Grand Average Hydropathy Research Articles

B-cell epitope prediction of MPB83 protein as a candidate for serodiagnostic antigen of bovine tuberculosis in human: In silico study

Background: Bovine tuberculosis (bTB) can be transmitted to humans by inhalation or consumption of incomplete pasteurized milk and dairy products derived from infected cows. Most cases of Mycobacterium tuberculosis (M. bovis) infection are resistant to tuberculosis (TB) drugs. The risk of death during treatment for bTB has been reported to be 2.55 times higher than for TB. However, the quality of diagnostic methods for bTB remains relatively low.Objective: We aim to evaluate the potential of the B-cell epitope of the MPB83 protein as a candidate bTB serodiagnostic antigen using an in silico approach. Methods: This study was a computer-based descriptive study using secondary data from the National Center for Biotechnology Information (NCBI) protein database. The MPB83 protein sequence was obtained from M. tuberculosis variant bovis AF2122/97 from the United Kingdom. We described the characteristics of the linear epitope of the M. bovis B-cell protein MPB83 by measuring antigenicity, molecular weight, instability index, and Grand Average of Hydropathy (GRAVY) score. The tools used in this study were IBIVU PRALINE, VaxiJen v2.0, IEDB, ExPASy ProtParam, Cluspro, and the PyMOL application.Results: We found an epitope that could be used for bTB serodiagnostic antigen with low conservation, the 106KLNPDVNLVDTLN118 epitope. It has the molecular weight, instability index, and GRAVY score of 1638.76 Da, -28.44, and -0.300, respectively. Epitopes with the best criteria were simulated by docking to human major histocompatibility complex (MHC) class II. Docking results showed that the lowest binding energy was -644.8 kcal/mol. Further analysis using the PyMOL application obtained 14 hydrogen bonds with bond distances ranging from 1.7 Å to 2.2 Å, all of which showed strong hydrogen bonds.Conclusion: The B-cell epitope of MPB83 protein sequence 106KLNPDVNLVDTLN118 has a potential serodiagnostic antigen candidate for human bTB.

Molecular cloning and characterization of FLOWERING LOCUS T (FT)gene from kinnow mandarin (Citrus reticulata)

FLOWERING LOCUS T (FT) is considered as a crucial regulator involved in early flowering induction which functions by switching the vegetative phase into reproductive phase. The role of early flowering has been elucidated by many workers but till date, there has been no report on cloning of FT gene from Kinnow mandarin (Citrus reticulata Blanco). An experiment was conducted during 2022–23 at Punjab Agricultural University, Ludhiana, Punjab for molecular cloning and characterization of FT gene from Kinnow mandarin. During the study, FT gene was cloned into pGEM-T Easy vector and characterized using in silico analysis. Sequence analysis revealed that the FT gene is comprised of 822 nucleotides, including a 5’- untranslated region (UTR) of 137 bp, a coding sequence (CDS) of 534 bp, and a 3’-UTR region of 151 bp. The BLASTn results of CrFT CDS showed high similarity to FT-like genes of other citrus species including C. unshiu, C. sinensis, and C. clementina which were found homologous to Phosphatidylethanolamine binding protein (PEBP). The predicted molecular weight of protein was approximately 20 kDa and isoelectric point (pI) was 6.73 indicating slightly acidic nature of the protein. The instability, aliphatic and GRAVY (Grand Average of Hydropathy) indices of the protein were determined as 40.97, 73.16 and -0.491, respectively. This study would help to elucidate the molecular mechanism behind flowering in Kinnow mandarin and facilitate the molecular breeding studies targeted to obtain early flowering phenotypes.

Short-Chained Linear Scorpion Peptides: A Pool for Novel Antimicrobials.

