Geographical, Molecular, and Computational Analysis of Migraine-Causing Genes

2021 ◽  
Vol 20 (04) ◽  
pp. 391-403
Author(s):  
Muhammad Naveed ◽  
Bakhtawar Bukhari ◽  
Nadia Afzal ◽  
Haleema Sadia ◽  
Bisma Meer ◽  
...  
Keyword(s):  
In Silico ◽  
Computational Analysis ◽  
Pcr Amplification ◽  
In Silico Analysis ◽  
Bivariate Analysis ◽  
Headache Disorders ◽  
Gender And Age ◽  
Migraine Pathophysiology ◽  
Silico Analysis

Migraine is a re-occurring type of headache and causes moderate-to-severe pain that is troubling or pulsing. The pain occurs in half of the head, and common symptoms are photophobia, phonophobia, nausea, depression, anxiety, vomiting, etc. This study evaluates the prevalence of migraine and responsible genes through molecular modeling in the region of Bahawalpur, Pakistan. This research was aimed to determine the prevalence of migraine-causing genes in the population of Bahawalpur and also to do molecular and in-silico analysis of migraine-causing gene as no similar research was conducted before. The disease was characterized and diagnosed under the criteria of the Second Edition of the International Classification of Headache Disorders and molecular identification of migraine-causing genes, i.e. GRIA1, GRIA3, and ESR1, by PCR amplification. The total number of samples collected for migraine patients was 230, out of which 30 were positive for PCR amplification of the genes GRIA1, GRIA3, and ESR1. Therapeutic potentials of commercial drugs, namely Cyclobenzaprine, Divalproex, Ergotamine, and Sumatriptan, were analyzed in silico through molecular docking. Ergotamine demonstrated the highest binding affinity of [Formula: see text]8.4 kcal/mol for the target molecule and, hence, the highest potential. The bivariate analysis showed that the prevalence of migraine concerning gender and age was significantly correlated ([Formula: see text], [Formula: see text]). It was observed that almost 31.4% of women suffered from headaches daily, 70% weekly, 28.1% monthly, and 23.5% rarely. Comparatively, only 8.3% of males suffered from daily headaches, 34% weekly, 12.8% monthly, and 14.9% rarely. The study shows promising results and encourages future researchers to conduct such a comprehensive epidemiological study on an even larger population to justify a more precise association of risk factors involved in migraine pathophysiology.

scholarly journals Bioinformatics Resources for In Silico Proteome Analysis

2003 ◽  
Vol 2003 (4) ◽  
pp. 231-236 ◽  
Author(s):  
Manuela Pruess ◽  
Rolf Apweiler
Keyword(s):  
In Silico ◽  
Computational Analysis ◽  
Tertiary Structure ◽  
Protein Sequences ◽  
In Silico Analysis ◽  
Proteome Analysis ◽  
Protein Modelling ◽  
Similarity Searches ◽  
Silico Analysis

In the growing field of proteomics, tools for the in silico analysis of proteins and even of whole proteomes are of crucial importance to make best use of the accumulating amount of data. To utilise this data for healthcare and drug development, first the characteristics of proteomes of entire species—mainly the human—have to be understood, before secondly differentiation between individuals can be surveyed. Specialised databases about nucleic acid sequences, protein sequences, protein tertiary structure, genome analysis, and proteome analysis represent useful resources for analysis, characterisation, and classification of protein sequences. Different from most proteomics tools focusing on similarity searches, structure analysis and prediction, detection of specific regions, alignments, data mining, 2D PAGE analysis, or protein modelling, respectively, comprehensive databases like the proteome analysis database benefit from the information stored in different databases and make use of different protein analysis tools to provide computational analysis of whole proteomes.

scholarly journals Revisiting the Metabolic Capabilities of Bifidobacterium longum susbp. longum and Bifidobacterium longum subsp. infantis from a Glycoside Hydrolase Perspective

