In silico identification of prolyl hydroxylase inhibitor by per-residue energy decomposition-based pharmacophore approach.

Hypoxia is an effective preconditioning stimulus and many cellular responses to hypoxia are mediated through a transcription control complex termed the hypoxia-inducible factor (HIF). The stability and activation of HIF are governed by HIF prolyl-4-hydroxylases 2 (PHD2). Hence, the development of a small molecule inhibitor for prolyl hydroxylase has been suggested as a potentially useful therapeutic strategy for the treatment of oxidative/ischemic stress conditions. Thus, to unveil a novel human PHD2 inhibitor, a custom-based virtual screening was carried out to identify the potential inhibitors against PHD2 based on; (1) the per-residue energy decomposition (PRED)-based pharmacophore model, (2) molecular docking, and (3) MD approaches. The PRED analysis was performed to identify the common interaction pattern of HIF fragment (5L9B) and crystallized ligand (4JZR) to develop a relevant accurate allosteric pharmacophore model. The custom pharmacophore model (AAARR) was developed and further used to screen multiple databases. The docking was performed as a secondary strategy for screening the pharmacophore hits. Furthermore, the docked complexes were screened by molecular dynamics (MD) simulation and molecular mechanics/generalized Born surface area (MM-GBSA) based binding free energy calculations to determine the binding energy of the inhibitors and to identify crucial interaction energy fingerprint. One hit has demonstrated good binding free energy and a better binding affinity for PHD2 compared to the other four selected ligands. Thus, the results obtained from pharmacophore, docking, and MD simulations depicted that linker length and metal binding in the scaffold could be effectively used as a potent inhibitor toward human PHD2 in AD therapeutics.

In silico identification of hydantoin derivatives: a novel natural prolyl hydroxylase inhibitor.

Alzheimer's disease (AD) is the most common dementia in late life memory related issues. It is estimated that worldwide 46.8 million people suffer from dementia. The hypoxia inducible factor (HIF) upregulation could be a potential neuroprotective strategy by modulating the multiple survival pathways in AD. Hence, the development of small molecules that induce HIF-α activation via inhibition of prolyl hydroxylase enzyme (PHD) has been suggested as a potentially useful therapeutic strategy for the treatment of AD. Thus, to unveil a novel human PHD inhibitor, 2D-QSAR (Quantitative Structure Activity Relationship) modeling was performed with the 213 PHD inhibitors reported in the USA patent database. Best model with the r2 score of 0.8273 and q2 value of 0.8284 with dendritic fingerprint was developed and visualized by kernel partial least squares (KPLS) methods, which were used for visualization and screening of natural/derivative compounds database for novel and effective drug or scaffold. The docking was performed as a secondary strategy for screening the top 5000 compounds retrieved by 2D-QSAR based screening. Further, the docked complexes were screened by molecular dynamics (MD) simulation and molecular mechanics/generalized Born surface area (MM-GBSA) based binding free energy calculations to determine the binding energy of the inhibitors and to identify crucial interacting energy contributors. Three leads have demonstrated good binding free energy and the better binding affinity for PHD compared to other selected ligands. Thus, the results obtained from QSAR, docking and MD simulations depicted that hydantoin scaffold could be effectively used as a potent inhibitor toward human PHD in AD therapeutics.Communicated by Ramaswamy H. Sarma.

Ligand-based pharmacophore modeling and docking studies on vitamin D receptor inhibitors.

In recent years, pharmacophore modeling and molecular docking approaches have been extensively used to characterize the structural requirements and explore the conformational space of a ligand in the binding pocket of the selected target protein. Herein, we report a pharmacophore modeling and molecular docking of 45 compounds comprising of the indole scaffold as vitamin D receptor (VDR) inhibitors. Based on the selected best hypothesis (DRRRR.61), an atom-based three-dimensional quantitative structure-activity relationships model was developed to rationalize the structural requirement of biological activity modulating components. The developed model predicted the binding affinity for the training set and test set with R2(training) = 0.8869 and R2(test) = 0.8139, respectively. Furthermore, molecular docking and dynamics simulation were performed to understand the underpinning of binding interaction and stability of selected VDR inhibitors in the binding pocket. In conclusion, the results presented here, in the form of functional and structural data, agreed well with the proposed pharmacophores and provide further insights into the development of novel VDR inhibitors with better activity.

