Influence of Nitrogen-Doped Carbon Dots on H• Radical-Mediated Au-H Formation in the Hydrogenation of 4-Nitrophenol Using NCDs-Au Nanohybrids.

The hydrogenation of 4-nitrophenol using carbon dot-stabilized gold (Au) nanoparticles is well-studied, with Au-H species known to catalyze the reaction. However, the impact of specific nitrogen moieties in nitrogen-doped carbon dots on Au-H formation and catalytic activity remains unexplored. These nitrogen species, acting as surface ligands, may influence the catalytic properties through the generation of Au-H species via H• radicals. In this regard, modulation of the catalytic properties of Au nanoparticles has been explored by conjugating their surface with nitrogen-doped carbon dots (NCDs). Three distinct nanohybrid formulations comprising NCDs and Au nanoparticles (i.e., NCDs-Au) have been prepared, where the NCDs were derived from different carbon sources (e.g., citric acid and l-malic acid) and varying mole ratios of the nitrogen source (i.e., urea). The impact of NCDs on Au nanoparticle-mediated catalysis has been investigated using the model reaction of hydrogenation of 4-nitrophenol (4-NP) in the presence of NaBH4. The fractions of different nitrogen species (such as pyrrolic, pyridinic, and amidic) in the different NCDs-Au nanohybrids were quantified through XPS analysis, and their roles in catalytic performance have been studied. Further, the size, shape, crystallinity, defects, and exposed facets of the NCDs-Au nanohybrids have also been assessed (through XRD, HRTEM, and Raman studies), and their structure-activity relationships have been corroborated. The hydrogenation of 4-NP is proposed to happen through the formation of gold-hydride (Au-H) species facilitated by H• radicals, as confirmed by EPR analysis. The NCDs-Au nanohybrid, synthesized from NCDs derived from a 1:3 molar ratio of l-malic acid and urea (MU13-Au), exhibits superior catalytic efficiency with a rate constant of 1.013 min-1, attributed to its abundant defects and a notably high relative content of catalytically favorable pyridinic nitrogen species compared to other tested nanohybrids.

Biocompatible fluorescent carbon nanoparticles as nanocarriers for targeted delivery of tamoxifen for regression of Breast carcinoma.

Breast cancer (BC) is the most common malignancy among females worldwide, and its high metastasis rates are the leading cause of death just after lung cancer. Currently, tamoxifen (TAM) is a hydrophobic anticancer agent and a selective estrogen modulator (SERM), approved by the FDA that has shown potential anticancer activity against BC, but the non-targeted delivery has serious side effects that limit its ubiquitous utility. Therefore, releasing anti-cancer drugs precisely to the tumor site can improve efficacy and reduce the side effects on the body. Nanotechnology has emerged as one of the most important strategies to solve the issue of overdose TAM toxicity, owing to the ability of nano-enabled formulations to deliver desirable quantity of TAM to cancer cells over a longer period of time. In view of this, use of fluorescent carbon nanoparticles in targeted drug delivery holds novel promise for improving the efficacy, safety, and specificity of TAM therapy. Here, we synthesized biocompatible carbon nanoparticles (CNPs) using chitosan molecules without any toxic surface passivating agent. Synthesized CNPs exhibit good water dispersibility and emit intense blue fluorescence upon excitation (360 nm source). The surface of the CNPs has been functionalized with folate using click chemistry to improve the targeted drug uptake by the malignant cell. The pH difference between cancer and normal cells was successfully exploited to trigger TAM release at the target site. After six hours of incubation, CNPs released âˆ¼ 74 % of the TAM drug in acidic pH. In vitro, studies have also demonstrated that after treatment with the synthesized CNPs, significant inhibition of the tumor growth could be achieved.

White light emission from helically stacked humin-mimic based H-aggregates in heteroatom free carbon dots.

