Critical appraisal and systematic review of genes linked with cocaine addiction, depression and anxiety

Recent lifestyle changes have resulted in tremendous peer pressure and mental stress, and increased the incidences of chronic psychological disorders; like addiction, depression and anxiety (ADA). In this context, the stress-tolerance levels vary amongst individuals and genetic factors play prominent roles. Vulnerable individuals may often be drawn towards drug-addiction to combat stress. This systematic review critically appraises the relationship of various genetic factors linked with the incidences of ADA development. For coherence, we focused solely on cocaine as a substance of abuse in this study. Online scholarly databases were used to screen pertinent literature using apt keywords; and the final retrieval included 42 primary-research articles. The major conclusion drawn from this systematic analysis states that there are 51 genes linked with the development of ADA; and 3 (BDNF, PERIOD2 and SLC6A4) of them are common to all the three aspects of ADA. Further, inter-connectivity analyses of the 51 genes further endorsed the central presence of BDNF and SLC6A4 genes in the development of ADA disorders. The conclusions derived from this systematic study pave the way for future studies for the identification of diagnostic biomarkers and drug targets; and for the development of novel and effective therapeutic regimens against ADA.

Diet as a modifiable factor in tumorigenesis: Focus on microbiome-derived bile acid metabolites and short-chain fatty acids

Several lines of evidences have implicated the resident microbiome as a key factor in the modulation of host physiology and pathophysiology; including the resistance to cancers. Gut microbiome heavily influences host lipid homeostasis by their modulatory effects on the metabolism of bile acids (BAs). Microbiota-derived BA metabolites such as deoxycholic acid (DCA), lithocholic acid (LCA), and ursodeoxycholic acid (UDCA) are implicated in the pathogeneses of various cancer types. The pathogenic mechanisms are multimodal in nature, with widespread influences on the host immunes system, cell survival and growth signalling and DNA damage. On the other hand, short-chain fatty acids (SCFAs) produced by the resident microbial activity on indigestible dietary fibres as well as during intermittent fasting regimens (such as the Ramazan fasting) elicit upregulation of the beneficial anti-inflammatory and anticancer pathways in the host. The present review first provides a brief overview of the molecular mechanisms of microbiota-derived lipid metabolites in promotion of tumour development. The authors then discuss the potential of diet as a therapeutic route for beneficial alteration of microbiota and the consequent changes in the production of SCFAs, particularly butyrate, in relation to the cancer prevention and treatment.

Microbial dysbiosis and epigenetics modulation in cancer development - A chemopreventive approach

An overwhelming number of research articles have reported a strong relationship of the microbiome with cancer. Microbes have been observed more commonly in the body fluids like urine, stool, mucus of people with cancer compared to the healthy controls. The microbiota is responsible for both progression and suppression activities of various diseases. Thus, to maintain healthy human physiology, host and microbiota relationship should be in a balanced state. Any disturbance in this equilibrium, referred as microbiome dysbiosis becomes a prime cause for the human body to become more prone to immunodeficiency and cancer. It is well established that some of these microbes are the causative agents, whereas others may encourage the formation of tumours, but very little is known about how these microbial communications causing change at gene and epigenome level and trigger as well as encourage the tumour growth. Various studies have reported that microbes in the gut influence DNA methylation, DNA repair and DNA damage. The genes and pathways that are altered by gut microbes are also associated with cancer advancement, predominantly those implicated in cell growth and cell signalling pathways. This study exhaustively reviews the current research advancements in understanding of dysbiosis linked with colon, lung, ovarian, breast cancers and insights into the potential molecular targets of the microbiome promoting carcinogenesis, the epigenetic alterations of various potential targets by altered microbiota, as well as the role of various chemopreventive agents for timely prevention and customized treatment against various types of cancers.

Role of epigenetics in carcinogenesis: Recent advancements in anticancer therapy

The role of epigenetics in the etiology of cancer progression is being emphasized for the past two decades to check the impact of chromatin modifiers and remodelers. Histone modifications, DNA methylation, chromatin remodeling, nucleosome positioning, regulation by non-coding RNAs and precisely microRNAs are influential epigenetic marks in the field of progressive cancer sub-types. Furthermore, constant epigenetic changes due to hyper or hypomethylation could efficiently serve as effective biomarkers of cancer diagnosis and therapeutic development. Ongoing research in the field of epigenetics has resulted in the resolutory role of various epigenetic markers and their inhibition using specific inhibitors to arrest their key cellular functions in in-vitro and pre-clinical studies. Although, the mechanism of epigenetics in cancer largely remains unexplored. Nevertheless, various advancements in the field of epigenetics have been made through transcriptome analysis and in-vitro genome targeting technologies to unravel the applicability of epigenetic markers for future cancer therapeutics and management. Therefore, this review emphasizes on recent advances in epigenetic landscapes that could be targeted/explored using novel approaches as personalized treatment modalities for cancer containment.

Quorum Quenching-Guided Inhibition of Mixed Bacterial Biofilms and Virulence Properties by Protein Derived From Leaves of Carissa carandas

The inhibition/degradation potential of Carissa carandas proteinaceous leaf extract against mixed bacterial biofilm of Staphylococcus aureus MTCC 96, Escherichia coli MTCC 1304, Pseudomonas aeruginosa MTCC 741, and Klebsiella pneumoniae MTCC 109, responsible for nosocomial infections, was evaluated. Distinct inhibition/degradation of mixed bacterial biofilm by the proteinaceous leaf extract of C. carandas was observed under a microscope, and it was found to be 80%. For mono-species biofilm, the maximum degradation of 70% was observed against S. aureus biofilm. The efficiency of aqueous plant extracts to inhibit the mono-species biofilm was observed in terms of minimum inhibitory concentration (MIC), and the best was found against P. aeruginosa (12.5 μg/ml). The presence of flavonoids, phenols, and tannins in the phytochemical analysis of the plant extract suggests the main reason for the antibiofilm property of C. carandas. From the aqueous extract, protein fraction was precipitated using 70% ammonium sulfate and dialyzed. This fraction was purified by ion-exchange chromatography and found to be stable and active at 10°C (pH 7). The purified fraction showed less than 40% cytotoxicity, which suggests that it can be explored for therapeutic purposes after in-depth testing. In order to investigate the mechanistic action of the biofilm inhibition, the plant protein was tested against Chromobacterium violaceum CV026, and its inhibitory effect confirmed its quorum quenching nature. Based on these experimental analyses, it can be speculated that the isolated plant protein might influence the signaling molecule that leads to the inhibition effect of the mixed bacterial biofilm. Further experimental studies are warranted to validate our current findings.

