Screening of promising molecules against MurG as drug target in multi-drug-resistant-Acinetobacter baumannii - insights from comparative protein modeling, molecular docking and molecular dynamics simulation

A comprehensive computational study to explore promising natural bioactive compounds targeting glycosyltransferase MurG in Escherichia coli for potential drug development

Peptidoglycan is a carbohydrate with a cross-linked structure that protects the cytoplasmic membrane of bacterial cells from damage. The mechanism of peptidoglycan biosynthesis involves the main synthesizing enzyme glycosyltransferase MurG, which is known as a potential target for antibiotic therapy. Many MurG inhibitors have been recognized as MurG targets, but high toxicity and drug-resistant Escherichia coli strains remain the most important problems for further development. In addition, the discovery of selective MurG inhibitors has been limited to the synthesis of peptidoglycan-mimicking compounds. The present study employed drug discovery, such as virtual screening using molecular docking, drug likeness ADMET proprieties predictions, and molecular dynamics (MD) simulation, to identify potential natural products (NPs) for Escherichia coli. We conducted a screening of 30,926 NPs from the NPASS database. Subsequently, 20 of these compounds successfully passed the potency, pharmacokinetic, ADMET screening assays, and their validation was further confirmed through molecular docking. The best three hits and the standard were chosen for further MD simulations up to 400 ns and energy calculations to investigate the stability of the NPs-MurG complexes. The analyses of MD simulations and total binding energies suggested the higher stability of NPC272174. The potential compounds can be further explored in vivo and in vitro for promising novel antibacterial drug discovery.

Identification and characterization of candidate genes for primary root length in Asiatic cotton (Gossypium arboreum L.)

KEY MESSAGE

One major gene controlling primary root length (PRL) in Gossypium arboreum is identified and this research provides a theoretical basis for root development for cotton. Primary root elongation is an essential process in plant root system structure. Here, we investigated the primary root length (PRL) of 215 diploid cotton (G. arboreum) accessions at 5, 8, 10, 15 days after sowing. A Genome-wide association study was performed for the PRL, resulting in 49 significant SNPs associated with 32 putative candidate genes. The SNP with the strongest signal (Chr07_8047530) could clearly distinguish the PRLs between accessions with two haplotypes. GamurG is the only gene that showed higher relative expression in the long PRL genotypes than the short PRL genotypes, which indicated it was the most likely candidate gene for regulating PRL. Moreover, the GamurG-silenced cotton seedlings showed a shorter PRL, while the GamurG-overexpressed Arabidopsis exhibited a significantly longer PRL. Our findings provide insight into the regulation mechanism of cotton root growth and will facilitate future breeding programs to optimize the root system structure in cotton.

Screening of potential phytomolecules against MurG as drug target in nosocomial pathogen Pseudomonas aeruginosa: perceptions from computational campaign

The nosocomial infection outbreak caused by Pseudomonas aeruginosa remains a public health concern. Multi-drug resistant (MDR) strains of P. aeruginosa are rapidly spreading leading to a huge mortality rate because of the unavailability of promising antimicrobials. MurG glycotransferase [UDP-N-acetylglucosamine-N-acetylmuramyl (pentapeptide) pyrophosphoryl-undecaprenol N-acetylglucosamine transferase] is located at the plasma membrane and plays a key role in murein (peptidoglycan) biosynthesis in bacteria. Since MurG is required for bacterial cell wall synthesis and is non-homologous to Homo sapiens; it can be a potential target for the antagonist to treat P. aeruginosa infection. The discovery of high-resolution crystal structure of P. aeruginosa MurG offers an opportunity for the computational identification of its prospective inhibitors. Therefore, in the present study, the crystal structure of MurG (PDB ID: 3S2U) from P. aeruginosa was selected, and computational docking analyses were performed to search for functional inhibitors of MurG. IMPPAT (Indian medicinal plants, phytochemicals and therapeutic) phytomolecule database was screened by computational methods with MurG catalytic site. Docking results identified Theobromine (-8.881 kcal/mol), demethoxycurcumin (-8.850 kcal/mol), 2-alpha-hydroxycostic acid (-8.791 kcal/mol), aurantiamide (-8.779 kcal/mol) and petasiphenol (-8.685 kcal/mol) as a potential inhibitor of the MurG activity. Further, theobromine and demethoxycurcumin were subjected to MDS (molecular dynamics simulation) and free energy (MM/GBSA) analysis to comprehend the physiological state and structural stability of MurG-phytomolecules complexes. The outcomes suggested that these two phytomolecules could act as most favorable natural hit compounds for impeding the enzymatic action of MurG in P. aeruginosa, and thus it needs further validation by both in vitro and in vivo analysis. HIGHLIGHTSThe top phytomolecules such as theobromine, demethoxycurcumin, 2-alpha-hydroxycostic acid, aurantiamide and petasiphenol displayed promising binding with MurG catalytic domain.MurG complexed with theobromine and demethoxycurcumin showed the best interaction and stable by MD simulation at 100 ns.The outcome of MurG binding phytomolecules has expanded the possibility of hit phytomolecules validation.Communicated by Ramaswamy H. Sarma.

