Chapter 2. In Silico Tools for Toxicity Prediction

2011 ◽  
pp. 9-25 ◽  
Author(s):  
Mark T. D. Cronin
Keyword(s):  
In Silico ◽  
Toxicity Prediction ◽  
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.

Novel Thiazole-Based Thiazolidinones as Potent Anti-infective Agents: In silico PASS and Toxicity Prediction, Synthesis, Biological Evaluation and Molecular Modelling

2020 ◽  
Vol 23 (2) ◽  
pp. 126-140 ◽  
Author(s):  
Christophe Tratrat
Keyword(s):  
In Silico ◽  
Antimicrobial Agents ◽  
Target Identification ◽  
Biological Evaluation ◽  
Microbial Infection ◽  
Toxicity Prediction ◽  
Discovery Studio ◽  
Bacteria And Fungi ◽  
Multiple Drugs ◽  
Antibacterial And Antifungal

Aims and Objective: The infectious disease treatment remains a challenging concern owing to the increasing number of pathogenic microorganisms associated with resistance to multiple drugs. A promising approach for combating microbial infection is to combine two or more known bioactive heterocyclic pharmacophores in one molecular platform. Herein, the synthesis and biological evaluation of novel thiazole-thiazolidinone hybrids as potential antimicrobial agents were dissimilated. Materials and Methods: The preparation of the substituted 5-benzylidene-2-thiazolyimino-4- thiazolidinones was achieved in three steps from 2-amino-5-methylthiazoline. All the compounds have been screened in PASS antibacterial activity prediction and in a panel of bacteria and fungi strains. Minimum inhibitory concentration and minimum bacterial concentration were both determined by microdilution assays. Molecular modeling was conducted using Accelrys Discovery Studio 4.0 client. ToxPredict (OPEN TOX) and ProTox were used to estimate the toxicity of the title compounds. Results: PASS prediction revealed the potentiality antibacterial property of the designed thiazolethiazolidinone hybrids. All tested compounds were found to kill and to inhibit the growth of a vast variety of bacteria and fungi, and were more potent than the commercial drugs, streptomycin, ampicillin, bifomazole and ketoconazole. Further, in silico study was carried out for prospective molecular target identification and revealed favorable interaction with the target enzymes E. coli MurB and CYP51B of Aspergillus fumigatus. Toxicity prediction revealed that none of the active compounds was found toxic. Conclusion: Substituted 5-benzylidene-2-thiazolyimino-4-thiazolidinones, endowing remarkable antibacterial and antifungal properties, were identified as a novel class of antimicrobial agents and may find a potential therapeutic use to eradicate infectious diseases.

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 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.

scholarly journals Reverse Docking, Molecular Docking, Absorption, Distribution, and Toxicity Prediction of Artemisinin as an Anti-diabetic Candidate

Molekul ◽  
2020 ◽  
Vol 15 (2) ◽  
pp. 88
Author(s):  
Ruswanto Ruswanto ◽  
Richa Mardianingrum ◽  
Siswandono Siswandono ◽  
Dini Kesuma
Keyword(s):  
Molecular Docking ◽  
Aldose Reductase ◽  
Glucose Concentration ◽  
In Silico ◽  
Reductase Activity ◽  
Polyol Pathway ◽  
Toxicity Prediction ◽  
In Silico Studies

Aldose reductase is an enzyme that catalyzes one of the steps in the sorbitol (polyol) pathway that is responsible for fructose formation from glucose. In diabetes, aldose reductase activity increases as the glucose concentration increases. The purpose of this research was to identify and develop the use of artemisinin as an anti-diabetic candidate through in silico studies, including reverse docking, receptor analysis, molecular docking, drug scan, absorption, and distributions and toxicity prediction of artemisinin. Based on the results, we conclude that artemisinin can be used as an anti-diabetic candidate through inhibition of aldose reductase

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