Self-optimized Prediction Method Research Articles

In Silico Protein Analysis of Phoenix dactylifera (Date Palm) by a Bioinformatics Approach

In recent years, there has been a global increase in the study of traditional medicinal plants due to their natural origins and their bioactive compounds, allowing them to complement current pharmaceutical approaches. Conversely, computer technology has advanced, and in silico investigation has proven to be a vital tool for systematically harnessing the structural variety of natural products. The present study presents comprehensive information about the traditional plant Phoenix dactylifera (commonly known as date palm) using in silico methods. The ExPASy ProtParam server, self-optimized prediction method with alignment (SOPMA), and SWISS model were employed to identify the protein′s primary, secondary, and tertiary structures. In addition, the sequence alignment was examined by Clustal Omega, and a phylogenetic tree was constructed using the bootstrap joining technique. This bioinformatics study of P. dactylifera resulted in a quicker, low-cost, and potentially effective search for plant-based medicines or mass manufacture of bioactive compounds.

Antimicrobial peptides in Dendrobium officinale: Genomic parameters, peptide structures, and gene expression patterns.

A weak codon usage bias was found in Dendrobium catenatum (D. officiale) antimicrobial peptides (AMPs), after the analysis of relative synonymous codon usage, GC contents, and the effective number of codons. The codon usage preference was mainly influenced by natural selection pressure. The self-optimized prediction method and SWISS-MODEL were applied for peptide structural and domain analyses, and some typical antimicrobial domains were found in D. officinale AMP amino sequences, such as knot1 domain, gibberellins-stimulated domain, cupin_1 domain, defensin_like domain, and SLR1-BP (S locus-related glycoprotein 1 binding pollen coat protein) domain. To investigate the AMPs gene expression pattern, abiotic stresses, such as salt stress, drought stress, salicylic acid (SA), and methyl jasmonate (JA), were applied and the gene expression levels were detected by the real-time fluorescent quantitative polymerase chain reaction. Results showed that, even though the basic AMPs gene expressions were low, some AMPs can still be induced by salt dress, while the drought dress did not show the same impact. The SA and JA signaling pathways might be involved in most of the AMPs expressions. The natural selection of the D. officinale AMPs and thus forming diverse types of AMPs enhanced the plant's innate immunity and disease resistance capability, which would lead to a better understanding of the molecular mechanism for D. officinale adapting to the environment. The finding that salt stress, SA, and JA signaling pathways can induce AMP expression lays a foundation for the further development and functional verification of D. officinale AMPs.

In-silico structural modelling of cytochrome complex proteins of white turmeric (Curcuma zedoaria)

Curcuma zedoaria (Christm.) Roscoe (white turmeric) is a perennial herbaceous plant of family Zingiberaceae and mainly found in the wild areas of tropical and subtropical regions worldwide. The cytochrome proteins in plants play important roles in promoting their growth and development, as well as protecting them from stresses and diseases. Cytochrome proteins like psbF, psbE, petB, petD, petN, petG, and ccsA play important roles in degradation of mis-folded proteins, ATP formation, cyclic electron flow and biogenesis of c-type cytochrome of C. zedoaria. However, due to lack of structural availability of these C. zedoaria cytochrome proteins in structural databases, the physiochemical parameters of sequences were estimated using Expasy ProtParam web tool. Self-Optimized Prediction Method with Alignment (SOPMA) server and MODELLER version 9.23 were used for modelling along with Qualitative Model Energy Analysis (QMEAN) and Protein Structure Analysis (ProSA) servers were implemented for validating the secondary and tertiary structures of these proteins. The obtained QMEAN4 values of the modelled cytochrome proteins were -2.04, -1.20, -3.01, -1.57, -2.11, -1.74 and -12.87. The Z-scores obtained from ProSA server were 0.5, -0.83, -1.5, -0.58, -0.02, 0.14 and -3.73. All seven modelled structures have been submitted to protein model database (PMDB). The derived results will be helpful in further investigations towards determining the crystal structure of the hypothetical proteins, structural motifs, physiochemical properties, and also protein-protein interaction studies of various cytochrome proteins.

