Microwave-Assisted Synthesis of Functionalized Carbon Nanospheres Using Banana Peels: pH-Dependent Synthesis, Characterization, and Selective Sensing Applications.

This work presents a microwave-based green synthesis method for producing carbon nanospheres (CNSs) and investigates the impact of presynthesis pH on their size and assembly. The resulting CNSs are monodispersed, averaging 35 nm in size, and exhibit notable characteristics including high water solubility, photostability, and a narrow size distribution, achieved within a synthesis time of 15 min. The synthesized CNS features functional groups such as -OH, -COOH, -NH, -C-O-C, =C-H, and -CH. This diversity empowers the CNS for various applications including sensing. The CNS exhibits a distinct UV peak at 282 nm and emits intense fluorescence at 430 nm upon excitation at 350 nm. These functionalized CNSs enable selective and specific sensing of Cu2+ ions and the amino acid tryptophan (Trp) in aqueous solutions. In the presence of Cu2+ ions, static-based quenching of CNS fluorescence was observed due to the chelation-enhanced quenching (CHEQ) effect. Notably, Cu2+ ions induce a substantial change in UV spectra alongside a red-shift in the peak position. The limits of detection and quantification for Cu2+ ions with CNS are determined as 0.73 and 2.45 µg/mL, respectively. Additionally, on interaction with tryptophan, the UV spectra of CNS display a marked increase in the peak at 282 nm, accompanied by a red-shift phenomenon. The limits of detection and quantification for l-tryptophan are 4.510 × 10-3 and 1.50 × 10-2 µg/mL, respectively, indicating its significant potential for biological applications. Furthermore, the practical applicability of CNSs is demonstrated by their successful implementation in analyzing real water samples and filter paper-based examination, showcasing their effectiveness for on-site sensing.

Corrigendum to "Exploiting cheminformatic and machine learning to navigate the available chemical space of potential small molecule inhibitors of SARS-CoV-2″ [Computational and Structural Biotechnology Journal 19 (2021) 424-438].

[This corrects the article DOI: 10.1016/j.csbj.2020.12.028.].

Quinoxalinone substituted pyrrolizine (4h)-induced dual inhibition of AKT and ERK instigates apoptosis in breast and colorectal cancer by modulating mitochondrial membrane potential.

AKT and ERK 1/2 play a pivotal role in cancer cell survival, proliferation, migration, and angiogenesis. Therefore, AKT and ERK 1/2 are considered crucial targets for cancer intervention. In this study, we envisaged the role of AKT and ERK signaling in apoptosis regulation in presence of compound 4h, a novel synthetic derivative of quinoxalinone substituted spiropyrrolizines exhibiting substantial antiproliferative activity in various cancer cell lines. Structurally 4h is a spiropyrrolizine derivative. Molecular docking analysis revealed that compound 4h shows strong binding affinity with AKT-1 (-9.5 kcal/mol) and ERK2 (-9.0 kcal/mol) via binding at allosteric sites of AKT and active site of ERK2. The implications of 4h binding with these two survival kinases resulted in the obstruction for ATP binding, hence, hampering their phosphorylation dependent activation. We demonstrate that 4h mediated apoptotic induction via disruption in the mitochondrial membrane potential of MCF-7 and HCT-116 cells and 4h-mediated inhibition of survival pathways occurred in a wild type PTEN background and is diminished in PTEN-/- cells. In 4T1 mammary carcinoma model, 4h exhibited pronounced reduction in the tumor size and tumor volume at significantly low doses. Besides, 4h reached the highest plasma concentration of 5.8 µM within a period of 1 h in mice model intraperitoneally. Furthermore, 4h showed acceptable clearance with an adequate elimination half-life and satisfactory pharmacokinetic behaviour, thus proclaiming as a potential lead molecule against breast and colorectal cancer by specifically inhibiting simultaneously AKT and ERK1/2 kinases.

Fluorescence "Turn-Off" and Colorimetric Sensor for Fe2+, Fe3+, and Cu2+ Ions Based on a 2,5,7-Triarylimidazopyridine Scaffold.