Scorpion venom peptides are generally classified into two main groups: the disulfide bridged peptides (DBPs), which usually target membrane-associated ion channels, and the non-disulfide bridged peptides (NDBPs), a smaller group with multifunctional properties. In the past decade, these peptides have gained interest because most of them display functions that include antimicrobial, anticancer, haemolytic, and anti-inflammatory activities. Our current study focuses on the short (9-19 amino acids) antimicrobial linear scorpion peptides. Most of these peptides display a net positive charge of 1 or 2, an isoelectric point at pH 9-10, a broad range of hydrophobicity, and a Grand Average of Hydropathy (GRAVY) Value ranging between -0.05 and 1.7. These features allow these peptides to be attracted toward the negatively charged phospholipid head groups of the lipid membranes of target cells, a force driven by electrostatic interactions. This review outlines the antimicrobial potential of short-chained linear scorpion venom peptides. Additionally, short linear scorpion peptides are in general more attractive for large-scale synthesis from a manufacturing point of view. The structural and functional diversity of these peptides represents a good starting point for the development of new peptide-based therapeutics.

From PDB files to protein features: a comparative analysis of PDB bind and STCRDAB datasets.

Understanding protein structures is crucial for various bioinformatics research, including drug discovery, disease diagnosis, and evolutionary studies. Protein structure classification is a critical aspect of structural biology, where supervised machine learning algorithms classify structures based on data from databases such as Protein Data Bank (PDB). However, the challenge lies in designing numerical embeddings for protein structures without losing essential information. Although some effort has been made in the literature, researchers have not effectively and rigorously combined the structural and sequence-based features for efficient protein classification to the best of our knowledge. To this end, we propose numerical embeddings that extract relevant features for protein sequences fetched from PDB structures from popular datasets such as PDB Bind and STCRDAB. The features are physicochemical properties such as aromaticity, instability index, flexibility, Grand Average of Hydropathy (GRAVY), isoelectric point, charge at pH, secondary structure fracture, molar extinction coefficient, and molecular weight. We also incorporate scaling features for the sliding windows (e.g., k-mers), which include Kyte and Doolittle (KD) hydropathy scale, Eisenberg hydrophobicity scale, Hydrophilicity scale, Flexibility of the amino acids, and Hydropathy scale. Multiple-feature selection aims to improve the accuracy of protein classification models. The results showed that the selected features significantly improved the predictive performance of existing embeddings.

Advanced vaccinomic, immunoinformatic, and molecular modeling strategies for designing Multi- epitope vaccines against the Enterobacter cloacae complex.

The increasing and ongoing issue of antibiotic resistance in bacteria is of huge concern globally, mainly to healthcare facilities. It is now crucial to develop a vaccine for therapeutic and preventive purposes against the bacterial species causing hospital-based infections. Among the many antibiotic- resistant bacterial pathogens, the Enterobacter cloacae complex (ECC) including six species, E. Colcae, E. absuriae, E. kobie, E. hormaechei, E. ludwigii, and E. nimipressuralis, are dangerous to public health and may worsen the situation. Vaccination plays a vital role in the prevention of infections and infectious diseases. This research highlighted the construction and design of a multi-epitope vaccine for the E. cloacae complex by retrieving their complete sequenced proteome. The retrieved proteome was assessed to opt for potential vaccine candidates using immunoinformatic tools. Both B and T-cell epitopes were predicted in order to create both humoral and cellular immunity and further scrutinized for antigenicity, allergenicity, water solubility, and toxicity analysis. The final potential epitopes were subjected to population coverage analysis. Major histocompatibility complex (MHC) class combined, and MHC Class I and II world population coverage was obtained as 99.74%, and 98.55% respectively while a combined 81.81% was covered. A multi-epitope peptide-based vaccine construct consisting of the adjuvant, epitopes, and linkers was subjected to the ProtParam tool to calculate its physiochemical properties. The total amino acids were 236, the molecular weight was 27.64kd, and the vaccine construct was stable with an instability index of 27.01. The Grand Average of Hydropathy (GRAVY) (hydrophilicity) value obtained was -0.659, being more negative and depicting the hydrophilic character. It was non-allergen antigenic with an antigenicity of 0.8913. The vaccine construct was further validated for binding efficacy with immune cell receptors MHC-I, MHC-II, and Toll-like receptor (TLR)-4. The molecular docking results depict that the designed vaccine has good binding potency with immune receptors crucial for antigen presentation and processing. Among the Vaccine-MHC-I, Vaccine-MHC-II, and Vaccine-TLR-4 complexes, the best-docked poses were identified based on their lowest binding energy scores of -886.8, -995.6, and -883.6, respectively. Overall, we observed that the designed vaccine construct can evoke a proper immune response and the construct could help experimental researchers in the formulation of a vaccine against the targeted pathogens.

