Gaurao V. Dhoke

p38 Mitogen-Activated Protein Kinase Inhibitors: A Review on Pharmacophore Mapping and QSAR Studies

p38 mitogen-activated protein (MAP) kinases are the serine/threonine protein kinases, which play a vital role in cellular responses to external stress signals. p38 MAP kinase inhibitors have shown anti-inflammatory effects in the preclinical disease models, primarily through inhibition of the expression of inflammatory mediators. A number of structurally diverse p38 MAP kinase inhibitors have been developed as potential anti-inflammatory agents. Most of the inhibitors have failed in the clinical trials either due to poor pharmacokinetic profile or selectivity issue, which makes p38 MAP kinase a promising target for molecular modelling studies. Several quantitative structure activity relationships (QSAR) and pharmacophore models have been developed to identify the structural requirements essential for p38 MAP kinase inhibitory activity. In this review, we provide an overview of the presently known p38 MAP kinase inhibitors and how QSAR analyses among series of compounds have led to the development of molecular models and pharmacophores, allowing the design of novel inhibitors.

Identification of p38α MAP kinase inhibitors by pharmacophore based virtual screening.

The p38α mitogen-activated protein (MAP) kinase plays a vital role in treating many inflammatory diseases. In the present study, a combined ligand and structure based pharmacophore model was developed to identify potential DFG-in selective p38 MAP kinase inhibitors. Conformations of co-crystallised inhibitors were used in the development and validation of ligand and structure based pharmacophore modeling approached. The validated pharmacophore was utilized in database screening to identify potential hits. After Lipinskis rule of five filter and molecular docking analysis, nineteen hits were purchased and selected for in vitro analysis. The virtual hits exhibited promising activity against tumor necrosis factor-α (TNF-α) with 23-98% inhibition at 10μM concentration. Out of these seven compounds has shown potent inhibitory activity against p38 MAP kinase with IC50 values ranging from 12.97 to 223.5nM. In addition, the toxicity study against HepG2 cells was also carried out to confirm the safety profile of identified virtual hits.

3D QSAR pharmacophore-based virtual screening and molecular docking studies to identify novel matrix metalloproteinase 12 inhibitors

Matrix metalloproteinase 12 (MMP-12) is a potential therapeutic target for the treatment of chronic obstructive pulmonary disorder and other inflammatory disorders. Ligand-based 3D QSAR pharmacophore modelling approach was employed to reveal structural and chemical features necessary for the inhibition of MMP-12. The best HypoGen pharmacophore model Hypo1 for MMP-12 inhibitors contains two hydrogen bond acceptors, one hydrophobic aliphatic and one hydrophobic aromatic feature. Molecular docking studies of all inhibitors showed hydrogen bond interactions with important amino acids (Glu219, Ala182 and Leu181), and these interactions were compared with Hypo1, which shows that the Hypo1 has a good predictive ability. The best pharmacophore hypothesis was further cross-validated using test set, decoy set and Cat-Scramble methodology. The validated pharmacophore model Hypo1 was used for screening the chemical databases of small compounds, including Specs, NCI and ChemDiv, to identify the new compounds that are presumably able to act as MMP-12 inhibitors. The screened virtual hits from Hypo1 were subjected to several filters such as toxicity, quantitative estimation of drug-likeness and molecular docking analysis. Finally, four novel compounds with diverse scaffolds were selected as possible candidates for the designing of potent MMP-12 inhibitors.

Structure based virtual screening to identify selective phosphodiesterase 4B inhibitors

Phosphodiesterase 4 (PDE4), is a hydrolytic enzyme, is proposed as a promising target in asthma and chronic obstructive pulmonary disease. PDE4B selective inhibitors are desirable to reduce the dose limiting adverse effect associated with non-selective PDE4B inhibitors. To achieve this goal, ligand based pharmacophore modeling and molecular docking approach is employed. Pharmacophore hypotheses for PDE4B and PDE4D are generated using HypoGen algorithm. The best PDE4B pharmacophore hypothesis (Hypo1_PDE4B) consist of one hydrogen-bond acceptor and two ring aromatic features, whereas PDE4D pharmacophore hypothesis (Hypo1_PDE4D) consist of one hydrogen-bond acceptor, one hydrophobic aliphatic, and two ring aromatic features. The validated pharmacophore hypotheses are used in virtual screening to identify selective PDE4B inhibitors. The hits were screened for their estimated activity, FitValue, and quantitative estimation of drug likeness. After molecular docking analysis, ten hits were purchased for in vitro analysis. Out of these, six hits have shown potent and selective inhibitory activity against PDE4B with IC50 values ranging from 2 to 378nM.

Identification of dual Acetyl-CoA carboxylases 1 and 2 inhibitors by pharmacophore based virtual screening and molecular docking approach

Acetyl-CoA carboxylase (ACC) is a crucial metabolic enzyme that plays a vital role in obesity-induced type 2 diabetes and fatty acid metabolism. To identify dual inhibitors of Acetyl-CoA carboxylase1 and Acetyl-CoA carboxylase2, a pharmacophore modelling approach has been employed. The best HypoGen pharmacophore model for ACC2 inhibitors (Hypo1_ACC2) consists of one hydrogen bond acceptor, one hydrophobic aliphatic and one hydrophobic aromatic feature, whereas the best pharmacophore (Hypo1_ACC1) for ACC1 consists of one additional hydrogen-bond donor (HBD) features. The best pharmacophore hypotheses were validated by various methods such as test set, decoy set and Cat-Scramble methodology. The validated pharmacophore models were used to screen several small-molecule databases, including Specs, NCI, ChemDiv and Natural product databases to identify the potential dual ACC inhibitors. The virtual hits were then subjected to several filters such as estimated

A combined ligand and structure based approach to design potent PPAR-alpha agonists

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A combined pharmacophore modeling, 3D-QSAR and molecular docking study of substituted bicyclo-[3.3.0]oct-2-enes as liver receptor homolog-1 (LRH-1) agonists

value, quantitative estimation of drug-likeness and molecular docking analysis. Finally, three novel compounds with diverse scaffolds were selected as potential starting points for the design of novel dual ACC inhibitors.

Structure based de novo design of IspD inhibitors as anti-tubercular agents

Cytochrome bc1 (EC 1.10.2.2, bc1) is an essential component of the cellular respiratory chain, which catalyzes electron transfer from quinol to cytochrome c and concomitantly the translocation of protons across the membrane. It has been identified as a promising target in malaria parasites. The structure-based pharmacophore modelling and molecular dynamic simulation approach have been employed to identify novel inhibitors of cytochrome bc1. The best structure-based pharmacophore hypothesis (Hypo1) consists of one hydrogen bond acceptor (HBA), one general hydrophobic (HY), and two hydrophobic aromatic features (HYAr). Further, hydrogen interactions and hydrophobic interactions of known potent inhibitors with cytochrome bc1 were compared with Hypo1, which showed that the Hypo1 has good predictive ability. The validated Hypo1 was used to screen the chemical databases. The hits obtained were subsequently subjected to the molecular docking analysis to identify false-positive hits. Moreover, the molecular docking results were further validated by molecular dynamics simulations. Binding-free energy analysis using MM-GBSA method reveals that the van der Waals interactions and the electrostatic energy provide the basis for favorable absolute free energy of the complex. The five virtual hits were identified as possible candidates for the designing of potent cytochrome bc1 inhibitors.