Two cyanoimidazopyridine-based sensors (SS1 and SS2) were explored for the colorimetric and fluorometric detection of Fe2+, Fe3+, and Cu2+ ions in the semi-aqueous medium. The "turn-off" fluorescence response of both sensors to these ions was due to the restriction in internal charge transfer. Job's plot and semi-empirical calculations revealed that SS1 and SS2 complexed with Cu2+ ions in a 1:1 ratio and Fe2+/3+ ions in a 2:1 ratio, respectively. The sensors were found to have high binding constant (K a) values and low detection limit values. FMO analysis using the semi-empirical quantum mechanics method revealed the decrease in energy gap after complexation with metal ions. Sensor-coated filter paper strips were prepared and analyzed, where the color changes in the strips could be utilized for the real-time detection of Fe2+, Fe3+, and Cu2+ ions.

Chemical Space Exploration of DprE1 Inhibitors Using Chemoinformatics and Artificial Intelligence.

Tuberculosis (TB), entrained by Mycobacterium tuberculosis, continues to be an enfeebling disease, killing nearly 1.5 million people in 2019, with 2 billion people worldwide affected by latent TB. The multidrug-resistant and totally drug-resistant emerging strains further exacerbate the TB infection. The cell wall of bacteria provides critical virulence components such as cell surface proteins, regulators, signal transduction proteins, and toxins. The cell wall biosynthesis pathway of Mycobacterium tuberculosis is exhaustively studied to discover novel drug targets. Decaprenylphosphoryl-ß-d-ribose-2'-epimerase (DprE1) is an important enzyme involved in the arabinogalactan biosynthetic pathway of Mycobacterium tuberculosis cell wall and is essential for both latent and persistent bacterial infection. We analyzed all known ∼1300 DprE1 inhibitors to gain deep insights into the chemogenomic space of DprE1-ligand complexes. Physicochemical descriptors of the DprE1 inhibitors showed a marked lipophilic character forming a cluster distinct from the existing TB drugs, as revealed by the principal component analysis. Similarity analysis using Murcko scaffolds and rubber band scaling revealed scarce representation of the chemical space. Further, Murcko scaffold analysis uncovered favorable and unfavorable scaffolds, where benzo and pyridine-based core scaffolds exhibit the highest biological activity, as evidenced by their MIC and IC50 values. Automatic SAR and R-group decomposition analysis resulted in the identification of substructures responsible for the inhibitory activity of the DprE1 enzyme. Further, with activity cliff analysis, we observed prominent discontinuity in the SAR of DprE1 inhibitors, where even simple structural modification in the chemical scaffold resulted in significant potency difference, presumably due to the binding orientation and interaction in the active site. Thiophene, 6-membered aromatic rings, and unsubstituted benzene ring-based toxicophores were identified in the DprE1 chemical space using an artificial intelligence approach based on inductive logic programming. This paper, hence, ushers in new insights for the design and development of potent covalent and non-covalent DprE1 inhibitors and guides hit and lead optimization for the development of non-hazardous small molecule therapeutics for Mycobacterium tuberculosis.

Discovery and characterization of small molecule SIRT3-specific inhibitors as revealed by mass spectrometry.

Sirtuins play a prominent role in several cellular processes and are implicated in various diseases. The understanding of biological roles of sirtuins is limited because of the non-availability of small molecule inhibitors, particularly the specific inhibitors directed against a particular SIRT. We performed a high-throughput screening of pharmacologically active compounds to discover novel, specific, and selective sirtuin inhibitor. Several unique in vitro sirtuin inhibitor pharmacophores were discovered. Here, we present the discovery of novel chemical scaffolds specific for SIRT3. We have demonstrated the in vitro activity of these compounds using label-free mass spectroscopy. We have further validated our results using biochemical, biophysical, and computational studies. Determination of kinetic parameters shows that the SIRT3 specific inhibitors have a moderately longer residence time, possibly implying high in vivo efficacy. The molecular docking results revealed the differential selectivity pattern of these inhibitors against sirtuins. The discovery of specific inhibitors will improve the understanding of ligand selectivity in sirtuins, and the binding mechanism as revealed by docking studies can be further exploited for discovering selective and potent ligands targeting sirtuins.

Exploiting cheminformatic and machine learning to navigate the available chemical space of potential small molecule inhibitors of SARS-CoV-2.