An Overview of Morpho-Physiological, Biochemical, and Molecular Responses of Sorghum Towards Heavy Metal Stress

Heavy metal (HM) contamination is a serious global environmental crisis. Over the past decade, industrial effluents, modern agricultural practices, and other anthropogenic activities have significantly depleted the soil environment. In plants, metal toxicity leads to compromised growth, development, productivity, and yield. Also, HMs negatively affect human health due to food chain contamination. Thus, it is imperative to reduce metal accumulation and toxicity. In nature, certain plant species exhibit an inherent capacity of amassing large amounts of HMs with remarkable tolerance. These plants with unique characteristics can be employed for the remediation of contaminated soil and water. Among different plant species, Sorghum bicolor has the potential of accumulating huge amounts of HMs, thus could be regarded as a hyperaccumulator. This means that it is a metal tolerant, high biomass producing energy crop, and thus can be utilized for phytoremediation. However, high concentrations of HMs hamper plant height, root hair density, shoot biomass, number of leaves, chlorophyll, carotenoid, and carbohydrate content. Thus, understanding the response of Sorghum towards different HMs holds considerable importance. Considering this, we have uncovered the basic information about the metal uptake, translocation, and accumulation in Sorghum. Plants respond to different HMs via sensing, signaling, and modulations in physico-chemical processes. Therefore, in this review, a glimpse of HM toxicity and the response of Sorghum at the morphological, physiological, biochemical, and molecular levels has been provided. The review highlights the future research needs and emphasizes the extensive molecular dissection of Sorghum to explore its genetic adaptability towards different abiotic stresses that can be exploited to develop resilient crop varieties.

Silybin B and Cianidanol Inhibit M pro and Spike Protein of SARS-CoV-2: Evidence from in Silico Molecular Docking Studies

BACKGROUND

The main proteases (Mpro) and Spike Proteins (SP) of Severe Acute Respiratory Syndrome Coronavirus 2 (SARSCoV-2) play a major role in viral infection development by producing several non-structural proteins (nsPs) and penetrating the host cells respectively. In this study, the potential of in silico molecular docking-based drug repositioning approach was exploited for identifying the inhibitors of Mpro and SP of SARS-CoV-2.

METHODS

A total of 196 compounds including various US-FDA-approved drugs, vitamins and their analogs were docked with Mpro (PDB IDs: 6YB7 and 6Y84), and the top six ligands were further tested for ADME properties followed by docking with SP (PDB IDs: 6LXT and 6W41).

RESULTS

Out of 196 compounds, binding energy (DE) of Silybin B (6YB7: DE: -11.20 kcal/mol; 6Y84: DE: -10.18 kcal/mol; 6LXT:DE: -10.47 kcal/mol; 6W41:DE: -10.96 kcal/mol) and Cianidanol (6YB7:DE: -8.85 kcal/mol; 6Y84:DE:-10.02 kcal/mol; 6LXT:DE:-9.36 kcal/mol; 6W41:DE: -9.52 kcal/mol) demonstrated better binding and ADME properties compared with the currently endeavored drugs like Hydroxychloroquine and Lopinavir. Additionally, Elliptinone, Diospyirin, SCHEMBL94263 and Fiboflavin have shown encouraging results. Fiboflavin, an immunity booster, was found to inhibit both the Mpro and spike protein of SARS-CoV-2. It was observed that amino acid residues MET6, ALA7, PHE8, PRO9, ASP295, GLY302, VAL303 and THR304 play significant roles in protein-ligand interactions through hydrogen bonds and Vander Waals forces.

CONCLUSION

Silybin B and Cianidanol showed excellent binding and ADME properties compared with the currently endeavored drugs and can be exploited as therapeutic options against SARS-CoV-2 infection after experimental validation and clinical trials.

Potency of inhibitors depends upon the accessibility of their aromatic rings within the hydrophobic specificity pocket: a novel avenue for future aldose reductase inhibitor design

Communicated by Ramaswamy H. Sarma.

3D Bioprinting in Plant Science: An Interdisciplinary Approach

Here we highlight advances and opportunities for using 3D bioprinting in plant biology research that could lead to low-cost solutions for biomedical and other applications. For example, the development of plant cell-based and plant-inspired 3D-printed constructs could provide information about single-cell, tissue, and whole-plant interactions with the surrounding environment.

RSM-GA Based Optimization of Bacterial PHA Production and In Silico Modulation of Citrate Synthase for Enhancing PHA Production

The inexhaustible nature and biodegradability of bioplastics like polyhydroxyalkanoates (PHAs) make them suitable assets to replace synthetic plastics. The eventual fate of these eco-friendly and non-toxic bioplastics relies upon the endeavors towards satisfying cost and, in addition, execution necessity. In this study, we utilized and statistically optimized different food (kitchen-/agro-) waste as a sole carbon/nitrogen source for the production of PHA at a reduced cost, indicating a proficient waste administration procedure. Seven different types of kitchen-/agro-waste were used as unique carbon source and four different types of nitrogen source were used to study their impact on PHA production by Bacillus subtilis MTCC 144. Among four different studied production media, mineral salt medium (MSM) (biomass: 37.7 g/L; cell dry weight: 1.8 g/L; and PHA: 1.54 g/L) was found most suitable for PHA production. Further, carbon and nitrogen components of MSM were optimized using one-factor-at-a-time experiments, and found that watermelon rind (PHA = 12.97 g/L) and pulse peel (PHA = 13.5 g/L) were the most suitable carbon and nitrogen sources, respectively, in terms of PHA (78.60%) recovery. The concentrations of these factors (sources) were statistically optimized using response surface methodology coupled with the genetic algorithm approach. Additionally, in order to enhance microbial PHA production, the interaction of citrate synthase, a key enzyme in the TCA cycle, with different known inhibitors was studied using in silico molecular docking approach. The inhibition of citrate synthase induces the blockage of the tricarboxylic cycle (TCA), thereby increasing the concentration of acetyl-CoA that helps in enhanced PHA production. Molecular docking of citrate synthase with different inhibitors of PubChem database revealed that hesperidin (PubChem compound CID ID 10621), generally present in citrus fruits, is the most efficient inhibitor of the TCA cycle with the binding score of –11.4 and warrants experimental validation. Overall, this study provides an efficient food waste management approach by reducing the production cost and enhancing the production of PHA, thereby lessening our reliance on petroleum-based plastics.