White light emission (WLE), particularly from heteroatom free carbon dots (CDs), is unusual. Besides, deciphering the origin of WLE from a H-aggregated molecular fluorophore in such kinds of CDs is a challenging task due to their non-fluorescent character resulting from a forbidden transition from a lower-energy excitonic state. Therefore, rigorous investigation on their elusive excited state photophysical properties along with their steady-state optical phenomena has to be carried out to shed light on the nature of distinct emissive states formed in the CDs. Herein, for the first time, we report WLE from imperfect H-aggregates of co-facially π-π stacked humin-like structures comprising furfural monomer units as a unique molecular fluorophore in CDs, as revealed from combined spectroscopic and microscopic studies, synthesized through hydrothermal treatment of the single precursor, dextrose. H-aggregates in CDs show a broad range of excitation-dependent emission spectra with color coordinates close to pure white light, i.e., CIE (0.35, 0.37) and a color temperature of 6000 K. Imperfect orientation between the transition dipole moments of adjacent monomer units in the H-aggregate's molecular arrangement is expected to cause ground state symmetry breaking, as confirmed by Circular Dichroism (CD) studies, which established helically stacked nature in molecular aggregates and produced significant oscillatory strength at lower energy excitonic states to enable fluorescence. TRES and TAS investigations have been performed to minimise the intricacies associated with excited state photophysics, which is regarded as an essential step in gaining a grasp on emissive states. Based on the observation of two isoemissive spots in the time-resolved area normalized emission spectra (TRANES), the existence of three oligomeric species in the excited state equilibrium of the pure/hybrid H-aggregates has been established. The exciton dynamics through electron relaxation from the higher to the lower excitonic states, charge transfer (CT) states, and surface trap mediated emission in excimer states of H-aggregates have also been endorsed as three distinct emissive states from femtosecond transient absorption spectroscopy (TAS) studies corroborating with their steady-state absorption and emission behavior. The results would demonstrate the usage of CDs as a cutting-edge fluorescent material for creating aggregate-induced white light emission.

Optical Asymmetry and Structural Complexity in Hierarchically Organized Chiral CuO Nanostructures: Insight into the Geometric and Crystallographic Effects on Cooperative Chirality.

Optical asymmetry and structural complexity across different length scales were realized in flower-shaped CuO nanostructures, prepared through refluxing an aqueous solution of copper acetate, sodium hydroxide, and D-tartaric acid, as well as in their toroid-like forms obtained on calcination at 600 °C. Atomic scale chirality in the flower morphology could be visualized as putative Boerdijk-Coexter-Bernal like tetrahelical fragments, while that in the toroid form could be identified as screw dislocation-driven helicity. The fraction of asymmetry in the nanostructures has been evaluated from their chiroptical responses based on Kuhn asymmetry factor (g) from circular dichroism (CD) spectroscopy in the entire UV-vis range. The origin of chirality in the two CuO nanostructures has been assigned to the helical arrangement of the Cu-O-Cu network in accordance with their microscopic and spectroscopic observations. Attempts have been made to interpret the crystallographic and geometric chiralities in the two CuO nanostructures based on the redshift and augmented intensity of the CD signal along with an increase in their corresponding anisotropic factor on calcination. Further, the diverse interaction of the toroid-shaped CuO nanostructures with enantiomeric tryptophan moieties has been illustrated from the measurement of their corresponding thermodynamic parameters.

Pyridinic-N-rich carbon dots in IFE-based Turn-off Fluorometric detection of nerve agent Mimic- Diethyl chlorophosphate and multicolor cell imaging.

Fluorometric sensors for the detection of nerve agent mimics have received a lot of interest nowadays due to their high sensitivity and selectivity, ease of operation, and real-time monitoring. Pyridinic-N-rich carbon dots (NCDs) prepared through microwave-assisted pyrolysis of l-Malic acid and urea have been explored first time in this work as a novel turn-off fluorescent probe for the sensitive and selective detection of diethyl chlorophosphate (DCP), a nerve agent mimic. The as-prepared carbon dots contained a large amount of pyridinic nitrogen on their surface, which can modulate the photoluminescence properties of the NCDs. The blue emissive NCDs possessed both excitation wavelength-dependent and independent emission behavior. The detection of DCP was premised on quenching of the fluorescence emission intensity of NCDs in the presence of similar chemical reagents (e.g., trimethyl phosphate, triethyl phosphate, triethyl phosphonoacetate, triphenyl phosphate, diphenyl phosphate, tributyl phosphate). Fluorescence quenching of the NCDs in the presence of DCP has been attributed to the inner filter effect (IFE). From the linear Stern-Volmer plot (R2 = 0.9992), the limit of detection (LOD) was found to be 84 µM for sensing DCP for the concentration ranging between 3 and 15 mM. The biocompatibility of NCDs was assessed through cytotoxicity assay on MDA-MB-231 breast cancer cells. Fluorescence imaging demonstrated that NCDs have low cytotoxicity and can be employed successfully in cell imaging.

Bicyclo-DNA mimics with enhanced protein binding affinities: insights from molecular dynamics simulations.

