Identification of immucillin analogue natural compounds to inhibit Helicobacter pylori MTAN through high throughput virtual screening and molecular dynamics simulation

Molecular docking, molecular dynamics simulation, and MM/PBSA analysis of ginger phytocompounds as a potential inhibitor of AcrB for treating multidrug-resistant Klebsiella pneumoniae infections

The emergence of Multidrug resistance (MDR) in human pathogens has defected the existing antibiotics and compelled us to understand more about the basic science behind alternate anti-infective drug discovery. Soon, proteome analysis identified AcrB efflux pump protein as a promising drug target using plant-driven phytocompounds used in traditional medicine systems with lesser side effects. Thus, the present study aims to explore the novel, less toxic, and natural inhibitors of Klebsiella pneumoniae AcrB pump protein from 69 Zingiber officinale phyto-molecules available in the SpiceRx database through computational-biology approaches. AcrB protein's homology-modelling was carried out to get a 3D structure. The multistep-docking (HTVS, SP, and XP) were employed to eliminate less-suitable compounds in each step based on the docking score. The chosen hit-compounds underwent induced-fit docking (IFD). Based on the XP GScore, the top three compounds, epicatechin (-10.78), 6-gingerol (-9.71), and quercetin (-9.09) kcal/mol, were selected for further calculation of binding free energy (MM/GBSA). Furthermore, the short-listed compounds were assessed for their drug-like properties based on in silico ADMET properties and Pa, Pi values. In addition, the molecular dynamics simulation (MDS) studies for 250 ns elucidated the binding mechanism of epicatechin, 6-gingerol, and quercetin to AcrB. From the dynamic binding free energy calculations using MM/PBSA, 6-gingerol exhibited a strong binding affinity towards AcrB. Further, the 6-gingerol complex's energy fluctuation was observed from the free energy landscape. In conclusion, 6-gingerol has a promising inhibiting potential against the AcrB efflux pump and thus necessitates further validation through in vitro and in vivo experiments.

Computational-driven discovery of AI-2 quorum sensing inhibitor targeting the 5'- methylthioadenosine/S-adenosylhomocysteine nucleosidase (MTAN) to combat drug-resistant Helicobacter pylori

MTAN is an attainable therapeutic target for H. pylori because it may minimize virulence production, limit resistance, and impair quorum sensing without affecting gut flora. Here, 457 compounds with anti-H. pylori activity were methodically analyzed, revealing a diverse array of chemical classes and unique compounds. Molecular docking studies identified three potential compounds with high binding affinities, Dehydrocostus lactone, keramamine B, and ZINC00013531409, each having binding affinity of -7.9, -9.2, and -8.3 kcal/mol, respectively. Molecular dynamics simulations of the ZINC00013531409-MTAN interactions in comparison with Apo-MTAN demonstrated stability and interactions of 300 ns, with key residues involved in protein-ligand binding illuminated. Analysis of hydrogen bonds (Ile52, Met174, and Arg194) and secondary structure variations further elucidated the binding interactions and conformational changes within the complex. Binding free energy calculations shed light on the energetics and interactions governing the complex formation of the ZINC00013531409-MTAN complex. PCA elucidated the dominant modes of motion, along with FEL revealed the energetically favorable states and then DCCM shed light on the correlated motions between residues. Overall, this study offers a detailed computational evaluation of ZINC00013531409 with anti-H. pylori activity, highlighting toxicity profile, conformational stability, and binding interactions, providing a foundation for further drug development efforts toward bacterial resistance.

Virtual screening of natural compounds as selective inhibitors of polo-like kinase-1 at C-terminal polo box and N-terminal catalytic domain

The over-expression of Polo-like kinase-1 (PLK1) is associated with cancer prognosis due to its pivotal role in cell proliferation. The N-terminal catalytic domain (NCD) and C-terminal polo box domain (PBD) of PLK1 are critical for the activity of the protein. Drugs that inhibit PLK1 by targeting these domains are on clinical trials, but so far, none has been approved by FDA. Thus, this study targets the two domains of PLK1 to identify compounds with inhibitory potential. Four validated e-pharmacophore models from NCD (PDB ID: 2OU7 and 4J52) and PBD (PDB ID: 5NEI and 5NN2) were used to screen over 26,000 natural compounds from NPASS database. Hits were identified after the well-fitted compounds were subjected to molecular docking study and ADME prediction. The pIC50 and electronic behaviour of the identified hits selectively targeting NCD and PBD of PLK1 were predicted via an externally validated QSAR model and quantum mechanics. The results showed that CAA180504, CAA197326, CAA74619, CAA328856 modulating PLK1 at NCD, and CBB130581, CBB230713, CBB206123, CBB12656 and CBB267117 modulating PLK1 at PBD had better molecular docking scores, pharmacokinetics and drug-like properties than NCD (volasertib) and PBD (purpurogallin) reference inhibitors. The compounds all had satisfactory inhibitory (pIC50) values which range from 6.187 to 7.157. The electronic behaviours of understudied compounds using HOMO/LUMO and global descriptive parameters revealed the atomic portion of the compounds prone to donating and accepting electrons. In conclusion, the hit compounds identified from the library of natural compounds are worthy of further experimental validation.Communicated by Ramaswamy H. Sarma.

Targeting p53-MDM2 interactions to identify small molecule inhibitors for cancer therapy: beyond "Failure to rescue"

At present, disrupting p53-MDM2 interactions through small molecule ligands is a promising approach to safe treatment and management of human cancer. Tumor cells unlike the normal cells, are rapidly evolving affecting the efficacy of many approved anti-cancer agents due to drug resistance. Therefore, identifying a potential anticancer compound is crucial. Pharmacophore based virtual screening, followed by molecular docking, ADMET evaluation, and molecular dynamics studies against MDM2 protein was investigated to identify potential ligands that may act as inhibitors. The model (AHRR_1) with survival score (4.176) was selected among the top ranked generated Pharmacophore hypothesis. Validation of the model hypothesis by an external dataset of actives and inactive compounds produced significant validation attributes including; AUC = 0.85, BEDROC = 0.56 at α = 20.0, RIE = 8.18, AUAC = 0.88, and EF of 6.2 at the top 2% of the dataset. The model was use for screening the ZINC database, and the top 1375 hits satisfying the model hypothesis were subjected to molecular docking studies to understand the molecular and structural basis of selectivity of compounds for MDM2 protein. A sub-set of 25 compounds with binding energy lower than the reference inhibitors were evaluated for pharmacokinetic properties. Four compounds (ZINC02639178, ZINC06752762, ZINC38933175, and ZINC77969611) showed the most desired pharmacokinetic profile. Lastly, investigation of the dynamic behaviour of leads-protein complexes through MD simulation showed similar RMSD, RMSF, and H-bond occupancy profile compared to a reference inhibitor, suggesting stability throughout the simulation time. However, ZINC02639178 was found to satisfy the molecular enumeration the most compared to the other three leads. It may emerge as potential treatment option after extensive experimental studies. Communicated by Ramaswamy H. Sarma.