Integrated computer-aided drug design and biophysical simulation approaches to determine natural anti-bacterial compounds for Acinetobacter baumannii

Identification of novel drug targets for Helicobacter pylori: structure-based virtual screening of potential inhibitors against DAH7PS protein involved in the shikimate pathway

Background

Helicobacter pylori, a bacterium associated with severe gastrointestinal diseases and malignancies, poses a significant challenge because of its increasing antibiotic resistance rates. This study aimed to identify potential drug targets and inhibitors against H. pylori using a structure-based virtual screening (SBVS) approach.

Methods

Core-proteome analysis of 132 H. pylori genomes was performed using the EDGAR database. Essential genes were identified and human and gut microbiota homolog proteins were excluded. The DAH7PS protein involved in the shikimate pathway was selected for the structure-based virtual screening (SBVS) approach. The tertiary structure of the protein was predicted through homology modeling (based on PDB ID: 5UXM). Molecular docking was performed to identify potential inhibitors of DAH7PS among StreptomeDB compounds using the AutoDock Vina tool. Molecular dynamics (MD) simulations assessed the stability of DAH7PS-ligand complexes. The complexes were further evaluated in terms of their binding affinity, Lipinski's Rule of Five, and ADMET properties.

Results

A total of 54 novel drug targets with desirable properties were identified. DAH7PS was selected for further investigation, and virtual screening of StreptomeDB compounds yielded 36 high-affinity binding of the ligands. Two small molecules, 6,8-Dihydroxyisocoumarin-3-carboxylic acid and Epicatechin, also showed favorable RO5 and ADMET properties. MD simulations confirmed the stability and reliability of DAH7PS-ligand complexes, indicating their potential as inhibitors.

Conclusion

This study identified 54 novel drug targets against H. pylori. The DAH7PS protein as a promising drug target was evaluated using a computer-aided drug design. 6,8-Dihydroxyisocoumarin-3-carboxylic acid and Epicatechin demonstrated desirable properties and stable interactions, highlighting their potential to inhibit DAH7PS as an essential protein. Undoubtedly, more experimental validations are needed to advance these findings into practical therapies for treating drug-resistant H. pylori.

Novel Coumarins Derivatives for A. baumannii Lung Infection Developed by High-Throughput Screening and Reinforcement Learning

With the increasing resistance of Acinetobacter baumannii (A. baumannii) to antibiotics, researchers have turned their attention to the development of new antimicrobial agents. Among them, coumarin-based heterocycles have attracted much attention due to their unique biological activities, especially in the field of antibacterial infection. In this study, a series of coumarin derivatives were synthesized and screened for their bactericidal activities (Ren et al. 2018; Salehian et al. 2021). The inhibitory activities of these compounds on bacterial strains were evaluated, and the related mechanism of the new compounds was explored. Firstly, the MIC values and bacterial growth curves were measured after compound treatment to evaluate the antibacterial activity in vitro. Then, the in vivo antibacterial activities of the new compounds were assessed on A. baumannii-infected mice by determining the mice survival rates, counting bacterial CFU numbers, measuring inflammatory cytokine levels, and histopathology analysis. In addition, the ROS levels in the bacterial cells were measured with DCFH-DA detection kit. Furthermore, the potential target and detailed mechanism of the new compounds during infection disease therapy were predicted and evidenced with molecular docking. After that, ADMET characteristic prediction was completed, and novel, synthesizable, drug-effective molecules were optimized with reinforcement learning study based on the probed compound as a training template. The interaction between the selected structures and target proteins was further evidenced with molecular docking. This series of innovative studies provides important theoretical and experimental data for the development of new anti-A. baumannii infection drugs.

Based on molecular docking and real-time PCR technology, the two-component system Bae SR was investigated on the mechanism of drug resistance in CRAB

