Pred-Skin: A Fast and Reliable Web Application to Assess Skin Sensitization Effect of Chemicals

Braga, Rodolpho C.; Alves, Vinícius M.; Muratov, Eugene; Strickland, Judy; Kleinstreuer, Nicole; Trospsha, Alexander; Andrade, Carolina Horta

doi:10.1021/acs.jcim.7b00194

Cited by 71 publications

(74 citation statements)

References 24 publications

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“…The following filter conditions were set: Molecular Weight: 20-300; LogS (Predicted Solubility): −9.0 to 1.0; LogKp (Predicted Skin Permeability): −8.0 to 1.0; Jm (Predicted Transdermal Transport Rate): <10; Reactive Functional Groups: 0-2; Skin irritancy: low or none (Potts and Guy, 1992;Lian et al, 2008;Mitragotri et al, 2011). A total of 3,379,981 small molecules collected from the e-molecules database (https://www.emolecules.com), IBS database (synthetic and natural compounds) (https://www.ibscreen.com/bases), the dataset from Braga et al (2017), and US-FDA approved drugs (Table 1) (https://www.fda.gov/Drugs/default.htm) were passed through the series of filters as mentioned above. In addition, pharmacophore-based (protein cavity) (Loving et al, 2009) screening and molecular docking-based (Standard Precision and Extra Precision) (Friesner et al, 2004) screening were performed to find good scoring compounds.…”

Section: Chemical Datasets and Virtual Screening Methodsmentioning

confidence: 99%

Computational Modeling on Aquaporin-3 as Skin Cancer Target: A Virtual Screening Study

et al. 2020

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Aquaporin-3 (AQP3) is one of the aquaglyceroporins, which is expressed in the basolateral layer of the skin membrane. Studies have reported that human skin squamous cell carcinoma overexpresses AQP3 and inhibition of its function may alleviate skin tumorigenesis. In the present study, we have applied a virtual screening method that encompasses filters for physicochemical properties and molecular docking to select potential hit compounds that bind to the Aquaporin-3 protein. Based on molecular docking results, the top 20 hit compounds were analyzed for stability in the binding pocket using unconstrained molecular dynamics simulations and further evaluated for binding free energy. Furthermore, examined the ligand-unbinding pathway of the inhibitor from its bound form to explore possible routes for inhibitor approach to the ligand-binding site. With a good docking score, stability in the binding pocket, and free energy of binding, these hit compounds can be developed as Aquaporin-3 inhibitors in the near future.

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Section: Chemical Datasets and Virtual Screening Methodsmentioning

confidence: 99%

Computational Modeling on Aquaporin-3 as Skin Cancer Target: A Virtual Screening Study

et al. 2020

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“…The Pred-Skin 24 is an open source web-based and mobile application for evaluation of skin sensitization potential using externally validated QSAR models based on human and animal (local lymph node assay, LLNA) data. The app represents a benchmark for the prediction of skin sensitization, since it is the first tool to provide predictions from models based on human data.…”

Section: Pred-skinmentioning

confidence: 99%

“…17 Scientific applications implemented in a web interface (web apps) are an interesting alternative to standalone software applications, since they are ready to use, fast, and they usually present an intuitive interface. Several web apps to solve chemical and molecular modeling problems have been proposed through the years, such as the Platform for Unified Molecular Analysis (PUMA), 18 SWISS-MODEL, 19,20 Chembench, 21 Pred-hERG, 22,23 Pred-Skin, 24 among others. Conversely, to a lesser extent, chemistry mobile apps have also been developed and they tend to see a rapid uptake in the next few years since smartphones and tablet computers are becoming ubiquitous.…”

Section: Introductionmentioning

confidence: 99%

“…Recently, our group has developed and implemented predictive QSAR models in two distinctive tools available as a web app (Pred-hERG) 23 and web and mobile apps (Pred-Skin), 24 for the fast prediction of hERG cardiac toxicity and skin sensitization, respectively. Here, we aim to describe the details behind the development of these two innovative and impactful web-based and mobile applications for chemical toxicity prediction.…”

Section: Introductionmentioning

confidence: 99%

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Development of Web and Mobile Applications for Chemical Toxicity Prediction

Alves¹,

Braga²,

Muratov³

et al. 2018

J. Braz. Chem. Soc.

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Computational tools are recognized to provide high-quality predictions for the assessment of chemical toxicity. In the recent years, mobile devices have become ubiquitous, allowing for the development of innovative and useful models implemented as chemical software applications. Here, we will briefly discuss this recent uptick in the development of web-based and mobile applications for chemical problems, focusing on best practices, development, usage and interpretation. As an example, we also describe two innovative apps (Pred-hERG and Pred-Skin) for chemical toxicity prediction developed in our laboratory. These applications are based on predictive quantitative structure-activity relationships (QSAR) models developed using the largest publicly available datasets of structurally diverse compounds. The developed tools ensure both highly accurate predictions and easy interpretation of the models, allowing users to discriminate potential toxicants and to purpose structural modifications to design safer chemicals.

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“…The models were constructed using a largest database containing human and LLNA data. It was employed to check skin sensitizing property of Taxifolin and Emetine 17 . The ligands Taxifolin and Emetine have the valid MolDock score (-99.8747, -120.545), Re-rank score (-88.4713, -74.09) and Drug likeness score (1.29, 1.0) respectively and was selected and subjected to toxicity test.…”

Section: Toxicity Testmentioning

confidence: 99%

Molecular Docking Studies of Phytochemicals Against Leishmania Donovani Trypanothione Reductase

Kothandan¹,

Sivaramakrishnan²,

Sharavanan³

et al. 2018

Int. Res. J. Pharm.

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Leishmaniasis is a parasitic disease which occurs as a co-infection with AIDS, and is spread by the bite of female sand flies possessing antibiotic resistance. To identify a potential lead compound by virtual screening, capable of inhibiting the target protein Trypanothione reductase (E.C 1.6.4.8) (TRP) thereby reducing the symptoms caused by leishmaniasis. The potential ligands were screened based on the MolDock score by docking and subjected to ADMET test to identify the suitable lead compound against leishmaniasis. In total 24 ligands were docked against TRP and 19 potential ligands were screened as hits based on the MolDock score.The ADME test identified hits based on Lipinski's rule of five; 6 ligands which had a good MolDock score but failed to obey Lipinski's rule was eliminated. Out of remaining 13 Hits only two ligands Taxifolin (1.29), and Emetine (1.0) which had good drug likeness score were considered. Toxicology studies revealed Emetine as a nontoxic compound. Docking studies showed that emetine shows greater affinity towards TRP due to hydrogen bond formation exactly at aforementioned positions: N (7) and ASP 326 has the minimal distance of 2.7 Å with -0.251 Kcal/mol, 2: O (8) and SER 178 has the minimal distance of 3.34 Å with -1.049 Kcal/mol. This study reports the molecular interaction mechanism between emetine and TRP using molecular docking and identified the emetine as potential lead compound against leishmaniasis. Further study on emetine analogues, lead optimization and validation may lead to novel drug and drug targets for lead compounds against Leishmaniasis.

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Pred-Skin: A Fast and Reliable Web Application to Assess Skin Sensitization Effect of Chemicals

Cited by 71 publications

References 24 publications

Computational Modeling on Aquaporin-3 as Skin Cancer Target: A Virtual Screening Study

Computational Modeling on Aquaporin-3 as Skin Cancer Target: A Virtual Screening Study

Development of Web and Mobile Applications for Chemical Toxicity Prediction

Molecular Docking Studies of Phytochemicals Against Leishmania Donovani Trypanothione Reductase

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