The current life-threatening and tenacious pandemic eruption of coronavirus disease in 2019 (COVID-19) has posed a significant global hazard concerning high mortality rate, economic meltdown, and everyday life distress. The rapid spread of COVID-19 demands countermeasures to combat this deadly virus. Currently, there are no drugs approved by the FDA to treat COVID-19. Therefore, discovering small molecule therapeutics for treating COVID-19 infection is essential. So far, only a few small molecule inhibitors are reported for coronaviruses. There is a need to expand the small chemical space of coronaviruses inhibitors by adding potent and selective scaffolds with anti-COVID activity. In this context, the huge antiviral chemical space already available can be analysed using cheminformatic and machine learning to unearth new scaffolds. We created three specific datasets called "antiviral dataset" (N = 38,428) "drug-like antiviral dataset" (N = 20,963) and "anticorona dataset" (N = 433) for this purpose. We analyzed the 433 molecules of "anticorona dataset" for their scaffold diversity, physicochemical distributions, principal component analysis, activity cliffs, R-group decomposition, and scaffold mapping. The scaffold diversity of the "anticorona dataset" in terms of Murcko scaffold analysis demonstrates a thorough representation of diverse chemical scaffolds. However, physicochemical descriptor analysis and principal component analysis demonstrated negligible drug-like features for the "anticorona dataset" molecules. The "antiviral dataset" and "drug-like antiviral dataset" showed low scaffold diversity as measured by the Gini coefficient. The hierarchical clustering of the "antiviral dataset" against the "anticorona dataset" demonstrated little molecular similarity. We generated a library of frequent fragments and polypharmacological ligands targeting various essential viral proteins such as main protease, helicase, papain-like protease, and replicase polyprotein 1ab. Further structural and chemical features of the "anticorona dataset" were compared with SARS-CoV-2 repurposed drugs, FDA-approved drugs, natural products, and drugs currently in clinical trials. Using machine learning tool DCA (DMax Chemistry Assistant), we converted the "anticorona dataset" into an elegant hypothesis with significant functional biological relevance. Machine learning analysis uncovered that FDA approved drugs, Tizanidine HCl, Cefazolin, Raltegravir, Azilsartan, Acalabrutinib, Luliconazole, Sitagliptin, Meloxicam (Mobic), Succinyl sulfathiazole, Fluconazole, and Pranlukast could be repurposed as effective drugs for COVID-19. Fragment-based scaffold analysis and R-group decomposition uncovered pyrrolidine and the indole molecular scaffolds as the potent fragments for designing and synthesizing the novel drug-like molecules for targeting SARS-CoV-2. This comprehensive and systematic assessment of small-molecule viral therapeutics' entire chemical space realised critical insights to potentially privileged scaffolds that could aid in enrichment and rapid discovery of efficacious antiviral drugs for COVID-19.

Epigenetic drug discovery: systematic assessment of chemical space.

Aim: The druggability of epigenetic targets has prompted researchers to develop small-molecule therapeutics. However, no systematic assessment has ever been done to investigate the chemical space of epigenetic modulators. Herein, we report a comprehensive chemoinformatic analysis of epigenetic ligands from EpiDBase, HEMD, ChEMBL and PubChem databases. Results: Nearly, 0.45 × 106 ligands were analyzed for assay interference compounds, target profiling, drug-like properties and hit prioritization. After eliminating approximately 96,000 problematic compounds, the remaining 0.36 × 106 compounds were studied for their physicochemical distributions, principal component analysis and hit prioritization. More than 30% of assay interference compounds were determined for many proteins. Conclusion: This systematic assessment of epigenetic ligands will help in the enrichment of screening libraries with high-quality compounds and thus, the generation of efficacious drug candidates.

AutophagySMDB: a curated database of small molecules that modulate protein targets regulating autophagy.

