Computational Studies of Epidermal Growth Factor Receptor: Docking Reliability, Three-Dimensional Quantitative Structure−Activity Relationship Analysis, and Virtual Screening Studies

2009 ◽  
Vol 52 (4) ◽  
pp. 964-975 ◽  
Author(s):  
Concettina La Motta ◽  
Stefania Sartini ◽  
Tiziano Tuccinardi ◽  
Erika Nerini ◽  
Federico Da Settimo ◽  
...  
Keyword(s):  
Epidermal Growth Factor Receptor ◽  
Growth Factor ◽  
Three Dimensional ◽  
Growth Factor Receptor ◽  
Quantitative Structure Activity Relationship ◽  
Computational Studies ◽  
Quantitative Structure ◽  
Relationship Analysis ◽  
Structure Activity ◽  
Epidermal Growth

Looking for New Inhibitors for the Epidermal Growth Factor Receptor

2018 ◽  
Vol 18 (3) ◽  
pp. 219-232 ◽  
Author(s):  
Riccardo Concu ◽  
M. Natalia D.S. Cordeiro
Keyword(s):  
Epidermal Growth Factor Receptor ◽  
Growth Factor ◽  
Epidermal Growth Factor ◽  
Cell Cancer ◽  
Growth Factor Receptor ◽  
Quantitative Structure Activity Relationship ◽  
New Drugs ◽  
Main Target ◽  
Epidermal Growth ◽  
Neck Squamous Cell Cancer

Epidermal Growth Factor Receptor (EGFR) is still the main target of the Head and Neck Squamous Cell Cancer (HNSCC) because its overexpression has been detected in more than 90% of this type of cancer. This overexpression is usually linked with more aggressive disease, increased resistance to chemotherapy and radiotherapy, increased metastasis, inhibition of apoptosis, promotion of neoplastic angiogenesis, and, finally, poor prognosis and decreased survival. Due to this reason, the main target in the search of new drugs and inhibitors candidates is to downturn this overexpression. Quantitative Structure-Activity Relationship (QSAR) is one of the most widely used approaches while looking for new and more active inhibitors drugs. In this contest, a lot of authors used this technique, combined with others, to find new drugs or enhance the activity of well-known inhibitors. In this paper, on one hand, we will review the most important QSAR approaches developed in the last fifteen years, spacing from classical 1D approaches until more sophisticated 3D; the first paper is dated 2003 while the last one is from 2017. On the other hand, we will present a completely new QSAR approach aimed at the prediction of new EGFR inhibitors drugs. The model presented here has been developed over a dataset consisting of more than 1000 compounds using various molecular descriptors calculated with the DRAGON 7.0© software.

Antileishmanial Chalcones:  Statistical Design, Synthesis, and Three-Dimensional Quantitative Structure−Activity Relationship Analysis

1998 ◽  
Vol 41 (24) ◽  
pp. 4819-4832 ◽  
Author(s):  
Simon Feldbæk Nielsen ◽  
Søren Brøgger Christensen ◽  
Gabriele Cruciani ◽  
Arsalan Kharazmi ◽  
Tommy Liljefors
Keyword(s):  
Three Dimensional ◽  
Statistical Design ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Design Synthesis ◽  
Relationship Analysis ◽  
Structure Activity
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