An In Silico Comparative Study of Eleven Wasp Venom Allergens: An Arena for Therapeutic Approach

Peptide toxins in animals as part of the chemical arsenal for predation and/or protection, and they can also safeguard the host from pathogenic infections. Insects including the hymenopterans generate a battery of toxic bactericidal or bacteriostatic molecules which are small multifunctional, linear peptides that cause pain, have antimicrobial effects, and inflammatory processes . The toxins under the experiment are active against gram-positive, gram-negative bacteria and fungi. The present in silico study aims to predict the physicochemical attributes like molecular weight, theoretical pI, amino acid composition, extinction co-efficient, estimated half-life, instability index, aliphatic index and grand average of hydropathy (gravy) of wasps’ (class: Insecta; order: Hymenoptera) 11 wasp venom allergens through Expasy Protparam & Pepstat software tools. The secondary structures of the toxins were predicted using psi-Blast-based secondary structure prediction GOR4 tools revealing the % α helix, extended β strand, random coil and ambiguous state reflecting a comparative picture of physicochemical parameters of these defensins. 3D Homology modelling of these toxins was accomplished through Swiss-model webserver tool and validated through various in silico tools like ANOLEA, ProSA-web, QMean4 determining Z score, PROCHEK establishing the 3D models of these toxins. Use of Inter Pro, CDD, PROSITE, P fam, Tox DL, PrDOS software predicted the protein family, protein toxicity, protein disorder respectively. Scratch Protein Predictor software tools predicted cysteine – cysteine bonds. Docking of the eleven (11) wasp venom allergens individually with bacterial cell wall component N-acetylglucosamine was done by CB DOCK webserver resulting negative affinity scores reflecting towards the strong binding between the mentioned 11 toxins and N-acetylglucosamine indicating that the mentioned wasps’ toxin molecules might be used as potential antibacterial therapeutic molecules binding to N-acetylglucosamine leading to an avenue to the probable bacterial drug discovery.

Application Of Wasps’ Defensins As Anti-Fungal Therapeutic Molecules: An In Silico Comparative Study

Animal peptide toxins as part of chemical arsenal for predation and/or protection that can safeguard host from pathogenic infections. Hymenopterans generate toxic bactericidal or bacteriostatic molecules, called defensins are small multifunctional, linear, polycationic peptides causing pain, have antimicrobial effects. Defensins are active against gram-positive, gram-negative bacteria and fungi. The present in silico study aims to predict the physicochemical attributes like molecular weight, theoretical pI, amino acid composition, extinction co-efficient, estimated half-life, instability index, aliphatic index and grand average of hydropathy (gravy) of 09 different wasps’ defensins using Expasy Protparam tool. The secondary structures of the toxins were predicted using psi-Blast-based PSIPRED, SOPMA tools revealing % α helix, extended β strand, random coil and ambiguous state reflecting a comparative physico-chemical parameters of these defensins. 3D Homology modelling of these toxins was accomplished through Swiss-model webserver and validated through ProSA-web, QMean4 determining Z score,PROCHEK establishing the 3D models of these defensins. Use of InterPro, CDD, ToxDL, PrDOS software predicted protein family, conserved domain, protein toxicity, protein disorder respectively. CYSCON and CYSPRED tools predicted cysteine-cysteine bonds. Docking of the nine (09) wasps’ defensins individually with fungal cellwall component 1,4 Beta-D-Glucan was done by DockThor webserver resulting negative affinity scores refleting strong binding between the defensins and 1,4 beta-D-Glucan indicating that the mentioned wasps’ defensin molecules might be used as potential antifungal therapeutic molecules binding to 1, 4 Beta-D-Glucan indicating an avenue to antifungal drug discovery.

