In silico analysis of cross reactivity among phospholipases from Hymenoptera species

Background: Phospholipases are enzymes with the capacity to hydrolyze membrane lipids and have been characterized in several allergenic sources, such as hymenoptera species. However, cross-reactivity among phospholipases allergens are little understood. The objective of this study was to determine potential antigenic regions involved in cross-reactivity among allergens of phospholipases using an in silico approach. Methods: In total, 18 amino acids sequences belonging to phospholipase family derived from species of the order hymenoptera were retrieved from the UniProt database to perform phylogenetic analysis to determine the closest molecular relationship. Multialignment was done to identify conserved regions and matched with antigenic regions predicted by ElliPro server. 3D models were obtained from modeling by homology and were used to locate cross-reactive antigenic regions. Results: Phylogenetic analysis showed that the 18 phospholipases split into four monophyletic clades (named here as A, B, C and D). Phospholipases from A clade shared an amino acid sequences’ identity of 79%. Antigenic patches predicted by Ellipro were located in highly conserved regions, suggesting that they could be involved in cross-reactivity in this group (Ves v 1, Ves a 1 and Ves m 1). Conclusions: At this point, we advanced to the characterization of potential antigenic sites involved in cross-reactivity among phospholipases. Inhibition assays are needed to confirm our finding.

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In-Vitro and In-Silico Characterization of Xylose Reductase from Emericella nidulans

Current Chemical Biology ◽

10.2174/2212796812666180622103906 ◽

2019 ◽

Vol 13 (2) ◽

pp. 159-170 ◽

Cited By ~ 1

Author(s):

Vishal Ahuja ◽

Aashima Sharma ◽

Ranju Kumari Rathour ◽

Vaishali Sharma ◽

Nidhi Rana ◽

...

Keyword(s):

Production Process ◽

In Silico ◽

Xylose Reductase ◽

In Silico Analysis ◽

Emericella Nidulans ◽

Higher Temperature ◽

In Silico Characterization ◽

Silico Analysis

Background: Lignocellulosic residues generated by various anthropogenic activities can be a potential raw material for many commercial products such as biofuels, organic acids and nutraceuticals including xylitol. Xylitol is a low-calorie nutritive sweetener for diabetic patients. Microbial production of xylitol can be helpful in overcoming the drawbacks of traditional chemical production process and lowring cost of production. Objective: Designing efficient production process needs the characterization of required enzyme/s. Hence current work was focused on in-vitro and in-silico characterization of xylose reductase from Emericella nidulans. Methods: Xylose reductase from one of the hyper-producer isolates, Emericella nidulans Xlt-11 was used for in-vitro characterization. For in-silico characterization, XR sequence (Accession No: Q5BGA7) was used. Results: Xylose reductase from various microorganisms has been studied but the quest for better enzymes, their stability at higher temperature and pH still continues. Xylose reductase from Emericella nidulans Xlt-11 was found NADH dependent and utilizes xylose as its sole substrate for xylitol production. In comparison to whole cells, enzyme exhibited higher enzyme activity at lower cofactor concentration and could tolerate higher substrate concentration. Thermal deactivation profile showed that whole cell catalysts were more stable than enzyme at higher temperature. In-silico analysis of XR sequence from Emericella nidulans (Accession No: Q5BGA7) suggested that the structure was dominated by random coiling. Enzyme sequences have conserved active site with net negative charge and PI value in acidic pH range. Conclusion: Current investigation supported the enzyme’s specific application i.e. bioconversion of xylose to xylitol due to its higher selectivity. In-silico analysis may provide significant structural and physiological information for modifications and improved stability.

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In silico analysis of selenoprotein N (Gallus gallus): absence of EF-hand motif and the role of CUGS-helix domain in antioxidant protection

Metallomics ◽

10.1093/mtomcs/mfab004 ◽

2021 ◽

Vol 13 (3) ◽

Author(s):

Shi-Yong Zhu ◽

Li-Li Liu ◽

Yue-Qiang Huang ◽

Xiao-Wei Li ◽

Milton Talukder ◽

...

Keyword(s):

In Silico ◽

Common Ancestor ◽

In Silico Analysis ◽

Antioxidant Protection ◽

Jnk Pathway ◽

Downstream Target ◽

Ef Hand ◽

Silico Analysis

Abstract Selenoprotein N (SEPN1) is critical to the normal muscular physiology. Mutation of SEPN1 can raise congenital muscular disorder in human. It is also central to maturation and structure of skeletal muscle in chicken. However, human SEPN1 contained an EF-hand motif, which was not found in chicken. And the biochemical and molecular characterization of chicken SEPN1 remains unclear. Hence, protein domains, transcription factors, and interactions of Ca2+ in SEPN1 were analyzed in silico to provide the divergence and homology between chicken and human in this work. The results showed that vertebrates’ SEPN1 evolved from a common ancestor. Human and chicken's SEPN1 shared a conserved CUGS-helix domain with function in antioxidant protection. SEPN1 might be a downstream target of JNK pathway, and it could respond to multiple stresses. Human's SEPN1 might not combine with Ca2+ with a single EF-hand motif in calcium homeostasis, and chicken SEPN1 did not have the EF-hand motif in the prediction, indicating the EF-hand motif malfunctioned in chicken SEPN1.