ISOLATION AND DETERMINATION OF CHROMIUM (VI) AND NICKEL (II) RESISTANT SIDEROPHORE PRODUCING BACILLUS CEREUS(sp) AND ANALYSIS OF THE PROTEIN EXPRESSION USING BIOINFORMATICS TOOLS

Siderophores are produced by bacteria, fungi and plants to facilitate uptake of iron, they are low-molecular-weight chelation agents and protect from stress responses. Pyoverdines act as fluorescent siderophores, plays an important role under iron-limiting conditions. During the stress condition a change in the broth culture was observed where it turned green from yellow, indicating some kind of pigment release. According to some reports the pigment release happens due to the presence of Siderophore in microorganisms. This colour change can also be considered as microbial sensor for color change detection. The bacterial sample was tested for the chromium (VI) and Nickel (II) resistant capacity, presence of siderophore, DNA and protein content. The chromium (VI) and nickel (II) resistant isolates were identified as Bacillus cereus (BF2). The siderophore was detected using qualitative and quantitative assays. Using various bioinformatics softwares the siderophore produced by Bacillus cereus (Rock 3-28) was compared with the isolated culture because both of their molecular weight varied from the range of 48kDa-65kDa. National Center For Biotechnology Information (NCBI), Basic Local Alignment Search Tool (BLAST), Clustal Omega, Expert Protein Analysis System (ExPASy), Self-Optimized Prediction Method with Alignment (SOPMA) and SWISS-MODEL tools were used to study the pyoverdine protein which coded for the enzyme L-ornithine N5-oxygenase. The FASTA sequences of the query sequence were compared with other species using BLAST. The sequences of protein were used for structural and functional analysis and for phylogenetic tree construction.

Binding site identification of COVID-19 main protease 3D structure by homology modeling

The influx of coronavirus in 2019 (COVID-19) from Wuhan of China has led to a global pandemic, undesirable hiatus, and recorded millions of infection cases with several deaths worldwide. The strain of COVID-19 has neither known treatments nor vaccines, but recent studies have shown that a few of its enzymes may have been considered as potential drug target. Since its influx, the virus has been well-studied, but a lot is not known about its protease yet. The purpose of this work was to identify the binding site in-silico and present 3D structure of COVID-19 main protease (Mpro) by homology modeling through multiple alignment followed by optimization and validation. The modeling was done by Swiss-Model template library and basic local alignment search tool (BLAST). The obtained homotrimer oligo-state model was verified for reliability using structural validation software such as PROCHECK, Verify3D, MolProbity and QMEAN. The HHBlits software was used to determine the structures that matched the target sequence by evolution. Best template, 6u7h.1.A was used to build a tertiary structure for Mpro with ProMod3 3.0.0 on the Swiss-Model workspace. Self-optimized prediction method with alignment (SOPMA) was applied to compute features of the secondary structure. The verification of quality of COVID-19 structure through Ramachandran plot showed an abundance of 99.3% of amino acid residues in allowed regions while 0.1% in disallowed region. The Verify3D rated the structure a 90.87% PASS of residues having an average 3D-1D score of at least 0.2, which validates a good environment profile for the COVID-19 Mpro model. The features of the secondary structure indicated that the modeled 3D structure of Mpro contains 32.05% α-helix and 37.17% random coil with 25.92 extended strand. DeepSite algorithm elucidates the binding site area that captured local patterns in the structure and exposed the surface cavity of the binding pocket of this protein. The main result of this study suggests that blocking expression of the protein may constitute an efficient approach for transmission blockage. Hence, our thought is that Mpro of COVID-19 may be considered a potential drug target. Nevertheless, more experimental analyses, verification and validation experiments will be required as a targeted drug or vaccine design against COVID-19 virus.