DNA-protein interactions occur at all levels of DNA expression and replication and are crucial determinants for the survival of a cell. Several modified nucleotides have been utilized to manipulate these interactions and have implications in drug discovery. In the present article, we evaluated the binding of bicyclo-nucleotides (generated by forming a methylene bridge between C1' and C5' in sugar, leading to a bicyclo system with C2' axis of symmetry at the nucleotide level) to proteins. We utilized four ssDNA-protein complexes with experimentally known binding free energies and investigated the binding of modified nucleotides to proteins via all-atom explicit solvent molecular dynamics (MD) simulations (200 ns), and compared the binding with control ssDNA-protein systems. The modified ssDNA displayed enhanced binding to proteins as compared to the control ssDNA, as seen by means of MD simulations followed by MM-PBSA calculations. Further, the Delphi-based electrostatic estimation revealed that the high binding of modified ssDNA to protein might be related to the enhanced electrostatic complementarity displayed by the modified ssDNA molecules in all the four systems considered for the study. The improved binding achieved with modified nucleotides can be utilized to design and develop anticancer/antisense molecules capable of targeting proteins or ssRNAs.Communicated by Ramaswamy H. Sarma.

Role of Surface Oxygen Vacancies and Oxygen Species on CuO Nanostructured Surfaces in Model Catalytic Oxidation and Reductions: Insight into the Structure-Activity Relationship Toward the Performance.

Defect engineering, such as modification of oxygen vacancy density, has been considered as an effective approach to tailor the catalytic performance on transition-metal oxide nanostructured surfaces. The role of oxygen vacancies (OV) on the surface of the as-prepared, zinnia-shaped morphology of CuO nanostructures and their marigold forms on calcination at 800 °C has been investigated through the study of model catalytic reactions of reduction of 4-nitrophenol and aerobic oxidation of benzyl alcohol. The OV on the surfaces of different morphologies of CuO have been identified and quantified through Rietveld analysis and HRTEM, EPR, and XPS studies. The structure-activity relationships between surface oxygen vacancies (OV) and catalytic performance have been systematically investigated. The enhanced catalytic performance of the cubic CuO nanostructures compared to their as-prepared forms has been attributed to the formation of surface oxygen species on the reactive and dominant (110) surface that has low oxygen vacancy formation energy. The mechanistic role of surface oxygen species in the studied reactions has been quantitatively correlated with the catalytic activity of the different morphological forms of the CuO nanostructures.

Seq2Enz: An application of mask BLAST methodology with a new chemical logic of amino acids for improved enzyme function prediction.

Seq2Enz method is a new way to identify whether a query protein sequence is an enzyme and to assign an enzyme class to the protein sequence. The method is based on mask BLAST fortified with some novel structural-chemical properties (NCL) of the building blocks of proteins. All available reviewed enyme sequences (267,276 in number) in Uniprot/SwissProt and most recent depositions (7062) not used for training in ECPred, a state of the art software for enzyme class prediction, are taken for assessment and the results are compared with those from conventional BLAST and ECPred respectively. Seq2Enz is seen to perform consistently better for all the enzyme classes to all the four levels. Seq2Enz methodology is converted into an easy to use web-server and made freely accessible at http://www.scfbio-iitd.res.in Seq2Enz/.

Symmetric Nucleosides as Potent Purine Nucleoside Phosphorylase Inhibitors.

Nucleic acids are one of the most enigmatic biomolecules crucial to several biological processes. Nucleic acid-protein interactions are vital for the coordinated and controlled functioning of a cell, leading to the design of several nucleoside/nucleotide analogues capable of mimicking these interactions and hold paramount importance in the field of drug discovery. Purine nucleoside phosphorylase is a well-established drug target due to its association with numerous immunodeficiency diseases. Here, we study the binding of human purine nucleoside phosphorylase (PNP) to some bidirectional symmetric nucleosides, a class of nucleoside analogues that are more flexible due to the absence of sugar pucker restraints. We compared the binding energies of PNP-symmetric nucleosides to the binding energies of PNP-inosine/Imm-H (a transition-state analogue), by means of 200 ns long all-atom explicit-solvent Gaussian accelerated molecular dynamics simulations followed by energetics estimation using the MM-PBSA methodology. Quite interestingly, we observed that a few symmetric nucleosides, namely, ν3 and ν4, showed strong binding with PNP (-14.1 and -12.6 kcal/mol, respectively), higher than inosine (-6.3 kcal/mol) and Imm-H (-9.6 kcal/mol). This is rationalized by an enhanced hydrogen-bond network for symmetric nucleosides compared to inosine and Imm-H while maintaining similar van der Waals contacts. We note that the chemical structures of both ν3 and ν4, due to an additional unsaturation in them, resemble enzymatic transition states and fall in the category of transition-state analogues (TSAs), which are quite popular.

