Establishment of in silico prediction models for cytochrome P450 inductions in human hepatocytes using azole compounds

2018 ◽  
Vol 33 (1) ◽  
pp. S50-S51
Author(s):  
Mika Nagai ◽  
Kouichi Yoshinari
Keyword(s):  
Cytochrome P450 ◽  
In Silico ◽  
Prediction Models ◽  
Human Hepatocytes ◽  
In Silico Prediction

scholarly journals In Silico Prediction of Cytochrome P450-Drug Interaction: QSARs for CYP3A4 and CYP2C9

2016 ◽  
Vol 17 (6) ◽  
pp. 914 ◽  
Author(s):  
Serena Nembri ◽  
Francesca Grisoni ◽  
Viviana Consonni ◽  
Roberto Todeschini
Keyword(s):  
Cytochrome P450 ◽  
Drug Interaction ◽  
In Silico ◽  
In Silico Prediction

In Silico Prediction of Cytochrome P450-Mediated Site of Metabolism (SOM)

2013 ◽  
Vol 20 (3) ◽  
pp. 279-289
Author(s):  
Xian Liu ◽  
Qiancheng Shen ◽  
Jing Li ◽  
Shanshan Li ◽  
Cheng Luo ◽  
...  
Keyword(s):  
Cytochrome P450 ◽  
In Silico ◽  
In Silico Prediction

scholarly journals Efficient Multi-Objective Molecular Optimization in a Continuous Latent Space

2019 ◽  
Author(s):  
Robin Winter ◽  
Floriane Montanari ◽  
Andreas Steffen ◽  
Hans Briem ◽  
Frank Noé ◽  
...  
Keyword(s):  
Objective Function ◽  
In Silico ◽  
Prediction Models ◽  
Chemical Space ◽  
In Silico Prediction ◽  
Swarm Optimization ◽  
Starting Compound ◽  
Latent Space ◽  
Novel Method ◽  
Short Time

In this work, we propose a novel method that combines in silico prediction of molecular properties such as biological activity or pharmacokinetics with an in silico optimization algorithm, namely Particle Swarm Optimization. Our method takes a starting compound as input and proposes new molecules with more desirable (predicted) properties. It navigates a machine-learned continuous representation of a drug-like chemical space guided by a de fined objective function. The objective function combines multiple in silico prediction models, de fined desirability ranges and substructure constraints. We demonstrate that our proposed method is able to consistently fi nd more desirable molecules for the studied tasks in relatively short time.<br>

scholarly journals Development of Simplified in Vitro P-Glycoprotein Substrate Assay and in Silico Prediction Models To Evaluate Transport Potential of P-Glycoprotein

2019 ◽  
Vol 16 (5) ◽  
pp. 1851-1863 ◽  
Author(s):  
Rikiya Ohashi ◽  
Reiko Watanabe ◽  
Tsuyoshi Esaki ◽  
Tomomi Taniguchi ◽  
Nao Torimoto-Katori ◽  
...  
Keyword(s):  
In Silico ◽  
Prediction Models ◽  
In Silico Prediction ◽  
P Glycoprotein ◽  
Transport Potential

In silico prediction of linear free energy relationship descriptors of neutral and ionic compounds

RSC Advances ◽  
2015 ◽  
Vol 5 (98) ◽  
pp. 80634-80642 ◽  
Author(s):  
Chul-Woong Cho ◽  
Stefan Stolte ◽  
Yeoung-Sang Yun ◽  
Ingo Krossing ◽  
Jorg Thöming
Keyword(s):  
Free Energy ◽  
In Silico ◽  
Prediction Models ◽  
Molar Refraction ◽  
Linear Free Energy Relationship ◽  
In Silico Prediction ◽  
Linear Free Energy ◽  
Neutral Compounds ◽  
Ionic Compounds

Prediction models for LFER descriptors – excess molar refraction (E), dipolarity/polarizability (S), H-bonding acidity (A) & basicity (B), McGowan volume (V), and interaction of cations (J+) and anions (J−) – of both ionic and neutral compounds.

Identification and in silico prediction of metabolites of tebufenozide derivatives by major human cytochrome P450 isoforms

2020 ◽  
Vol 28 (9) ◽  
pp. 115429
Author(s):  
Hiroaki Edamatsu ◽  
Masataka Yagawa ◽  
Shinichi Ikushiro ◽  
Toshiyuki Sakaki ◽  
Yoshiaki Nakagawa ◽  
...  
Keyword(s):  
Cytochrome P450 ◽  
In Silico ◽  
In Silico Prediction ◽  
Human Cytochrome ◽  
Cytochrome P450 Isoforms
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