Exploring the inhibitory potential of novel piperidine-derivatives against main protease (Mpro) of SARS-CoV-2: A hybrid approach consisting of molecular docking, MD simulations and MMPBSA analysis

In the current study, a hybrid computational approach consisting of different computational methods to explore the molecular electronic structures, bioactivity and therapeutic potential of piperidine compounds against SARS-CoV-2. The quantum chemical methods are used to study electronic structures of designed derivatives, molecular docking methods are used to see the most potential docking interactions for main protease (M^Pro) of SARS-CoV-2 while molecular dynamic and MMPBSA analyses are performed in bulk water solvation process to mimic real protein like aqueous environment and effectiveness of docked complexes. We designed and optimized piperidine derivatives from experimentally known precursor using quantum chemical methods. The UV-Visible, IR, molecular orbitals, molecular electrostatic plots, and global chemical reactivity descriptors are carried out which illustrate that the designed compounds are kinetically stable and reactive. The results of MD simulations and binding free energy revealed that all the complex systems possess adequate dynamic stability, and flexibility based on their RMSD, RMSF, radius of gyration, and hydrogen bond analysis. The computed net binding free energy ( Δ G b i n d ) as calculated by MMPBSA method for the complexes showed the values of -4.29 kcal.mol^-1 for P1, -5.52 kcal.mol^-1 for P2, -6.12 kcal.mol^-1 for P3, -6.35 kcal.mol^-1 for P4, -5.19 kcal.mol^-1 for P5, 3.09 kcal.mol^-1 for P6, -6.78 kcal.mol^-1 for P7, and -6.29 kcal.mol^-1 for P8.The ADMET analysis further confirmed that none of among the designed ligands violates the Lipinski rule of five (RO5). The current comprehensive investigation predicts that all our designed compounds are recommended as prospective therapeutic drugs against M^pro of SARS-CoV-2 and it provokes the scientific community to further perform their in-vitro analysis.

Identification and prioritization of potential therapeutic molecules against LpxA from Acinetobacter baumannii - A computational study

A. baumannii is a ubiquitously found gram-negative, multi-drug resistant bacterial species from the ESKAPE family of pathogens known to be the causative agent for hospital-acquired infections such as pneumonia, meningitis, endocarditis, septicaemia and urinary tract infections. A. baumannii is implicated as a contributor to bloodstream infections in approximately 2% of all worldwide infections. Hence, exploring novel therapeutic agents against the bacterium is essential. LpxA or UDP-N-acetylglucosamine acetyltransferase is an essential enzyme important in Lipid A biosynthesis which catalyses the reversible transfer of an acetyl group on the glucosamine 3-OH of the UDP-GlcNAc which is a crucial step in the biosynthesis of the protective Lipopolysaccharides (LPS) layer of the bacteria which upon disruption can lead to the elimination of the bacterium which delineates LpxA as an appreciable drug target from A. baumannii. The present study performs high throughput virtual screening of LpxA against the enamine-HTSC-large-molecule library and performs toxicity and ADME screening to identify the three promising lead molecules subjected to molecular dynamics simulations. Global and essential dynamics analysis of LpxA and its complexes along with FEL and MM/PBSA based binding free energy delineate Z367461724 and Z219244584 as potential inhibitors against LpxA from A. baumannii.

