Virtual screening of RAGE inhibitors using molecular docking

Advanced Glycation End products (AGEs) interaction with Receptor for AGEs (RAGE) activates downstream signaling and evokes inflammatory responses in vascular cells. Therefore, it is of interest to design a novel series of molecules with a library of 352 compounds based on natural Isoflavone and Argpyrimidine moities. The compounds screened against the optimized structure of RAGE (PDB code: 3CJJ) using MolDock aided with molecular docking algorithm. This exercise identified compound number 62 with appreciable ADME properties having no toxicity and pharmacophore features. Therefore, compound 62 identified as a RAGE inhibitor is proposed for further validation in the context of Diabetic Retinopathy (DR) and vascular complications.

©2016 as MGO scavengers. These compounds have been designed by fusing key structural moieties of Isoflavones and Argpyrimidines.
In order to assess the pharmacological efficiency of our proposed compounds we compared them with established inhibitors like PF-04494700 (Pfizer) and 4-fluorophenoxy analogs developed by Han et al. 2014 (specifically analogue 39 [5-(4-(4-(trifluoromethyl)

Detection of active site:
Extensive literature mining was done in order to deduce the active site in the protein (12)(13)(14)(15). Further, the volumetric and surface area descriptors of the active site ( Table 1) were calculated using Gaussian filter based DOG site finder [16]. The detected cavity in the RAGE receptor is shown in Figure 2.

Molecular docking of compounds:
Molegro Virtual Docker 2010.4.0, a Molecular docking program provides a flexible platform for docking and predicting how the molecules interact with protein receptor. The structure, based virtual screening of the compounds was based on rerank score, a mathematical representation for ligand-protein affinity which is based on MolDock scoring function (MolDock Score) derived from the Piecewise Linear Potential (PLP) scoring functions [17]. Further, the total energy was minimized using Nelder Mead Simplex Minimization (using non-grid force field and H bond directionality) [18]. Based on the internal electrostatic, hydrogen bond interactions and sp2-sp2 torsions binding affinity and receptor interactions with the compound were evaluated. Best compound with highest binding affinity against RAGE protein was selected as a function of rerank score.

Bioactivity and ADMET profiling of compounds:
Drug-likeness of the compounds was screened by Lipinski filters. Molinspiration webserver (© Molinspiration Cheminformatics 2014) was used to predict the biological activity of ligands. LC50 was predicted using T.E.S.T. Version 4.1 (2012, U.S. Environmental Protection Agency) software. The complete ADMET properties were calculated using ADMETSAR [19]. LAZAR server was used to predict the mutagenic and carcinogenic potential of the compounds [20].

Results & Discussion:
Top four compounds with best affinity along with established inhibitors Pfizer (PF-04494700) ( Figure 3A), 4-fluorophenoxy analogs 39 ( Figure 3B) and 40 ( Figure 3C) against RAGE is shown in Table 2. Evident from the re-rank scores compound 62 ( Figure 3D) shows highest binding affinity in comparison to all the designed compounds towards RAGE. Compound 62 showed almost 1.3 folds higher affinity than Pfizer (PF-04494700) and almost 1.20 and 1.24 folds better affinity than4fluorophenoxy analogs 39 and 40 respectively. From the docking scores, therefore, it can be well assumed that compound 62 can form a high affinity candidate against RAGE receptor surpassing the binding efficiency of established inhibitors discovered hitherto.
In the further perusal, the pursuit was to reveal the rationale behind superior binding profile of compound 62 which can be deduced from the energy contributing descriptors of receptorligand interactions (as shown in Table 3). Apparent from the docking profile of interaction energy values the descriptors; external ligand interactions contribute 4.9 folds higher stability than internal ligand interactions. Further external ligand interactions were stabilized mostly by steric energy guided by piecewise linear potentials. While in internal ligand interactions, it's the torsional strain contributes to the stability of the ligand receptor interactions. In the next step, best-docked compounds 62 and 326 were tested for their ADMET properties. As shown in Table 4, both the compounds demonstrated to be safe showing noncarcinogenic and non-mutagenic property in different cell lines. In addition the LC50 values of both the best docked proposed compounds were appreciably less than all the established compounds viz. Pfizer (PF-04494700) and 4fluorophenoxy analogs 39 and 40. As elaborated in Table 5, the compounds proposed, in addition to non-toxic property, are also endowed with excellent absorption, distribution, metabolic and excretion profiles.
Poor oral absorption and lower solubility have always been a concern in the drug development process. In the present study, we tested; the absorption and solubility parameters of the 62 and 326 considering aqueous solubility and important partition co-efficients some of them being hexadecane/gas, octanol/gas and partition co-efficients (Table 6). Interestingly, both the compounds fall in the allowed range of solubility as predicted for 95% of all the FDA approved drugs.  Table 4: In silico toxicity testing of compound in different cell lines for carcinogenic and mutagenenic property using LAZAR online server. All compounds screened in the study was found to be non carcinogenic (denoted as NC) and Non-Mutagenic (dented as NM).
Compound 62 proposed in the study show least LC 50 value implying far better non -toxicity profile than all the compounds analyzed in the study.    Owing to optimal affinity, high inhibitory activity and nontoxicity of 62, it was further analyzed for pharmacophoric mappings. Comprehensively shown in Figure 4,