Reactivation potency of two novel oximes (K456 and K733) against paraoxon-inhibited acetyl and butyrylcholinesterase: In silico and in vitro models

2019 ◽  
Vol 310 ◽  
pp. 108735 ◽  
Author(s):  
Amna Iqbal ◽  
Shahrukh Malik ◽  
Syed M. Nurulain ◽  
Kamil Musilek ◽  
Kamil Kuca ◽  
...  
Keyword(s):  
In Silico ◽  
In Vitro Models

scholarly journals Inherited and Acquired Rhythm Disturbances in Sick Sinus Syndrome, Brugada Syndrome, and Atrial Fibrillation: Lessons from Preclinical Modeling

Cells ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. 3175
Author(s):  
Laura Iop ◽  
Sabino Iliceto ◽  
Giovanni Civieri ◽  
Francesco Tona
Keyword(s):  
Atrial Fibrillation ◽  
Cardiovascular Diseases ◽  
Brugada Syndrome ◽  
In Silico ◽  
Cardiac Fibrosis ◽  
Sick Sinus Syndrome ◽  
In Vitro Models ◽  
Global Functioning

Rhythm disturbances are life-threatening cardiovascular diseases, accounting for many deaths annually worldwide. Abnormal electrical activity might arise in a structurally normal heart in response to specific triggers or as a consequence of cardiac tissue alterations, in both cases with catastrophic consequences on heart global functioning. Preclinical modeling by recapitulating human pathophysiology of rhythm disturbances is fundamental to increase the comprehension of these diseases and propose effective strategies for their prevention, diagnosis, and clinical management. In silico, in vivo, and in vitro models found variable application to dissect many congenital and acquired rhythm disturbances. In the copious list of rhythm disturbances, diseases of the conduction system, as sick sinus syndrome, Brugada syndrome, and atrial fibrillation, have found extensive preclinical modeling. In addition, the electrical remodeling as a result of other cardiovascular diseases has also been investigated in models of hypertrophic cardiomyopathy, cardiac fibrosis, as well as arrhythmias induced by other non-cardiac pathologies, stress, and drug cardiotoxicity. This review aims to offer a critical overview on the effective ability of in silico bioinformatic tools, in vivo animal studies, in vitro models to provide insights on human heart rhythm pathophysiology in case of sick sinus syndrome, Brugada syndrome, and atrial fibrillation and advance their safe and successful translation into the cardiology arena.

scholarly journals Prediction of the skin permeability of topical drugs using in silico and in vitro models

2019 ◽  
Vol 136 ◽  
pp. 104945 ◽  
Author(s):  
Cristina Alonso ◽  
Víctor Carrer ◽  
Sonia Espinosa ◽  
Miriam Zanuy ◽  
Mònica Córdoba ◽  
...  
Keyword(s):  
In Silico ◽  
In Vitro Models ◽  
Skin Permeability ◽  
Topical Drugs

scholarly journals Antiproliferative Benzoindazolequinones as Potential Cyclooxygenase-2 Inhibitors

Molecules ◽  
2019 ◽  
Vol 24 (12) ◽  
pp. 2261 ◽  
Author(s):  
Aurora Molinari ◽  
Alfonso Oliva ◽  
Marlene Arismendi-Macuer ◽  
Leda Guzmán ◽  
Waldo Acevedo ◽  
...  
Keyword(s):  
Cell Lines ◽  
In Silico ◽  
Antitumor Agents ◽  
Human Cancer ◽  
In Vitro Models ◽  
Cyclooxygenase 2 ◽  
Binding Energies ◽  
Human Cancer Cells ◽  
Mcf 7

Quinones and nitrogen heterocyclic moieties have been recognized as important pharmacophores in the development of antitumor agents. This study aimed to establish whether there was any correlation between the in silico predicted parameters and the in vitro antiproliferative activity of a family of benzoindazolequinones (BIZQs), and to evaluate overexpressed proteins in human cancer cells as potential biomolecular targets of these compounds. For this purpose, this study was carried out using KATO-III and MCF-7 cell lines as in vitro models. Docking results showed that these BIZQs present better binding energies (ΔGbin) values for cyclooxygenase-2 (COX-2) than for other cancer-related proteins. The predicted ∆Gbin values of these BIZQs, classified in three series, positively correlated with IC50 measured in both cell lines (KATO-III: 0.72, 0.41, and 0.90; MCF-7: 0.79, 0.55, and 0.87 for Series I, II, and III, respectively). The results also indicated that compounds 2a, 2c, 6g, and 6k are the most prominent BIZQs, because they showed better IC50 and ∆Gbin values than the other derivatives. In silico drug absorption, distribution, metabolism, and excretion (ADME) properties of the three series were also analyzed and showed that several BIZQs could be selected as potential candidates for cancer pre-clinical assays.