Identification and characterization of genes encoding phosphoinositide-specific phospholipase C revealed role in drought stress condition in cassava (Manihot esculenta)

Phosphoinositide-specific phospholipase C (PI-PLC) has been known as one of the key enzymes that involved in the phospholipid hydrolysis. However, the PI-PLC family in cassava has not been fully recorded. In this study, we reported a comprehensive analysis of the PI-PLC family in cassava assembly based on various bioinformatics tools. Particularly, a total of seven members of the PI-PLC family has been identified and annotated in the cassava genome. By using the full-length protein sequence of each member of the PI-PLC family in cassava, we analyzed the properties of these proteins, including the length, size, iso-electric point, instability index, aliphatic index and grand average of hydropathy. Of our interest, we investigated the expression patterns of genes encoding the PI-PLC family in various major organs/tissues in different conditions. Taken together, our study could provide a solid foundation for the PI-PLC family in cassava for further functional characterization towards the improvements of drought stress tolerance in cassava plants.

An integrated multi-pronged reverse vaccinology and biophysical approaches for identification of potential vaccine candidates against Nipah virus

Nipah virus, a paramyxovirus linked to Hendra virus that first appeared in Malaysia and is the etiological agent of viral lethal encephalitis, has emerged as a strong threat to the health community in recent decades. Viral infections are seriously affecting global health. Since there are now no efficient therapeutic options, it will take considerable effort to develop appropriate therapeutic management for the Nipah virus. The main purpose of this study was to design a messenger RNA-based multi-epitope vaccine construct against Nipah virus. This purpose was achieved through multiple immunogenic epitopes prediction using Nipah virus antigenic protein using the immune epitope database and analysis resource (IEDB) followed by the vaccine construction and processing. As in multi-epitopes vaccine construction we selected immunogenic potential fragments of viral proteins, therefore in host immune stimulation we observed proper immune responses toward a multi-epitopes vaccine. In this study, the Nipah virus V protein was used to identify immunodominant epitopes utilizing several reverse vaccinology, immunoinformatics and biophysical methods. The potential antigenic predicted epitopes were further analyzed for immunoinformatics analysis and only selected probable antigenic and non-toxic epitopes were used in designing a multi-epitope mRNA based in silico vaccine against the target pathogen. In vaccine designing a total number of 03B cell epitopes, 09 Cytotoxic T lymphocytes (CTLs) and 01 Helper T lymphocytes (HTL) were prioritized as a good vaccine candidate. In the vaccine construction phase, the selected epitopes were linked together using EAAAK, GPGPG, KK, and AAY linkers, and B-defensin (adjuvant), and MITD sequences were also added to the vaccine construct to increase the potency. After vaccine construction, the physiochemical properties of the vaccine construct were evaluated which predicted that the vaccine construct comprises 320 amino acids with 34.29 kDa (kDa) molecular weight. The instability index was 36.55 proving its stability with the aliphatic index of 82.88. Furthermore, 9.0 theoretical pI and −0.317, GRAVY (Grand Average of Hydropathy) values were predicted in physicochemical properties analysis. A solubility check was applied against the vaccine construct depicting that the vaccine construct is soluble with its calculated value of 0.6. Additionally, after prediction the 3D structure was modeled and refined for docking analysis, the refined 3D structure of the vaccine candidate was further checked for binding affinity with immune cell receptors through docking analysis, in the docking analysis we observed that the vaccine construct has a good binding affinity with immune cells receptor and can induce a proper immune response in host cells. As we predicted effective binding of the designed vaccine construct, hence it can further facilitate the development of vaccine formulation against the Nipah virus. Additionally, molecular dynamic simulation was done using the AMBER v20 package for analysis of the dynamic behaviour of the docked complexes and we observed proper binding stability of the vaccine with target receptor. In C-immune simulation, different humoral and cellular antibody titer was observed in response to the vaccine. Overall using bioinformatics, immunoinformatics, and biophysical approaches we observed that this mRNA base epitopes vaccine construct could facilitate the proof of concept for the formation of the experimental base vaccine against the Nipah virus, as the in silico predictions indicated that the vaccine is highly promising in terms of developing protective immunity. However experimental validation is required to disclose the real immune-protective efficacy of the vaccine.

