scholarly journals Evaluation of different types of milk proteins-derived epitopes using in-silico tools: a primarily study to propose a new definition for bioactive peptides

2022 ◽  
Author(s):  
Meisam BARATI ◽  
Masoumeh JABBARI ◽  
Matin FATHOLLAHI ◽  
Anwar FATHOLLAHI ◽  
Vahid KHAKI ◽  
...  
Keyword(s):  
In Silico ◽  
Bioactive Peptides ◽  
Milk Proteins ◽  
Different Types ◽  
In Silico Tools

Identification of BAP1-associated MicroRNAs and Implications in Cancer Development

2019 ◽  
pp. 1-4
Author(s):  
Tikam Chand ◽  
Tikam Chand
Keyword(s):  
Gene Regulation ◽  
In Silico ◽  
Mirna Target ◽  
Target Prediction ◽  
Differential Regulation ◽  
Cancer Development ◽  
Mirna Target Prediction ◽  
Cancer Types ◽  
In Silico Tools

Having role in gene regulation and silencing, miRNAs have been implicated in development and progression of a number of diseases, including cancer. Herein, I present potential miRNAs associated with BAP1 gene identified using in-silico tools such as TargetScan and Exiqon miRNA Target Prediction. I identified fifteen highly conserved miRNA (hsa-miR-423-5p, hsa-miR-3184-5p, hsa-miR-4319, hsa-miR125b-5p, hsa-miR-125a-5p, hsa-miR-6893-3p, hsa-miR-200b-3p, hsa-miR-200c-3p, hsa-miR-505-3p.1, hsa-miR-429, hsa-miR-370-3p, hsa-miR-125a-5p, hsa-miR-141-3p, hsa-miR-200a-3p, and hsa-miR-429) associated with BAP1 gene. We also predicted the differential regulation of these twelve miRNAs in different cancer types.

Ligand and Structure-based Modeling of Passive Diffusion through the Blood-Brain Barrier

2018 ◽  
Vol 25 (9) ◽  
pp. 1073-1089 ◽  
Author(s):  
Santiago Vilar ◽  
Eduardo Sobarzo-Sanchez ◽  
Lourdes Santana ◽  
Eugenio Uriarte
Keyword(s):  
Blood Brain Barrier ◽  
In Silico ◽  
Passive Diffusion ◽  
Brain Barrier ◽  
Barrier Permeability ◽  
Blood Brain Barrier Permeability ◽  
Blood Brain ◽  
Brain Barrier Permeability ◽  
Different Types ◽  
The Brain

Background: Blood-brain barrier transport is an important process to be considered in drug candidates. The blood-brain barrier protects the brain from toxicological agents and, therefore, also establishes a restrictive mechanism for the delivery of drugs into the brain. Although there are different and complex mechanisms implicated in drug transport, in this review we focused on the prediction of passive diffusion through the blood-brain barrier. Methods: We elaborated on ligand-based and structure-based models that have been described to predict the blood-brain barrier permeability. Results: Multiple 2D and 3D QSPR/QSAR models and integrative approaches have been published to establish quantitative and qualitative relationships with the blood-brain barrier permeability. We explained different types of descriptors that correlate with passive diffusion along with data analysis methods. Moreover, we discussed the applicability of other types of molecular structure-based simulations, such as molecular dynamics, and their implications in the prediction of passive diffusion. Challenges and limitations of experimental measurements of permeability and in silico predictive methods were also described. Conclusion: Improvements in the prediction of blood-brain barrier permeability from different types of in silico models are crucial to optimize the process of Central Nervous System drug discovery and development.

An Update of In Silico Tools for the Prediction of Pathogenesis in Missense Variants

2011 ◽  
Vol 6 (2) ◽  
pp. 185-198
Author(s):  
Alejandro j. Brea-Fernandez ◽  
Marta Ferro ◽  
Ceres Fernandez-Rozadilla ◽  
Ana Blanco ◽  
Laura Fachal ◽  
...  
Keyword(s):  
In Silico ◽  
Missense Variants ◽  
In Silico Tools

scholarly journals Antimicrobial peptide induced colloidal transformations in bacteria-mimetic vesicles: Combining in silico tools and experimental methods

2021 ◽  
Vol 596 ◽  
pp. 352-363
Author(s):  
Rafael V.M. Freire ◽  
Yeny Pillco-Valencia ◽  
Gabriel C.A. da Hora ◽  
Madeleine Ramstedt ◽  
Linda Sandblad ◽  
...  
Keyword(s):  
Antimicrobial Peptide ◽  
In Silico ◽  
Experimental Methods ◽  
In Silico Tools

scholarly journals In Silico Bioactive Peptide Prediction from The Enzymatic Hydrolysates of Edible Seaweed Rubisco Large Chain

2021 ◽  
Vol 21 (12) ◽  
pp. 615-625
Author(s):  
Ayse Kose
Keyword(s):  
In Silico ◽  
Bioactive Peptides ◽  
Antioxidant Properties ◽  
In Silico Analysis ◽  
Bioactive Peptide ◽  
Bioactive Substances ◽  
Edible Seaweed ◽  
Ic50 Values ◽  
Peptide Prediction ◽  
Ancient Food

Seaweeds are one of the ancient food supplements on Earth. Especially Asian countries use seaweeds as the fundamental ingredient in their cuisine. Seaweeds are photosynthetic organisms living in aquatic ecosystems and in the coastal territories. Seaweeds out of farm areas are frequently observed as coastal wastes. However, seaweeds are outstanding sources for bioactive substances and investigation bioactive properties of seaweed RuBisCO has never been done. RuBisCO is the most abundant protein on Earth but a vast amount of RuBisCO goes through waste. In this study, bioactive peptide prediction of frequently consumed seaweed RuBisCO proteins were analyzed in silico to identify possible bioactive peptides as substitute or support for grain, meat, and dairy based bioactive peptides. A huge portion of peptides were di-, tri- peptides with IC50 values less than 300 µM according to the comparison of BIOPEP database. Including gastric digestion, more than half of the peptides showed DDP-IV and ACE inhibitory activity followed by antioxidant properties. Also, novel antiinflammatory and anti-cancer peptides were found through in silico analysis.

scholarly journals A New Validation Methodology for In Silico Tools Based on X-ray Computed Tomography Images of Tablets and a Performance Analysis of One Tool

Pharmaceutics ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1488
Author(s):  
Sebastian Bollmann ◽  
Peter Kleinebudde
Keyword(s):  
Computed Tomography ◽  
In Silico ◽  
Pharmaceutical Formulations ◽  
Prediction Errors ◽  
Micro Computed Tomography ◽  
Pharmaceutical Dosage Forms ◽  
X Ray ◽  
Computed Tomography Images ◽  
X Ray Computed ◽  
In Silico Tools

In silico tools which predict the dissolution of pharmaceutical dosage forms using virtual matrices can be validated with virtual matrices based on X-ray micro-computed tomography images of real pharmaceutical formulations. Final processed images of 3 different tablet batches were used to check the performance of the in silico tool F-CAD. The goal of this work was to prove the performance of the software by comparing the predicted dissolution profiles to the experimental ones and to check the feasibility and application of the validation concept for in silico tools. Both virtual matrices based on X-ray micro-computed tomography images and designed by the software itself were used. The resulting dissolution curves were compared regarding their similarity to the experimental curve. The kinetics were analysed with the Higuchi and Korsmeyers–Peppas plot. The whole validation concept as such was feasible and worked well. It was possible to identify prediction errors of the software F-CAD and issues with the virtual tablets designed within the software.

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