Structure based docking and molecular dynamics studies: Peroxisome proliferator-activated receptors –α/γ dual agonists for treatment of metabolic disorders

Molecular dynamics articulated multilevel virtual screening protocol to discover novel dual PPAR α/γ agonists for anti-diabetic and metabolic applications

PPARα and PPARγ are isoforms of the nuclear receptor superfamily which regulate glucose and lipid metabolism. Activation of PPARα and PPARγ receptors by exogenous ligands could transactivate the expression of PPARα and PPARγ-dependent genes, and thereby, metabolic pathways get triggered, which are helpful to ameliorate treatment for the type 2 diabetes mellitus, and related metabolic complications. Herein, by understanding the structural requirements for ligands to activate PPARα and PPARγ proteins, we developed a multilevel in silico-based virtual screening protocol to identify novel chemical scaffolds and further design and synthesize two distinct series of glitazone derivatives with advantages over the classical PPARα and PPARγ agonists. Moreover, the synthesized compounds were biologically evaluated for PPARα and PPARγ transactivation potency from nuclear extracts of 3T3-L1 cell. Furthermore, glucose uptake assay on L6 cells confirmed the potency of the synthesized compounds toward glucose regulation. Percentage lipid-lowering potency was also assessed through triglyceride estimate from 3T3-L1 cell extracts. Results suggested the ligand binding mode was in orthosteric fashion as similar to classical agonists. Thus molecular docking and molecular dynamics (MD) simulation experiments were executed to validate our hypothesis on mode of ligands binding and protein complex stability. Altogether, the present study developed a newer protocol for virtual screening and enables to design of novel glitazones for activation of PPARα and PPARγ-mediated pathways. Accordingly, present approach will offer benefit as a therapeutic strategy against type 2 diabetes mellitus and associated metabolic complications.

Structure based drug design and fragment based approach to identify potential methotrexate analogues as dual inhibitors for management of psoriasis

Psoriasis is characterized as chronic inflammatory disorder of skin having unregulated hyperproliferation and shedding of plaques. As per first line treatment methotrexate is the most widely used cytotoxic drug for psoriasis. It shows anti-proliferative effect with hDHFR while anti-inflammatory and immunosuppressive action is due to AICART. Serious hepatotoxic effects are recognized with long-term treatment of methotrexate. In this study, in silico technique is used in this work to find Dual-Acting Methotrexate-like molecules with increased efficacy and decreased toxicity. Structure-based virtual screening assisted by a fragment-based method against a library of chemicals that are similar to methotrexate revealing 36 and 27 potential inhibitors of hDHFR and AICART respectively. Further, based on dock score, binding energy, molecular interactions, and ADME/T analysis compound 135565151 was chosen for dynamic stability evaluation. Overall, these findings provided information on possible methotrexate analogues for the treatment of psoriasis that had lower hepatotoxicity.Communicated by Ramaswamy H. Sarma.

Review of in silico studies dedicated to the nuclear receptor family: Therapeutic prospects and toxicological concerns

Being in the center of both therapeutic and toxicological concerns, NRs are widely studied for drug discovery application but also to unravel the potential toxicity of environmental compounds such as pesticides, cosmetics or additives. High throughput screening campaigns (HTS) are largely used to detect compounds able to interact with this protein family for both therapeutic and toxicological purposes. These methods lead to a large amount of data requiring the use of computational approaches for a robust and correct analysis and interpretation. The output data can be used to build predictive models to forecast the behavior of new chemicals based on their in vitro activities. This atrticle is a review of the studies published in the last decade and dedicated to NR ligands in silico prediction for both therapeutic and toxicological purposes. Over 100 articles concerning 14 NR subfamilies were carefully read and analyzed in order to retrieve the most commonly used computational methods to develop predictive models, to retrieve the databases deployed in the model building process and to pinpoint some of the limitations they faced.

