14 research outputs found
Virtual Screening of PRK1 Inhibitors: Ensemble Docking, Rescoring Using Binding Free Energy Calculation and QSAR Model Development
Protein kinase C Related Kinase 1
(PRK1) has been shown to be involved
in the regulation of androgen receptor signaling and has been identified
as a novel potential drug target for prostate cancer therapy. Since
there is no PRK1 crystal structure available to date, multiple PRK1
homology models were generated in order to address the protein flexibility.
An in-house library of compounds tested on PRK1 was docked into the
ATP binding site of the generated models. In most cases a correct
pose of the inhibitors could be identified by ensemble docking, while
there is still a challenge of finding a reasonable scoring function
that is able to rank compounds according to their biological activity.
We estimated the binding free energy for our data set of structurally
diverse PRK1 inhibitors using the MM-PBĀ(GB)ĀSA and QM/MM-GBSA methods.
The obtained results demonstrate that a correlation between calculated
binding free energies and experimental IC<sub>50</sub> values was
found to be usually higher than using docking scores. Furthermore,
the developed approach was tested on a set of diverse PRK1 inhibitors
taken from literature, which resulted in a significant correlation.
The developed method is computationally inexpensive and can be applied
as a postdocking filter in virtual screening as well as for optimization
of PRK1 inhibitors in order to prioritize compounds for further biological
characterization
Inhibitors of the NAD<sup>+</sup>āDependent Protein Desuccinylase and Demalonylase Sirt5
NAD<sup>+</sup>-dependent histone deacetylases (sirtuins)
play important roles in epigenetic regulation but also through nonhistone
substrates for other key cellular events and have been linked to the
pathogenesis of cancer, neurodegeneration, and metabolic diseases.
The subtype Sirt5 has been shown recently to act as a desuccinylating
and demalonylating enzyme. We have established an assay for biochemical
testing of Sirt5 using a small labeled succinylated lysine derivative.
We present a comparative study on the profiling of several established
sirtuin inhibitors on Sirt1ā3 as well as Sirt5 and also present
initial results on a screening for new compounds that block Sirt5.
Thiobarbiturates were identified as new Sirt5 inhibitors in the low
micromolar range, which are selective over Sirt3 that can be found
in the same cell compartment as Sirt5
2D structures of the three compounds with log <i>P</i> values >14, included in AfroDb.
<p>2D structures of the three compounds with log <i>P</i> values >14, included in AfroDb.</p
Summary of average predicted pharmacokinetic property distributions of the total AfroDb library in comparison with the various subsets.
<p>Summary of average predicted pharmacokinetic property distributions of the total AfroDb library in comparison with the various subsets.</p
Pairwise comparison of mutual relationships between molecular descriptors.
<p>(A) The distribution of the calculated log <i>P</i> versus MW, (B) HBA against MW, (C) HBD against MW and (D) NRB versus MW. LCR represents the Lipinski compliant regions.</p
2D structures of selected promising compounds derived from the African flora and included in AfroDb.
<p>2D structures of selected promising compounds derived from the African flora and included in AfroDb.</p
Comparison of property distribution for the two datasets by percentage distributions.
<p>(A) MW, (B) log <i>P</i>, (C) HBA and (D) HBD. DNP in red and AfroDb in blue. For subfigure B, the <i>x</i>-axis label is the lower limit of binned data, e.g. ā2 is equivalent to ā2 to ā1.</p
A principal component analysis (PCA) plot, showing the comparison of the chemical space defined by the NPs in AfroDb (green) and the chemical space represented by NPs in the ChemBridge Diversity (red) databases.
<p>A principal component analysis (PCA) plot, showing the comparison of the chemical space defined by the NPs in AfroDb (green) and the chemical space represented by NPs in the ChemBridge Diversity (red) databases.</p
Distribution curves for #stars within the AfroDb library, along with the standard ādrug-likeā, ālead-likeā and āfragment-likeā subsets.
<p>Blueā=āAfroDb library, redā=āādrug-likeā subset, greenā=āālead-likeā subset and violetā=āāfragment-likeā subset.</p
Bar chart showing the distribution of the compounds within AfroDb by region of collection.
<p>Bar chart showing the distribution of the compounds within AfroDb by region of collection.</p