2017
DOI: 10.1016/j.taap.2017.10.013
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Natural modulators of nonalcoholic fatty liver disease: Mode of action analysis and in silico ADME-Tox prediction

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Cited by 13 publications
(4 citation statements)
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“…In silico assessment of physicochemical properties and ADME predictions of the best active compound was carried out using ACD/Percepta v14.1.0 and SwissADME. , For the most promising novel Rolipram–Tranilast hybrids, a series of ADMET properties (absorption, distribution, metabolism, excretion, and toxicological properties) were calculated. In detail, we took into account the logarithmic ratio of the octanol–water partitioning coefficient (clog P), molecular weight (MW), rotatable bonds, H-bond acceptors, H-bond donors (Lipinski’s Rule of Five), Caco2 (derived from human colon adenocarcinoma cells) permeability, and CNS penetration scores. , As shown in Table , compound 5 was predicted to reach the CNS, being characterized by adequate lipophilicity values and followed the Lipinski’s rules.…”
Section: Results and Discussionmentioning
confidence: 99%
“…In silico assessment of physicochemical properties and ADME predictions of the best active compound was carried out using ACD/Percepta v14.1.0 and SwissADME. , For the most promising novel Rolipram–Tranilast hybrids, a series of ADMET properties (absorption, distribution, metabolism, excretion, and toxicological properties) were calculated. In detail, we took into account the logarithmic ratio of the octanol–water partitioning coefficient (clog P), molecular weight (MW), rotatable bonds, H-bond acceptors, H-bond donors (Lipinski’s Rule of Five), Caco2 (derived from human colon adenocarcinoma cells) permeability, and CNS penetration scores. , As shown in Table , compound 5 was predicted to reach the CNS, being characterized by adequate lipophilicity values and followed the Lipinski’s rules.…”
Section: Results and Discussionmentioning
confidence: 99%
“…A knowledge-based approach to rank metabolites based on known metabolic reactions . To predict the first metabolic step of contilisant, we analyze the Phase I biotransformation pathways, combining two different methods . A qualitative [absolute reasoning (AR)] and quantitative [site of metabolism (SOM) scoring] assessment was applied, selecting the matching metabolites.…”
Section: Methodsmentioning
confidence: 99%
“…19 To predict the first metabolic step of contilisant, we analyze the Phase I biotransformation pathways, combining two different methods. 27 A qualitative [absolute reasoning (AR)] and quantitative [site of metabolism (SOM) scoring] assessment was applied, selecting the matching metabolites. The AR evaluated the likelihood level for biotransformation to occur, and the minimal likelihood level was settled in "plausible," which means that the weight of evidence supports the proposition.…”
Section: Methodsmentioning
confidence: 99%
“…To predict metabolism, we use Meteor Nexus v 3.1.0 (knowledge base 2018 1.0.0), a knowledge-based approach to rank metabolites based on known metabolic reactions 78 . To predict first metabolic step of the parent compound (hybrid 6 ), we analysed the phase-I biotransformation pathways, combining two different methods 80 . A qualitative [absolute reasoning (AR)] and quantitative (site of metabolism (SOM) scoring) assessment was applied, selecting the matching metabolites.…”
Section: Methodsmentioning
confidence: 99%