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Definition and Characterization of a “Trypsinosome” from Specific Peptide Characteristics by Nano-HPLC−MS/MS and in Silico Analysis of Complex Protein Mixtures

Journal of Proteome Research ◽

10.1021/pr049909x ◽

2004 ◽

Vol 3 (6) ◽

pp. 1138-1148 ◽

Cited By ~ 24

Author(s):

Thierry Le Bihan ◽

Mark D. Robinson ◽

Ian I. Stewart ◽

Daniel Figeys

Keyword(s):

In Silico ◽

In Silico Analysis ◽

Complex Protein ◽

Silico Analysis ◽

Specific Peptide

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The Bioactivity Prediction of Peptides from Tuna Skin Collagen Using Integrated Method Combining In Vitro and In Silico

Foods ◽

10.3390/foods10112739 ◽

2021 ◽

Vol 10 (11) ◽

pp. 2739

Author(s):

Liza Devita ◽

Hanifah Nuryani Lioe ◽

Mala Nurilmala ◽

Maggy T. Suhartono

Keyword(s):

Antioxidant Activity ◽

In Silico ◽

Antioxidant Activities ◽

In Silico Analysis ◽

Weight Fraction ◽

Amino Acid Sequences ◽

Skin Collagen ◽

Dpph Method ◽

Peptide Fractions

The hydrolysates and peptide fractions of bigeye tuna (Thunnus obesus) skin collagen have been successfully studied. The hydrolysates (HPA, HPN, HPS, HBA, HBN, HBS) were the result of the hydrolysis of collagen using alcalase, neutrase, and savinase. The peptide fractions (PPA, PPN, PPS, PBA, PBN, PBS) were the fractions obtained following ultrafiltration of the hydrolysates. The antioxidant activities of the hydrolysates and peptide fractions were studied using the DPPH method. The effects of collagen types, enzymes, and molecular sizes on the antioxidant activities were analyzed using profile plots analysis. The amino acid sequences of the peptides in the fraction with the highest antioxidant activity were analyzed using LC-MS/MS. Finally, their bioactivity and characteristics were studied using in silico analysis. The hydrolysates and peptide fractions provided antioxidant activity (6.17–135.40 µmol AAE/g protein). The lower molecular weight fraction had higher antioxidant activity. Collagen from pepsin treatment produced higher activity than that of bromelain treatment. The fraction from collagen hydrolysates by savinase treatment had the highest activity compared to neutrase and alcalase treatments. The peptides in the PBN and PPS fractions of <3 kDa had antidiabetic, antihypertensive and antioxidant activities. In conclusion, they have the potential to be used in food and health applications.

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Molecular characterization of enterocin EF35 against human pathogens and its in-silico analysis against human cancer proteins TOP1 and PI3K

Biocatalysis and Agricultural Biotechnology ◽

10.1016/j.bcab.2019.101485 ◽

2020 ◽

Vol 23 ◽

pp. 101485 ◽

Cited By ~ 2

Author(s):

Rajesh P. Shastry ◽

R.R. Arunrenganathan ◽

V. Ravishankar Rai

Keyword(s):

Molecular Characterization ◽

In Silico ◽

Human Cancer ◽

In Silico Analysis ◽

Human Pathogens ◽

Silico Analysis

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Conserved regions of Plasmodium vivax potential vaccine candidate antigens in Sri Lanka: Conscious in silico analysis of prospective conformational epitope regions

Asian Pacific Journal of Tropical Medicine ◽

10.1016/s1995-7645(14)60146-2 ◽

2014 ◽

Vol 7 (10) ◽

pp. 832-840 ◽

Cited By ~ 3

Author(s):

Shanika Amarasinghe ◽

Hashendra Kathriarachchi ◽

Preethi Udagama

Keyword(s):

Sri Lanka ◽

Plasmodium Vivax ◽

In Silico ◽

Vaccine Candidate ◽

In Silico Analysis ◽

Conformational Epitope ◽

Potential Vaccine Candidate ◽

Conserved Regions ◽

Potential Vaccine ◽

Silico Analysis

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In silico, Physico-chemical characterization and analysis of Sandalwood proteins

International Journal of Agricultural Invention ◽

10.46492/ijai/2018.3.2.10 ◽

2018 ◽

Vol 3 (02) ◽

pp. 150-157

Author(s):

Asad Amir ◽

Neelesh Kapoor ◽

Hirdesh Kumar ◽

Mohd. Tariq ◽

Mohd. Asif Siddiqui

Keyword(s):

Secondary Structure ◽

In Silico ◽

Chemical Characterization ◽

In Silico Analysis ◽

Chemical Parameters ◽

Physico Chemical ◽

In Silico Studies ◽

The Family ◽

Silico Analysis

Sandalwood is a commercially and culturally important plant species belonging to the family Santalaceae and the genus Santalum. In Indian sandalwood is renowned for its oil, which is highly rated for its sweet, fragrant, persistent aroma and the fixative property which is highly demanded by the perfume industry. For better production and varieties, requires to understanding the functions of proteins, their analysis and characterization of proteins sequences and their structures, their localizations in cell and their interaction with other functional partner. Due to limited number of in silico studies on sandalwood, in the present study we have performed in silico analysis by characterization of sandalwood proteins. Total 23 proteins were obtained and characterization using UniProtKB, identifying their physico-chemical parameters using ProtParam tool and prediction of their secondary structure elements using GOR of all 23 proteins.

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