bank. Then, a virtual screening was done to recognize the hit compounds from GalaXi_2019-10, KnowledgeSpace_2019-05, and REALspace_2019-12 databases. This collection, then, was imported to the ligandScout software, on the base of Adenosine Diphosphate Ribose (ADPR) pharmacophore model. Result: Among seven compounds, five compounds were finally evaluated as the structural analogs of ADPR or other nucleotides, from which one compound was a non-FDA-approved sulphonamide and was removed. The other compound, losartan, was finally selected for molecular docking and molecular dynamic simulation. According to the virtual screening and docking, losartan was candidate as an effective ligand for TRPM2 and macrodomain. Conclusion: In the current study losartan earned a proper dock score and binding affinity to create the complexes with TRPM2 and macrodomain. The inhibitory effect of losartan on PARP has been shown and it could interfere positively in several points (PARP, PARG- macrodomain and TRPM2) and decreases oxidative stress and apoptosis in COVID-19.

Pseudomonas aeruginosa has different antibiotic resistance pathways, such as broad-spectrum lactamases and metallo-β-lactamases (MBL), penicillin-binding protein (PBP) alteration, and active efflux pumps. Polymerase chain reaction (PCR) and sequencing methods were applied for double-locus sequence typing (DLST) and New Delhi metallo-β-lactamase (NDM) typing. We deduced the evolutionary pathways for DLST and NDM genes of P. aeruginosa using phylogenetic network. Among the analyzed isolates, 62.50% of the P. aeruginosa isolates were phenotypically carbapenem resistance (CARBR) isolates. Characterization of isolates revealed that the prevalence of bla_NDM, bla_VIM, bla_IMP, undetermined carbapenemase, and MexAB-OprM were 27.5%, 2%, 2.5%, 12.5%, and 15%, respectively. The three largest clusters found were DLST t20-105, DLST t32-39, and DLST t32-52. The network phylogenic tree revealed that DLST t26-46 was a hypothetical ancestor for other DLSTs, and NDM-1 was as a hypothetical ancestor for NDMs. The combination of the NDM and DLST phylogenic trees revealed that DLST t32-39 and DLST tN2-N3 with NDM-4 potentially derived from DLST t26-46 along with NDM-1. Similarly, DLST t5-91 with NDM-5 diversified from DLST tN2-N3 with NDM-4. This is the first study in which DLST and NDM evolutionary routes were performed to investigate the origin of P. aeruginosa isolates. Our study showed that the utilization of medical equipment common to two centers, staff members common to two centers, limitations in treatment options, and prescription of unnecessary high levels of meropenem are the main agents that generate new types of resistant bacteria and spread resistance among hospitals.

New Delhi metallo-β-lactamase variants and different types of metallo-β-lactamases have attracted enormous consideration for hydrolyzing almost all β-lactam antibiotics, which leads to multi drug resistance bacteria. Metallo-β-lactamases genes have disseminated in hospitals and all parts of the world and became a public health concern. There is no inhibitor for new Delhi metallo-β-lactamase-1 and other metallo-β-lactamases classes, so metallo-β-lactamases inhibitor drugs became an urgent need. In this study, multi-steps virtual screening was done over the NPASS database with 35032 natural compounds. At first Captopril was extracted from 4EXS PDB code and use as a template for the first structural screening and 500 compounds obtained as hit compounds by molecular docking. Then the best ligand, i.e. NPC120633 was used as templet and 800 similar compounds were obtained. As a final point, ten compounds i.e. NPC171932, NPC100251, NPC18185, NPC98583, NPC112380, NPC471403, NPC471404, NPC472454, NPC473010 and NPC300657 had proper docking scores, and a 50 ns molecular dynamics simulation was performed for calculation binding free energy of each compound with new Delhi metallo-β-lactamase. 3D conformational alignment and protein sequence alignment of all new Delhi metallo-β-lactamase variants and all types of metallo-β-lactamases were done. Then the conserved and crucial residues in the catalytic activity of metallo-β-lactamases were detected. These residues had similar 3D coordinates in the 3D conformational alignment. So it is possible that all types of metallo-β-lactamases can inhibit by these ten compounds. Therefore, these compounds were proper to mostly inhibit all new Delhi metallo-β-lactamase and metallo-β-lactamases in experimental studies.