Mask blast with a new chemical logic of amino acids for improved protein function prediction.

With the exponential increase in protein sequence data, there is an urgency to acquire a knowledge of function of the millions of sequences, using automated methods with high reliability. Conventional methods for annotating a protein sequence transfer the function of a homologous sequence with known functions based on evolutionary information. Here, we present a newer way of classifying amino acids based on chemical measures and demonstrate that, when integrated with mask BLAST, the chemical properties identified outperform current classifications of amino acids as well as evolutionary measures in function detection.

Tuning of structural and optical properties with enhanced catalytic activity in chemically synthesized Co-doped MoS2 nanosheets.

Molybdenum disulfide (MoS2) nanosheets, due to having a highly active nature, being low cost and having unique physical and chemical properties, have shown their efficacy in the catalytic reduction of nitroarenes. Doping of transition metal ions in molybdenum disulfide (MoS2) nanosheets is a well-known strategy to enhance their catalytic efficiency for the reduction of nitroarenes, however, finding the optimum dopant amount is still a subject of ongoing research. Herein, we have synthesized few-layered cobalt (Co) doped MoS2 nanosheets with different cobalt content (2%, 4%, 6% and 8%) through the solvothermal approach, taking sodium molybdate dihydrate (Na2MoO4·2H2O), thiourea (CH4N2S) and cobalt acetate tetrahydrate [Co(CH3COO)2·4H2O] as precursors and their catalytic performance has been affirmed by monitoring the reduction of p-nitrophenol by NaBH4 in real time using UV-visible absorption spectroscopy. The 6% Co doped MoS2 nanosheets have exhibited superior catalytic activity with a pseudo-first order rate constant of 3.03 × 10-3 s-1 attributed to the abundant defects in the active edge sites having a dominant metallic 1T phase with Co ion activated defective basal planes, sulphur (S) edges, synergistic structural and electronic modulation between MoS2 and Co ions and enhanced electron transfer assisted through redox cycling in the active sites. An attempt has also been made to study the manipulation of structural and optical properties with cobalt doping in MoS2 nanosheets to establish a correlation between the catalytic efficiency and dopant content. This study demonstrates that proper tuning of Co doping in MoS2 nanosheets paves the way in searching for a potential alternative of a noble metal catalyst for the catalytic reduction of nitroarenes.

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.

Identification of promising molecules against MurD ligase from Acinetobacter baumannii: insights from comparative protein modelling, virtual screening, molecular dynamics simulations and MM/PBSA analysis.

Acinetobacter baumannii, an opportunistic bacterium of the multidrug-resistant (MDR) ESKAPE family of pathogens, is responsible for 2-10% infections associated with all gram-negative bacteria. The hospital-acquired nosocomial infections caused by A.baumannii include deadly diseases like ventilator-associated pneumonia, bacteremia, septicemia and urinary tract infections (UTI). Over the last 3 years, it has evolved into multiple strains demonstrating high antibiotic resistance against a wide array of antibiotics. Hence, it becomes imperative to identify novel drug-like molecules to treat such infections effectively. UDP-N-acetylmuramoyl-L-alanine-D-glutamate ligase (MurD) is an essential enzyme of the Mur family which is responsible for peptidoglycan biosynthesis, making it a unique and ideal drug target. Initially, a homology modelling approach was employed to predict the three-dimensional model of MurD from A. baumannii using MurD from Escherichia coli (PDB ID: 4UAG) as a suitable structural template. Subsequently, an optimised model of MurD was subjected to virtual high-throughput screening (vHTS) against a ZINC library of ~ 642,759 commercially available molecules to identify promising lead compounds demonstrating high binding affinities towards it. From the screening process, four promising molecules were identified based on the estimated binding affinities (ΔG), estimated inhibition constants (Ki), catalytic residue interactions and drug-like properties, which were then subjected to molecular dynamics (MD) simulation studies to reflect the physiological state of protein molecules in vivo equivalently. The binding free energies of the selected MurD-ligand complexes were also calculated using MM/PBSA (molecular mechanics with Poisson-Boltzmann and surface area solvation) approach. Finally, the global dynamics along with binding free energy analysis suggested that ZINC19221101 (ΔG = - 62.6 ± 5.6 kcal/mol) and ZINC12454357 (ΔG = - 46.1 ± 2.6 kcal/mol) could act as most promising candidates for inhibiting the function of MurD ligase and aid in drug discovery and development against A.baumannii. Graphical abstract.