Preparation and Evaluation of the ZnO NP-Ampicillin/Sulbactam Nanoantibiotic: Optimization of Formulation Variables Using RSM Coupled GA Method and Antibacterial Activities

Nanoparticles (NPs) possessing antibacterial activity represent an effective way of overcoming bacterial resistance. In the present work, we report a novel formulation of a nanoantibiotic formed using Ampicillin/sulbactam (Ams) and a zinc oxide nanoparticle (ZnO NP). 'ZnO NP-Ams' nanoantibiotic formulation is optimized using response surface methodology coupled genetic algorithm approach. The optimized formulation of nanoantibiotic (ZnO NP: 49.9 μg/mL; Ams: 33.6 μg/mL; incubation time: 27 h) demonstrated 15% enhanced activity compared to the unoptimized formulation against K. pneumoniae. The reactive oxygen species (ROS) generation was directly proportional to the interaction time of nanoantibiotic and K. pneumoniae after the initial lag phase of ~18 h as evident from 2'-7'-Dichlorodihydrofluorescein diacetate assay. A low minimum inhibitory concentration (6.25 μg/mL) of nanoantibiotic formulation reveals that even a low concentration of nanoantibiotic can prove to be effective against K. pneumoniae. The importance of nanoantibiotic formulation is also evident by the fact that the 100 μg/mL of Ams and 25 µg of ZnO NP was required individually to inhibit the growth of K. pneumonia, whereas only 6.25 μg/mL of optimized nanoantibiotic formulation (ZnO NP and Ams in the ratio of 49.9: 33.6 in μg/mL and conjugation time of 27 h) was needed for the same.

Quantitative structure-activity relationship and molecular docking studies on human proteasome inhibitors for anticancer activity targeting NF-κB signaling pathway

The abnormal ubiquitin-proteasome is found as an important target in various human diseases, especially in cancer, and recently it has received prevalent attention as a challenging therapeutic target. The current work is designed to derive a predictive two-dimensional quantitative structure-activity relationship model for anticancer human proteasome target of NF-κB signaling pathway. The established 2 D-QSAR is dependent on multiple linear regression approach and validated through leave-One-Out and external test set prediction method. The robust QSAR model showed the r² of 0.83 and q² of 0.80 and pred_r² of 0.77. Three chemical properties, electronegativity count, average potential, and T_2_N_6 were identified as significant descriptors to predict the anticancer activities of the proteasome antagonists. Besides, the predicted top hit compounds were considered to check out the compliance with Rule of five and pharmacokinetic parameters for oral bioavailability in the human body. The molecular docking was accomplished to unravel the molecular mode of action of best-predicted compounds which was compatible with the standard drug. Following this approach, lastly two compounds NP and AP were recognized as the best candidates since these top compounds follow all the standard limit point of entire filters and indicated effective and decent docking score. The outcomes of the study sturdily suggested that the developed model and top hit compound's binding conformation are rational in the exploration of unknown antagonist's anticancer activity. The research would be of great support and is supposed to be of immense significance in the development and designing of drug-like candidates in preliminary drug discovery. Communicated by Ramaswamy H. Sarma.

3D-QSAR and docking studies on ursolic acid derivatives for anticancer activity based on bladder cell line T24 targeting NF-kB pathway inhibition

Bladder cancer is the common reason for mortality worldwide, and its increasing rate announces as a significant area of research in drug designing. The side effects and toxicity of existing drugs and the consequence of gradual cancer cell resistance against the available therapy make the treatment poor. Globally, there is a continuous high demand to develop new, more potent, and easily affordable drugs against cancer. The current research article illustrates the application of developed three-dimensional quantitative structure-activity relationship (3D-QSAR) based on human bladder cancer cell line T24 in vitro anticancer activity. The derived QSAR model has been used for prediction of natural compounds and analogs with 80% similarity of the most active compound of the dataset. The developed model describes the structure-activity relationship for terpenes and their derivatives at the molecular level. The developed comparative molecular field analysis (CoMFA) model shows a satisfactory cross-validation correlation coefficient (q2) of 0.54 and a regression correlation coefficient (r2) of 0.86. In order to evaluate the compliance with electronic pharmacokinetic parameters, Lipinski's rule of five filter, absorption, distribution, metabolism, and excretion (ADME) and toxicity of predicted compounds have been calculated. Furthermore, molecular-docking study has been performed to prioritize these predicted compounds based on their docking score and binding pocket similarity through the identified potential anticancer targets. Finally, two compounds T9 and B42 have been identified as the best hit because these two fall within the standard limits of all filters and show a good binding affinity. Conclusively, all satisfactory results strongly suggest that the derived 3D-QSAR model and obtained candidate's binding structures are reasonable in the prediction of a new antagonist's activity. The strategy adopted in the present research is expected to be of immense importance and a great support in the identification and optimization of lead in the early and advance drug discovery.

In-Silico Identification of Drug Lead Molecule Against Pesticide Exposed-neurodevelopmental Disorders Through Network-Based Computational Model Approach

Background:

Neurodevelopmental Disorders (NDDs) are impairment of the growth and development of the brain or central nervous system, which occurs at the developmental stage. This can include developmental brain dysfunction, which can manifest as neuropsychiatric problems or impaired motor function, learning, language or non-verbal communication. These include the array of disorder, including: Autism Spectrum Disorders (ASD), Attention Deficit Hyperactivity Disorders (ADHD) etc. There is no particular diagnosis and cure for NDDs. These disorders seem to be result from a combination of genetic, biological, psychosocial and environmental risk factors. Diverse scientific literature reveals the adverse effect of environmental factors specifically, exposure of pesticides, which leads to growing number of human pathological conditions; among these, neurodevelopmental disorder is an emerging issue nowadays.

Objective:

The current study focused on in silico identification of potential drug targets for pesticides induced neurodevelopmental disorder including Attention Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD) and to design potential drug molecule for the target through drug discovery approaches.

Methods:

We identified 139 candidate genes for ADHD and 206 candidate genes for ASD from the NCBI database for detailed study. Protein-protein interaction network analysis was performed to identify key genes/proteins in the network by using STRING 10.0 database and Cytoscape 3.3.0 software. The 3D structure of target protein was built and validated. Molecular docking was performed against twenty seven possible phytochemicals i.e. beta amyrin, ajmaline, serpentine, urosolic, huperzine A etc. having neuroprotective activity. The best-docked compound was identified by the lowest Binding Energy (BE). Further, the prediction of drug-likeness and bioactivity analysis of leads were performed by using molinspiration cheminformatics software.

Result & Conclusion:

Based on betweenness centrality and node degree as a network topological parameter, solute carrier family 6 member 4 (SLC6A4) was identified as a common key protein in both the networks. 3-D structure of SLC6A4 protein was designed and validated respectively. Based on the lowest binding energy, beta amyrin (B.E = -8.54 kcal/mol) was selected as a potential drug candidate against SLC6A4 protein. Prediction of drug-likeness and bioactivity analysis of leads showed drug candidate as a potential inhibitor. Beta amyrin (CID: 73145) was obtained as the most potential therapeutic inhibitor for ASD & ADHD in human.