Macroautophagy/autophagy is a complex self-degradative mechanism responsible for clearance of non functional organelles and proteins. A range of factors influences the autophagic process, and disruptions in autophagy-related mechanisms lead to disease states, and further exacerbation of disease. Despite in-depth research into autophagy and its role in pathophysiological processes, the resources available to use it for therapeutic purposes are currently lacking. Herein we report the Autophagy Small Molecule Database (AutophagySMDB; http://www.autophagysmdb.org/ ) of small molecules and their cognate protein targets that modulate autophagy. Presently, AutophagySMDB enlists ~10,000 small molecules which regulate 71 target proteins. All entries are comprised of information such as EC50 (half maximal effective concentration), IC50 (half maximal inhibitory concentration), Kd (dissociation constant) and Ki (inhibition constant), IUPAC name, canonical SMILE, structure, molecular weight, QSAR (quantitative structure activity relationship) properties such as hydrogen donor and acceptor count, aromatic rings and XlogP. AutophagySMDB is an exhaustive, cross-platform, manually curated database, where either the cognate targets for small molecule or small molecules for a target can be searched. This database is provided with different search options including text search, advanced search and structure search. Various computational tools such as tree tool, cataloging tools, and clustering tools have also been implemented for advanced analysis. Data and the tools provided in this database helps to identify common or unique scaffolds for designing novel drugs or to improve the existing ones for autophagy small molecule therapeutics. The approach to multitarget drug discovery by identifying common scaffolds has been illustrated with experimental validation. Abbreviations: AMPK: AMP-activated protein kinase; ATG: autophagy related; AutophagySMDB: autophagy small molecule database; BCL2: BCL2, apoptosis regulator; BECN1: beclin 1; CAPN: calpain; MTOR: mechanistic target of rapamycin kinase; PPARG: peroxisome proliferator activated receptor gamma; SMILES: simplified molecular input line entry system; SQSTM1: sequestosome 1; STAT3: signal transducer and activator of transcription.

Bifidobacterium adolescentis is intrinsically resistant to antitubercular drugs.

Multiple mutations in the ß subunit of the RNA polymerase (rpoß) of Mycobacterium tuberculosis (Mtb) are the primary cause of resistance to rifamycin (RIF). In the present study, bifidobacterial rpoß sequences were analyzed to characterize the mutations that contribute to the development of intrinsic resistance to RIF, isoniazid, streptomycin and pyrazinamide. Sequence variations, which mapped to cassettes 1 and 2 of the rpoß pocket, are also found in multidrug-resistant Mtb (MDR Mtb). Growth curves in the presence of osmolytes and different concentrations of RIF showed that the bacteria adapted rapidly by shortening the growth curve lag time. Insight into the adapted rpoß DNA sequences revealed that B. adolescentis harbored mutations both in the RIF pocket and in regions outside the pocket. The minimum inhibitory concentrations (MICs) and mutant prevention concentrations (MPCs) indicated that B. longum, B. adolescentis and B. animalis are resistant to antitubercular drugs. 3D-homology modeling and binding interaction studies using computational docking suggested that mutants had reduced binding affinity towards RIF. RIF-exposed/resistant bacteria exhibited variant protein profiles along with morphological differences, such as elongated and branched cells, surface conversion from rough to smooth, and formation of a concentrating ring.

Crystal structure of the N-terminal domain of human SIRT7 reveals a three-helical domain architecture.

Human SIRT7 is an NAD(+) dependent deacetylase, which belongs to sirtuin family of proteins. SIRT7, like other sirtuins has conserved catalytic domain and is flanked by N- and C-terminal domains reported to play vital functional roles. Here, we report the crystal structure of the N-terminal domain of human SIRT7 (SIRT7(NTD) ) at 2.3 Å resolution as MBP-SIRT7(NTD) fusion protein. SIRT7(NTD) adopts three-helical domain architecture and comparative structural analyses suggest similarities to some DNA binding motifs and transcription regulators. We also report here the importance of N- and C-terminal domains in soluble expression of SIRT7. Proteins 2016; 84:1558-1563. © 2016 Wiley Periodicals, Inc.

Transcription factors and cognate signalling cascades in the regulation of autophagy.

Autophagy is a process that maintains the equilibrium between biosynthesis and the recycling of cellular constituents; it is critical for avoiding the pathophysiology that results from imbalance in cellular homeostasis. Recent reports indicate the need for the design of high-throughput screening assays to identify targets and small molecules for autophagy modulation. For such screening, however, a better understanding of the regulation of autophagy is essential. In addition to regulation by various signalling cascades, regulation of gene expression by transcription factors is also critical. This review focuses on the various transcription factors as well as the corresponding signalling molecules that act together to translate the stimuli to effector molecules that up- or downregulate autophagy. This review rationalizes the importance of these transcription factors functioning in tandem with cognate signalling molecules and their interfaces as possible therapeutic targets for more specific pharmacological interventions.