Human Papillomavirus Infections in Cervical Samples From HIV-Positive Women: Evaluation of the Presence of the Nonavalent HPV Genotypes and Genetic Diversity.

Non-nonavalent vaccine (9v) Human papillomavirus (HPV) types have been shown to have high prevalence among HIV-positive women. Here, 1444 cervical samples were tested for HPV DNA positivity. Co-infections of the 9v HPV types with other HPV types were evaluated. The HPV81 L1 and L2 genes were used to investigate the genetic variability of antigenic epitopes. HPV-positive samples were genotyped using the HPVCLART2 assay. The L1 and L2 protein sequences were analyzed using a self-optimized prediction method to predict their secondary structure. Co-occurrence probabilities of the 9v HPV types were calculated. Non9v types represented 49% of the HPV infections; 31.2% of the non9v HPV types were among the low-grade squamous intraepithelial lesion samples, and 27.3% among the high-grade squamous intraepithelial lesion samples, and several genotypes were low risk. The co-occurrence of 9v HPV types with the other genotypes was not correlated with the filogenetic distance. HPV81 showed an amino-acid substitution within the BC loop (N75Q) and the FGb loop (T315N). In the L2 protein, all of the mutations were located outside antigenic sites. The weak cross-protection of the 9v types suggests the relevance of a sustainable and effective screening program, which should be implemented by HPV DNA testing that does not include only high-risk types.

Determination of B- and T- cell epitopes for Helicobacter pylori cagPAI: An in silico approach.

Helicobacter pylori is classified as a gram-negative bacteria and can cause significant diseases, including gastric cancer, mucosa-associated lymphoid tumor, peptic ulcer, and chronic gastritis. Recent studies have shown that some autoimmune diseases are also associated with H. pylori. In the past decades, polymorphisms of certain genes of H. pylori, mechanisms and strains of H. pylori, and new therapeutic approaches have continued to be defined. Bioinformatic tools continue to be used in drug design and vaccine design. This study aimed to investigate the cag pathogenicity island (cagPAI) of H. pylori using an in silico approach, which could contribute to vaccine studies. The pathogenicity island of H. pylori was obtained from GenBank and analyzed with ClustalW software. Structures of cag Virb11 (Hp0525) and an inhibitory protein (Hp1451) were obtained, and codon optimization and secondary and tertiary structure prediction for the cagPAI of H. pylori were analyzed using Garnier-Osguthorpe-Rabson IV secondary structure prediction method and self-optimized prediction method with alignment software. The BcePred prediction server was used to distinguish linear B-cell epitopes, and prediction of T-cell was obtained with NetCTL and MHCPred. According to the physicochemical parameters, the cagPAI of H. pylori was analyzed and found to be stable, and 2 B-cell epitopes of cagPAI of H. pylori and 2 T-cell epitopes of cagPAI were found in this study. B- and T-cell epitopes that we have identified can induce both humoral and cellular immune responses. Thus, these epitopes have a potential for vaccine studies. Consequently, this in silico analysis should be combined with other pieces of evidence, including experimental data, to assign function.

Molecular Dynamic (MD) Simulation and Modeling the Bio-molecular Structure of Human UDP glucose -6-dehydrogenase Isoform 1 (hUGDH) Related to Prostate Cancer

