scholarly journals Evaluation of antileishmanial potential of Gentiana kurroo Royle by in vitro and in silico methods

2018 ◽  
Keyword(s):  
In Silico ◽  
Gentiana Kurroo ◽  
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

Bioassays and In Silico Methods in the Identification of Human DNA Topoisomerase IIα Inhibitors

2018 ◽  
Vol 25 (28) ◽  
pp. 3286-3318 ◽  
Author(s):  
Kaja Bergant ◽  
Matej Janezic ◽  
Andrej Perdih
Keyword(s):  
In Silico ◽  
In Vivo Studies ◽  
Topoisomerase Iiα ◽  
Dna Topoisomerase ◽  
Human Dna ◽  
Practical Guidelines ◽  
In Silico Methods ◽  
Dna Topoisomerase Iiα

Background: The family of DNA topoisomerases comprises a group of enzymes that catalyse the induction of topological changes to DNA. These enzymes play a role in the cell replication machinery and are, therefore, important targets for anticancer drugs - with human DNA topoisomerase IIα being one of the most prominent. Active compounds targeting this enzyme are classified into two groups with diverse mechanisms of action: DNA poisons act by stabilizing a covalent cleavage complex between DNA and the topoisomerase enzyme, transforming it into a cellular toxin, while the second diverse group of catalytic inhibitors, provides novel inhibition avenues for tackling this enzyme due to frequent occurrence of side effects observed during the DNA poison therapy. Methods: Based on a comprehensive literature search we present an overview of available bioassays and in silico methods in the identification of human DNA topoisomerase IIα inhibitors. Results and Conclusion: A comprehensive outline of the available methods and approaches that explore in detail the in vitro mechanistic and functional aspects of the topoisomerase IIα inhibition of both topo IIα inhibitor groups is presented. The utilized in vitro cell-based assays and in vivo studies to further explore the validated topo IIα inhibitors in subsequent preclinical stages of the drug discovery are discussed. The potential of in silico methods in topoisomerase IIα inhibitor discovery is outlined. A list of practical guidelines was compiled to aid new as well experienced researchers in how to optimally approach the design of targeted inhibitors and validation in the preclinical drug development stages.

scholarly journals Comparative Assessment of In Vitro and In Silico Methods for Aerodynamic Characterization of Powders for Inhalation

Pharmaceutics ◽  
2021 ◽  
Vol 13 (11) ◽  
pp. 1831
Author(s):  
Jelisaveta Ignjatović ◽  
Tijana Šušteršič ◽  
Aleksandar Bodić ◽  
Sandra Cvijić ◽  
Jelena Đuriš ◽  
...  
Keyword(s):  
In Silico ◽  
Aerodynamic Performance ◽  
Dry Powders ◽  
In Vitro Methods ◽  
Discrete Phase Modeling ◽  
Discrete Phase ◽  
Computational Fluid Dynamics Cfd ◽  
In Silico Methods

In vitro assessment of dry powders for inhalation (DPIs) aerodynamic performance is an inevitable test in DPI development. However, contemporary trends in drug development also implicate the use of in silico methods, e.g., computational fluid dynamics (CFD) coupled with discrete phase modeling (DPM). The aim of this study was to compare the designed CFD-DPM outcomes with the results of three in vitro methods for aerodynamic assessment of solid lipid microparticle DPIs. The model was able to simulate particle-to-wall sticking and estimate fractions of particles that stick or bounce off the inhaler’s wall; however, we observed notable differences between the in silico and in vitro results. The predicted emitted fractions (EFs) were comparable to the in vitro determined EFs, whereas the predicted fine particle fractions (FPFs) were generally lower than the corresponding in vitro values. In addition, CFD-DPM predicted higher mass median aerodynamic diameter (MMAD) in comparison to the in vitro values. The outcomes of different in vitro methods also diverged, implying that these methods are not interchangeable. Overall, our results support the utility of CFD-DPM in the DPI development, but highlight the need for additional improvements in these models to capture all the key processes influencing aerodynamic performance of specific DPIs.

Identifying potential liver toxicants using in vitro and in silico methods in a weight-of-evidence based approach

2017 ◽  
Vol 280 ◽  
pp. S133 ◽  
Author(s):  
Judith Madden ◽  
Julia Pletz ◽  
Steven Webb ◽  
Steven Enoch ◽  
Mark Cronin
Keyword(s):  
In Silico ◽  
Weight Of Evidence ◽  
Evidence Based ◽  
In Silico Methods
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