Identification of hit compounds for squalene synthase: Three-dimensional quantitative structure-activity relationship pharmacophore modeling, virtual screening, molecular docking, binding free energy calculation, and molecular dynamic simulation

2017 ◽  
Vol 31 (11) ◽  
pp. e2923 ◽  
Author(s):  
M. Hou ◽  
G. Yan ◽  
X. Ma ◽  
J. Luo ◽  
X. Hou ◽  
...  
Keyword(s):  
Free Energy ◽  
Binding Free Energy ◽  
Three Dimensional ◽  
Quantitative Structure Activity Relationship ◽  
Pharmacophore Modeling ◽  
Squalene Synthase ◽  
Free Energy Calculation ◽  
Energy Calculation ◽  
Quantitative Structure ◽  
Structure Activity

Three Dimensional Quantitative Structure Activity Relationship and Pharmacophore Modeling of Tacrine Derivatives as Acetylcholinesterase Inhibitors in Alzheimer's Treatment

2020 ◽  
Vol 16 (2) ◽  
pp. 155-168
Author(s):  
Fatemeh Ansari ◽  
Jahan B. Ghasemi ◽  
Ali Niazi
Keyword(s):  
Three Dimensional ◽  
Acetylcholinesterase Inhibitors ◽  
Quantitative Structure Activity Relationship ◽  
Structure Activity Relationship ◽  
Pharmacophore Modeling ◽  
Activity Relationship ◽  
Quantitative Structure ◽  
Statistical Parameters ◽  
Data Set ◽  
Structure Activity

Background: Three dimensional quantitative structure activity relationship and pharmacophore modeling are studied for tacrine derivatives as acetylcholinesterase inhibitors. Methods: The three dimensional quantitative structure–activity relationship and pharmacophore methods were used to model the 68 derivatives of tacrine as human acetylcholinesterase inhibitors. The effect of the docked conformer of each molecule in the enzyme cavity was investigated on the predictive ability and statistical quality of the produced models. Results: The whole data set was divided into two training and test sets using hierarchical clustering method. 3D-QSAR model, based on the comparative molecular field analysis has good statistical parameters as indicated by q2 =0.613, r2 =0.876, and r2pred =0.75. In the case of comparative molecular similarity index analysis, q2, r2 and r2pred values were 0.807, 0.96, and 0.865 respectively. The statistical parameters of the models proved that the inhibition data are well fitted and they have satisfactory predictive abilities. Conclusion : The results from this study illustrate the reliability of using techniques in exploring the likely bonded conformations of the ligands in the active site of the protein target and improve the understanding over the structural and chemical features of AChE.

scholarly journals Binding Free Energy (BFE) Calculations and Quantitative Structure–Activity Relationship (QSAR) Analysis of Schistosoma mansoni Histone Deacetylase 8 (smHDAC8) Inhibitors

Molecules ◽  
2021 ◽  
Vol 26 (9) ◽  
pp. 2584
Author(s):  
Conrad V. Simoben ◽  
Ehab Ghazy ◽  
Patrik Zeyen ◽  
Salma Darwish ◽  
Matthias Schmidt ◽  
...  
Keyword(s):  
Free Energy ◽  
Schistosoma Mansoni ◽  
Histone Deacetylase ◽  
Binding Free Energy ◽  
Quantitative Structure Activity Relationship ◽  
Activity Relationship ◽  
Binding Modes ◽  
Quantitative Structure ◽  
Structure Activity ◽  
Qsar Models

Histone-modifying proteins have been identified as promising targets to treat several diseases including cancer and parasitic ailments. In silico methods have been incorporated within a variety of drug discovery programs to facilitate the identification and development of novel lead compounds. In this study, we explore the binding modes of a series of benzhydroxamates derivatives developed as histone deacetylase inhibitors of Schistosoma mansoni histone deacetylase (smHDAC) using molecular docking and binding free energy (BFE) calculations. The developed docking protocol was able to correctly reproduce the experimentally established binding modes of resolved smHDAC8–inhibitor complexes. However, as has been reported in former studies, the obtained docking scores weakly correlate with the experimentally determined activity of the studied inhibitors. Thus, the obtained docking poses were refined and rescored using the Amber software. From the computed protein–inhibitor BFE, different quantitative structure–activity relationship (QSAR) models could be developed and validated using several cross-validation techniques. Some of the generated QSAR models with good correlation could explain up to ~73% variance in activity within the studied training set molecules. The best performing models were subsequently tested on an external test set of newly designed and synthesized analogs. In vitro testing showed a good correlation between the predicted and experimentally observed IC50 values. Thus, the generated models can be considered as interesting tools for the identification of novel smHDAC8 inhibitors.

scholarly journals Molecular Shape Descriptors. 2. Quantitative Structure-Activity Relationships Based Upon Three-Dimensional Molecular Shape Descriptor

1985 ◽  
Vol 40 (11) ◽  
pp. 1114-1120
Author(s):  
loan Motoc ◽  
Garland R. Marshall
Keyword(s):  
Enzyme Inhibitor ◽  
Three Dimensional ◽  
Shape Descriptor ◽  
Molecular Shape ◽  
Quantitative Structure Activity Relationship ◽  
Quantitative Structure ◽  
E Coli ◽  
Interactional Pattern ◽  
Structure Activity ◽  
Quantitative Structure Activity Relationships

A methodology to incorporate the three-dimensional molecular shape descriptor (3 D-MSD) into a quantitative structure-activity relationship is discussed in detail. The 3 D-MSD is calculated and correlated with Kiapp values for a set of 2,4-diamino-5-benzylpyrimidines which inhibit E. coli DHFR. The correlation (n = 22, r = 0.95, s = 0.214, F = 55.10) indicates that the polarization interaction dominates the enzyme-inhibitor interactional pattern.

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