Computational methods were used to investigate both the physical and chemical properties of UDP-glucose 6-dehydrogenase (hUGDH). Secondary structure analysis of the query model was done using the Self-Optimized Prediction method With Alignment (SOPMA), the secondary structure predictions comprise of 40.69% Alpha helixes (Hh), 17.61% Extended strand (Ee), 7.69% Beta turn (Tt) and 34.01% of Random coil (Cc) with aliphatic index of 90.00 and instability index of 33.26 which classify the protein model to be thermally stable irrespective of it environment. Comparative modeling was used to predict a reliable tertiary structure for hUGDH and the obtained 3-dimensional model was validated using DOPE score profile, Ramachandran plot, and the QMEAN Z-score. The DOPE score profile shows a high similarity between the model and the template as little or no disparity was found in the profile patterns. Ramachandran plot of the model also shows that 92.5% of the amino acid residues were found at the most favored regions which make it stereo-chemically stable. The QMEAN z-score of UDP-glucose 6-dehydrogenase was predicted to be -0.15. The superimposed structure of the model and the template also gave RMSD of 0.125. All this shows that the predicted model is of good quality. An RMSD and Rg run via molecular dynamics (MD) simulation equally shows that the protein model attained stability at around 10ns. Protein – Protein interaction (PPI) network was also generated for the model with a high confidence score from UDP-glucuronic acid decarboxylase 1 (UXS1) when interacted with the other twenty proteins. In addition, the docking studies of the model and 3PRJ receptors with two prostate cancer drugs i.e. Apalutamide and Darolutamide gave similar binding affinity ranging between 6.0kcal/mol – 8.0kcal/mol for the most favored binding of the two drugs. Hence, the model can serve as a molecular target for designing new inhibitors for prostate cancer

In silico structural modeling and analysis of physicochemical properties of curcumin synthase (CURS1, CURS2, and CURS3) proteins of Curcuma longa

BackgroundPharmaceutically important curcuminoid synthesis in C. longa is controlled by CURS1, CURS2, and CURS3 genes. The present study detected the physicochemical properties and structural characteristics including the secondary and 3D structure of CURS proteins. The primary, secondary, and tertiary structure of the CURS proteins were modeled and characterized using multiple bioinformatics tools such as ExPasy ProtParam tools, self-optimized prediction method with alignment (SOPMA), PSIPRED, and SWISS-MODEL. The predicted secondary structure of curcumin synthase provided an α-helix and random coil as the major components. The reliability of the modeled structure was confirmed using PROCHECK and QMEAN programs. ResultsThe molecular weight of CURS1 is 21093.19 Da, theoretical pI as 4.93, and an aliphatic index of 99.19. Molecular weight of CURS2 and CURS3 proteins are 20266.13 Da and 20629.52 Da, theoretical pI as 5.28 and 4.96, and an aliphatic index of 89.30 and 86.37, respectively. In the predicted secondary structure of CURS proteins, alpha helices and random coils of CURS1, CUR2, and CURS3 were 42.72, 41.38, and 44.74% and 24.87, 31.03, and 17.89, respectively. The extended strands were 16.24, 19.40, and 17.89. QMEAN Z-score is − 0.83, − 0.89, and − 1.09 for CURS1, CURS2, and CURS3, respectively. ConclusionPrediction of the 3D model of a protein by in silico analysis is a highly challenging aspect to confirm the NMR or X-ray crystallographic data. This report can contribute to the understanding of the structure, physicochemical properties, structural motifs, and protein-protein interaction of CURS1, CUR2, and CURS3.

PATSIM: Prediction and analysis of protein sequences using hybrid Knuth-Morris Pratt (KMP) and Boyer-Moore (BM) algorithm

