scholarly journals The inhibition of human farnesyl pyrophosphate synthase by nitrogen-containing bisphosphonates. Elucidating the role of active site threonine 201 and tyrosine 204 residues using enzyme mutants

Bone ◽  
2015 ◽  
Vol 81 ◽  
pp. 478-486 ◽  
Author(s):  
Maria K. Tsoumpra ◽  
Joao R. Muniz ◽  
Bobby L. Barnett ◽  
Aaron A. Kwaasi ◽  
Ewa S. Pilka ◽  
...  
Keyword(s):  
Active Site ◽  
Farnesyl Pyrophosphate ◽  
Farnesyl Pyrophosphate Synthase ◽  
Human Farnesyl Pyrophosphate Synthase

scholarly journals Human farnesyl pyrophosphate synthase is allosterically inhibited by its own product

2017 ◽  
Vol 8 (1) ◽  
Author(s):  
Jaeok Park ◽  
Michal Zielinski ◽  
Alexandr Magder ◽  
Youla S. Tsantrizos ◽  
Albert M. Berghuis
Keyword(s):  
Farnesyl Pyrophosphate ◽  
Farnesyl Pyrophosphate Synthase ◽  
Human Farnesyl Pyrophosphate Synthase

scholarly journals QSAR Models for Nitrogen Containing Monophosphonate and Bisphosphonate Derivatives as Human Farnesyl Pyrophosphate Synthase Inhibitors Based on Monte Carlo Method

Drug Research ◽  
2018 ◽  
Vol 69 (03) ◽  
pp. 159-167 ◽  
Author(s):  
Parvin Kumar ◽  
Ashwani Kumar ◽  
Jayant Sindhu ◽  
Sohan Lal
Keyword(s):  
Monte Carlo ◽  
Monte Carlo Method ◽  
Mevalonate Pathway ◽  
Predictive Ability ◽  
Correlation Technique ◽  
Farnesyl Pyrophosphate ◽  
Farnesyl Pyrophosphate Synthase ◽  
End Point ◽  
Qsar Models ◽  
Human Farnesyl Pyrophosphate Synthase

AbstractHuman farnesyl pyrophosphate synthase (hFPPS) is a well-settled therapeutic target and it is an enzyme of the mevalonate pathway which catalyzes the biosynthesis of the C-15 isoprenoid farnesyl pyrophosphate. QSAR studies by using Monte Carlo method for human farnesyl pyrophosphate synthase inhibitors has been carried out using balance of correlation technique with Index of ideality correlation. For construction of QSAR models, six random splits were prepared from the data of 73 phosphonates and hybrid optimal descriptors procured from graph (HFG) and SMILES based notations were employed. The developed QSAR models have robustness, good fitting ability, generalizability and internal predictive ability. The external predictive ability has been certified by testing various precedents. The values of R2, IIC, Q2 and ∆R2 m for the best model are 0.9304, 0.9614, 0.9061 and 0.0861 respectively. The developed QSAR models met with the specified standards given in OECD guideline and applicability domain. The structural feature promoters for the end point increase and promoters for end point decrease have been extracted. The predicted pIC50 for the new proposed compounds have also been reported.

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