Online Alkaline-pH Reverse Phase Nanoelectrospray-Tandem Mass Spectrometry Complements Conventional Low-pH Method for Global Proteomic Analysis.

The global proteome analysis was limited by the identification of peptides with low abundance or specific physiochemical properties. Here, a one-dimensional online alkaline-pH reverse phase nanoelectrospray-tandem mass spectrometry (alkaline-pH-MS/MS) method was developed and optimized for global proteomic analysis. In this method, peptides were separated on a nanoflow C18 column with an alkaline-pH mobile phase (pH = 8.0) and directly injected into the mass spectrometer. The unique peptides overlapped between alkaline-pH-MS/MS and conventional online low-pH reverse phase nanoelectrospray-tandem mass spectrometry (low-pH-MS/MS) were as low as 45%, strongly indicating that these two methods were complementary to each other. In addition, alkaline-pH-MS/MS showed identification capacity for a higher proportion of peptides with negative grand average of hydropathy (GRAVY) or high isoelectric point (pI). Compared to low-pH-MS/MS, alkaline-pH-MS/MS enabled enrichment preference toward histidine-, lysine-, methionine-, and proline-containing peptides. The complementarity of alkaline-pH-MS/MS and low-pH-MS/MS was further demonstrated for the analysis of tryptic digests from 15 intrahepatic cholangiocarcinoma (iCCA) cell lines. The alternating 60 min alkaline-pH-MS/MS plus 60 min low-pH-MS/MS method outperformed the conventional 120 min low-pH-MS/MS method in both the identification of amino acid variants and protein groups. Therefore, we established the alkaline-pH-MS/MS method as a simple, competitive, alternative method to low-pH-MS/MS for global proteomic analysis.

Screening and characterization of highly responsive genes related to the blast disease caused by Pyricularia oryzae in rice (Oryza sativa)

Blast, caused by Pyricularia oryzae, has been regarded as one of the most critical diseases in rice plants (Oryza sativa). Seeking a list of candidate genes is a major step for resistance breeding programs. In this study, at least 24 RNA-Seq datasets related to blast disease infection in rice plants have been obtained from databases. Among them, four microarray datasets obtained from blast-infected leaf samples in Indica rice varieties, including GSE122258, GSE126961, GSE78266 and GSE39635 were selected for further in silico analysis. Particularly, a total of 216 differentially expressed genes in blast-treated leaves were obtained by exploring four microarray atlas. Among them, at least 32 blast-responsive genes that exhibited similar expression patterns were selected for further bioinformatics analysis. Particularly, these differentially expressed genes encode important transcription factors and enzyme families. By using Expasy and Yloc tools, the physic-chemical properties of these proteins, including lengths, molecular weights, iso-electric points and grand average of hydropathy were greatly variable and the majority of these blast-responsive gene-encoding proteins was localized in the cytoplasm and nucleus. To sum up, this current study has provided fundamental knowledge about potential candidate differentially expressed genes for further functional characterization of genes aiming to control blast resistance in rice.

ApInAPDB: a database of apoptosis-inducing anticancer peptides

ApInAPDB (Apoptosis-Inducing Anticancer Peptides Database) consists of 818 apoptosis-inducing anticancer peptides which are manually collected from research articles. The database provides scholars with peptide related information such as function, binding target and affinity, IC50 and etc. In addition, GRAVY (grand average of hydropathy), net charge at pH 7, hydrophobicity and other physicochemical properties are calculated and presented. Another category of information are structural information includes 3D modeling, secondary structure prediction and descriptors for QSAR (quantitative structure-activity relationship) modeling. In order to facilitate the browsing process, three types of user-friendly searching tools are provided: top categories browser, simple search and advanced search. Overall ApInAPDB as the first database presenting apoptosis-inducing anticancer peptides can be useful in the field of peptide design and especially cancer therapy. Researchers can freely access the database at http://bioinf.modares.ac.ir/software/ApInAPDB/ .

A Novel Insight into Screening for Antioxidant Peptides from Hazelnut Protein: Based on the Properties of Amino Acid Residues.