In phylogenomic profiling, the genomic context based methods are based on the observation that two or more proteins having the same pattern of presence or absence in many diverse genomes most likely have a functional link. In this research work, a tool (PATSIM) has been developed to predict the protein patterns based on the SOPM tool. In this tool, the secondary structure for CATH database protein sequences, predicted by the SOPM (Self Optimized Prediction Method) server is passed as input to fulfill objectives such as, (i) Predict the Amino Acid Pattern using the proposed Hybrid KMP and BM algorithm, (ii) Predict the physiochemical properties such as Hydrophobic Non-Polar ALKYL Amino Acid groups, Hydrophobic Non-Polar AROMATIC Amino Acid groups, Hydrophilic Polar Neutral Amino Acid groups, Hydrophilic Polar Acidic Amino Acid groups and Hydrophilic Polar Basic Amino Acid groups of protein sequence, (iii) Predict the secondary structure of protein where the structure of protein sequence is unknown, and (iv) Similarity analysis of protein sequence (structure unknown) with the CATH database. From the results, it is inferred that this tool effectively predicts the similarity between the sequences and also identifies the protein patterns for four secondary structural classes, namely Alpha Helix (h), Beta Sheet (e), Turn (t) and Coil (c). Based on the experimental results, it is inferred that this tool identifies the physiochemical properties of the protein sequence in an effective manner. The source code and its documentation for the PATSIM tool is freely available in the GitHub public repository (https://github.com/manimkn89/Protein-Sequence-Analysis).

Bioinformatic prediction of the epitopes of Echinococcus granulosus antigen 5.

The aim of the present study was to predict and analyze the secondary structure, and B and T cell epitopes of Echinococcus granulosus antigen 5 (Ag5) using online software in order to investigate its immunogenicity and preliminarily evaluate its potential as an effective antigen peptide vaccine for cystic echinococcosis. The PortParam program was used to analyze molecular weight, the theoretical isoelectric point, instability index and other physicochemical properties. The secondary structure of the Ag5 protein was predicted using Self-Optimized Prediction method With Alignment and the tertiary structure of the Ag5 protein was predicted using 3DLigandSite together with Center for Biological Sequence Analysis Prediction Servers. Furthermore, the Immune Epitope Database software was used to predict B cell epitopes, and T cell epitopes were predicted with the BioInformatics and Molecular Analysis Section and SYFPEITHI programs. The results demonstrated that α-helixes, β-turns, random coils and extended strands account for 23.35, 10.95, 41.32, and 24.38% of the secondary structure of the Ag5 protein, respectively. Ten potential B cell epitopes of Ag5 were identified as the amino acids sequences 27–39, 70–80, 117–130, 146–168, 250–262, 284–293, 339–349, 359–371, 403–412 and 454–462, and seven potential T cell epitopes were identified as the amino acid sequences 52–60, 57–65, 182–190, 231–239, 273–281, 318–326 and 467–475. Thus, ten B cell epitopes and seven T cell epitopes were identified on Ag5, suggesting the strong immunogenicity of this protein, which could be applied to design antigen peptide vaccines for echinococcosis.

English

β-galactosidase (EC.3.2.1.23) is an important enzyme, mainly used in the preparation of lactose hydrolyzed milk suitable for people with lactose intolerance. It is essential to understand the structural and functional aspects of various β-galactosidase produced from different sources. The present work deals with the use of bioinformatics to describe the physiochemical, functional and structural properties of β-galactosidase enzymes on Bacillus sp. selected from the gene bank of NCBI. The grand average hydropathy (GRAVY) and low range of AFY63015.1 value indicates the possibility of better interaction with water and instability index were computed to characterise YP_004205251.1, ZP_10511829.1, BAL72724.1, AFY63015.1, NP_242888.1 stating that they are stable and disulfide bridges, CYS_REC recognizes the presence of 38 cysteine residues in β-galactosidase sequences and predicted most probable SS bond patterns of pairs in YP_004981461 and 1AFY63015.1. The self- optimized prediction method (SOPM) was used to predict the secondary structure. The SOPM results indicated the presence of alpha helix is more dominated in sequences AFY63015.1 and YP_004981461.1. Overall this represents in silico analysis of sequence, structural and functional information of β-galactosidase of Bacillus species. Key words: Bacillus sp., β-galactosidase, in silico analysis, physico-chemical characterization, proteomics tools.