Isolation, Purification, and Characterization of Heparinase from Streptomyces variabilis MTCC 12266

Arterial/venous thrombosis is the major cardiovascular disorder accountable for substantial mortality; and the current demand for antithrombotic agents is extensive. Heparinases depolymerize unfractionated heparin (UFH) for the production of low molecular-weight heparins (LMWHs; used as anticoagulants against thrombosis). A microbial strain of Streptomyces sp. showing antithrombotic activity was isolated from the soil sample collected from north India. The strain was characterized by using 16S rRNA homology technique and identified as Streptomyces variabilis MTCC 12266 capable of producing heparinase enzyme. This is the very first communication reporting Streptomyces genus as the producer of heparinase. It was observed that the production of intracellular heparinase was [63.8 U/mg protein (specific activity)] 1.58 folds higher compared to extracellular heparinase [40.28 U/mg protein]. DEAE-Sephadex A-50 column followed by Sepharose-6B column purification of the crude protein resulted 19.18 folds purified heparinase. SDS-PAGE analysis of heparinase resulted an estimated molecular-weight of 42 kDa. It was also found that intracellular heparinase has the ability to depolymerize heparin to generate LMWHs. Further studies related to the mechanistic action, structural details, and genomics involved in heparinase production from Streptomyces variabilis are warranted for large scale production/purification optimization of heparinase for antithrombotic applications.

A trial sequential meta-analysis of IFN-γ +874 A>T (rs2430561) gene polymorphism and extrapulmonary tuberculosis risk

Interferon-γ (IFN-γ) plays a crucial role in immunological responses against Mycobacterium tuberculosis (M.tb) infection. The polymorphism at +874 A > T (rs2430561) influences the levels of IFN-γ, which may further influence the susceptibility to extrapulmonary tuberculosis (EPTB). This polymorphism has been investigated with respect to EPTB occurrence in different populations and provided contradictory and conflicting results. This study was performed to meta-statistically analyze the data and draw a more accurate conclusion regarding the association of IFN-γ +874 A > T gene polymorphism and EPTB susceptibility. A quantitative synthesis was executed for the pertinent studies retrieved from online web-databases viz. Google Scholar, PubMed/Medline and EMBASE. The pooled odds ratios (ORs) and confidence intervals (95% CIs) were estimated for all the genetic models by meta-analysis. A total of eight studies were retrieved which included 762 confirmed EPTB cases and 1341 controls. The meta-analysis results revealed reduced association of EPTB in allelic contrast (T vs. A: p = 0.001; OR = 0.668, 95% CI = 0.524 to 0.850), homozygous (TT vs. AA: p = 0.017; OR = 0.450, 95% CI = 0.234 to 0.868), heterozygous (AT vs. AA: p = 0.004; OR = 0.574, 95% CI = 0.395 to 0.835), dominant (TT + AT vs. AA: p = 0.003; OR = 0.536, 95% CI = 0.354 to 0.810) and recessive (TT vs. AA + AT: p = 0.039; OR = 0.662, 95% CI = 0.448 to 0.980) genetic models. Furthermore, re-sampling statistics also revealed reduced risk of EPTB in overall population and Asian subgroup. This meta-analysis concluded that IFN-γ +874 A > T gene polymorphism is meaningfully related with the reduced EPTB risk in overall and Asian population, and further necessitates larger studies to be conducted on this topic in other races.

Association of MBL2 gene polymorphisms with pulmonary tuberculosis susceptibility: trial sequence meta-analysis as evidence

Background

Mannose-binding lectin (MBL) or mannose-binding protein (MBP), encoded by MBL2 gene and secreted by the liver, activates complement system through lectin pathway in innate immunity against the host’s infection. Conflictingly, a number of MBL2 variants, rs1800450 (A>B), rs1800451 (A>C), rs5030737 (A>D), rs7096206 (Y>X), rs11003125 (H>L), and rs7095891 (P>Q) allele, have been found to be associated with compromised serum levels and pulmonary tuberculosis (PTB) susceptibility. The present meta-analysis study was performed to evaluate the potential association of these MBL2 gene variants with PTB susceptibility.

Materials and methods

A quantitative synthesis was performed on PubMed (Medline), EMBASE, and Google Scholar web database searches. A meta-analysis was performed to calculate the pooled odds ratios and 95% CIs for all the genetic models.

Results

A total of 14 eligible studies were included to analyze their pooled data for associations between alleles, genotypes, and minor allele carriers. The statistical analysis revealed the significant reduced PTB risk with homozygous variant genotype of rs1800451 polymorphism (CC vs AA: P=0.043; OR =0.828, 95% CI =0.689–0.994). Contrary to this, the variant allele of rs5030737 polymorphism showed association with increased PTB risk (D vs A: P=0.026; OR =1.563, 95% CI =1.054–2.317). However, the other genetic models of rs1800450 (A>B), rs7096206 (Y>X), and rs11003125 (H>L) MBL2 gene polymorphisms did not divulge any association with PTB susceptibility.

Conclusion

The current meta-analysis concludes that rs1800451 (A>C) and rs5030737 (A>D) polymorphisms of MBL2 gene play a significant role in PTB susceptibility. Further, well-designed epidemiological studies with larger sample size including consideration of environmental factors are warranted for the future.

Angiotensin-Converting Enzyme Gene I/D Polymorphism Is Associated With Systemic Lupus Erythematosus Susceptibility: An Updated Meta-Analysis and Trial Sequential Analysis

Angiotensin-converting enzyme (ACE) gene is indispensable for endothelial control and vascular tone regulatory systems, usually affected in Systemic Lupus Erythematosus (SLE). ACE insertion/deletion (I/D) polymorphism may influence the progress of SLE. Earlier studies have investigated this association without any consistency in results. We performed this meta-analysis to evaluate the precise association between ACE I/D polymorphism and SLE susceptibility. The relevant studies were searched until December, 2017 using Medline (PubMed), Google-Scholar and EMBASE search engines. Twenty-five published studies involving 3,308 cases and 4,235 controls were included in this meta-analysis. Statistically significant increased risk was found for allelic (D vs. I: p = 0.007; OR = 1.202, 95% CI = 1.052–1.374), homozygous (DD vs. II: p = 0.025; OR = 1.347, 95% CI = 1.038–1.748), dominant (DD+ID vs. II: p = 0.002; OR = 1.195, 95% CI = 1.070–1.334), and recessive (DD vs. ID+II: p = 0.023; OR = 1.338, 95% CI = 1.042–1.718) genetic models. Subgroup analysis stratified by Asian ethnicity revealed significant risk of SLE in allelic (D vs. I: p = 0.045; OR = 1.238, 95% CI = 1.005–1.525) and marginal risk in dominant (DD+ID vs. II: p = 0.056; OR = 1.192, 95% CI = 0.995–1.428) models; whereas, no association was observed for Caucasian and African population. Publication bias was absent. In conclusion, ACE I/D polymorphism has significant role in overall SLE risk and it can be exploited as a prognostic marker for early SLE predisposition.