Analyses of Gingival Adhesion Molecules in Periodontitis: Theoretical In Silico, Comparative In Vivo, and Explanatory In Vitro Models

2016 ◽  
Vol 87 (2) ◽  
pp. 193-202 ◽  
Author(s):  
Ulvi K. Gürsoy ◽  
Fares Zeidán-Chuliá ◽  
Dogukan Yilmaz ◽  
Vural Özdemir ◽  
Juho Mäki-Petäys ◽  
...  
Keyword(s):  
Adhesion Molecules ◽  
In Silico ◽  
In Vitro Models

Prediction and validation of avascular tumor growth pattern in different metabolic conditions using in silico and in vitro models

2021 ◽  
pp. 2150024
Author(s):  
Mahshid Heidari ◽  
Mahboubeh Kabiri
Keyword(s):  
Tumor Growth ◽  
Computational Model ◽  
Growth Pattern ◽  
In Silico ◽  
Cell Activity ◽  
In Vitro Models ◽  
Growth Behavior ◽  
Cell Counting ◽  
Modeling Framework

Objectives: In recent years, scientists have taken many efforts for in vitro and in silico modeling of cancerous tumors. In fact, three-dimensional (3D) cultures of multicellular tumor spheroids (MCTSs) are good validators for computational results. The goal of this study is to simulate the 3D early growth of avascular tumors using MCTSs and to compare the in vitro models with the results and predictions of a specific computational modeling framework. Using these two types of models, the importance of metabolic condition on tumor growth behavior and necrosis could be predicted. Materials and methods: We took advantage of a previously developed computational model of tumor growth (constructed by integrating a generic metabolic network model of cancer cells with a multiscale agent-based framework). Among the computational predictions is the importance of glucose accessibility on tumor growth behavior. To study the effect of glucose concentration experimentally, MCTSs were grown in high and low glucose culture media. After that, tumor growth pattern was analyzed by MTT assay, cell counting and propidium iodide (PI) staining. Results: We obviously observed that the rate of necrosis increases and the rate of tumor growth and cell activity decreases as the glucose availability reduces, which is in line with the computational model prediction.

ADMET Profiling in Drug Discovery and Development: Perspectives of in silico, in vitro and integrated approaches

2021 ◽  
Vol 22 ◽  
Author(s):  
Nour El-Huda Daoud ◽  
Pobitra Borah ◽  
Pran Kishore Deb ◽  
Katharigatta N. Venugopala ◽  
Wafa Hourani ◽  
...  
Keyword(s):  
Drug Discovery ◽  
In Silico ◽  
Predictive Power ◽  
Early Stage ◽  
In Vitro Models ◽  
Prediction Ability ◽  
Drug Discovery And Development ◽  
In Silico Admet

: In the drug discovery setting, undesirable ADMET properties of a pharmacophore with good predictive power obtained after a tedious drug discovery and development process may lead to late-stage attrition. The early-stage ADMET profiling has introduced a new dimension to leading development. Although several high-throughput in vitro models are available for ADMET profiling, however, the in silico methods are gaining more importance because of their economic and faster prediction ability without the requirements of tedious and expensive laboratory resources. Nonetheless, in silico ADMET tools alone are not accurate and, therefore, ideally adopted along with in vitro and or in vivo methods in order to enhance predictability power. This review summarizes the significance and challenges associated with the application of in silico tools as well as the possible scope of in vitro models for integration to improve the ADMET predictability power of these tools.

scholarly journals A Hybrid in Silico and Tumor-on-a-Chip Approach to Model Targeted Protein Behavior in 3D Microenvironments

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2461
Author(s):  
Valentina Palacio-Castañeda ◽  
Simon Dumas ◽  
Philipp Albrecht ◽  
Thijmen J. Wijgers ◽  
Stéphanie Descroix ◽  
...  
Keyword(s):  
Mathematical Modeling ◽  
Tumor Cell ◽  
Tumor Cells ◽  
In Silico ◽  
Growth Factor Receptor ◽  
In Vitro Models ◽  
Protein Activity ◽  
Apparent Diffusion Coefficients ◽  
Ankyrin Repeat Proteins

To rationally improve targeted drug delivery to tumor cells, new methods combining in silico and physiologically relevant in vitro models are needed. This study combines mathematical modeling with 3D in vitro co-culture models to study the delivery of engineered proteins, called designed ankyrin repeat proteins (DARPins), in biomimetic tumor microenvironments containing fibroblasts and tumor cells overexpressing epithelial cell adhesion molecule (EpCAM) or human epithelial growth factor receptor (HER2). In multicellular tumor spheroids, we observed strong binding-site barriers in combination with low apparent diffusion coefficients of 1 µm2·s-1 and 2 µm2 ·s-1 for EpCAM- and HER2-binding DARPin, respectively. Contrasting this, in a tumor-on-a-chip model for investigating delivery in real-time, transport was characterized by hindered diffusion as a consequence of the lower local tumor cell density. Finally, simulations of the diffusion of an EpCAM-targeting DARPin fused to a fragment of Pseudomonas aeruginosa exotoxin A, which specifically kills tumor cells while leaving fibroblasts untouched, correctly predicted the need for concentrations of 10 nM or higher for extensive tumor cell killing on-chip, whereas in 2D models picomolar concentrations were sufficient. These results illustrate the power of combining in vitro models with mathematical modeling to study and predict the protein activity in complex 3D models.

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