ONRLDB--manually curated database of experimentally validated ligands for orphan nuclear receptors: insights into new drug discovery.

Orphan nuclear receptors are potential therapeutic targets. The Orphan Nuclear Receptor Ligand Binding Database (ONRLDB) is an interactive, comprehensive and manually curated database of small molecule ligands targeting orphan nuclear receptors. Currently, ONRLDB consists of ∼11,000 ligands, of which ∼6500 are unique. All entries include information for the ligand, such as EC50 and IC50, number of aromatic rings and rotatable bonds, XlogP, hydrogen donor and acceptor count, molecular weight (MW) and structure. ONRLDB is a cross-platform database, where either the cognate small molecule modulators of a receptor or the cognate receptors to a ligand can be searched. The database can be searched using three methods: text search, advanced search or similarity search. Substructure search, cataloguing tools, and clustering tools can be used to perform advanced analysis of the ligand based on chemical similarity fingerprints, hierarchical clustering, binning partition and multidimensional scaling. These tools, together with the Tree function provided, deliver an interactive platform and a comprehensive resource for identification of common and unique scaffolds. As demonstrated, ONRLDB is designed to allow selection of ligands based on various properties and for designing novel ligands or to improve the existing ones. Database URL: http://www.onrldb.org/.

Nicotinic Acid Adenine Dinucleotide Phosphate (NAADP) and Endolysosomal Two-pore Channels Modulate Membrane Excitability and Stimulus-Secretion Coupling in Mouse Pancreatic ß Cells.

Pancreatic ß cells are electrically excitable and respond to elevated glucose concentrations with bursts of Ca(2+) action potentials due to the activation of voltage-dependent Ca(2+) channels (VDCCs), which leads to the exocytosis of insulin granules. We have examined the possible role of nicotinic acid adenine dinucleotide phosphate (NAADP)-mediated Ca(2+) release from intracellular stores during stimulus-secretion coupling in primary mouse pancreatic ß cells. NAADP-regulated Ca(2+) release channels, likely two-pore channels (TPCs), have recently been shown to be a major mechanism for mobilizing Ca(2+) from the endolysosomal system, resulting in localized Ca(2+) signals. We show here that NAADP-mediated Ca(2+) release from endolysosomal Ca(2+) stores activates inward membrane currents and depolarizes the ß cell to the threshold for VDCC activation and thereby contributes to glucose-evoked depolarization of the membrane potential during stimulus-response coupling. Selective pharmacological inhibition of NAADP-evoked Ca(2+) release or genetic ablation of endolysosomal TPC1 or TPC2 channels attenuates glucose- and sulfonylurea-induced membrane currents, depolarization, cytoplasmic Ca(2+) signals, and insulin secretion. Our findings implicate NAADP-evoked Ca(2+) release from acidic Ca(2+) storage organelles in stimulus-secretion coupling in ß cells.

EpiDBase: a manually curated database for small molecule modulators of epigenetic landscape.

We have developed EpiDBase (www.epidbase.org), an interactive database of small molecule ligands of epigenetic protein families by bringing together experimental, structural and chemoinformatic data in one place. Currently, EpiDBase encompasses 5784 unique ligands (11 422 entries) of various epigenetic markers such as writers, erasers and readers. The EpiDBase includes experimental IC(50) values, ligand molecular weight, hydrogen bond donor and acceptor count, XlogP, number of rotatable bonds, number of aromatic rings, InChIKey, two-dimensional and three-dimensional (3D) chemical structures. A catalog of all epidbase ligands based on the molecular weight is also provided. A structure editor is provided for 3D visualization of ligands. EpiDBase is integrated with tools like text search, disease-specific search, advanced search, substructure, and similarity analysis. Advanced analysis can be performed using substructure and OpenBabel-based chemical similarity fingerprints. The EpiDBase is curated to identify unique molecular scaffolds. Initially, molecules were selected by removing peptides, macrocycles and other complex structures and then processed for conformational sampling by generating 3D conformers. Subsequent filtering through Zinc Is Not Commercial (ZINC: a free database of commercially available compounds for virtual screening) and Lilly MedChem regular rules retained many distinctive drug-like molecules. These molecules were then analyzed for physicochemical properties using OpenBabel descriptors and clustered using various methods such as hierarchical clustering, binning partition and multidimensional scaling. EpiDBase provides comprehensive resources for further design, development and refinement of small molecule modulators of epigenetic markers.