MIF -173 G > C (rs755622) Gene Polymorphism Modulates Tuberculosis Risk: Evidence from a Meta-analysis and Trial Sequential Analysis

The macrophage migration inhibitory factor (MIF) is a cytokine that plays an important role in inhibiting the growth of pathogenic Mycobacterium tuberculosis (M.tb) and regulates immune responses against M.tb pathogen. MIF -173 G > C gene polymorphism may affect immunity in an individual and leads to susceptibility to tuberculosis (TB). A large number of studies have investigated the relevance of this polymorphism with TB risk, but their results were inconclusive. To obtain a precise conclusion, a meta-analysis was performed by retrieving six eligible studies from Google Scholar, PubMed (Medline), and EMBASE online databases. Overall combined analysis suggested increased TB risk between MIF -173 G > C polymorphism and overall risk in four genetic models, i.e., allelic (C vs. G: p = 0.001; OR = 1.517, 95% CI = 1.312 to 1.753), homozygous (CC vs. GG: p = 0.026; OR = 1.874, 95% CI = 1.079 to 3.257), heterozygous (GC vs. GG: p = 0.001; OR = 1.542, 95% CI = 1.273 to 1.868) and dominant model (CC + GC vs. GG: p = 0.001; OR = 1.631, 95% CI = 1.362 to 1.955). Similarly, increased TB risk was observed in subgroup analysis of Asian ethnicity. No publication bias was observed. These results suggested that MIF -173 G > C variant is a significant risk factor for TB in overall and in Asian populations, and can be used as prognostic marker for TB susceptibility.

Genome-wide identification of novel vaccine candidates for Plasmodium falciparum malaria using integrative bioinformatics approaches

In spite of decades of malaria research and clinical trials, a fully effective and long-lasting preventive vaccine remains elusive. In the present study, 5370 proteins of Plasmodium falciparum genome were screened for the presence of signal peptide/anchor and GPI anchor motifs. Out of 45 screened surface-associated proteins, 22 were consensually predicted as antigens and had no orthologs in human and mouse except circumsporozoite protein (PF3D7_0304600). Among 22 proteins, 19 were identified as new antigens. In the next step, a total of 4944 peptides were predicted as CD8+ T cell epitopes from 22 probable antigens. Of these, the highest scoring 262 epitopes from each antigen were taken for optimization study in the malaria-endemic regions which covered a broad human population (~93.95%). The predicted epitope 13ILFYFFLWV21 of antigen 6-cysteine (PF3D7_1346800) was binding to the HLA-A*0201 allele with the highest fraction (26%) of immunogenicity in the target populations of North-East Asia, South-East Asia, and sub-Saharan Africa. Therefore, these epitopes are proposed to be favored in vaccine designs against malaria.

Vitamin D Receptor ApaI (rs7975232) Polymorphism Confers Decreased Risk of Pulmonary Tuberculosis in Overall and African Population, but not in Asians: Evidence from a Meta-analysis

GOALS

The involvement of the VDR ApaI gene polymorphism in the development of pulmonary tuberculosis (PTB) has been reported by numerous published studies and yielded inconsistent results. The present meta-analysis evaluated the association of VDR ApaI polymorphism and risk of PTB occurrence.

PROCEDURES

PubMed (Medline), EMBASE and Google Scholar web-databases were searched and a meta-analysis was performed by calculating the pooled odds ratios (ORs) and 95% confidence intervals (95% CIs).

RESULTS

This meta-analysis included a total of 14 eligible studies comprising of 1958 confirmed PTB cases and 2938 controls. We observed decreased risk of PTB in allelic (a vs. A: p=0.003; OR=0.873, 95% CI=0.798 to 0.955), homozygous (aa vs. AA: p=0.006; OR=0.761, 95% CI=0.626 to 0.924), dominant (aa+Aa vs. AA: p=0.039; OR=0.874, 95% CI=0.769 to 0.993) and recessive (aa vs. AA+Aa: p=0.025; OR=0.819, 95% CI=0.688 to 0.975) genetic models. During subgroup analysis, allele (a vs. A: p=0.005; OR=0.846, 95% CI=0.753 to 0.951), homozygous (aa vs. AA: p=0.002; OR=0.662, 95% CI=0.513 to 0.854) and recessive genetic models (aa vs. AA+Aa: p=0.003; OR=0.709, 95% CI=0.566 to 0.889) demonstrated decreased PTB risk in African population. However, no significant association was observed in Asian population.

CONCLUSION

In conclusion, VDR ApaI polymorphism is significantly associated with decreased risk of PTB for in overall and African population, but not in Asians.

Acacetin promotes healthy aging by altering stress response in Caenorhabditis elegans

The progression in lifespan has been associated with elevated intracellular reactive oxygen species (ROS) and oxidative stress level which contributes to development of age related disorders. The discovery of lifespan modulating phytomolecules may promote development of natural therapies against age related afflictions. Acacetin (5,7-dihydroxy-4-methoxyflavone), is a naturally occurring flavonoid known to possess therapeutic properties. To this end, the present study evaluates effect of acacetin (AC) on lifespan, stress and neurotoxicity for the first time by using well-established free living, multicellular Caenorhabditis elegans model system. The 25 μM dose of AC significantly prolonged the mean lifespan of worms by 27.31% in comparison to untreated control and other tested doses of AC. Additionally, AC enhanced stress resistance against oxidative and thermal stress in worms. Furthermore, AC attenuated age related intracellular ROS level, aggregation of age pigment lipofuscin and increased the mean survival in stress hypersensitive mev-1 mutant by 40.5%. AC supplementation also reduced the alpha synuclein aggregation in transgenic worm model of Parkinson's disease. The enhanced stress resistance, lifespan and alleviation of age related pathology can be attributed to increment in stress modulatory enzymes like superoxide dismutase (SOD) and catalase (CAT) level. Altogether the results suggest AC exposure maintains stress level, health span and extends mean lifespan of C. elegans. The longevity promoting and neuromodulatory effects of AC are mediated by up regulation of the stress response genes sod-3 and gst-4. The present finding gives new insights of natural remedies and their future prospects in developing therapeutic interventions for managing age related diseases.

Purification and characterization of chitinase from Streptomyces violascens NRRL B2700

Chitinase is one of the important enzymes as it is directly linked to Chitin that has wide applications in industrial, medical and commercial fields for its biocompatibility and biodegradability. Here, we report extracellular chitinase production by Streptomyces violascens NRRL B2700 under submerged fermentation condition. Chitinase production started after 10 h of incubation and reached to maximum level at 72 h of cultivation. Studies on the influence of additional carbon and nitrogen sources on chitinase production revealed that maltose, xylose, fructose, lactose, soybean meal and ammonium nitrate served as good carbon and nitrogen sources to enhance chitinase yield by 1.6 to 6 fold. Medium supplemented with 1% colloidal chitin produced high chitinase concentration (0.1714 U/mg). The enzyme chitinase was purified from the culture broth by 75% ammonium sulphate precipitation, DEAE-cellulose ion-exchange and sephadex G-100 gel filtration. The molecular mass of the purified chitinase was 65 kDa as estimated by SDS-PAGE. The apparent Michaelis constant (K(m)) and the maximum rate (V(max)) of the enzyme for colloidal chitin were 1.556 mg/mL and 2.680 μM/min/mg, respectively suggested high affinity towards-chitin. Possibly, it is the first report on production of chitinase from S. violascens NRRL B2700. The findings were encouraging, especially for cost effective production, and further warrants media and purification optimization studies for enhanced yield.