Glutathione S-Transferase Genes Differently Expressed by Pathogen-Infection in Vitis flexuosa

Glutathione S-transferase (GST) genes from transcripts of Vitis flexuosa leaves infected with Elsinoe ampelina were characterized and analyzed for their expression using primers based on specific regions. Comparison of deduced amino acid sequences from GST transcripts of V. flexuosa showed that the score of the deduced amino acid identity ranged from 43.38% (VfGST26625 and VfGST774) to 6.67% (VfGST13892 and VfGST774). Primary and secondary structure analysis was performed using the ProtParam and Self-Optimized Prediction Method with Alignment software. A phylogenetic tree was constructed from the GST proteins by the neighbor joining method using MEGA 6.0 to investigate the relationship among VfGST, VvGST, and At GST proteins. To evaluate the differential expression pattern of GST genes by real-time polymerase chain reaction (PCR), primers specific to unique regions in each gene were obtained by alignment of the sequences. Real-time PCR revealed that GST genes were expressed differentially in the leaves of V. flexuosa infected with Botrytis cinerea, E. ampelina, and Rhizobium vitis. The expression of VfGST26625 was up-regulated, while that of others were down-regulated among five GSTs in all grapevine leaves inoculated with each pathogen. The results provided herein improve our understanding of defense responses to various pathogen attacks in grapevines.

Analysis of Structure and Expression of Grapevine 2-oxoglutarate Oxygenase Genes in Response to Low Temperature

2-Oxoglutarate (2OG) acts as a signaling molecule and plays a critical role in secondary metabolism in a variety of organisms, including plants. Six 2-oxoglutarate (2OG) and Fe(II) oxygenase (2OGO) genes, VlCE2OGO1 [Vitis labruscana 2-oxoglutarate (2OG) and Fe(II) oxygenase 1], VlCE2OGO2, VlCE2OGO3, VlCE2OGO4, VlCE2OGO5, and VlCE2OGO6, which show different expression patterns upon transcriptome analysis of ‘Campbell Early’ grapevine exposed to low temperature for 4 weeks, were analyzed for their structure and expression. Comparison of the deduced amino acid sequences of the 2OGO genes from the V. labruscana transcripts revealed sequence similarities of 38.6% (VlCE2OGO1 and VlCE2OGO2) to 19.2% (VlCE2OGO2 and VlCE2OGO3). The lengths of these genes ranged from 1053 to 2298 bp, and they encoded 316 to 380 amino acids. The prediction of the secondary structure of the encoded proteins by Self-Optimized Prediction Method with Alignment (SOPMA) indicated that all the genes contained alpha helix (23.95 to 41.71%), extended strand (16 to 22.34%), beta turn (6.65 to 9.22%), and random coil (32.97 to 51.58%) in the analysis. Specific primers from unique regions in each gene obtained by alignment of nucleotide sequences were used in real time PCR for analysis of gene expression. All tested genes showed differential expression in grapevines exposed to low temperature. Of the six transcripts, VlCE2OGO1, VlCE2OGO2, and VlCE2OGO3 were up-regulated and VlCE2OGO4, VlCE2OGO5, and VlCE2OGO6 were down-regulated in response to cold treatments at all tested time points. The 2OG genes can be used for elucidation of mechanisms of tolerance to cold and as valuable molecular genetic resources for selection in breeding programs for cold-hardy grapevines.

Molecular Characterization and Drug Designing against Hypothetical Proteins of <i>Aspergillus fumigatus</i> Af293 by Homology Modeling and Molecular Docking

