scholarly journals Virtual Target Screening: Validation Using Kinase Inhibitors

2012 ◽  
Vol 52 (8) ◽  
pp. 2192-2203 ◽  
Author(s):  
Daniel N. Santiago ◽  
Yuri Pevzner ◽  
Ashley A. Durand ◽  
MinhPhuong Tran ◽  
Rachel R. Scheerer ◽  
...  
Keyword(s):  
Kinase Inhibitors ◽  
Virtual Target ◽  
Target Screening ◽  
Virtual Target Screening

scholarly journals Virtual target screening to rapidly identify potential protein targets of natural products in drug discovery

2014 ◽  
Vol 1 (2) ◽  
pp. 81-98 ◽  
Author(s):  
Yuri Pevzner ◽  
◽  
Daniel N. Santiago ◽  
Jacqueline L. von Salm ◽  
Rainer S. Metcalf ◽  
...  
Keyword(s):  
Natural Products ◽  
Drug Discovery ◽  
Protein Targets ◽  
Virtual Target ◽  
Target Screening ◽  
Virtual Target Screening

scholarly journals Identifying Biomolecular Targets of the Anticancer Vitamin-E-δ-Tocotrienol Using a Computational Approach: Virtual Target Screening

2020 ◽  
pp. 1-8
Author(s):  
Wesley H. Brooks ◽  
Yuri Pevzner ◽  
Elza Pevzner ◽  
Kenyon G. Daniel ◽  
Wayne C. Guida ◽  
...  
Keyword(s):  
Vitamin E ◽  
Small Molecules ◽  
Cellular Response ◽  
Large Scale ◽  
Initial Step ◽  
Antitumor Agent ◽  
Computational Approach ◽  
Virtual Target ◽  
Target Screening ◽  
Virtual Target Screening

In recent years, evidence has mounted that a particular form of vitamin E (its δ-tocotrienol variant) may have cellular functions beyond that of an antioxidant, a role commonly ascribed to the tocotrienol class of compounds. In particular, numerous studies of δ-tocotrienol’s effect on cancer cells have identified it as a potent anticancer and antitumor agent. However, this important revelation of potential therapeutic use poses a series of new challenges, with arguably the most important being the elucidation of the precise mechanism of action responsible for the anticancer activity of δ-tocotrienol. As an initial step to address this question, we have used a computational tool, Virtual Target Screening (a molecular docking-based tool that identifies potential binding partners for small molecules), to identify potential biomolecular targets of δ-tocotrienol. Then, to gain a consensus as to the type of biomolecular entity that could be a target for δ-tocotrienol, we utilized PharmMapper and PASS (a ligand-based chemoinformatic approach), and ProBiS (a tool that analyses binding site similarities across known proteins). The results of our multipronged computational consensus-seeking approach showed that such a strategy can identify potential cellular targets of small molecules. This is evidenced by our identification of estrogen receptor-beta, a protein that has been previously shown to bind δ-tocotrienol, which elicited a cellular response. This study supports the use of such a computational approach as an initial step in target identification to avoid time-consuming, costly large-scale experimental screening, greatly reducing the experimental work to just one or a few candidate proteins.

Lessons learned from the optimization of natural product based kinase inhibitors through molecular calculations

Planta Medica ◽  
2008 ◽  
Vol 74 (09) ◽  
Author(s):  
V Myrianthopoulos ◽  
P Magiatis ◽  
AL Skaltsounis ◽  
L Meijer ◽  
E Mikros
Keyword(s):  
Natural Product ◽  
Kinase Inhibitors ◽  
Lessons Learned ◽  
Molecular Calculations

Signal transduction therapy of colon tumors with multiple target kinase inhibitors

2009 ◽  
Vol 47 (05) ◽  
Author(s):  
G Kéri ◽  
L Őrfi ◽  
Z Greff ◽  
Z Varga ◽  
B Szokol ◽  
...  
Keyword(s):  
Signal Transduction ◽  
Kinase Inhibitors ◽  
Multiple Target ◽  
Colon Tumors ◽  
Signal Transduction Therapy

Effects of multi-kinase inhibitors on pulmonary vascular and right ventricular remodelling

Pneumologie ◽  
2011 ◽  
Vol 65 (S 01) ◽  
Author(s):  
B Kojonazarov ◽  
A Sydykov ◽  
H Luitel ◽  
D Kosanovic ◽  
S Pullamsetti ◽  
...  
Keyword(s):  
Right Ventricular ◽  
Kinase Inhibitors ◽  
Ventricular Remodelling
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