Length of Stay of Orthopaedic Inpatients at a Teaching Hospital in Eastern Part of Nepal

INTRODUCTION

This study aimed to analyze the average length of stay of all inpatients in the department of Orthopaedics and to compare the variations in hospital stay between age, gender, traumatic and non-traumatic co-morbidities and modality of payment.

METHODS

This hospital based retrospective descriptive epidemiological study was based on patients discharged from a tertiary level health care center of eastern Nepal. Registry data of 1 year was used to calculate length of stay and analyze the variations.

RESULTS

Average length of stay was 10.5 days. It was 10.7 days for males and 10.1 days for females. It was 10.12 days for patients paying themselves for their treatment whereas 14.98 days for patients receiving reimbursement (third party payment).

CONCLUSIONS

Average length of stay was more in elderly and patients of trauma (longest in pelvis injury). It was 1.5 times longer for patients receiving reimbursement for treatment.

Characterization of Plasmodium falciparum Proteome at Asexual Blood Stages for Screening of Effective Vaccine Candidates: An Immunoinformatics Approach

Malaria is a complex parasitic disease that is currently causing great concerns globally owing to the resistance to antimalarial drugs and lack of an effective vaccine. The present study involves the characterization of extracellular secretory proteins as vaccine candidates derived from proteome analysis of Plasmodium falciparum at asexual blood stages of malaria. Among the screened 32 proteins, 31 were predicted as antigens by the VaxiJen program, and 26 proteins had less than two transmembrane spanning regions predicted using the THMMM program. Moreover, 10 and 5 proteins were predicted to contain secretory signals by SignalP and TargetP, respectively. T-cell epitope prediction using MULTIPRED2 and NetCTL programs revealed that most of the predicted antigens are immunogenic and contain more than 10% supertype and 5% promiscuous epitopes of HLA-A, -B, or -DR. We anticipate that T-cell immune responses against asexual blood stages of Plasmodium are dispersed on a relatively large number of parasite antigens. This is the first report, to the best of our knowledge, offering new insights, at the proteome level, for the putative screening of effective vaccine candidates against the malaria pathogen. The findings also suggest new ways forward for the modern omics-guided vaccine target discovery using reverse vaccinology.

Reconstruction and visualization of carbohydrate, N-glycosylation pathways in Pichia pastoris CBS7435 using computational and system biology approaches

Pichia pastoris is an efficient expression system for production of recombinant proteins. To understand its physiology for building novel applications it is important to understand and reconstruct its metabolic network. The metabolic reconstruction approach connects genotype with phenotype. Here, we have attempted to reconstruct carbohydrate metabolism pathways responsible for high biomass density and N-glycosylation pathways involved in the post translational modification of proteins of P. pastoris CBS7435. Both these metabolic pathways play a crucial role in heterologous protein production. We report novel, missing and unannotated enzymes involved in the target metabolic pathways. A strong possibility of cellulose and xylose metabolic processes in P. pastoris CBS7435 suggests its use in the area of biofuels. The reconstructed metabolic networks can be used for increased yields and improved product quality, for designing appropriate growth medium, for production of recombinant therapeutics and for making biofuels.

GENOME WIDE IDENTIFICATION OF DNA BINDING MOTIFS OF NodD-FACTOR IN SINORHIZOBIUM MELILOTI AND MESORHIZOBIUM LOTI

NodD transcription factor is a regulatory protein of nitrogen fixing bacteria, which activates expression of nod genes participating in nodulation during interaction with its symbiont legumes. It's DNA binding motifs have been characterized and reported in Sinorhizobium meliloti and this pattern information has been used in our theoretical analyses to detect its novel regulated genes in genomes of S. meliloti and Mesorhizobium loti. M. loti, a symbiont to model legume plant Lotus japonicus, showed presence of these regulatory motifs in upstream sequences of nod and other functionally related genes. The methodology involved comparative potential weight matrix construction through GIBBS SAMPLER (RSAT) and MEME tools, using information of conserved upstream sequences of nine genes including nod and neighboring genes of both genomes possessing nod-box like motif. The resultant DNA consensus sequence had highly conserved nod-box like 17 bp long motif consensus sequence pattern for binding of detected NodD transcription factors as analyzed by homologous clustering method and therefore the genome wide predictions were considered highly accurate since confirmed by operon delineation method and the described methodology can be used in other nitrogen fixing bacteria to pursue the study in detail.

2D-QSAR model development and analysis on variant groups of anti-tuberculosis drugs

A quantitative structure activity relationship study was performed on different groups of anti-tuberculosis drug compound for establishing quantitative relationship between biological activity and their physicochemical /structural properties. In recent years, a large number of herbal drugs are promoted in treatment of tuberculosis especially due to the emergence of MDR (multi drug resistance) and XDR (extensive drug resistance) tuberculosis. Multidrug-resistant TB (MDR-TB) is resistant to front-line drugs (isoniazid and rifampicin, the most powerful anti-TB drugs) and extensively drug-resistant TB (XDR-TB) is resistant to front-line and second-line drugs. The possibility of drug resistance TB increases when patient does not take prescribed drugs for defined time period. Natural products (secondary metabolites) isolated from the variety of sources including terrestrial and marine plants and animals, and microorganisms, have been recognized as having antituberculosis action and have recently been tested preclinically for their growth inhibitory activity towards Mycobacterium tuberculosis or related organisms. A quantitative structure activity relationship (QSAR) studies were performed to explore the antituberculosis compound from the derivatives of natural products . Theoretical results are in accord with the in vitro experimental data with reported growth inhibitory activity towards Mycobacterium tuberculosis or related organisms. Antitubercular activity was predicted through QSAR model, developed by forward feed multiple linear regression method with leave-one-out approach. Relationship correlating measure of QSAR model was 74% (R(2) = 0.74) and predictive accuracy was 72% (RCV(2) = 0.72). QSAR studies indicate that dipole energy and heat of formation correlate well with anti-tubercular activity. These results could offer useful references for understanding mechanisms and directing the molecular design of new lead compounds with improved anti-tubercular activity. The generated QSAR model revealed the importance of structural, thermodynamic and electro topological parameters. The quantitative structure activity relationship provides important structural insight in designing of potent antitubercular agent.

