Note for: In Silico Screening Identifies a Novel Potential PARP1 Inhibitor Targeting Synthetic Lethality in Cancer Treatment_2015

Note for: In Silico Screening Identifies a Novel Potential PARP1 Inhibitor Targeting Synthetic Lethality in Cancer Treatment_2015

Doi: 10.3390/ijms17020258

Overview

-          Using computational approach to identify new PARP1 inhibitors

-          11,247 compounds -- > ZINC67913374

-          Achieved better grid score -- > -86.8

-          Amber score -- > -51.42

-          Binding free energy -- > -177.28 kJ/mole; olaparib -- > -159.16 kJ/mol

 

Method

3D structure -- > 4UND

Inhibitor in the complex -- > BMN673

Chimera -- > prepare for docking

-          Solvent remove

-          Non-complexed ions remove

-          Hydrogens and charges are added

Ligand

-          Analyticon Discovery NP

o   Download 25 July 2015

o   Filter based on criteria from Zinc

o   Prepare as ready-to-dock format; 3D

Docking

-          USCF-DOCK6

-          Assigning grid scores (creating a box for ligand binding)

-          Compounds with high scores -- > selected as hits

-          Rescoring the hits by DOCK amber rescoring function

Docking evaluation

Negative database -- > download from DUD-E database

-          TP -- > true positive (predict, correct and actual, correct)

-          FP -- > false positive (predict, correct and actual, wrong)

-          TN -- > true negative (predict wrong, and actual, wrong)

-          FN -- > false negative (predict wrong, and actual, correct)

TPR (true positive rate) = sensitivity = TP/(TP+FN)

FPR (false negative rate) = 1-specificity = 1-TN/(TN+FP)

-          742 actives -- > dock

-          3710 decoys -- > dock

Plotting the ROC using pROC library

-          Various threshold setting = Plot (sensitivity, specificity)

-          Calculate values of area under ROC curve (AUC) -- > used for quantitatively evaluating docking performance

MD stimulation

-          Using GROMACS 4.5 package

-          Amber ff99sb force field with TIP3P water molecule

Results

-          Receiver operating characteristic curves

o   Grid score

o   Amber score

o   Random condition

-          Olaparib was used as reference drug;

o   Set as grid +amber cut-off to screen for other potential compounds

o   Screen at grid score first -- > receive 631/11247 (5.65%)

o   Rescore -- > using amber score -- > got unique 1 compound

-          Binding modes

o   Both, olaparib and ZINC67913374 bind to PARP1’s pocket

o   Olaparib interaction

§  3 hydrogen bonds

·         O3 forms 2 hydrogen bonds with NE (3.1A) and NH (2.9A) of Arg878

·         N2 forms hydrogen bond with O (2.8A) of Gly863

o   ZINC67913374 interaction

§  Form 4 hydrogen bonds

·         O9 form H-bond (3A) with N of Arg878

·         O4 form H-bond (2.8A) with NE2 of His909

·         OD2 form 2 H-bonds with O10 (2.6A) and O11 (2.5A) of Asp770

Stability of receptor-ligand complex

Binding free energy

-          Both compounds can be superimposed

o   His862, Tyr907, Tyr896, Asn868, Arg878, Asp766, and Gly863 -- > conserved residues.

o   Gly863, Tyr907  -- > key amino acids for inhibitors-PARP1 interaction

§  Gly863 -- > hydrogen bonding interaction network

§  Typ907 -- > pi-pi stacking

o   Ser904, Phe897, Ala898, Glu763, Leu877, Ile872, Met890, and Gly888, interacted with PARP1 via hydrophobic contacts

o   Glu763, Asp766, Tyr896, Ser904, and Tyr907 were critical residues for the binding interaction

ADMET analysis

-          Using admetSAR -- > free tool