Exploring the inhibitory potential of novel bioactive compounds from mangrove actinomycetes against nsp10 the major activator of SARS-CoV-2 replication

The current study reveals the inhibitory potential of novel bioactive compounds of mangrove actinomycetes against nsp10 of SARS-CoV-2. A total of fifty (50) novel bioactive (antibacterial, antitumor, antiviral, antioxidant, and anti-inflammatory) compounds of mangrove actinomycetes from different chemical classes such as alkaloids, dilactones, sesquiterpenes, macrolides, and benzene derivatives are used for interaction analysis against nsp10 of SARS-CoV-2. The six antiviral agents sespenine, xiamycin c, xiamycin d, xiamycin e, xiamycin methyl ester, and xiamycin A (obeyed RO5 rule) are selected based on higher binding energy, low inhibition constant values, and better-docked positions. The effective hydrogen and hydrophobic (alkyl, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pi$$\end{document}π–sigma, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pi$$\end{document}π–\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pi$$\end{document}π T shaped and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\pi$$\end{document}π-alkyl) interaction analysis reveals the four antivirals sespenine, xiamycin C, xiamycin methyl ester, and xiamycin A are supposed to be the most auspicious inhibitors against nsp10 of SARS-CoV-2. Quantum chemistry methods such as frontier molecular orbitals and molecular electrostatic potential are used to explain the thermal stability and chemical reactivity of ligands. The toxicity profile shows that selected ligands are safe by absorption, distribution, metabolism, excretion, and toxicity profiling and also effective for inhibition of nsp10 protein of SARS-CoV-2. The molecular dynamic simulation investigation of apo and halo forms of nsp10 done by RMSD of C\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\alpha$$\end{document}α atoms of nsp10, all amino acid residues RMSF, count total number of hydrogen bonds and radius of gyration (R_g). MD simulations reveal the complexes are stable and increase the structural compactness of nsp10 in the binding pocket. The lead antiviral compounds sespenine, xiamycin C, xiamycin methyl ester, and xiamycin A are recommended as the most promising inhibitors against nsp10 of SARS-CoV-2 pathogenicity.

Targeting SARS-CoV-2: a systematic drug repurposing approach to identify promising inhibitors against 3C-like proteinase and 2'-O-ribose methyltransferase

The recent pandemic associated with SARS-CoV-2, a virus of the Coronaviridae family, has resulted in an unprecedented number of infected people. The highly contagious nature of this virus makes it imperative for us to identify promising inhibitors from pre-existing antiviral drugs. Two druggable targets, namely 3C-like proteinase (3CLpro) and 2'-O-ribose methyltransferase (2'-O-MTase) were selected in this study due to their indispensable nature in the viral life cycle. 3CLpro is a cysteine protease responsible for the proteolysis of replicase polyproteins resulting in the formation of various functional proteins, whereas 2'-O-MTase methylates the ribose 2'-O position of the first and second nucleotide of viral mRNA, which sequesters it from the host immune system. The selected drug target proteins were screened against an in-house library of 123 antiviral drugs. Two promising drug molecules were identified for each protein based on their estimated free energy of binding (ΔG), the orientation of drug molecules in the active site and the interacting residues. The selected protein-drug complexes were then subjected to MD simulation, which consists of various structural parameters to equivalently reflect their physiological state. From the virtual screening results, two drug molecules were selected for each drug target protein [Paritaprevir (ΔG = -9.8 kcal/mol) & Raltegravir (ΔG = -7.8 kcal/mol) for 3CLpro and Dolutegravir (ΔG = -9.4 kcal/mol) and Bictegravir (ΔG = -8.4 kcal/mol) for 2'-OMTase]. After the extensive computational analysis, we proposed that Raltegravir, Paritaprevir, Bictegravir and Dolutegravir are excellent lead candidates for these crucial proteins and they could become potential therapeutic drugs against SARS-CoV-2. Communicated by Ramaswamy H. Sarma.

Prioritization of Mur family drug targets against A. baumannii and identification of their homologous proteins through molecular phylogeny, primary sequence, and structural analysis

Background

The World Health Organization (WHO) report stated that Acinetobacter baumannii had been classified as one of the most important pathogenic bacteria causing nosocomial infection in hospital patients due to multi-drug resistance (MDR). It is vital to find out new bacterial drug targets and annotated their structure and function for the exploration of new anti-bacterial agents. The present study utilized a systematic route to prioritize the potential drug targets that belong to Mur family of Acinetobacter baumannii and identify their homologous proteins using a computational approach such as sequence similarity search, multiple sequence alignment, phylogenetic analysis, protein sequence, and protein structure analysis.

Results

From the results of protein sequence analysis of eight Mur family proteins, they divided into three main enzymatic classes namely transferases (MurG, MurA and MraY), ligases (MurC, MurD, MurE, and MurF), and oxidoreductase (MurB). Based on the results of intra-comparative protein sequence analysis and enzymatic classification, we have chosen MurB, MurE, and MurG as the prioritized drug targets from A. baumannii and subjected them for further detailed studies of inter-species comparison. This inter-species comparison help us to explore the sequential and structural properties of homologous proteins in other species and hence, opens a gateway for new target identification and using common inhibitor for different bacterial species caused by various diseases. The pairwise sequence alignment results between A. baumannii’s MurB with A. calcoaceticus’s MurB, A. baumannii’s MurE with A. seifertii’s MurE, and A. baumannii’s MurG with A. pittii’s MurG showed that every group of the proteins are highly similar with each other and they showed sequence identity of 95.7% and sequence similarity of 97.2%.

