In silico analysis of all point mutations on the 2B domain of K5/K14 causing epidermolysis bullosa simplex: a genotype–phenotype correlation

2014 ◽  
Vol 10 (10) ◽  
pp. 2567 ◽  
Author(s):  
Santasree Banerjee ◽  
Qian Wu ◽  
Ping Yu ◽  
Ming Qi ◽  
Chen Li
Keyword(s):  
Epidermolysis Bullosa ◽  
In Silico ◽  
Point Mutations ◽  
In Silico Analysis ◽  
Epidermolysis Bullosa Simplex ◽  
Phenotype Correlation ◽  
Genotype Phenotype Correlation ◽  
Silico Analysis

scholarly journals A Genotype-Phenotype Correlation of Haemophilia a in Victorian Patients with a Description of Novel Mutations

Blood ◽  
2018 ◽  
Vol 132 (Supplement 1) ◽  
pp. 2498-2498
Author(s):  
Shreerang Sirdesai ◽  
Kerryn Weekes ◽  
Asif Alam ◽  
Huyen A Tran ◽  
Christopher Barnes ◽  
...  
Keyword(s):  
In Silico ◽  
Family Members ◽  
In Silico Analysis ◽  
Clinical Severity ◽  
Missense Mutations ◽  
Phenotype Correlation ◽  
Novel Mutations ◽  
Mild Phenotype ◽  
Genotype Phenotype Correlation ◽  
Silico Analysis

Abstract Aim: Hemophilia A (HA) is caused by abnormalities in the Factor VIII gene. Certain abnormalities correlate with disease severity. Here, we report the genotype-phenotype correlation for all Victorian HA patients. Methods: Using the Australian Bleeding Disorders Registry, Victorian HA patients were identified. All genetic testing was conducted at Southern Health. The testing algorithm is summarized in Figure 1. Mutations were compared with the list of known Factor 8 mutations on the Champ and EAHAD F8 Variant Databases. A PubMed search was undertaken for any mutations not on either database. If this too was unrevealing, the mutation was designated novel. In-silico analysis was conducted on all novel mutations using three open-access, online prediction tools: a) Mutation Taster; b) Poly-Phen 2; c) Human Splice Site Predictor. Results: 318 patients with matched clinical and genetic records were identified. 275 had known FVIII mutations and 36 novel FVIII mutations were discovered. Eight patients (3%) had no mutations identified. (Table 1) In severe HA the intron-22 inversion was the most common mutation (47/122, 38%). Missense mutations predominated in mild and moderate HA. Inhibitors were present in 44/318 patients, the majority of whom had 26/44 (59%) severe HA. 20/36 novel mutations (55%) were associated with severe HA, 12/36 (33%) with mild HA and 4/36 (11%) with a moderate HA. Novel mutations associated with non-severe phenotypes were mostly missense mutations (15/16); More diversity was seen in the novel mutations causing a severe HA with a fairly even distribution of mutations: missense (7/20), nonsense (4/20) and small deletions and insertions (8/20). One large deletion involving a 6.5kb region of exon 26, as well as one duplication of exons 7 to 9 - was seen in the severe group. In-silico analysis predicted that all novel severe HA mutations were likely to be pathogenic.Inhibitors were seen in 7 patients with novel mutations. Of the 36 novel mutations we described, 9/36 (25%) were seen in other family members - often female carriers. All 9 mutations caused a severe phenotype which is not unexpected given that the screening and testing of family members would be unlikely to take place in patients who have a mild phenotype and rarely require supportive medical care Conclusion: This study adds 36 novel mutations to the currently known FVIII haemophilic mutations. It also confirms that the frequency and correlative clinical severity of known genetic mutations in the Victorian HA cohort is similar to that described internationally. Disclosures No relevant conflicts of interest to declare.

scholarly journals In Silico Study of the Resistance to Organophosphorus Pesticides Associated with Point Mutations in Acetylcholinesterase of Lepidoptera: B. mandarina, B. mori, C. auricilius, C. suppressalis, C. pomonella, H. armígera, P. xylostella, S. frugiperda, and S. litura

2019 ◽  
Vol 20 (10) ◽  
pp. 2404
Author(s):  
Francisco Reyes-Espinosa ◽  
Domingo Méndez-Álvarez ◽  
Miguel A. Pérez-Rodríguez ◽  
Verónica Herrera-Mayorga ◽  
Alfredo Juárez-Saldivar ◽  
...  
Keyword(s):  
Molecular Docking ◽  
In Silico ◽  
Structural Modification ◽  
Organophosphorus Pesticides ◽  
Point Mutations ◽  
In Silico Analysis ◽  
Computational Tools ◽  
Structural Modifications ◽  
In Silico Study ◽  
Silico Analysis

An in silico analysis of the interaction between the complex-ligands of nine acetylcholinesterase (AChE) structures of Lepidopteran organisms and 43 organophosphorus (OPs) pesticides with previous resistance reports was carried out. To predict the potential resistance by structural modifications in Lepidoptera insects, due to proposed point mutations in AChE, a broad analysis was performed using computational tools, such as homology modeling and molecular docking. Two relevant findings were revealed: (1) Docking results give a configuration of the most probable spatial orientation of two interacting molecules (AChE enzyme and OP pesticide) and (2) a predicted ΔGb. The mutations evaluated in the form 1 acetylcholinesterase (AChE-1) and form 2 acetylcholinesterase (AChE-2) structures of enzymes do not affect in any way (there is no regularity of change or significant deviations) the values of the binding energy (ΔGb) recorded in the AChE–OPs complexes. However, the mutations analyzed in AChE are associated with a structural modification that causes an inadequate interaction to complete the phosphorylation of the enzyme.

scholarly journals In silico analysis of the potential effects of the disease-associated point mutations on the kinase activity of TGFBR1 and TGFBR2 receptors

2014 ◽  
Vol 4 (S2) ◽  
Author(s):  
Pierre Rougé ◽  
Annick Barre ◽  
Jean-Philippe Borges ◽  
Stéphanie Caze-Subra ◽  
Camille Gironde
Keyword(s):  
In Silico ◽  
Kinase Activity ◽  
Point Mutations ◽  
In Silico Analysis ◽  
Silico Analysis

A systematic review with in silico analysis on transcriptomic profile of gallbladder carcinoma

2020 ◽  
Vol 47 (6) ◽  
pp. 398-408
Author(s):  
Sonam Tulsyan ◽  
Showket Hussain ◽  
Balraj Mittal ◽  
Sundeep Singh Saluja ◽  
Pranay Tanwar ◽  
...  
Keyword(s):  
Systematic Review ◽  
Gallbladder Carcinoma ◽  
In Silico ◽  
In Silico Analysis ◽  
Transcriptomic Profile ◽  
Silico Analysis

Enalos Suite of Tools: Enhancing Cheminformatics and Nanoinfor - matics through KNIME

2020 ◽  
Vol 27 (38) ◽  
pp. 6523-6535 ◽  
Author(s):  
Antreas Afantitis ◽  
Andreas Tsoumanis ◽  
Georgia Melagraki
Keyword(s):  
Data Analysis ◽  
Virtual Screening ◽  
In Silico ◽  
Model Development ◽  
In Silico Analysis ◽  
Material Design ◽  
Efficient Solutions ◽  
Biological Data ◽  
Cost Efficient ◽  
Silico Analysis

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.

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