scholarly journals In Silico Analysis of the Novel Variant Q375R in the Phenylalanine Hydroxylase Gene

2019 ◽  
Vol In Press (In Press) ◽  
Author(s):  
Seyed Reza Kazeminejad ◽  
Tina Shaffaf ◽  
Franz Romer
Keyword(s):  
In Silico ◽  
Phenylalanine Hydroxylase ◽  
In Silico Analysis ◽  
The Novel ◽  
Hydroxylase Gene ◽  
Phenylalanine Hydroxylase Gene ◽  
Novel Variant ◽  
Silico Analysis

scholarly journals Novel mutation in the gonadotropin-releasing hormone receptor (GNRHR) gene in a patient with normosmic isolated hypogonadotropic hypogonadism

2012 ◽  
Vol 56 (8) ◽  
pp. 540-544 ◽  
Author(s):  
Daiane Beneduzzi ◽  
Ericka B. Trarbach ◽  
Ana Claudia Latronico ◽  
Berenice Bilharinho de Mendonca ◽  
Letícia F. G. Silveira
Keyword(s):  
In Silico ◽  
Novel Mutation ◽  
Hypogonadotropic Hypogonadism ◽  
In Silico Analysis ◽  
Control Group ◽  
Coding Region ◽  
Novel Variant ◽  
Gonadotropin Releasing Hormone Receptor ◽  
Inactivating Mutation ◽  
Silico Analysis

We report a novel GNRHR mutation in a male with normosmic isolated hypogonadotropic hypogonadism (nIHH). The coding region of the GNRHR gene was amplified and sequenced. Three variants p.[Asn10Lys;Gln11Lys]; [Tyr283His] were identified in the GNRHR coding region in a male with sporadic complete nIHH. The three variants were absent in the controls (130 normal adults). Familial segregation showed that the previously described p.Asn10Lys and p.Gln11Lys are in the same allele, in compound heterozygozity with the novel variant p.Tyr283His. The p.[Asn10Lys;Gln11Lys] are known inactivating mutations. The p.Tyr283His affects a well-conserved residue, and in silico analysis suggested it is a deleterious variant. We describe a novel GNRHR mutation in a male with nIHH. Absence of the mutation in the control group, conservation among species, in silico analysis, and familial segregation suggest that p.Tyr283His, which was identified in compound heterozygozity with the p.[Asn10Lys;Gln11Lys] variants, is an inactivating mutation. Arq Bras Endocrinol Metab. 2012;56(8):540-4

scholarly journals In-silico analysis of heat shock protein 47 for identifying the novel therapeutic agents in the management of oral submucous fibrosis

2014 ◽  
Vol 25 (5) ◽  
pp. 580 ◽  
Author(s):  
JayasankarP Pillai ◽  
GirishJ Parmar ◽  
Rakesh Rawal ◽  
GirishR Chauhan ◽  
RajarajeswariJ Pillai ◽  
...  
Keyword(s):  
Heat Shock ◽  
Heat Shock Protein ◽  
In Silico ◽  
Oral Submucous Fibrosis ◽  
In Silico Analysis ◽  
Therapeutic Agents ◽  
The Novel ◽  
Submucous Fibrosis ◽  
Silico Analysis ◽  
Novel Therapeutic

scholarly journals Sea Urchin Pigments as Potential Therapeutic Agents Against the Spike Protein of SARS-CoV-2 Based on in Silico Analysis

2020 ◽  
Author(s):  
Elena Susana Barbieri ◽  
Tamara Rubilar ◽  
Ayelén Gázquez ◽  
Marisa Avaro ◽  
Erina Noé Seiler ◽  
...  
Keyword(s):  
Sea Urchin ◽  
In Silico ◽  
In Silico Analysis ◽  
Protein S ◽  
Host Cells ◽  
Spike Protein ◽  
Therapeutic Drug ◽  
The Novel ◽  
Novel Coronavirus ◽  
Silico Analysis

Several studies have been published regarding the interaction between the spike protein of the novel coronavirus SARS-CoV-2 and ACE2 receptor in the host cells. In the presente work, we evaluated the in silico properties of two sea urchin pigments, Echinochrome A (EchA) and Spinochromes (SpinA) against the Spike protein (S) towards finding a potential therapeutic drug against the disease caused by the novel coronavirus (COVID-19). The best ensemble docking pose of EchaA and SpinA showed a binding affinity of -5.9 and -6.7 kcal mol-1, respectively. The linked aminoacids (T505, G496 and Y449 for EchA and Y449, Q493 and G496 for SpinA) are in positions involved in ACE2 binding in both RBDs frim SARS-CoV and SARS-CoV-2 suggesting that EchA and SpinA may interact with Spike proteins drom both viruses. The results suggest that these pigments could act as inhibitors of S protein, pointing them as antiviral drugs for SARS-CoV-2.<br>

scholarly journals Sea Urchin Pigments as Potential Therapeutic Agents Against the Spike Protein of SARS-CoV-2 Based on in Silico Analysis

2020 ◽  
Author(s):  
Elena Susana Barbieri ◽  
Tamara Rubilar ◽  
Ayelén Gázquez ◽  
Marisa Avaro ◽  
Erina Noé Seiler ◽  
...  
Keyword(s):  
Sea Urchin ◽  
In Silico ◽  
In Silico Analysis ◽  
Protein S ◽  
Host Cells ◽  
Spike Protein ◽  
Therapeutic Drug ◽  
The Novel ◽  
Novel Coronavirus ◽  
Silico Analysis

Several studies have been published regarding the interaction between the spike protein of the novel coronavirus SARS-CoV-2 and ACE2 receptor in the host cells. In the presente work, we evaluated the in silico properties of two sea urchin pigments, Echinochrome A (EchA) and Spinochromes (SpinA) against the Spike protein (S) towards finding a potential therapeutic drug against the disease caused by the novel coronavirus (COVID-19). The best ensemble docking pose of EchaA and SpinA showed a binding affinity of -5.9 and -6.7 kcal mol-1, respectively. The linked aminoacids (T505, G496 and Y449 for EchA and Y449, Q493 and G496 for SpinA) are in positions involved in ACE2 binding in both RBDs frim SARS-CoV and SARS-CoV-2 suggesting that EchA and SpinA may interact with Spike proteins drom both viruses. The results suggest that these pigments could act as inhibitors of S protein, pointing them as antiviral drugs for SARS-CoV-2.<br>

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.

In-Silico Analysis of Chromone Containing Sulfonamide Derivatives as Human Carbonic Anhydrase Inhibitors

2013 ◽  
Vol 9 (4) ◽  
pp. 608-616 ◽  
Author(s):  
Zaheer Ul-Haq ◽  
Saman Usmani ◽  
Uzma Mahmood ◽  
Mariya al-Rashida ◽  
Ghulam Abbas
Keyword(s):  
Carbonic Anhydrase ◽  
In Silico ◽  
In Silico Analysis ◽  
Carbonic Anhydrase Inhibitors ◽  
Human Carbonic Anhydrase ◽  
Silico Analysis
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