This study used the properties of amino acid residues to screen antioxidant peptides from hazelnut protein. It was confirmed that the type and position of amino acid residues, grand average of hydropathy, and molecular weight of a peptide could be comprehensively applied to obtain desirable antioxidants after analyzing the information of synthesized dipeptides and BIOPEP database. As a result, six peptides, FSEY, QIESW, SEGFEW, IDLGTTY, GEGFFEM, and NLNQCQRYM were identified from hazelnut protein hydrolysates with higher antioxidant capacity than reduced Glutathione (GSH) against linoleic acid oxidation. The peptides having Tyr residue at C-terminal were found to prohibit the oxidation of linoleic acid better than others. Among them, peptide FSEY inhibited the rancidity of hazelnut oil very well in an oil-in-water emulsion. Additionally, quantum chemical parameters proved Tyr-residue to act as the active site of FSEY are responsible for its antioxidation. This is the first presentation of a novel approach to excavating desired antioxidant peptides against lipid oxidation from hazelnut protein via the properties of amino acid residues.

In silico Structural and Functional Annotation of Tomato Chocolate spot Virus

Aims: The study aims to predict in-silico the structural and functional annotation of Tomato Chocolate Spot Virus (TCSV) retrieved from Uniprotkb with the accession number C7EXM3.
 Study design: To use the In-silico approach for the structural and functional annotation of the Tomato Chocolate Spot Virus.
 Place and Duration of Study: The research was conducted at the Bioinformatics Unit, Chevron Biotechnology Centre, Modibbo Adama University Yola, Nigeria. Between August 2021 to September 2021.
 Methodology: The sequence of the Tomato Chocolate Spot Virus was retrieved from Uniprotkb with accession number C7EXM3, Physicochemical characteristics were computed using the ProtParam tool. The sever SOPMA was used for secondary structure analysis (Helix, Sheets and Coils). The tool CELLO v2.5 was used to predict the subcellular localization of the protein. Four different Homology Modelling tools (trRosetta, Lomet, RaptorX and IntFOLD5) were used to predict the 3D structure of the protein, the quality of the predicted proteins was assessed used PROCHECK. Three tools (InterProScan, NCBI conserved domains and Phobius) were used to get the possible function(s) of the protein.
 Results: ProtParam tool computed various Physical and Chemical properties such as Molecular weight (MW) 20396.96 Daltons, isoelectric point (pI) of 6.92. Instability Index 41.94, and Grand Average Hydropathy (GRAVY) -0.503. SOPMA was used for calculating the secondary structure parameters of the protein as Helices (Hh) 43.48%, Extended strands (Ee) 18.48%, Random coils (Cc) 38.04%. CELLO v2.5 was used for subcellular localization of the protein, it predicted that the protein can be both Nuclear and Cytoplasmic with the reliability of 1.653 and 1.504 respectively. Different Homology modelling tools were used to obtain the best 3D structure of the protein. Furthermore, PROCHECK was used to assess the quality of the models obtained. Model from trRosetta was found to be the best because of the quality of the Ramachandran Plot obtained from PROCHECK which has more than 90% of amino acid in the most favourable regions. NCBI-CDD and interproScan predicted that protein is a DNA double-strand break repair Rad50 ATPase, which is involved in the early steps of DNA double-strand break (DSB) repair. Furthermore, the Phobius server predicted the protein to be non-cytoplasmic in its domain, which means they help target proteins to their final destinations.
 Conclusion: The study has helped in obtaining the 3D structure of the protein Tomato Chocolate Spot Virus from different Modelling tools, as well as the possible function of the protein.