Conclusion

Together with the results of secondary and three-dimensional structure predictions explained that three selected proteins (MurB, MurE, and MurG) from A. baumannii and their related proteins (AcMurB, AsMurE, and ApMurG) belong to mixed αβ class and they are very similar.

Structure based drug designing and discovery of promising lead molecules against UDP-N-acetylenolpyruvoylglucosamine reductase (MurB): A potential drug target in multi-drug resistant Acinetobacter baumannii

According to the world health organization (WHO) reports, Acinetobacter baumannii was considered as one of the significant and first-line priority pathogens, which causes hospital-acquired nosocomial infections in human. The enzymes involved in the peptidoglycan biosynthetic pathway are critical for the survival of this bacterium. Therefore, these enzymes are ideal drug target since they are conserved among most of the species and non-homologous to human. Here, we utilized the structure-based virtual screening (SBVS) technique to identify the promising lead molecules against MurB (UDP-N-acetylenolpyruvoylglucosamine reductase) protein using computational approaches. Initially, the three-dimensional structure of MurB was predicted based on MurB from P. aeruginosa (PDB ID: 4JAY), which is used as a structural template for homology modeling. During the High-throughput Virtual screening (HTVS) analysis, we started with 30,792 molecules against MurB model, among these; only 5238 molecules could be considered suitable for further step. Finally, only twenty molecules were able to pass Lipinski's and ADMET properties. After a thorough examination of interaction analysis, higher ΔG and Ki values, we had chosen five promising molecules (ZINC IDs: ZINC12530134, ZINC15675540, ZINC15675762, ZINC15675624 and ZINC15707270) and three control molecules (PubChem IDs: 54682555, 729933 and 39964628) for Molecular dynamics (MD) simulation to understand the effect of ligands towards the structural stability, structural integrity and structural compactness of MurB protein. Further, the MM/PBSA binding free energy analysis was performed for eight ligands bound MurB structures. Together the results obtained from global dynamics, essential dynamics and MM-PBSA binding free energy analysis, we concluded that apart from the control molecules, ZINC12530134 should be considered as one of the most promising ones and it could be the potent inhibitor against A baumannii and provide valuable insight for further experimental studies.

Identification of inhibitor binding hotspots in Acinetobacter baumannii β-ketoacyl acyl carrier protein synthase III using molecular dynamics simulation

Acinetobacter baumannii is a gram-negative bacterium that is rapidly developing drug resistance due to the abuse of antibiotics. The emergence of multidrug-resistant A. baumannii has greatly contributed to the urgency of developing new antibiotics. Previously, we had discovered two potent inhibitors of A. baumannii β-ketoacyl acyl carrier protein synthase III (abKAS III), YKab-4 and YKab-6, which showed potent activity against A. baumannii. In addition, we have reported the crystal structure of abKAS III. In the present study, we investigated the binding between abKAS III and its inhibitors by docking simulation. Molecular dynamics (MD) simulations were performed using docked inhibitor models to identify the hotspot residues related to inhibitor binding. The binding free energies estimated using the MD simulations suggest that residues I198 and F260 of abKAS III serve as the inhibitor binding hotspots. I198, found to be responsible for mediating hydrophobic interactions with inhibitors, had the strongest residual binding energy among all abKAS III residues. We modeled glutamine substitutions of residues I198 and F260 and estimated the relative binding energies of the I198Q and F260Q variants. The results confirmed that I198 and F260 are the key inhibitor binding residues. The roles of the key residues in inhibitor binding, i.e. F260 in the α9 helix and the I198 in the β6β7 loop region, were investigated using principal component analysis (PCA). PCA revealed the structural changes resulting from the abKAS III I198Q and F260Q mutations and described the essential dynamics of the α9 helix. In addition, the results suggest that the β6β7 loop region may act as a gate keeper for ligand binding. Hydrophobic interactions involving I198 and F260 in abKAS III appear to be essential for the binding of the inhibitors YKab-4 and YKab-6. In conclusion, this study provides valuable information for the rational design of antibiotics via the inhibition of abKAS III.