Exploring biogenic chalcones as DprE1 inhibitors for antitubercular activity via in silico approach

Exploring α, β-unsaturated carbonyl compounds against bacterial efflux pumps via computational approach

Antibiotic resistance has become a pressing global health crisis, with bacterial infections increasingly difficult to treat due to the emergence of multidrug resistance. This study aims to identify potential chalcone molecules that interact with two key multidrug efflux pumps, AcrB and EmrD, of Escherichia coli, using advanced computational tools. In silico ADMET (absorption, distribution, metabolism, excretion, and toxicity), drug-likeness prediction, molecular docking, and molecular dynamics simulation analyses were conducted on a ligand library comprising 100 chalcone compounds against AcrB (PDB: 4DX5) and EmrD (PDB: 2GFP). The results demonstrated that Elastichalcone A (PubChem CID 102103730) exhibited a remarkable binding affinity of -9.9 kcal/mol against AcrB, while 4'-methoxy-4-hydroxychalcone (PubChem CID 5927890) displayed a binding affinity of -9.8 kcal/mol against EmrD. Both ligands satisfied drug-likeness rules and possessed favorable pharmacokinetic profiles. Molecular dynamics simulation of the AcrB-Elastichalcone A complex remained stable over 100 ns, with minimal fluctuations in root-mean-square deviation and root-mean-square fluctuation. The screened ligand library demonstrated good drug-likeness and pharmacokinetic properties. Moreover, the MM/PB(GB)SA calculation indicated the tight binding and thermodynamic stability of the simulated protein-ligand complexes. Overall, this study highlights the potential of chalcones as promising candidates for targeting multidrug efflux pumps, offering a potential strategy to overcome antibiotic resistance. Further exploration and optimization of these compounds may lead to the development of effective therapeutics against multidrug-resistant bacterial infections.Communicated by Ramaswamy H. Sarma.

Identification of potential biogenic chalcones against antibiotic resistant efflux pump (AcrB) via computational study

The cases of bacterial multidrug resistance are increasing every year and becoming a serious concern for human health. Multidrug efflux pumps are key players in the formation of antibiotic resistance, which transfer out a broad spectrum of drugs from the cell and convey resistance to the host. Efflux pumps have significantly reduced the efficacy of the previously available antibiotic armory, thereby increasing the frequency of therapeutic failures. In gram-negative bacteria, the AcrAB-TolC efflux pump is the principal transporter of the substrate and plays a major role in the formation of antibiotic resistance. In the current work, advanced computer-aided drug discovery approaches were utilized to find hit molecules from the library of biogenic chalcones against the bacterial AcrB efflux pump. The results of the performed computational studies via molecular docking, drug-likeness prediction, pharmacokinetic profiling, pharmacophore mapping, density functional theory, and molecular dynamics simulation study provided ZINC000004695648, ZINC000014762506, ZINC000014762510, ZINC000095099506, and ZINC000085510993 as stable hit molecules against the AcrB efflux pumps. Identified hits could successfully act against AcrB efflux pumps after optimization as lead molecules.Communicated by Ramaswamy H. Sarma.

Identification of DprE1 inhibitors for tuberculosis through integrated in-silico approaches

Decaprenylphosphoryl-β-D-ribose-2'-epimerase (DprE1), a crucial enzyme in the process of arabinogalactan and lipoarabinomannan biosynthesis, has become the target of choice for anti-TB drug discovery in the recent past. The current study aims to find the potential DprE1 inhibitors through in-silico approaches. Here, we built the pharmacophore and 3D-QSAR model using the reported 40 azaindole derivatives of DprE1 inhibitors. The best pharmacophore hypothesis (ADRRR_1) was employed for the virtual screening of the chEMBL database. To identify prospective hits, molecules with good phase scores (> 2.000) were further evaluated by molecular docking studies for their ability to bind to the DprE1 enzyme (PDB: 4KW5). Based on their binding affinities (< - 9.0 kcal/mole), the best hits were subjected to the calculation of free-binding energies (Prime/MM-GBSA), pharmacokinetic, and druglikeness evaluations. The top 10 hits retrieved from these results were selected to predict their inhibitory activities via the developed 3D-QSAR model with a regression coefficient (R2) value of 0.9608 and predictive coefficient (Q2) value of 0.7313. The induced fit docking (IFD) studies and in-silico prediction of anti-TB sensitivity for these top 10 hits were also implemented. Molecular dynamics simulations (MDS) were performed for the top 5 hit molecules for 200 ns to check the stability of the hits with DprE1. Based on their conformational stability throughout the 200 ns simulation, hit 2 (chEMBL_SDF:357100) was identified as the best hit against DprE1 with an accepted safety profile. The MD results were also in accordance with the docking score, MM-GBSA value, and 3D-QSAR predicted activity. The hit 2 molecule, (N-(3-((2-(((1r,4r)-4-(dimethylamino)cyclohexyl)amino)-9-isopropyl-9H-purin-6-yl)amino)phenyl)acrylamide) could serve as a lead for the discovery of a novel DprE1 inhibiting anti-TB drug.