Structure, dynamics, and interaction of Mycobacterium tuberculosis (Mtb) DprE1 and DprE2 examined by molecular modeling, simulation, and electrostatic studies.

The enzymes decaprenylphosphoryl-ß-D-ribose oxidase (DprE1) and decaprenylphosphoryl-ß-D-ribose-2-epimerase (DprE2) catalyze epimerization of decaprenylphosporyl ribose (DPR) todecaprenylphosporyl arabinose (DPA) and are critical for the survival of Mtb. Crystal structures of DprE1 so far reported display significant disordered regions and no structural information is known for DprE2. We used homology modeling, protein threading, molecular docking and dynamics studies to investigate the structural and dynamic features of Mtb DprE1 and DprE2 and DprE1-DprE2 complex. A three-dimensional model for DprE2 was generated using the threading approach coupled with ab initio modeling. A 50 ns simulation of DprE1 and DprE2 revealed the overall stability of the structures. Principal Component Analysis (PCA) demonstrated the convergence of sampling in both DprE1 and DprE2. In DprE1, residues in the 269-330 area showed considerable fluctuation in agreement with the regions of disorder observed in the reported crystal structures. In DprE2, large fluctuations were detected in residues 95-113, 146-157, and 197-226. The study combined docking and MD simulation studies to map and characterize the key residues involved in DprE1-DprE2 interaction. A 60 ns MD simulation for DprE1-DprE2 complex was also performed. Analysis of data revealed that the docked complex is stabilized by H-bonding, hydrophobic and ionic interactions. The key residues of DprE1 involved in DprE1-DprE2 interactions belong to the disordered region. We also examined the docked complex of DprE1-BTZ043 to investigate the binding pocket of DprE1 and its interactions with the inhibitor BTZ043. In summary, we hypothesize that DprE1-DprE2 interaction is crucial for the synthesis of DPA and DprE1-DprE2 complex may be a new therapeutic target amenable to pharmacological validation. The findings have important implications in tuberculosis (TB) drug discovery and will facilitate drug development efforts against TB.

Discovery of Mycobacterium tuberculosis α-1,4-glucan branching enzyme (GlgB) inhibitors by structure- and ligand-based virtual screening.

GlgB (α-1,4-glucan branching enzyme) is the key enzyme involved in the biosynthesis of α-glucan, which plays a significant role in the virulence and pathogenesis of Mycobacterium tuberculosis. Because α-glucans are implicated in the survival of both replicating and non-replicating bacteria, there exists an exigent need for the identification and development of novel inhibitors for targeting enzymes, such as GlgB, involved in this pathway. We have used the existing structural information of M. tuberculosis GlgB for high throughput virtual screening and molecular docking. A diverse database of 330,000 molecules was used for identifying novel and efficacious therapeutic agents for targeting GlgB. We also used three-dimensional shape as well as two-dimensional similarity matrix methods to identify diverse molecular scaffolds that inhibit M. tuberculosis GlgB activity. Virtual hits were generated after structure and ligand-based screening followed by filters based on interaction with human GlgB and in silico pharmacokinetic parameters. These hits were experimentally evaluated and resulted in the discovery of a number of structurally diverse chemical scaffolds that target M. tuberculosis GlgB. Although a number of inhibitors demonstrated in vitro enzyme inhibition, two compounds in particular showed excellent inhibition of in vivo M. tuberculosis survival and its ability to get phagocytosed. This work shows that in silico docking and three-dimensional chemical similarity could be an important therapeutic approach for developing inhibitors to specifically target the M. tuberculosis GlgB enzyme.

α-Glucan pathway as a novel Mtb drug target: structural insights and cues for polypharmcological targeting of GlgB and GlgE.