Molecular docking studies on quinazoline antifolate derivatives as human thymidylate synthase inhibitors

We have performed molecular docking on quinazoline antifolates complexed with human thymidylate synthase to gain insight into the structural preferences of these inhibitors. The study was conducted on a selected set of one hundred six compounds with variation in structure and activity. The structural analyses indicate that the coordinate bond interactions, the hydrogen bond interactions, the van der Waals interactions as well as the hydrophobic interactions between ligand and receptor are responsible simultaneously for the preference of inhibition and potency. In this study, fast flexible docking simulations were performed on quinazoline antifolates derivatives as human thymidylate synthase inhibitors. The results indicated that the quinazoline ring of the inhibitors forms hydrophobic contacts with Leu192, Leu221 and Tyr258 and stacking interaction is conserved in complex with the inhibitor and cofactor.

Identification and characterization of merozoite surface protein 1 epitope

Malaria is an important tropical infection which urgently requires intervention of an effective vaccine. Antigenic variations of the parasite and allelic diversity of the host are main problems in the development of an effective malaria vaccine. Cytotoxic T lymphocytes (CTL) directed against Plasmodium falciparum-derived antigens are shown to play an important role for the protection against malaria. The merozoite surface protein 1 (MSP1) is expressed in all the four life-cycle stages of Plasmodium falciparum and did not find any sequence similarity to human and mouse reference proteins. MSP1 is a known target of the immune response and a single CTL epitope binding to the HLA-A*0201 is available for merozoite form. Here, we report the results from the computational characterization of MSP1, precursor (1720 residue) and screening of highest scoring potential CTL epitopes for 1712 overlapping peptides binding to thirty four HLA class-I alleles and twelve HLA class-I supertypes (5 HLA-A and 7 HLA-B) using bioinformatics tools. Supertypes are the clustered groups of HLA class-I molecules, representing a sets of molecules that share largely overlapping peptide binding specificity. The prediction results for MSP1 as adhesin and adhesin-like in terms of probability is 1.0. Results also show that MSP1 has orthologs to other related species as well as having non allergenicity and single transmembrane properties demonstrating its suitability as a vaccine candidate. The predicted peptides are expected to be useful in the design of multi-epitope vaccines without compromising the human population coverage.

Prediction of MHC class I binding peptides using probability distribution functions

Binding of peptides to specific Major Histo-compatibility Complex (MHC) molecule is important for understanding immunity and has applications to vaccine discovery and design of immunotherapy. Artificial neural networks (ANN) are widely used by predictions tools to classify the peptides as binders or non-binders (BNB). However, the number of known binders to a specific MHC molecule is limited in many cases, which poses a computational challenge for prediction of BNB and hence, needs improvement in learning of ANN. Here, we describe, the application of probability distribution functions to initialize the weights and biases of the artificial neural network in order to predict HLA-A*0201 binders and non-binders. The 10-fold cross validation has been used to validate the results. It is evident from the results that the A(ROC) for 90% of test cases for Weibull, Uniform and Rayleigh distributions is in the range 0.90-1.0. Further, the standard deviation for AROC was minimum for Weibull distribution, and may be used to train the artificial neural network for HLA-A*0201 MHC Class-I binders and non-binders prediction.

Detection of aerolysin gene in Aeromonas hydrophila isolated from fish and pond water

Aerolysin is a hemolytic toxin encoded by aerolysin gene (1482 bp) that plays a key role in the pathogenesis of Aeromonas hydrophila infection in fish. New speciesspecific primers were designed to amplify 326 bp conserved region of aerolysin gene for A. hydrophila. Twenty-five isolates of A. hydrophila recovered from fish and pond water were studied for detection of aerolysin gene. Aerolysin gene was detected in 85% of the isolates during the study. The designed primers were highly specific and showed no cross reactivity with Escherichia coli, Aeromonas veronii, Vibrio cholerae, Flavobacterium spp., Chyseobacterium spp. and Staphylococcus aureus. The sensitivity limit of primers for detection of aerolysin gene in the genomic DNA of A. hydrophila was 5 pg.

Performance evaluation of DNA motif discovery programs

Methods for the identification of transcription factor binding sites have proved to be useful for deciphering genetic regulatory networks. The strengths and weaknesses for a number of available web tools are not fully understood. Here, we designed a comprehensive set of performance measures and benchmarked sequence-based motif discovery tools using large scale datasets (derived from Escherichia coli genome and RegulonDB database). The benchmark study showed that nucleotide based and binding site based prediction accuracy is often low and activator binding site based prediction accuracy is high.

Gene cloning, expression and homology modeling of hemolysin gene from Aeromonas hydrophila

Hemolysin is a significant toxin secreted by Aeromonas hydrophila, which contributes pathogenicity of fish to humans. The complete ORF of hemolysin gene (1886 bp) was amplified using PCR. It was cloned in TA and sub-cloned in pET28a vector then transformed into Escherichia coli BL21(DE3) codon plus RP cells expressed by the induction with 1.0 mM of IPTG. The expected size of expressed protein was 68.0 kDa estimated by migration in 12% SDS-PAGE. Anti-His monoclonal antibodies were used to substantiate the recombinant protein by Western blotting. The percent similarity between hemolysin of A. hydrophila with other hemolytic toxins revealed that the hemolysin/aerolysin/cytotoxin sequence varied from 99.35 to 50.40%. Homology modeling was used to construct 3-D structure of hemolysin of A. hydrophila with the known crystal 3-D structure (PDB: 1XEZ). This protein can be used for immunoassays and it is suitable for vaccine candidate against A. hydrophila infection.

Molecular docking studies on DMDP derivatives as human DHFR inhibitors

Molecular docking is routinely used for understanding drug-receptor interaction in modern drug design. Here, we describe the docking of 2, 4-diamino-5-methyl-5-deazapteridine (DMDP) derivatives as inhibitors to human dihydrofolate reductase (DHFR). We docked 78 DMDP derivates collected from literature to DHFR and studied their specific interactions with DHFR. A new shape-based method, LigandFit, was used for docking DMDP derivatives into DHFR active sites. The result indicates that the molecular docking approach is reliable and produces a good correlation coefficient (r² = 0.499) for the 73 compounds between docking score and IC(50) values (Inhibitory Activity). The chloro substituted naphthyl ring of compound 63 makes significant hydrophobic contact with Leu 22, Phe 31 and Pro 61 of the DHFR active site leading to enhanced inhibition of the enzyme. The docked complexes provide better insights to design more potent DHFR inhibitors prior to their synthesis.