GENOME-WIDE IDENTIFICATION AND COMPUTATIONAL CHARACTERIZATION OF THE NUCLEAR FACTOR-YC SUB-UNITS IN GRAIN AMARANTH (Amaranthus hypochondriacus)

Nuclear factor-Y (NF-Y) has been known as one of the plant-specific transcription factors that play key roles in numerous biological processes during the growth and development of plant species. In this study, a comprehensive analysis of NF-YC sub-units in grain amaranth (Amaranthus hypochondriacus) was carried out based on the bioinformatics approaches. Firstly, a total of five members of the NF-YC sub-units was reported in the grain amaranth. Its structural analyses revealed that the NF-YC sub-units were variable in physic-chemical properties, like protein sizes, molecular masses, isoelectric point, instability index, and grand average of hydropathy. Of our interest, the expression profiles of genes encoding NF-YC sub-units in various tissues\organs during the growth and development of grain amaranth. We found that three genes, including AhNF-YC01, AhNF-YC04, and AhNF-YC05 were highly expressed in leaf, root, floral, immature seed, and stem tissues. Interestingly, AhNF-YC05 was exclusively expressed in leaf and stem tissues. Taken together, our study could provide a solid understanding for further functional characterization of genes encoding NF-YC sub-units in grain amaranth.

In Silico prediction and Comparative Modeling of proteins in Creeping Fig (Ficus pumila) plant

In the present study, the Ficus pumila have taken to analyze the proteins by their preliminary characters from the database and predicted vital role of different sequences. The F. pumila (Creeping fig) is a prostrate/climbing shrub, experiments proved various active phytochemicals and antioxidant, antimicrobial, antimutagenic, analgesic, anti-inflammatory, antiproliferative, hypoglycemic, hypolipidemic, antihyperprolactinemic, anticholinesterase, nephroprotective properties. In addition to all metabolites, it also constitutes specific proteins that were evaluated through insilico homology modeling. Though it is considered as a poisonous weed, the protein present in this plant is evaluated by physicochemical, phylogeny and amino acid proportions by protparam, Swiss model, SOPMA, Clustal omega tools to describe its structural features and to understand molecular function. The computed theoretical isoelectric point (pI) found to be more than 7 indicates basic nature of proteins. The aliphatic index ranges 67-113 indicates thermal stability of proteins. The predicted Grand average hydropathy(GRAVY) shows possibilities of enhanced interaction of these proteins with water by lowest value. Functional analysis of these proteins was performed by SOSUI server which predicted transmembrane helix and solubility. Secondary structure analysis was carried out by SOPMA revealed that Alpha helix and random coil dominated followed by extended strand, and beta turns among secondary structure elements. The modelling of three-dimensional structure of proteins was performed by Swiss model. The model was validated using protein structure checking tool- VADAR. Particularly, NAD(P)H –quinoneoxidoreductase and Glyceraldehyde-3-phosphate dehydrogenase structures were analysed by phylogenetic analysis to trace relationship and reported. The results suggesting its possible role in cellular and metabolic functions.

EmPAI-assisted strategy enhances screening and assessment of Mycobacteriumtuberculosis infection serological markers.

SummaryDiscovering new serological markers of Mycobacterium tuberculosis (MTB) infection and establishing a rapid and efficient detection technology is of great significance for the prevention and control of tuberculosis. In this study, we established an exponentially modified protein abundance index (emPAI) value‐assisted strategy to investigate and improve the screening efficiency of serological biomarkers of tuberculosis. First, we used LC‐MS/MS to analyse MTB culture filtrate proteins (MTB‐CFPs), and 632 MTB proteins were identified. Then, the characteristic values of MTB‐CFPs – including emPAI value, molecular weight (Mw), isoelectric point (pI), grand average of hydropathy (GRAVY), transmembrane domain (TMD) and functional groups were calculated. Next, we successfully prepared 10 MTB proteins with emPAI value > 1.0 and recombinantly expressed these proteins in Escherichia coli. At the same time, 3 MTB proteins with emPAI between 0.1 and 0.5 were randomly selected as the control groups, and the immunogenicity of the recombinant MTB proteins was detected using ELISA. The sensitivity and receiver operating characteristic (ROC) curves were calculated for each recombinant MTB protein. The results showed that the areas under the curve (AUC) value of Rv2031c, Rv0577, Rv0831c, Rv0934 and Rv3248c were all higher than those of Rv3875 (AUC, 0.6643). Further analysis of the relationship between emPAI value and antibody sensitivity, AUC value and antibody affinity in mice immunized with recombinant MTB protein showed that emPAI values were positively correlated with them, and R‐squared value ranged from 0.64 to 0.79. The only exception was ESAT‐6 (encoded by the Rv3875 gene), which AUC value was relatively low owing to its strong immunosuppressive properties. This study provides a rationale for the serological marker screening of emPAI‐assisted tuberculosis clinical test. The results also provide new technical support for the screening of candidate serological markers of infectious diseases in the future.