This study aimed to explore the role of the two-component system Bae SR in the mechanism of drug resistance in carbapenem-resistant A. baumannii (CRAB) using molecular docking and real-time polymerase chain reaction (PCR). The two-component system Bae SR of Acinetobacter baumannii was subjected to molecular docking with imipenem, meropenem, and levofloxacin. Antibacterial assays and fluorescence quantitative PCR were used to explore protein-ligand interactions and molecular biological resistance mechanisms related to CRAB. The analysis of the two-component system in A. baumannii revealed that imipenem exhibited the highest docking energy in Bae S at - 5.81 kcal/mol, while the docking energy for meropenem was - 4.92 kcal/mol. For Bae R, imipenem had a maximum docking energy of - 4.28 kcal/mol, compared with - 4.60 kcal/mol for meropenem. The highest binding energies for Bae S-levofloxacin and Bae R-levofloxacin were - 3.60 and - 3.65 kcal/mol, respectively. All imipenem-resistant strains had minimum inhibitory concentration (MIC) values of 16 µg/mL, whereas levofloxacin-resistant strains had MIC values of 8 µg/mL. The time-sterilization curve showed a significant decrease in bacterial colony numbers at 2 h under the action of 8 µg/mL imipenem, indicating antibacterial effects. In contrast, levofloxacin did not exhibit any antibacterial activity. Fluorescence quantitative PCR results revealed significantly increased relative expression levels of bae S and bae R genes in the CRAB group, which were 2 and 1.5 times higher than those in the CSAB group, respectively, with statistically significant differences. Molecular docking in this study found that the combination of Bae SR and carbapenem antibiotics (imipenem, meropenem) exhibited stronger affinity and stability compared with levofloxacin. Moreover, the overexpression of the two-component system genes in carbapenem-resistant A. baumannii enhanced its resistance to carbapenem, providing theoretical and practical insights into carbapenem resistance in respiratory tract infections caused by A. baumannii.

Computational insights into potential marine natural products as selective inhibitors of Mycobacterium tuberculosis InhA: A structure-based virtual screening study

Several factors are associated with the emergence of drug resistance mechanisms, such as impermeable cell walls, gene mutations, and drug efflux systems. Consequently, bacteria acquire resistance, leading to a decrease in drug efficacy. A new and innovative strategy is required to combat drug resistance in tuberculosis (TB) effectively. Therefore, targeting the mycolic acid biosynthesis pathway, which is involved in synthesising mycolic acids (MAs), essential structural components responsible for mycobacterial pathogenicity, has garnered interest in TB research and the concept of drug resistance. In this context, InhA, which plays a crucial role in the fatty acid synthase-II (FAS-II) system of the MA biosynthetic pathway, was selected as a druggable target for screening investigation. To identify potential lead molecules against InhA, diverse marine natural products (MNPs) were collected from the comprehensive marine natural products database (CMNPD). Virtual screening studies aided in selecting potential lead molecules that best fit within the substrate-binding pocket (SBP) of InhA, forming crucial hydrogen bond interaction with the catalytic residue Tyr158. Three MNPs, CMNPD30814, CMNPD1702, and CMNPD27355, were chosen as prospective alternative molecules due to their favorable pharmacokinetic properties and lack of toxicity according to ProTox-II predictions. Additionally, improved reactivity of the MNPs was observed in the results of density functional theory (DFT) studies. Furthermore, comparative molecular dynamics simulation (MDS), principal component (PC)-based free energy landscape (FEL) analysis, and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) were employed to show enhanced structural stability, increased H-bond potential, and high binding affinity toward the target InhA. Moreover, the hot spot residues that contributed to the high binding energy profile and anchored the stability of the complexes were revealed with their individual interaction energy. The computational insights from this study provide potential avenues to combat TB through the multifaceted mode of action of these marine lead molecules, which can be further explored in future experimental investigations.

Identification of potential death-associated protein kinase-1 (DAPK1) inhibitors by an integrated ligand-based and structure-based computational drug design approach

Death-associated protein kinase 1 (DAPK1) is a calcium/calmodulin (Ca2+/CaM)-dependent serine/threonine kinase that is abundantly expressed in the memory- and cognition-related brain areas. DAPK1 is associated with several pathological hallmarks of Alzheimer's disease (AD); it is an attractive target for designing a novel DAPK1 inhibitor as an effective therapeutic treatment for AD. In the present study, we have used an integrated ligand-based and structure-based drug design method to identify DAPK1 inhibitors. The pharmacophoric features of compound 38 G (PDB ID 4TXC) were mapped, and the models were evaluated using enrichment factor (EF) and goodness of hit (GH) score. The selected models were used to screen Zinc 15 compounds library. The identified hits were passed through drug-likeliness and PAINS filtering. The docking study was performed in three steps to yield molecules with good binding energy and ligand-target interactions. Finally, three hits were obtained, that is, ZINC000020648330, ZINC000006755051 and ZINC000020650468, which were subjected to rigorous molecular dynamics simulation. All three hits exhibited optimal stability under simulated conditions and low predicted toxicity.Communicated by Ramaswamy H. Sarma.

