Structure-activity relationships of pyrethroid insecticides. Part 2. The use of molecular dynamics for conformation searching and average parameter calculation

1992 ◽  
Vol 6 (2) ◽  
pp. 191-201 ◽  
Author(s):  
Brian D. Hudson ◽  
Ashley R. George ◽  
Martyn G. Ford ◽  
David J. Livingstone
Keyword(s):  
Molecular Dynamics ◽  
Pyrethroid Insecticides ◽  
Parameter Calculation ◽  
Structure Activity Relationships ◽  
Structure Activity

The structure/activity relationships of pyrethroid insecticides. 1. A Novel Approach Based upon the Use of Multivariate QSAR and Computational Chemistry

1989 ◽  
Vol 27 (3) ◽  
pp. 305-326 ◽  
Author(s):  
Martyn G. Ford ◽  
Richard Greenwood ◽  
Christopher H. Turner ◽  
Brian Hudson ◽  
David J. Livingstone
Keyword(s):  
Computational Chemistry ◽  
Pyrethroid Insecticides ◽  
Structure Activity Relationships ◽  
Structure Activity ◽  
Novel Approach

scholarly journals 3D-QSAR, Molecular Docking, and MD Simulations of Anthraquinone Derivatives as PGAM1 Inhibitors

2021 ◽  
Vol 12 ◽  
Author(s):  
Yuwei Wang ◽  
Yifan Guo ◽  
Shaojia Qiang ◽  
Ruyi Jin ◽  
Zhi Li ◽  
...  
Keyword(s):  
Molecular Dynamics ◽  
Molecular Docking ◽  
Rational Design ◽  
Binding Free Energy ◽  
3D Qsar ◽  
Md Simulations ◽  
Structure Activity Relationships ◽  
Structure Activity ◽  
Wide Range ◽  
Anthraquinone Derivatives

PGAM1 is overexpressed in a wide range of cancers, thereby promoting cancer cell proliferation and tumor growth, so it is gradually becoming an attractive target. Recently, a series of inhibitors with various structures targeting PGAM1 have been reported, particularly anthraquinone derivatives. In present study, the structure–activity relationships and binding mode of a series of anthraquinone derivatives were probed using three-dimensional quantitative structure–activity relationships (3D-QSAR), molecular docking, and molecular dynamics (MD) simulations. Comparative molecular field analysis (CoMFA, r2 = 0.97, q2 = 0.81) and comparative molecular similarity indices analysis (CoMSIA, r2 = 0.96, q2 = 0.82) techniques were performed to produce 3D-QSAR models, which demonstrated satisfactory results, especially for the good predictive abilities. In addition, molecular dynamics (MD) simulations technology was employed to understand the key residues and the dominated interaction between PGAM1 and inhibitors. The decomposition of binding free energy indicated that the residues of F22, K100, V112, W115, and R116 play a vital role during the ligand binding process. The hydrogen bond analysis showed that R90, W115, and R116 form stable hydrogen bonds with PGAM1 inhibitors. Based on the above results, 7 anthraquinone compounds were designed and exhibited the expected predictive activity. The study explored the structure–activity relationships of anthraquinone compounds through 3D-QSAR and molecular dynamics simulations and provided theoretical guidance for the rational design of new anthraquinone derivatives as PGAM1 inhibitors.

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