Proteomic insights into the biology of Clinostomum piscidium from a fish, Colisa fasciatus in India using computational tools

Clinostomum is a fish-borne pathogen,digenetic trematode with worldwide distribution. Despite its zoonootic significance, the molecules involved in the host-parasite interaction remains unknown. The present study deals with the proteome profile of the rDNA of Clinostomum piscidium using in silico workflow.The physicochemical properties, mass spectrometry ,atomic composition,estimated half-life in different hosts ,Grand average of hydropathy (GRAVY),extinction coefficient and instability index of the rDNA was studied.We identified hypothetical proteins(polar in nature) that showed similarities with proteins of Trichellina pseudospiralis and Melampsora laricipopulina.The functionality of these proteins revealed their role in intracellular signalling as a substrate for O - linked N - acetylglucosaminetransferases and death transcription factor(DIDO-1). This is the first report of our findings that aims to provide a better understanding of the mechanism by which this digenetic trematode adapts to extreme environments. It is expected that this study will lead to new insights into drug designing strategies and disease control.

In silico analysis and homology modeling of strictosidine synthase involved in alkaloid biosynthesis in catharanthus roseus

BackgroundIn this study, strictosidine synthase (STR) from Catharanthus roseus that plays an important role in alkaloid biosynthesis was selected. The purpose of this work was to perform in silico analysis and to predict the three-dimensional structure of this protein that is not available. ResultsPhysicochemical characterization was performed by Expasy’s Protparam server. The computed theoretical isoelectric point (pI) found to be less than 7 indicates the acidic nature of this protein. The aliphatic index 73.04 indicates the thermal stability of the protein. Grand average hydropathy (GRAVY) was predicted to be − 285; this lower value of GRAVY shows the possibility of better interaction of this protein with water. Functional analysis of these proteins was performed by SOSUI server which predicted the transmembrane helix. Secondary structure analysis was carried out by SOPMA that revealed that Alpha helix dominated among secondary structure elements followed by random coil, extended strand, and beta turns. The modeling of the three-dimensional structure of the STR was performed by Swiss model. The model was validated using protein structure checking tools PROCHECK and PROVE. ConclusionsThis study reveals in silico analysis by Expasy Protparam server, SOPMA, and SOSUI server. Homology modeling of STR was performed by Swiss model.

In-Silico Analysis and Protective Efficacy of the PcrV Recombinant Vaccine against Pseudomonas Aeruginosa in the Burned and PA-Infected BALB/c Mouse Model.

Pseudomonas aeruginosa is considered as the most severe cause of infections in burn patients and pneumonia infections. To study the protective effects of recombinant protein vaccine harboring the PcrV of P. aeruginosa in the mouse model of burn and respiratory infections. Recombinant protein vaccine harboring the PcrV was expressed in the E. coli BL-21 strain. Mice were immunized with the purified recombinant protein, and the antibody titer was measured in the sera obtained from the immunized mice. Immunized and control mice were challenged by active and passive immunization. The microbial counts in the lung, skin, liver, spleen, and kidney were compared with the control mice. Bioinformatics analysis indicated that the PcrV protein was conserved in 1552 clinical and environmental isolates. Also, the isoelectric point (pI), molecular weight, and Grand Average of Hydropathy (GRAVY) score were analyzed. Mice were injected with recombinant protein, and serum from immunized mice reacted strongly with recombinant antigen at a dilution of 1:64000. The survival rate of mice infected with 5xLD50 of the P. aeruginosa increased significantly up to 75% in the standard strains (PAO1 and PAK), and the number of bacteria, especially in the internal organs (kidney, spleen, and liver) significantly reduced compared to the mice immunized with placebo. Our results demonstrated that the PcrV protein could be an effective candidate vaccine for the generation of antibody response against P. aeruginosa infection.