D-QSAR Study of Indol-2-yl Ethanones Derivatives as Novel Indoleamine 2 , 3-Dioxygenase ( IDO ) Inhibitors

3D-QSAR approach using kNN-MFA was applied to a series of Indol-2-yl ethanones derivatives as novel IDO inhibitors. For the purpose, 22 compounds were used to develop models. To elucidate the structural properties required for IDO inhibitory activity, we report here k-nearest neighbor molecular field analysis (kNN-MFA)based 3D-QSAR model for Indol-2-yl ethanones derivatives as novel IDO inhibitors. Overall model classification accuracy was 76.27% (q = 0.7627, representing internal validation) in training set and 79.35% (pred_r = 0.7935, representing external validation) in test set using sphere exclusion and forward as a method of data selection and variable selection, respectively. Contour maps using this approach showed that hydrophobic and steric effects dominantly determine binding affinities. The information rendered by 3D-QSAR model may lead to a better understanding of structural requirements of IDO inhibitors and can help in the design of novel potent molecules.


Introduction
Human indoleamine 2,3-dioxygenase (IDO) (MW 47,000) has been implicated as a key participant in the development of senile cataracts and in a variety of immunological roles, many of which have implications for treatment of cancer [1][2][3][4] .It is known that IDO is over expressed in a variety of diseases, including cancer, neurodegenerative disorders (e.g., Alzheimer's diseases), age-related cataract, and HIV encephalitis 5 .Although IDO is critical to host defense against pathogens, it is now clear that this enzyme plays multiple roles in the immune system 6 .IDO is a ubiquitously expressed enzyme, encoded by the INDO gene, which catalyzes the initial and rate limiting step in the degradation of tryptophan along a pathway which can lead to the biosynthesis of NAD + (nicotinamide adenine dinucleotide).IDO does not, however, handle dietary catabolism of tryptophan, which is instead the role of the structurally unrelated liver-specific enzyme tryptophan dioxygenase (TDO2), nor does it appear to be critical for maintaining NAD + levels 7,8 .In order for IDO to be catalytically active, it is essential to maintain the heme iron ion in the ferrous (Fe 2+ ) state.As the enzyme is susceptible to autoxidation 8,9 .IDO is a monomeric extrahepatic cytosolic heme dioxygenase that catalyzes the addition of oxygen across the C-2/C-3 bond of the indole ring of tryptophan 10 .The oxidative cleavage of the 2,3 double bond in the indole moiety, resulting in the production of Nformylkynurenine.Heme iron that exists in the active site of IDO is active as its ferrous (Fe 2+ ) form, whereas the ferric (Fe 3+ ) form is inactive 9 .Under healthy conditions, IDO is expressed modestly in various tissues but it is highly induced by bacterial and viral infection.This induction is mediated mainly by IFN-γ and results in increased Trp degradation along the Kyn pathway.The Trp degradation induced by IDO during infection plays a role in the defense mechanism against the infectious pathogens 11 .Three dimensional quantitative structure activity relationship (3D-QSAR) is widely used tool to identify the steric, electrostatic and hydrophobic structural requirements of various drugs acting via receptor modulation for exerting biological activity.Thus, 3D-QSAR is valuable molecular modeling tool for drug design.By the application of 3D-QSAR models, the number of compounds that need to be synthesized by a medicinal chemist can be reduced greatly.Thus, the time and cost of drug discovery and development can also be reduced 12,13 .

Experimental Work
Hardware and software 3D-QSAR study was performed using the Molecular Design Suite (VLife MDS software package, version 3.5; from VLife Sciences, Pune, India) 14 user interface implemented on Acer PC with a Pentium IV processor and Windows XP operating system.