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 αß 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.

Computer aided ligand based screening for identification of promising molecules against enzymes involved in peptidoglycan biosynthetic pathway from Acinetobacter baumannii.

A. baumannii has been considered as Priority-I as suggested by the World Health Organization (WHO) and the most critical pathogenic microorganism for causing nosocomial infection in imunno-compromised hospital-acquired patients due to multi-drug resistance (MDR). In the current study, we utilized "Computer-aided ligand-based virtual screening approach" for identification of promising molecules against Mur family proteins based on the known inhibitor (Naphthyl Tetronic Acids ((5Z)-3-(4-chlorophenyl)-4-hydroxy-5-(1-naphthylmethylene) furan-2(5H)-one)) of MurB from E. coli. The in-house library was prepared using a similarity search of a known inhibitor (Drug Bank ID: DB07296) against several relevant chemical databases. The molecules obtained from virtual screening of Naphthyl Tetronic Acids in-house library were successively subjected to physicochemical and ADMET screening. After this, the molecules which passed all the filters, subsequently subjected into interaction analysis with the drug target proteins (MurB, MurD, MurE and MurG) of A. baumanni and the results explained that four molecules were promising (CHEMBL468144, DB07296, Enamine_T5956969 and 54723243) for further molecular dynamics simulations. The free and ligand bounded proteins that undergone MD simulation are listed as follows: MurB, MurB-CHEMBL468144, MurB-DB07296, MurE, MurE-54723243, MurE-DB07296, MurD, MurD-Enamine_T5956969, MurD-DB07296, MurG, MurG-CHEMBL468144, and MurG-DB07296. Based on global and essential dynamics analysis, the stability order of molecules towards MurB (CHEMBL468144 > DB07296); MurD (Enamine_T5956969 > DB07296); MurE (54723243 > DB07296) and MurG (CHEMBL468144 > DB07296) indicates that the newly identified molecules are more promising one in comparison with the existing inhibitor. Based on all the docking and MD simulation results, the stability order of the free and ligand bounded protein are as follows; MurB and MurB-ligand complexes > MurD and MurD-ligand complexes > MurG and MurG-ligand complexes > MurE and MurE-ligand complexes. Finally, the selected compounds would be recommended for further experimental investigations and used as promising inhibitors of the infection caused by A. baumannii.

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.

The UDP-N-acetylglucosamine-N-acetylmuramyl-(pentapeptide) pyrophosphoryl-undecaprenol N-acetylglucosamine transferase (MurG) is located in plasma membrane which plays a crucial role for peptidoglycan biosynthesis in Gram-negative bacteria. Recently, this protein is considered as an important and unique drug target in Acinetobacter baumannii since it plays a key role during the synthesis of peptidoglycan as well as which is not found in Homo sapiens. In this study, initially we performed comparative protein modeling approach to predict the three-dimensional model of MurG based on crystal structure of UDP-N-acetylglucosamine-N-acetylmuramyl-(pentapeptide) pyrophosphoryl-undecaprenol N-acetylglucosamine transferase (PDB ID: 1F0K) from E.coli K12. MurG model has two important functional domains located in N and C- terminus which are separated by a deep cleft. Active site residues are located between two domains and they are Gly20, Arg170, Gly200, Ser201, Gln227, Phe254, Leu275, Thr276, and Glu279 which play essential role for the function of MurG. In order to inhibit the function of MurG, we employed the High Throughput Virtual Screening (HTVS) and docking techniques to identify the promising molecules which will further subjected into screening for computing their drug like and pharmacokinetic properties. From the HTVS, we identified 5279 molecules, among these, 12 were passed the drug-like and pharmacokinetic screening analysis. Based on the interaction analysis in terms of binding affinity, inhibition constant and intermolecular interactions, we selected four molecules for further MD simulation to understand the structural stability of protein-ligand complexes. All the analysis of MD simulation suggested that ZINC09186673 and ZINC09956120 are identified as most promising putative inhibitors for MurG protein in A. baumannii.Communicated by Ramaswamy H. Sarma.

Symmetrization of the backbone of nucleic acids: a molecular dynamics study.