Genome sequencing projects have led to an explosion of the huge amount of gene products in which many are of Hypothetical Proteins (HPs) with an unidentified function. Exploring and annotating the functions of HPs is important in ( Aspergillus fumigatus ) which is a pathogenic fungus that cause disease in individuals associated with immunodeficiency. In this study, sequence of five HPs of ( A. fumigatus Af293), which are nonhomologous to human, has been annotated from NCBI. Various computational tools such as three-dimensional (3D) structure was determined by means of homology modeling through Phyre2 and refined by ModRefiner. Then, the designed structure was evaluated with a structure validation program for instance ERRAT, PROCHECK, and QMEAN, for further structural analysis. The secondary structural features of proteins were determined through self-optimized prediction method with alignment and interacting networks by STRING. The receptor was analyzed by the active site and pocket finder tools. Docking studies were done through AutodockVina software. The 3D structure of five proteins was modeled and their ligand binding sites were identified. We have found domains and families of two proteins and these revealed that these proteins might have adenosine diphosphate-ribosylation activity, molecular chaperone, heat shock protein activity, plasminogen/hepatocyte growth factor activity, etc. Protein-ligand study of our predicted ligand shows the lowest energy of -7.4 kcal/mol for gi|66851587 and -6.7 kcal/mol for gi|66845370. Structural prediction of these proteins, detection of binding sites, and drug designing of current study will cover the way for further extensive investigation of these proteins in wet laboratory experiments and in that way assist drug design against Aspergillosis.

Molecular modeling of the human sperm associated antigen 11 B (SPAG11B) proteins

Antimicrobial proteins and peptides are ubiquitous in nature with diverse structural and biological properties. Among them, the human beta-defensins are known to contribute to the innate immune response. Besides the defensins, a number of defensin-like proteins and peptides are expressed in many organ systems including the male reproductive system. Some of the protein isoforms encoded by the sperm associated antigen 11B (SPAG11) gene in humans are beta-defensin-like and exhibit structure dependent and salt tolerant antimicrobial activity, besides contributing to sperm maturation. Though some of the functional roles of these proteins are reported, the structural and molecular features that contribute to their antimicrobial activity is not yet reported. In this study, using in silico tools, we report the three dimensional structure of the human SPAG11B proteins and their C-terminal peptides. web-based hydropathy, amphipathicity, and topology (WHAT) analyses and grand average of hydropathy (GRAVY) indices show that these proteins and peptides are amphipathic and highly hydrophilic. Self-optimized prediction method with alignment (SOPMA) analyses and circular dichroism data suggest that the secondary structure of these proteins and peptides primarily contain beta-sheet and random coil structure and alpha-helix to a lesser extent. Ramachandran plots show that majority of the amino acids in these proteins and peptides fall in the permissible regions, thus indicating stable structures. The secondary structure of SPAG11B isoforms and their peptides were not perturbed with increasing NaCl concentration (0-300 mM) and at different pH (3, 7, and 10), thus reinforcing our previously reported observation that their antimicrobial activity is salt tolerant. To the best of our knowledge, for the first time, results of our study provide vital information on the structural features of SPAG11B protein isoforms and their contribution to antimicrobial activity.

Molecular Characterization of Legionellosis Drug Target Candidate Enzyme Phosphoglucosamine Mutase from Legionella pneumophila (strain Paris): An In Silico Approach.

The harshness of legionellosis differs from mild Pontiac fever to potentially fatal Legionnaire's disease. The increasing development of drug resistance against legionellosis has led to explore new novel drug targets. It has been found that phosphoglucosamine mutase, phosphomannomutase, and phosphoglyceromutase enzymes can be used as the most probable therapeutic drug targets through extensive data mining. Phosphoglucosamine mutase is involved in amino sugar and nucleotide sugar metabolism. The purpose of this study was to predict the potential target of that specific drug. For this, the 3D structure of phosphoglucosamine mutase of Legionella pneumophila (strain Paris) was determined by means of homology modeling through Phyre2 and refined by ModRefiner. Then, the designed model was evaluated with a structure validation program, for instance, PROCHECK, ERRAT, Verify3D, and QMEAN, for further structural analysis. Secondary structural features were determined through self-optimized prediction method with alignment (SOPMA) and interacting networks by STRING. Consequently, we performed molecular docking studies. The analytical result of PROCHECK showed that 95.0% of the residues are in the most favored region, 4.50% are in the additional allowed region and 0.50% are in the generously allowed region of the Ramachandran plot. Verify3D graph value indicates a score of 0.71 and 89.791, 1.11 for ERRAT and QMEAN respectively. Arg419, Thr414, Ser412, and Thr9 were found to dock the substrate for the most favorable binding of S-mercaptocysteine. However, these findings from this current study will pave the way for further extensive investigation of this enzyme in wet lab experiments and in that way assist drug design against legionellosis.