2020 ◽  
Vol 8 (5) ◽  
pp. 723
Author(s):  
Guillermo Blanco ◽  
Lorena Ruiz ◽  
Hector Tamés ◽  
Patricia Ruas-Madiedo ◽  
Florentino Fdez-Riverola ◽  
...  
Keyword(s):  
In Silico ◽  
Genetic Background ◽  
Bifidobacterium Longum ◽  
In Silico Analysis ◽  
Glycoside Hydrolases ◽  
Computational Tools ◽  
Beneficial Effects ◽  
Silico Analysis ◽  
Insight Into

Bifidobacteria are among the most abundant microorganisms inhabiting the intestine of humans and many animals. Within the genus Bifidobacterium, several beneficial effects have been attributed to strains belonging to the subspecies Bifidobacterium longum subsp. longum and Bifidobacterium longum subsp. infantis, which are often found in infants and adults. The increasing numbers of sequenced genomes belonging to these two subspecies, and the availability of novel computational tools focused on predicting glycolytic abilities, with the aim of understanding the capabilities of degrading specific carbohydrates, allowed us to depict the potential glycoside hydrolases (GH) of these bacteria, with a focus on those GH profiles that differ in the two subspecies. We performed an in silico examination of 188 sequenced B. longum genomes and depicted the commonly present and strain-specific GHs and GH families among representatives of this species. Additionally, GH profiling, genome-based and 16S rRNA-based clustering analyses showed that the subspecies assignment of some strains does not properly match with their genetic background. Furthermore, the analysis of the potential GH component allowed the distinction of clear GH patterns. Some of the GH activities, and their link with the two subspecies under study, are further discussed. Overall, our in silico analysis poses some questions about the suitability of considering the GH activities of B. longum subsp. longum and B. longum subsp. infantis to gain insight into the characterization and classification of these two subspecies with probiotic interest.

scholarly journals Comprehensive in silico Analysis of IKBKAP gene that could potentially cause Familial dysautonomia

2018 ◽  
Author(s):  
Mujahed I. Mustafa ◽  
Enas A. Osman ◽  
Abdelrahman H. Abdelmoneiom ◽  
Dania M. Hassn ◽  
Hadeel M. Yousif ◽  
...  
Keyword(s):  
In Silico ◽  
Genetic Disorder ◽  
In Silico Analysis ◽  
Familial Dysautonomia ◽  
Structural Effect ◽  
Structure And Function ◽  
Genetic Studies ◽  
And Function ◽  
Silico Analysis

AbstractBackgroundFamilial dysautonomia (FD) is a rare neurodevelopmental genetic disorder within the larger classification of hereditary sensory and autonomic neuropathies. We aimed to identify the pathogenic SNPs in IKBKAP gene by computational analysis software’s, and to determine the structure, function and regulation of their respective proteins.Materials and MethodsWe carried out in silico analysis of structural effect of each SNP using different bioinformatics tools to predict SNPs influence on protein structure and function.Result41 novel mutations out of 973 nsSNPs that are found be deleterious effect on the IKBKAP structure and function.ConclusionThis is the first in silico analysis in IKBKAP gene to prioritize SNPs for further genetic studies.

scholarly journals COMPARATIVE GENOME OF TWO STRAIN MORAXELLA CATARRHALIS USING IN SILICO ANALYSIS

2017 ◽  
Vol 2 (2) ◽  
pp. 1
Author(s):  
Oktira Roka Aji
Keyword(s):  
In Silico ◽  
Moraxella Catarrhalis ◽  
Computational Analysis ◽  
Genomic Analysis ◽  
In Silico Analysis ◽  
Comparative Genomic ◽  
Chronic Obstructive ◽  
Obstructive Pulmonary Disease ◽  
Comparative Genome ◽  
Silico Analysis

<p>Moraxella catarrhalis can cause otitis media and exacerbations of chronic obstructive pulmonary disease in human. Here we describe the comparison between two publicly available genomes of two strain of M.catarrhalis using computational analysis to obtain genomic features between them. Comparative genomic analysis were carried out using available tools in public domain websites. The aim of this study was to investigate the differences and similarities between two strains by comparing their genomic sequences. The results indicated that may be used to offer better understanding M.catarrhalis lifestyle.</p><p> </p><p><strong>Keywords:</strong> <em>Moraxella catarrhalis; In Silico; Comparative genome analysis</em></p>

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
Sign in / Sign up

Export Citation Format

Share Document