DNA displays directional asymmetry (5'→3'), a fundamental property associated with each strand of the nucleic acids and is crucial to several biological processes such as transcription and replication. We observe that this asymmetry can be altered by a number of ways leading to directionally symmetric nucleic acids. We report six such approaches for the creation of symmetric backbones, their insertion in a regular B-DNA structure followed by their characterization using molecular dynamics (MD) simulations on a microsecond timescale in explicit solvent. We compared the resultant MD structures of symmetric nucleic acids with that of regular B-DNA in terms of helicoidal parameters, dihedrals, groove geometry, and solvent/ions accessibility. We also compared the Watson-Crick hydrogen bond strength of these symmetric molecules to that of the control B-DNA system. It was found that the symmetric DNAs with a few substituents designed retained the double helical B-DNA type structure as seen by means of structural and energetic parameters. As an application of such symmetric molecules, we evaluated the binding free energies of single stranded symmetric nucleic acids with a short stretch of complementary RNA and found that a few molecules designed have comparable energies to that of control DNA-RNA hybrid system. As the chemical modifications in the oligonucleotides have been a remarkable tool for control over the nucleotide properties, mainly the nucleotide bending, binding to RNA targets, and stability to nucleases to design nucleoside drug analogs; the importance of the proposed symmetric molecules in these areas is foreseen.Communicated by Ramaswamy H. Sarma.

A Statistical Model-driven Surgical Case Scheduling System Improves Multiple Measures of Operative Suite Efficiency: Findings From a Single-center, Randomized Controlled Trial.

OBJECTIVE: We sought to determine whether a data-driven scheduling approach improves Operative Suite (OS) efficiency. BACKGROUND: Although efficient use of the OS is a critical determinant of access to health care services, OS scheduling methodologies are simplistic and do not account for all the available characteristics of individual surgical cases. METHODS: We randomly scheduled cases in a single OS by predicting their length using either the historical mean (HM) duration of the most recent 4 years; or a regression modeling (RM) system that accounted for operative and patient characteristics. The primary endpoint was the imprecision in prediction of the end of the operative day. Secondary endpoints included measures of OS efficiency; personnel burnout captured by the Maslach Burnout Inventory; and a composite endpoint of 30-day mortality, myocardial infarction, wound infection, bleeding, amputation, or reoperation. RESULTS: Two hundred and seven operative days were allocated to scheduling with either the RM or the HM methodology. Mean imprecision in predicting the end of the operative day was higher with the HM approach (30.8 vs 7.2 minutes, P = 0.024). RM was associated with higher throughput (379 vs 356 cases scheduled over the course of the study, P = 0.04). The composite rate of adverse 30-day events was similar (2.2% vs 3.2%, P = 0.44). The mean depersonalization score was higher (3.2 vs 2.0, P = 0.044), and mean personal accomplishment score was lower during HM weeks (37.5 vs 40.5, P = 0.028). CONCLUSIONS: Compared to the HM scheduling approach, the proposed data-driven RM scheduling methodology improves multiple measures of OS efficiency and OS personnel satisfaction without adversely affecting clinical outcomes.

Targeting of EGFR, VEGFR2, and Akt by Engineered Dual Drug Encapsulated Mesoporous Silica-Gold Nanoclusters Sensitizes Tamoxifen-Resistant Breast Cancer.

Tamoxifen administration enhanced overall disease-free survival and diminished mortality rates in cancer patients. However, patients with breast cancer often fail to respond for tamoxifen therapy due to the development of a drug-resistant phenotype. Functional analysis and molecular studies suggest that protein mutation and dysregulation of survival signaling molecules such as epidermal growth factor receptor, vascular endothelial growth factor receptor 2, and Akt contribute to tamoxifen resistance. Various strategies, including combinatorial therapies, show chemosensitize tamoxifen-resistant cancers. Based on chemotoxicity issues, researchers are actively investigating alternative therapeutic strategies. In the current study, we fabricate a mesoporous silica gold cluster nanodrug delivery system that displays exceptional tumor-targeting capability, thus promoting accretion of drug indices at the tumor site. We employ dual drugs, ZD6474, and epigallocatechin gallate (EGCG) that inhibit EGFR2, VEGFR2, and Akt signaling pathways since changes in these signaling pathways confer tamoxifen resistance in MCF 7 and T-47D cells. Mesoporous silica gold cluster nanodrug delivery of ZD6474 and EGCG sensitize tamoxifen-resistant cells to apoptosis. Western and immune-histochemical analyses confirmed the apoptotic inducing properties of the nanoformulation. Overall, results with these silica gold nanoclusters suggest that they may be a potent nanoformulation against chemoresistant cancers.