Sequence characterization and computational analysis of the non-ribosomal peptide synthetases controlling biosynthesis of lipopeptides, fengycins and bacillomycin D, from Bacillus amyloliquefaciens Q-426

Lipopeptides secreted by bacteria attract interest because of their uses in biomedicine, biotechnology and food technology; however, harnessing their megasynthases (non-ribosomal peptide synthetases, NRPSs) has met with some difficulties in heterologous expression and crystallization. Here, we used similarity and phylogenetic analysis of NRPS sequences, including the fengycin and iturin family synthetases from Bacillus spp., and have developed a novel approach for delineating the length and boundaries of NRPS domains from Bacillus amyloliquefaciens strain Q-426. The sequences were further characterized (including specific residues and conserved motifs) that gave insight into the basis of the substrate specificity. Data from the prediction of the NRPS domains, obtained by the self-optimized prediction method with Alignment program, showed they are all structurally unstable, making it difficult to determine their crystal structures.

Bioinformatic prediction of epitopes in the Emy162 antigen of Echinococcus multilocularis

The aim of the present study was to predict the secondary structure and the T- and B-cell epitopes of the Echinococcus multilocularis Emy162 antigen, in order to reveal the dominant epitopes of the antigen. The secondary structure of the protein was analyzed using the Gamier-Robson method, and the improved self-optimized prediction method (SOPMA) server. The T- and B-cell epitopes of Emy162 were predicted using Immune Epitope Database (IEDB), Syfpeithi, Bcepred and ABCpred online software. The characteristics of hydrophilicity, flexibility, antigenic propensity and exposed surface area were predicted. The tertiary structure of the Emy162 protein was predicted by the 3DLigandSite server. The results demonstrated that random coils and β sheets accounted for 34.64 and 21.57% of the secondary structure of the Emy162 protein, respectively. This was indicative of the presence of potential dominant antigenic epitopes in Emy162. Following bioinformatic analysis, numerous distinct antigenic epitopes of Emy162 were identified. The high-scoring T-cell epitopes were located at positions 16–29, 36–39, 97–103, 119–125 and 128–135, whilst the likely B-cell epitopes were located at positions 8–10, 19–25, 44–50, 74–81, 87–93, 104–109 and 128–136. In conclusion, five T-cell and seven B-cell dominant epitopes of the Emy162 antigen were revealed by the bioinformatic methods, which may be of use in the development of a dominant epitope vaccine.

ER<i>β</i> interacting protein ERAP 140 shows age dependent alteration in its interaction and expression in male mouse brain

Estrogen mediates multiple functions in the brain through the interaction of estrogen receptor (ER)α and ERβ with a host of nuclear proteins that regulate specific gene transcription. We have identified ERAP 140, AIB 1, Trk A, Src, pCREB and CREB as ERβ interacting proteins in the mouse brain. Earlier we showed that the interaction of ERβ with ERAP 140 decreased whereas its expression increased with aging in the brain of female mice. Here we report that the pattern of interaction and expression is different in male mice as compared to females. The interaction of ERAP 140 with ERβ decreased in adult male mouse brain as compared to young and remained almost similar in old whereas its expression was higher in adult than young and old, which were almost similar. Further in silico secondary structure analysis by self-optimized prediction method alignment (SOPMA) and PSIPRED revealed that ERβ interacting proteins were rich in alpha helices and coils. Such findings might help to design ER modulators which can regulate specific functions of estrogen in the brain during aging and degenerative diseases.