3D-QSAR Study Biological activity data set
A data set of 22 molecules of reported series for IDO inhibitory activities have been taken for 3D-QSAR study 8 .IDO inhibitory activity was expressed as pIC 50.The structures of all compounds were constructed in Chem sketch version 12.0 15 .All structures are cleaned and 3D optimized.All structures were optimized using Merck Molecular Force Field (MMFF) with distance dependent dielectric function and energy gradient of 0.001 kcal/mol Å.The conformers for all structures are generated and selected the low energy conformer for each compound and used for further study.Molecular modeling for 3D-QSAR 3D-QSAR studies were performed using a Sphere Exclusion Method selected training set of 18 compounds for generating 3D-QSAR models and a test set of 4 compounds for validating the quality of the models.In vitro inhibitory concentrations (IC 50 ) of the molecules were converted into corresponding pIC 50 values and used as dependent variables in 3D-QSAR calculations (Table 1

Alignment procedure
Alignment of all 22 compounds was done using the template-based alignment by using the most active molecule (7m) as reference and indole as a basic template (Figure1) in MDS; the aligned structures were used for the study.These aligned conformations were used to generate the predictive QSAR models.

Figure 1
Basic template for alignment.

Calculation of descriptors
Using Tripos force field 16 and Gasteiger and Marsili charge type, 17 electrostatic, steric and hydrophobic field descriptors were calculated.This resulted in calculation of 4290 field descriptors (1430 for each electrostatic, steric & hydrophobic) for all the compounds in separate columns.QSAR analysis was performed after removal of all the invariable columns, as they do not contribute to the QSAR.3D-QSAR studies were carried out by kNN method using Forward Stepwise Variable Selection as variable selection method.

Results and discussion
For 3D-QSAR kNN-MFA of Indol-2-yl ethanones derivatives with reported activities as novel IDO inhibitors were prepared.Several 3D-QSAR models were generated using stepwise variable selection method resulted several statistically significant models, of which the corresponding best model is reported herein.3D-QSAR model was selected based on the value of statistical parameters & the best kNN MFA 3D-QSAR model with 18 training set compounds have a q 2 = 0.76 and pred_r 2 = 0.79 (Table 3).It can be seen that the kNN MFA model obtained by using forward stepwise variable selection method shows that hydrophobic and steric interactions play major role in determining biological activity.

Conclusions
In the present study, 3D-QSAR model of Indol-2-yl ethanones was developed using Vlife MDS software.The location and range of function values at the field points selected by model (Figure 3) provide the clues for the design of new molecules thus giving insight on structural requirements for designing more potent analogues as IDO inhibitors.The 3D-QSAR study has shown that more hydrophobic substituents and less steric groups would be favourable for the IDO inhibitory activity.This model is expected to provide a good alternative to predict the biological activity prior to synthesis of other analogues as potent and novel IDO inhibitors.

Figure 2 )
Figure 2 Comparison of observed activity versus predicted activity for training set & test set compounds according to 3D-QSAR model by kNN MFA.Observed activity (pIC 50 )

Figure 3
Figure 3 Stereoview of the molecular rectangular field grid around the superposed molecular units of Indol-2-yl ethanones series of compounds using SW-kNN MFA method.

Table 1 .
). 3D-Qsar Study of Indol-2-Yl Ethanones Derivatives 1755 Structure of training and test sets of compounds along with observed and predicted activity.This approach resulted in selection of compounds nos.12a, 7f, 7g and 8a as the test set and the remaining 18 compounds as the training set.Selection of molecules in the training set and test is a key and important feature of any QSAR model.Therefore the care was taken in such a way that biological activities of all compounds in test lie within the maximum and minimum value range of biological activities of training set of compounds.The UniColumn Statistics of test and training sets further reflected the correct selection of test and training sets.A Uni-Column statistics for training set and test set were generated to check correctness of selection criteria for trainings and test set molecules (Table 2).

Table 2 .
Unicolumn statistics of the training and test sets for QSAR models.

Table 3 .
Statistical results of 3D-QSAR model generated by forward stepwise variable selection kNN MFA method for indol-2-yl ethanones derivatives.
H_1348 (0.255712, 0.27929) 2. S_1366 (-0.009408, -0.003614)The observed, predicted activities for IDO inhibitory activities against IDO enzyme of both training & test sets molecules are given in Table 1.The plots of observed versus predicted activity of both training & test sets molecules helped in cross-validation of kNN-MFA QSAR model are depicted in Figure 2.