Computational exploration and design of a multi-epitopes vaccine construct against Chlamydia psittaci

Chlamydia psittaci is an intracellular pathogen and causes variety of deadly infections in humans. Antibiotics are effective against C. psittaci however high percentage of resistant strains have been reported in recent times. As there is no licensed vaccine, we used in-silico techniques to design a multi-epitopes vaccine against C. psittaci. Following a step-wise protocol, the proteome of available 26 strains was retrieved and filtered for subcellular localized proteins. Five proteins were selected (2 extracellular and 3 outer membrane) and were further analyzed for B-cell and T-cell epitopes prediction. Epitopes were further checked for antigenicity, solubility, stability, toxigenicity, allergenicity, and adhesive properties. Filtered epitopes were linked via linkers and the 3D structure of the designed vaccine construct was predicted. Binding of the designed vaccine with immune receptors: MHC-I, MHC-II, and TLR-4 was analyzed, which resulted in docking energy scores of -4.37 kcal/mol, -0.20 kcal/mol and -22.38 kcal/mol, respectively. Further, the docked complexes showed stable dynamics with a maximum value of vaccine-MHC-I complex (7.8 Å), vaccine-MHC-II complex (6.2 Å) and vaccine-TLR4 complex (5.2 Å). As per the results, the designed vaccine construct reported robust immune responses to protect the host against C. psittaci infections. In the study, the C. psittaci proteomes were considered in pan-genome analysis to extract core proteins. The pan-genome analysis was conducted using bacterial pan-genome analysis (BPGA) software. The core proteins were checked further for non-redundant proteins using a CD-Hit server. Surface localized proteins were investigated using PSORTb v 3.0. The surface proteins were BLASTp against Virulence Factor Data Base (VFDB) to predict virulent factors. Antigenicity prediction of the shortlisted proteins was further done using VAXIGEN v 2.0. The epitope mapping was done using the immune epitope database (IEDB). A multi-epitopes vaccine was built and a 3D structure was generated using 3Dprot online server. The docking analysis of the designed vaccine with immune receptors was carried out using PATCHDOCK. Molecular dynamics and post-simulation analyses were carried out using AMBER v20 to decipher the dynamics stability and intermolecular binding energies of the docked complexes.Communicated by Ramaswamy H. Sarma.

Carbapenem resistance gene crisis in A. baumannii: a computational analysis

Acinetobacter baumannii (A. baumannii) is one of the members of ESKAPE bacteria which is considered multidrug resistant globally. The objective of this study is to determine the protein docking of different antibiotic resistance gene (ARGs) in A. baumannii. In silico analysis of antibiotic resistance genes against carbapenem are the blaOXA-51, blaOXA-23, blaOXA-58, blaOXA-24, blaOXA-143, NMD-1 and IMP-1 in A. baumannii. The doripenem, imipenem and meropenem were docked to blaOXA-51 and blaOXA-23 using PyRx. The top docking energy was -5.5 kcal/mol by imipenem and doripenem and meropenem showed a binding score of -5. 2 kcal/mol each and blaOXA-23 energy was -4.3 kcal/mol by imipenem and meropenem showed a binding score of -2.3 kcal/mol, while doripenem showed the binding score of -3.4 kcal/mol. Similarly, doripenem imipenem and meropenem were docked to blaOXA-58, IMP-1, Rec A and blaOXA-143, with docking energy was -8.8 kcal/mol by doripenem and meropenem each while imipenem showed a binding score of -4.2 kcal/mol and with IMP-1 demonstrated their binding energies. was -5.7 kcal/mol by meropenem and doripenem showed a binding score of -5.3 kcal/mol, while imipenem showed a binding score of -4.5 kcal/mol. And docking energy was -4.9 kcal/mol by imipenem and meropenem showed binding energy of -3.6 kcal/mol each while doripenem showed a binding score of -3.9 kcal/mol in RecA and with blaOXA-143 docking energy was -3.0 kcal/mol by imipenem and meropenem showed a binding score of -1.9 kcal/mol, while doripenem showed the binding score of -2.5 kcal/mol respectively. Doripenem, imipenem, and meropenem docking findings with blaOXA-24 confirmed their binding energies. Doripenem had the highest docking energy of -5.5 kcal/mol, meropenem had a binding score of -4.0 kcal/mol, and imipenem had a binding score of -3.9 kcal/mol. PyRx was used to dock the doripenem, imipenem, and meropenem to NMD-1. Docking energies for doripenem were all - 4.0 kcal/mol, whereas meropenem had docking energy of -3.3 kcal/mol and imipenem was -1.50 kcal/mol. To the best of our knowledge the underlying mechanism of phenotypic with genotypic resistance molecular docking regarding carbapenem resistance A. baumannii is unclear. Our molecular docking finds the possible protein targeting mechanism for carbapenem-resistant A.baumannii.