scholarly journals New application of in silico methods in identifying mechanisms of action and key components of anti-cancer herbal formulation YIV-906

2020 ◽  
Author(s):  
Shuhan Liu ◽  
Junmei Wang ◽  
Xibing He ◽  
Viet Hoang Man ◽  
Beihong Ji ◽  
...  
Keyword(s):  
In Silico ◽  
Mechanisms Of Action ◽  
Herbal Formulation ◽  
Anti Cancer ◽  
In Silico Methods

New application of in silico methods in identifying mechanisms of action and key components of anti-cancer herbal formulation YIV-906 (PHY906)

2019 ◽  
Vol 21 (42) ◽  
pp. 23501-23513 ◽  
Author(s):  
Shuhan Liu ◽  
Xibing He ◽  
Viet Hoang Man ◽  
Beihong Ji ◽  
Junjun Liu ◽  
...  
Keyword(s):  
In Silico ◽  
Mechanisms Of Action ◽  
Herbal Formulation ◽  
Anti Cancer ◽  
In Silico Methods

Human metabolites and herbal chemicals from YIV-906 can act as phosphate mimics and occupy the catalytic centre of DUSP3.

Mechanisms of action of antihyperglycemic mexicanolides isolated from Swietenia humillis: in vivo and in silico approaches

Planta Medica ◽  
2016 ◽  
Vol 81 (S 01) ◽  
pp. S1-S381 ◽  
Author(s):  
B Ovalle-Magallanes ◽  
A Madariaga-Mazón ◽  
A Navarrete ◽  
R Mata
Keyword(s):  
In Silico ◽  
Mechanisms Of Action

Developing FGFR4 Inhibitors As Potential Anti-Cancer Agents Via In Silico Design, Supported by In Vitro and Cell-Based Testing

2013 ◽  
Vol 999 (999) ◽  
pp. 1-15
Author(s):  
H.K. Ho ◽  
G. Nemeth ◽  
Y.R. Ng ◽  
E. Pang ◽  
C. Szantai-Kis ◽  
...  
Keyword(s):  
In Silico ◽  
In Silico Design ◽  
Anti Cancer

Anticancer Properties of Essential Oils: An Overview

2018 ◽  
Vol 18 (10) ◽  
pp. 957-966 ◽  
Author(s):  
Milene Aparecida Andrade ◽  
Mariana Aparecida Braga ◽  
Pedro Henrique Souza Cesar ◽  
Marcus Vinicius Cardoso Trento ◽  
Mariana Araújo Espósito ◽  
...  
Keyword(s):  
Cancer Therapy ◽  
Essential Oils ◽  
Public Health Problem ◽  
Mechanisms Of Action ◽  
Low Molecular Weight ◽  
Anticancer Properties ◽  
Anti Cancer ◽  
Different Types ◽  
Antitumor Properties ◽  
Pharmaceutical Properties

Background: Essential oils are complex mixtures of low molecular weight compounds extracted from plants. Their main constituents are terpenes and phenylpropanoids, which are responsible for their biological and pharmaceutical properties, such as insecticidal, parasiticidal, antimicrobial, antioxidant, anti-inflammatory, analgesic, antinociceptive, anticarcinogenic, and antitumor properties. Cancer is a complex genetic disease considered as a serious public health problem worldwide, accounting for more than 8 million deaths annually. Objective: The activities of prevention and treatment of different types of cancer and the medicinal potential of essential oils are addressed in this review. Conclusion: Several studies have demonstrated anti-carcinogenic and antitumor activity for many essential oils obtained from various plant species. They may be used as a substitution to or in addition to conventional anti-cancer therapy. Although many studies report possible mechanisms of action for essential oils compounds, more studies are necessary in order to apply them safely and appropriately in cancer therapy.

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

Prediction of Drug-Drug Interactions Related to Inhibition or Induction of Drug-Metabolizing Enzymes

2019 ◽  
Vol 19 (5) ◽  
pp. 319-336 ◽  
Author(s):  
Alexander V. Dmitriev ◽  
Alexey A. Lagunin ◽  
Dmitry А. Karasev ◽  
Anastasia V. Rudik ◽  
Pavel V. Pogodin ◽  
...  
Keyword(s):  
In Silico ◽  
Computational Models ◽  
Field Analysis ◽  
Pharmaceutical Chemistry ◽  
Sources Of Information ◽  
Metabolizing Enzymes ◽  
Physiologically Based Pharmacokinetic ◽  
Pharmacophore Models ◽  
Drug Metabolising Enzymes ◽  
In Silico Methods

Drug-drug interaction (DDI) is the phenomenon of alteration of the pharmacological activity of a drug(s) when another drug(s) is co-administered in cases of so-called polypharmacy. There are three types of DDIs: pharmacokinetic (PK), pharmacodynamic, and pharmaceutical. PK is the most frequent type of DDI, which often appears as a result of the inhibition or induction of drug-metabolising enzymes (DME). In this review, we summarise in silico methods that may be applied for the prediction of the inhibition or induction of DMEs and describe appropriate computational methods for DDI prediction, showing the current situation and perspectives of these approaches in medicinal and pharmaceutical chemistry. We review sources of information on DDI, which can be used in pharmaceutical investigations and medicinal practice and/or for the creation of computational models. The problem of the inaccuracy and redundancy of these data are discussed. We provide information on the state-of-the-art physiologically- based pharmacokinetic modelling (PBPK) approaches and DME-based in silico methods. In the section on ligand-based methods, we describe pharmacophore models, molecular field analysis, quantitative structure-activity relationships (QSAR), and similarity analysis applied to the prediction of DDI related to the inhibition or induction of DME. In conclusion, we discuss the problems of DDI severity assessment, mention factors that influence severity, and highlight the issues, perspectives and practical using of in silico methods.

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