In Silico Analysis of a De Novo OTC Variant as a Cause of Ornithine Transcarbamylase Deficiency

2021 ◽  
Vol Publish Ahead of Print ◽  
Author(s):  
Yesim Ozdemir ◽  
Murat Cag ◽  
Seref Gul ◽  
Zafer Yüksel ◽  
Mahmut C. Ergoren
Marine Drugs ◽  
2020 ◽  
Vol 18 (9) ◽  
pp. 439
Author(s):  
Louis Benoist ◽  
Baptiste Houyvet ◽  
Joël Henry ◽  
Erwan Corre ◽  
Bruno Zanuttini ◽  
...  

Cuttlefish (Sepia officinalis) haemocytes are potential sources of antimicrobial peptides (AMPs). To study the immune response to Vibrio splendidus and identify new AMPs, an original approach was developed based on a differential transcriptomic study and an in-depth in silico analysis using multiple tools. Two de novo transcriptomes were retrieved from cuttlefish haemocytes following challenge by V. splendidus or not. A first analysis of the annotated transcripts revealed the presence of Toll/NF-κB pathway members, including newly identified factors such as So-TLR-h, So-IKK-h and So-Rel/NF-κB-h. Out of the eight Toll/NF-κB pathway members, seven were found up-regulated following V. splendidus challenge. Besides, immune factors involved in the immune response were also identified and up-regulated. However, no AMP was identified based on annotation or conserved pattern searches. We therefore performed an in-depth in silico analysis of unannotated transcripts based on differential expression and sequence characteristics, using several tools available like PepTraq, a homemade software program. Finally, five AMP candidates were synthesized. Among them, NF19, AV19 and GK28 displayed antibacterial activity against Gram-negative bacteria. Each peptide had a different spectrum of activity, notably against Vibrio species. GK28—the most active peptide—was not haemolytic, whereas NF19 and AV19 were haemolytic at concentrations between 50 and 100 µM, 5 to 10 times higher than their minimum inhibitory concentration.


2020 ◽  
Vol 47 (6) ◽  
pp. 398-408
Author(s):  
Sonam Tulsyan ◽  
Showket Hussain ◽  
Balraj Mittal ◽  
Sundeep Singh Saluja ◽  
Pranay Tanwar ◽  
...  

2020 ◽  
Vol 27 (38) ◽  
pp. 6523-6535 ◽  
Author(s):  
Antreas Afantitis ◽  
Andreas Tsoumanis ◽  
Georgia Melagraki

Drug discovery as well as (nano)material design projects demand the in silico analysis of large datasets of compounds with their corresponding properties/activities, as well as the retrieval and virtual screening of more structures in an effort to identify new potent hits. This is a demanding procedure for which various tools must be combined with different input and output formats. To automate the data analysis required we have developed the necessary tools to facilitate a variety of important tasks to construct workflows that will simplify the handling, processing and modeling of cheminformatics data and will provide time and cost efficient solutions, reproducible and easier to maintain. We therefore develop and present a toolbox of >25 processing modules, Enalos+ nodes, that provide very useful operations within KNIME platform for users interested in the nanoinformatics and cheminformatics analysis of chemical and biological data. With a user-friendly interface, Enalos+ Nodes provide a broad range of important functionalities including data mining and retrieval from large available databases and tools for robust and predictive model development and validation. Enalos+ Nodes are available through KNIME as add-ins and offer valuable tools for extracting useful information and analyzing experimental and virtual screening results in a chem- or nano- informatics framework. On top of that, in an effort to: (i) allow big data analysis through Enalos+ KNIME nodes, (ii) accelerate time demanding computations performed within Enalos+ KNIME nodes and (iii) propose new time and cost efficient nodes integrated within Enalos+ toolbox we have investigated and verified the advantage of GPU calculations within the Enalos+ nodes. Demonstration data sets, tutorial and educational videos allow the user to easily apprehend the functions of the nodes that can be applied for in silico analysis of data.


2013 ◽  
Vol 9 (4) ◽  
pp. 608-616 ◽  
Author(s):  
Zaheer Ul-Haq ◽  
Saman Usmani ◽  
Uzma Mahmood ◽  
Mariya al-Rashida ◽  
Ghulam Abbas

2019 ◽  
Vol 13 (2) ◽  
pp. 159-170 ◽  
Author(s):  
Vishal Ahuja ◽  
Aashima Sharma ◽  
Ranju Kumari Rathour ◽  
Vaishali Sharma ◽  
Nidhi Rana ◽  
...  

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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