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Research Article: Quantitative Structure Activity Relationship (QSAR) Study of Estrogen Derivatives Based on Descriptors of Energy and Softness
Author(s) -
Pasha Farhan Ahmad,
Neaz Morshed Mohammad,
Cho Seung Joo,
Kang Soon Bang
Publication year - 2007
Publication title -
chemical biology and drug design
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.59
H-Index - 77
eISSN - 1747-0285
pISSN - 1747-0277
DOI - 10.1111/j.1747-0285.2007.00593.x
Subject(s) - quantitative structure–activity relationship , chemistry , estrogen receptor , binding energy , protein data bank (rcsb pdb) , molecule , estrogen , stereochemistry , quantum chemical , computational chemistry , organic chemistry , medicine , physics , cancer , biology , breast cancer , genetics , nuclear physics
Quantum chemical interaction of estrogen derivatives with their receptor has been explored by using Klopman atomic softness. Four series of estrogen derivatives were taken from the literature and the structure of receptor (PDB code 1QKT) was obtained from the protein databank. It is proposed that three Lys, a His, a Tyr and a Cys residues are important for binding. The basic softness values ( E m ‡ ) and acidic softness values ( E n ‡ ) of all atoms of estrogen derivatives were evaluated. The required parameters for Klopman equation were taken from PM3 results. The highest E n ‡ values for each molecules and highest E m ‡ value for each residue were identified and Δ E nm ‡ has been derived using them. The lowest Δ E nm ‡ values were used in addition to Q min (highest negative charge), Δ H f 0 (heat of formation), E T (total energy), and E E (electronic energy). Multiple linear regression analysis was employed to correlate the variation of relative binding affinity values. The analyses show that Δ E nm ‡ values in combination with other descriptors provide significant correlation with relative binding affinity values. The result underscores that carbonyl oxygen of the receptor is important for interaction with estrogen derivatives. This model could be utilized to predict the binding affinity of a new compound of this series.