Prediction of MHC binding peptide using Gibbs motif sampler, weight matrix and artificial neural network

The identification of MHC restricted epitopes is an important goal in peptide based vaccine and diagnostic development. As wet lab experiments for identification of MHC binding peptide are expensive and time consuming, in silico tools have been developed as fast alternatives, however with low performance. In the present study, we used IEDB training and blind validation datasets for the prediction of peptide binding to fourteen human MHC class I and II molecules using Gibbs motif sampler, weight matrix and artificial neural network methods. As compare to MHC class I predictor based on sequence weighting (Aroc=0.95 and CC=0.56) and artificial neural network (Aroc=0.73 and CC=0.25), MHC class II predictor based on Gibbs sampler did not perform well (Aroc=0.62 and CC=0.19). The predictive accuracy of Gibbs motif sampler in identifying the 9-mer cores of a binding peptide to DRB1 alleles are also limited (40¢), however above the random prediction (14¢). Therefore, the size of dataset (training and validation) and the correct identification of the binding core are the two main factors limiting the performance of MHC class-II binding peptide prediction. Overall, these data suggest that there is substantial room to improve the quality of the core predictions using novel approaches that capture distinct features of MHC-peptide interactions than the current approaches.

Ranking of binding and nonbinding peptides to MHC class I molecules using inverse folding approach: implications for vaccine design

T cell recognition of the peptide-MHC complex initiates a cascade of immunological events necessary for immune responses. Accurate T-cell epitope prediction is an important part of the vaccine designing. Development of predictive algorithms based on sequence profile requires a very large number of experimental binding peptide data to major histocompatibility complex (MHC) molecules. Here we used inverse folding approach to study the peptide specificity of MHC Class-I molecule with the aim of obtaining a better differentiation between binding and nonbinding sequence. Overlapping peptides, spanning the entire protein sequence, are threaded through the backbone coordinates of a known peptide fold in the MHC groove, and their interaction energies are evaluated using statistical pairwise contact potentials. We used the Miyazawa & Jernigan and Betancourt & Thirumalai tables for pairwise contact potentials, and two distance criteria (Nearest atom >> 4.0 A & C-beta >> 7.0 A) for ranking the peptides in an ascending order according to their energy values, and in most cases, known antigenic peptides are highly ranked. The predictions from threading improved when used multiple templates and average scoring scheme. In general, when structural information about a protein-peptide complex is available, the current application of the threading approach can be used to screen a large library of peptides for selection of the best binders to the target protein. The proposed scheme may significantly reduce the number of peptides to be tested in wet laboratory for epitope based vaccine design.

CoMFA and CoMSIA 3D-QSAR analysis of DMDP derivatives as anti-cancer agents

Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) based on three dimensional quantitative structure–activity relationship (3D-QSAR) studies were conducted on a series (78 compounds) of 2, 4-diamino-5-methyl-5-deazapteridine (DMDP) derivatives as potent anticancer agents. The best prediction were obtained with a CoMFA standard model (q² = 0.530, r² = 0.903) and with CoMSIA combined steric, electrostatic, hydrophobic and hydrogen bond donor fields (q² = 0.548, r² = 0.909). Both models were validated by a test set of ten compounds producing very good predictive r² values of 0.935 and 0.842, respectively. CoMFA and CoMSIA contour maps were then used to analyze the structural features of ligands to account for the activity in terms of positively contributing physiochemical properties such as steric, electrostatic, hydrophobic and hydrogen bond donor fields. The resulting contour maps produced by the best CoMFA and CoMSIA models were used to identify the structural features relevant to the biological activity in this series of analogs. This study suggests that the highly electropositive substituents with low steric tolerance are required at 5 position of the pteridine ring and bulky electronegatve substituents are required at the meta-position of the phenyl ring. The information obtained from CoMFA and CoMSIA 3-D contour maps can be used for the design of deazapteridine-based analogs as anticancer agents.

Affinity purification and partial characterization of IgM-like immunoglobulins of African catfish, Clarias gariepinus (Burchell, 1822)

IgM like macroglobulin from bovine serum albumin (BSA)-immunized African catfish C. gariepinus was purified by affinity chromatography and partially characterized. The molecular weight of this macroglobulin was 840 kDa, as estimated by gel filtration chromatography. Purified macroglobulin was analyzed using SDS-PAGE under reducing and non-reducing conditions. The molecular weight (MW) of heavy and light chain was 74.8 kDa and 27.2 kDa respectively, in presence of a reducing agent. In non-reducing SDS-PAGE, a single high MW band was observed representing tetrameric form.

Response surface optimization of effective medium constituents for the production of alkaline protease from a newly isolated strain of Pseudomonas aeruginosa

Optimization of the fermentation medium for maximum alkaline protease production was carried out with a new strain of Pseudomonas aeruginosa (B-2). Replacing the protein source/inducer (albumin in place of casein) brought about significant increase in yield after 48 hr of inoculation. Three most effective medium constituents identified by initial screening method of Plackett-Burman were albumin, (NH4)2SO4 and glucose. Central Composite Design (CCD) and Response Surface Methodology (RSM) were used in the design of the experiment and in the analysis of the results. Optimum levels of the effective medium constituents were albumin (6.586%); (NH4)2SO4, 0.164%; and glucose, 6.72%. The alkaline protease production increased from 533460 to 793492 Ul(-1).

Psychiatric morbidity following neurocysticercosis

A Case of cerebral neurocysticercosis reported with manic episode on first presentation which was confirmed after CT scan of Brain. Psychiatric manifestation showed a gradual decline following treatment with medication. Normal social and occupational functioning was ensured by prolonged treatment with Mood Stabilizer.

Cloning, expression, activity and folding studies of serine hydroxymethyltransferase: a target enzyme for cancer chemotherapy

All the members of pyridoxal-5'-phosphate-dependent enzymes are involved in the metabolism of amino acids. The sequence homology studies further divide this family into three distinct groups. A fine scrutiny of the reactions catalyzed by these enzymes shows their regio specificity; they have been considered as the largest group of enzymes having tendency to affect the valency of the same carbon atom that carries the amino group forming an amine linkage with the coenzyme. Thus, this group was named 'alpha-class of enzymes'. Serine hydroxymethyltransferase (SHMT) is a member of this alpha-class; it reversibly catalyses the conversion of serine into glycine while the hydroxymethyl group is transferred to 5,6,7,8-tetrahydrofolate. The resultant compound is the sole precursor of purine biosynthesis. Henceforth, this enzyme greatly affects nucleic acid biosynthesis in all the organisms. It is obvious that SHMT plays an indispensable role in nucleic acid biosynthesis; therefore, designing and developing a repressor/inhibitor of the SHMT gene/protein may resolve the problem of drug resistance to cancer chemotherapy. SHMT has been widely studied in many living systems (e.g. Escherichia coli, humans, sheep, rabbits, Trypanosoma, Arabidopsis, peas, tobacco) in terms of its structure, cloning, expression, purification and folding patterns. Such studies have enabled one to assess the pattern of overall kinetic and activity behaviour of the enzyme, which may further help in developing a suitable cancer therapeutic molecule.