scholarly journals In vitro-in silico methods for risk assessment of organophosphate pesticides (OPs) as found in commonly consumed vegetables in Kenya

2022 ◽  
Author(s):  
Isaac Mokaya Omwenga
Keyword(s):  
Risk Assessment ◽  
In Silico ◽  
Organophosphate Pesticides ◽  
In Silico Methods

Elucidation of Phosphodiesterase-1 Inhibitory Effect of Some Selected Natural Polyphenolics Using In Vitro and In Silico Methods

2016 ◽  
Vol 17 (4) ◽  
pp. 412-417 ◽  
Author(s):  
Abdur Rauf ◽  
Ilkay Erdogan Orhan ◽  
Abdulselam Ertas ◽  
Hamdi Temel ◽  
Taibi Ben Hadda ◽  
...  
Keyword(s):  
In Silico ◽  
Inhibitory Effect ◽  
In Silico Methods

scholarly journals Predicting Absorption-Distribution Properties of Neuroprotective Phosphine-Borane Compounds Using In Silico Modeling and Machine Learning

Molecules ◽  
2021 ◽  
Vol 26 (9) ◽  
pp. 2505
Author(s):  
Raheem Remtulla ◽  
Sanjoy Kumar Das ◽  
Leonard A. Levin
Keyword(s):  
Machine Learning ◽  
Neural Networks ◽  
In Silico ◽  
Disulfide Bonds ◽  
Oral Absorption ◽  
In Vivo Studies ◽  
Drug Candidates ◽  
In Silico Methods

Phosphine-borane complexes are novel chemical entities with preclinical efficacy in neuronal and ophthalmic disease models. In vitro and in vivo studies showed that the metabolites of these compounds are capable of cleaving disulfide bonds implicated in the downstream effects of axonal injury. A difficulty in using standard in silico methods for studying these drugs is that most computational tools are not designed for borane-containing compounds. Using in silico and machine learning methodologies, the absorption-distribution properties of these unique compounds were assessed. Features examined with in silico methods included cellular permeability, octanol-water partition coefficient, blood-brain barrier permeability, oral absorption and serum protein binding. The resultant neural networks demonstrated an appropriate level of accuracy and were comparable to existing in silico methodologies. Specifically, they were able to reliably predict pharmacokinetic features of known boron-containing compounds. These methods predicted that phosphine-borane compounds and their metabolites meet the necessary pharmacokinetic features for orally active drug candidates. This study showed that the combination of standard in silico predictive and machine learning models with neural networks is effective in predicting pharmacokinetic features of novel boron-containing compounds as neuroprotective drugs.

scholarly journals Glucocorticoid resistance conferring mutation in the C-terminus of GR alters the receptor conformational dynamics

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Anna Kaziales ◽  
Florian Rührnößl ◽  
Klaus Richter
Keyword(s):  
Glucocorticoid Receptor ◽  
Steroid Hormones ◽  
In Silico ◽  
Conformational Dynamics ◽  
Glucocorticoid Resistance ◽  
Physiological Processes ◽  
C Terminus ◽  
Hsp90 Chaperone ◽  
In Silico Methods

AbstractThe glucocorticoid receptor is a key regulator of essential physiological processes, which under the control of the Hsp90 chaperone machinery, binds to steroid hormones and steroid-like molecules and in a rather complicated and elusive response, regulates a set of glucocorticoid responsive genes. We here examine a human glucocorticoid receptor variant, harboring a point mutation in the last C-terminal residues, L773P, that was associated to Primary Generalized Glucocorticoid Resistance, a condition originating from decreased affinity to hormone, impairing one or multiple aspects of GR action. Using in vitro and in silico methods, we assign the conformational consequences of this mutation to particular GR elements and report on the altered receptor properties regarding its binding to dexamethasone, a NCOA-2 coactivator-derived peptide, DNA, and importantly, its interaction with the chaperone machinery of Hsp90.

Silver nanoparticle uptake in the human lung assessed through in-vitro and in-silico methods

2020 ◽  
Vol 259 ◽  
pp. 113880 ◽  
Author(s):  
Kathryn Jalink ◽  
Sammi Sham Yin Cheng ◽  
S. Ben Ireland ◽  
M.A.F. Louise Meunier
Keyword(s):  
Silver Nanoparticle ◽  
In Silico ◽  
Human Lung ◽  
Nanoparticle Uptake ◽  
In Silico Methods

scholarly journals In Vitro, In Vivo, and In Silico Methods for Assessment of Muscle Size and Muscle Growth Regulation

Shock ◽  
2020 ◽  
Vol 53 (5) ◽  
pp. 605-615
Author(s):  
Joseph E. Rupert ◽  
Daenique H. A. Jengelley ◽  
Teresa A. Zimmers
Keyword(s):  
In Silico ◽  
Growth Regulation ◽  
Muscle Growth ◽  
Muscle Size ◽  
In Silico Methods

In silico methods for physiologically based biokinetic models describing bioactivation and detoxification of coumarin and estragole: Implications for risk assessment

2009 ◽  
Vol 54 (2) ◽  
pp. 195-207 ◽  
Author(s):  
Ivonne M. C. M. Rietjens ◽  
Ans Punt ◽  
Benoît Schilter ◽  
Gabriele Scholz ◽  
Thierry Delatour ◽  
...  
Keyword(s):  
Risk Assessment ◽  
In Silico ◽  
Physiologically Based ◽  
In Silico Methods
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