Tuberculosis continues to be a deadly infectious disease, mainly due to the existence of persistent bacterial populations that survive drug treatment and obstruct complete eradication of infection. The enzymes GlgE and GlgB, which are involved in the glycan pathway, have recently been identified as promising drug targets for combating persistent bacillus strains. In the glycan pathway, enzymes GlgE, GlgA, and Tre-xyz produce linear α-glucans, which are then converted to essential branched α-glucan by GlgB. This α-glucan is a vital cell-wall and storage polysaccharide, critical for Mtb virulence and persistence. We highlight recent insights into the significance of both GlgE and GlgB in the glycan pathway and also discuss drug strategies for tuberculosis such as polypharmcological targeting of GlgB and GlgE. Small molecule-based modulation of GlgB and GlgE to boost the design and development of novel and improved drugs for more selective and efficient targeting of tuberculosis are also discussed.

Mechanistic insight into the enzymatic reduction of truncated hemoglobin N of Mycobacterium tuberculosis: role of the CD loop and pre-A motif in electron cycling.

Many pathogenic microorganisms have evolved hemoglobin-mediated nitric oxide (NO) detoxification mechanisms, where a globin domain in conjunction with a partner reductase catalyzes the conversion of toxic NO to innocuous nitrate. The truncated hemoglobin HbN of Mycobacterium tuberculosis displays a potent NO dioxygenase activity despite lacking a reductase domain. The mechanism by which HbN recycles itself during NO dioxygenation and the reductase that participates in this process are currently unknown. This study demonstrates that the NADH-ferredoxin/flavodoxin system is a fairly efficient partner for electron transfer to HbN with an observed reduction rate of 6.2 µM/min(-1), which is nearly 3- and 5-fold faster than reported for Vitreoscilla hemoglobin and myoglobin, respectively. Structural docking of the HbN with Escherichia coli NADH-flavodoxin reductase (FdR) together with site-directed mutagenesis revealed that the CD loop of the HbN forms contacts with the reductase, and that Gly(48) may have a vital role. The donor to acceptor electron coupling parameters calculated using the semiempirical pathway method amounts to an average of about 6.4 10(-5) eV, which is lower than the value obtained for E. coli flavoHb (8.0 10(-4) eV), but still supports the feasibility of an efficient electron transfer. The deletion of Pre-A abrogated the heme iron reduction by FdR in the HbN, thus signifying its involvement during intermolecular interactions of the HbN and FdR. The present study, thus, unravels a novel role of the CD loop and Pre-A motif in assisting the interactions of the HbN with the reductase and the electron cycling, which may be vital for its NO-scavenging function.

Mycobacterium tuberculosis keto-mycolic acid and macrophage nuclear receptor TR4 modulate foamy biogenesis in granulomas: a case of a heterologous and noncanonical ligand-receptor pair.

The cell wall of Mycobacterium tuberculosis is configured of bioactive lipid classes that are essential for virulence and potentially involved in the formation of foamy macrophages (FMs) and granulomas. Our recent work established crosstalk between M. tuberculosis cell wall lipids and the host lipid-sensing nuclear receptor TR4. In this study, we have characterized, identified, and adopted a heterologous ligand keto-mycolic acid from among M. tuberculosis lipid repertoire for the host orphan NR TR4. Crosstalk between cell wall lipids and TR4 was analyzed by transactivation and promoter reporter assays. Mycolic acid (MA) was found to transactivate TR4 significantly compared with other cell wall lipids. Among the MA, the oxygenated form, keto-MA, was responsible for transactivation, and the identity was validated by TR4 binding assays followed by TLC and nuclear magnetic resonance. Isothermal titration calorimetry revealed that keto-MA binding to TR4 is energetically favorable. This keto-MA-TR4 axis seems to be essential to this oxygenated MA induction of FMs and granuloma formation as evaluated by in vitro and in vivo model of granuloma formation. TR4 binding with keto-MA features a unique association of host nuclear receptor with a bacterial lipid and adds to the presently known ligand repertoire beyond dietary lipids. Pharmacologic modulation of this heterologous axis may hold promise as an adjunct therapy to frontline tuberculosis drugs.