Molecular dynamics simulation and free energy calculation studies of Coagulin L as dipeptidyl peptidase-4 inhibitor

Plant derived product can be used as other alternatives to currently used drugs for controlling chronic diseases like Diabetes mellitus. The potential of Coagulin L (a constituent of Withania coagulans) as dipeptidyl peptidase-4 (DPP-4) inhibitor was evaluated by molecular modelling study. It was observed that amino acid residues such as Glu205, Glu206, Tyr 547, His 740, and Try662 interacts with Coagulin L and Saxagliptin (a known DPP-4 inhibitor). Other nonbonded interactions of Coagulin L and Saxagliptin with DPP-4 binding residues were also found similar. The docking energy of Coagulin L was found to be -7.69 Kcal/mol whereas -8.44 kcal/mol was recorded for Saxagliptin. MD simulation study revealed stable binding throughout 100 ns simulation. RMSD plot of the complex was stabilized in 43 ns and remained stable during entire simulation(100 ns). RMSF plot of DPP-4 Coagulin L interaction showed major fluctuations at residue 246 and 766, however, Arg 125, Glu 205, Ser 209 and His 740 showed no major perturbations. Principal Component Analysis showed that important dynamics of the protein remain unchanged during entire simulation since the non-polar, van der waals, ionic interaction and solvation energy, altogether play important role in the complex stability. The molecular modelling study of DPP-4 with Coagulin L was an effort to establish correlation with traditional practices of Withania coagulans as antidiabetic agent in Indian subcontinent.Communicated by Ramaswamy H. Sarma.

In silico strategies for probing novel DPP-IV inhibitors as anti-diabetic agents

Identification of new DPP-IV inhibitors by integrating validated in silico approach is being presented herein. Novel hits were identified by combining pharmacophore and structure based virtual screening of ZINC and Knowledge Base in house database followed by ADME profiling, consensus docking studies. Six potential hits were identified and analysed for their synthetic accessibility score, novelty analysis and pan assay interference compounds filtration. Out of six, three hits viz., ZINC25060187, ZINC53746227 and KB-10 were analysed for stability studies using Molecular Mechanics/Generalized Born Surface Area (MM/GBSA) and Molecular Dynamics (MD) simulation. The simulation studies of the identified hits revealed that these hits have good selectivity and stability in DPP-IV binding pocket. Important interactions with amino acids viz., Tyr547, Glu205 and Glu206 similar to co-crystallized ligand were also observed. One of the hits viz., KB-10 was synthesized and evaluated for its biological potential. The compound KB-10 showed good DPP-IV inhibition in both in vitro and in vivo studies with IC₅₀: 22.69 µM. This study supports the fact that these techniques hold potential for efficient screening of compounds with unknown affinity for DPP-IV that could serve as candidates for therapeutic development.Communicated by Ramaswamy H. Sarma.

Structure-based drug design of peroxisome proliferator-activated receptor gamma inhibitors: ferulic acid and derivatives

Peroxisome proliferator-activated receptor gamma (PPARγ), ligand-activated transcription factor, is a key modulator of genes considered in diabetes development as well as treatment. Adipogenesis differentiation through PPARγ, CCAAT-enhancer protein alpha (C/EBPα) is identified as a critical mechanism in fat accumulation and weight gain. Polyphenols studied against adipocyte differentiation is taken up for consistent support and drug discovery. Structure-based drug design found useful to distinguish the underlying mechanism of receptor-ligand interaction and function. In this work, phenolic acids, ferulic acid and its derivatives are used as ligands. Molecular parameters have been set to filter and sort the 34 derivatives from ZINC and PubChem databases. Besides, for affinity and activity identification, troglitazone and resveratrol co-crystallized ligands have been studied. Absorption, distribution, metabolism, elimination and toxicity, density functional theory, highest occupied molecular orbital-lowest unoccupied molecular orbital values and docking scores define the drug candidate as a potential inhibitor. Residues Ser 342 and Arg 280 bind with the ligands by forming hydrogen bonds and hydrophobic contacts. Based on the docking score, pharmacophore properties and functional energy values of the top six compounds are chosen for molecular dynamics and simulation. Consistency and stability maintained throughout the simulation up to 50 ns were observed. Free binding energy values and standard deviation of receptor and ligand calculated using molecular mechanics-generalized Born and surface area solvation method (MM_GBSA) is found significant. Therefore, ferulic acid derivatives and phenolic acids could be a potential inhibitor for adipocyte differentiation and lipid accumulation.Communicated by Ramaswamy H. Sarma.