Synthesis, Characterization, In Silico DFT, Molecular Docking, and Dynamics Simulation Studies of Phenylhydrazono Phenoxyquinolones for Their Hypoglycemic Efficacy

A series of novel 24 phenylhydrazono phenoxyquinoline derivatives were synthesized with moderate to excellent yield and screened for their efficacy against the α-amylase enzyme through in silico studies. The structures were characterized using spectroscopic techniques such as 1HNMR, 13CNMR, and HREI-MS. Comprehensive computational studies including, drug-likeness and ADMET profiling, quantum chemical calculations, molecular docking, and molecular dynamics (MD) simulation studies, were performed. A density functional theory study of the synthesized compounds indicated a favorable reactivity profile. The synthesized novel analogues were docked against α-amylase (PDB 6OCN) enzymes to investigate the binding interactions. Based on the docking studies, one of the compounds was found to be the hit with the highest negative binding affinity for α-amylase. A MD simulation study indicated stable binding throughout the simulation.

High-throughput computational screening for identification of potential hits against bacterial Acriflavine resistance protein B (AcrB) efflux pump

Antibiotic resistance is a pressing global health challenge, driven in part by the remarkable efflux capabilities of efflux pump in AcrB (Acriflavine Resistance Protein B) protein in Gram-negative bacteria. In this study, a multi-approached computational screening strategy encompassing molecular docking, In silico absorption, distribution, metabolism, excretion and toxicity (ADMET) analysis, druglikeness assessment, molecular dynamics simulations and density functional theory studies was employed to identify novel hits capable of acting against AcrB-mediated antibiotic resistance. Ligand library was acquired from the COCONUT database. Performed computational analyses unveiled four promising hit molecules (CNP0298667, CNP0399927, CNP0321542 and CNP0269513). Notably, CNP0298667 exhibited the highest negative binding affinity of -11.5 kcal/mol, indicating a possibility of strong potential to disrupt AcrB function. Importantly, all four hits met stringent druglikeness criteria and demonstrated favorable in silico ADMET profiles, underscoring their potential for further development. MD simulations over 100 ns revealed that the CNP0321542-4DX5 and CNP0269513-4DX5 complexes formed robust and stable interactions with the AcrB efflux pump. The identified hits represent a promising starting point for the design and optimization of novel therapeutics aimed at combating AcrB-mediated antibiotic resistance in Gram-negative bacteria.Communicated by Ramaswamy H. Sarma.

Exploring binding potential of two new indole alkaloids from Nauclea officinalis against third and fourth generation EGFR: druglikeness, in silico ADMET, docking, DFT, molecular dynamics simulation, and MMGBSA study

This study investigates the anti-cancer potential of recently discovered indole alkaloids from Nauclea Officinalis against third and fourth-generation EGFR mutations using computational tools. Through ADMET profiling, druglikeness prediction, docking, and simulations, we assessed their pharmacokinetics, binding interactions, and stability. Promising druglikeness and binding affinity were observed, particularly for (±)-19-O-butylangustoline, which demonstrated stronger binding against both EGFR mutants. MD simulations confirmed stable interactions, with (±)-19-O-butylangustoline exhibiting the highest stability. These findings highlight these indole alkaloids as potential anti-cancer agents, with (±)-19-O-butylangustoline warranting further optimisation for therapeutic development. This study informs their potential through insights into molecular properties and binding energetics.

Design, synthesis and antitubercular assessment of 1, 2, 3-triazole incorporated thiazolylcarboxylate derivatives

A library of 1, 2, 3-triazole incorporated thiazolylcarboxylate derivatives (7a-q) and (8a-j) were synthesized and evaluated for their in-vitro antitubercular activity against Mycobacterium tuberculosis H37Rv. The two compounds 7h and 8h have displayed excellent antitubercular activity with MIC values of 3.12 and 1.56 µg/mL respectively (MIC values of standard drugs; Ciprofloxacin 1.56 μg/mL & Ethambutol 3.12 μg/mL). Whereas, the four compounds 7i, 7n, 7p and 8i displayed noticeable antitubercular activity with a MIC value of 6.25 µg/mL. The active compounds of the series were further studied for their cytotoxicity against RAW264.7 cell line using MTT assay. Furthermore, to study the probable mechanism of antitubercular action, physicochemical property profiling, DFT calculation and molecular docking study were executed on mycobacterial cell wall target Decaprenylphosphoryl-β-d-ribose 2'-epimerase 1 (DprE1). Among all the compounds, 7h (-10 kcal/mol) and 8h (-10.1 kcal/mol) exerted the highest negative binding affinity against the targeted DprE1 (PDB: 4NCR) protein.

Identification of hits as anti-obesity agents against human pancreatic lipase via docking, drug-likeness, in-silico ADME(T), pharmacophore, DFT, molecular dynamics, and MM/PB(GB)SA analysis

Obesity, characterized by excessive fat accumulation, is a major health concern. Inhibition of human pancreatic lipase, an enzyme involved in fat digestion, offers a potential strategy for weight loss and obesity treatment. This study aimed to identify polyphenols capable of forming stable complexes with human pancreatic lipase to block its activity. Molecular docking, density functional theory (DFT), molecular dynamics (MD) simulations, and MMPBGBSA calculations were employed to evaluate ligand binding, stability, and energy profiles. Pharmacophore modeling was also performed to identify key structural features for effective inhibition. Virtual screening identified ZINC000015120539, ZINC000000899200, ZINC000001531702, and ZINC000013340267 as potential candidates, exhibiting favorable binding and stable interactions over 100 ns MD simulations. These findings provide insights into the inhibitory potential of selected polyphenols on human pancreatic lipase and support further experimental investigations for obesity treatment.Communicated by Ramaswamy H. Sarma.