A Stilbenoid Isorhapontigenin as a Potential Anti-Cancer Agent against Breast Cancer through Inhibiting Sphingosine Kinases/Tubulin Stabilization.

Isorhapontigenin (ISO), a tetrahydroxylated stilbenoid, is an analog of resveratrol (Rsv). The various biological activities of Rsv and its derivatives have been previously reported in the context of both cancer and inflammation. However, the anti-cancer effect of ISO against breast cancer has not been well established, despite being an orally bioavailable dietary polyphenol. In this study, we determine the anti-cancer effects of ISO against breast cancer using MCF7, T47D, and MDA-MB-231 cell lines. We observed that ISO induces breast cancer cell death, cell cycle arrest, oxidative stress, and the inhibition of cell proliferation. Additionally, sphingosine kinase inhibition by ISO controlled tubulin polymerization and cancer cell growth by regulating MAPK/PI3K-mediated cell cycle arrest in MCF7 cells. Interestingly, SPHK1/2 gene silencing increased oxidative stress, cell death, and tubulin destabilization in MCF7 cells. This suggests that the anti-cancer effect of ISO can be regulated by SPHK/tubulin destabilization pathways. Overall, ISO successfully induced breast cancer cell death and cell growth arrest, suggesting this phytochemical is a better alternative for breast cancer treatment. Further studies in animal models could confirm the potency and usability of ISO over Rsv for targeting breast cancer, potentially posing an alternative candidate for improved therapy in the near future.

ß-N-oxalyl-L-α, ß- diaminopropionic acid induces HRE expression by inhibiting HIF-prolyl hydroxylase-2 in normoxic conditions.

Hypoxia inducible factor (HIF)-1α, a subunit of HIF transcription factor, regulates cellular response to hypoxia. In normoxic conditions, it is hydroxylated by prolyl hydroxylase (PHD)-2 and targeted for proteosomal degradation. Drugs which inhibit PHD-2 have implications in conditions arising from insufficient blood supply. ß-ODAP (ß-N- oxalyl-L-α, ß- diaminopropionic acid), a non-protein excitatory amino acid present in Lathyrus sativus, is an α-amino-3-hydroxy-5-methyl-4-isoxazole propionic acid receptor agonist known to activate conventional protein kinase C and stabilize HIF-1α under normoxic conditions. However, the mechanism of HIF-1α stabilization by this compound is unknown. In silico approach was used to understand the mechanism of stabilization of HIF-1α which revealed ß-ODAP interacts with key amino acid residues and Fe2+ at the catalytic site of PHD-2. These results were further corroborated with luciferase HRE (hypoxia response element) reporter system in HeLa cells. Different chemical modulators of PHD-2 activity and HIF-1α levels were included in the study for comparison. Results obtained indicate that ß-ODAP inhibits PHD-2 and facilitates HIF dependent HRE expression and hence, might be helpful in conditions arising from hypoxia.

Computational repositioning and experimental validation of approved drugs for HIF-prolyl hydroxylase inhibition.

HIF stability and activation are governed by a family of dioxygenases called HIF prolyl-4-hydroxylases (PHDs). It has been identified as a new target to augment the adaptive machinery that governs cytoprotection in disorders associated with ischemia/reperfusion, inflammation, and oxidative stress. In this sense, PHD inhibition has been proposed to mimic, at least in part, the protective effects of exposure to hypoxia. Exploiting drug polypharmacology to identify novel modes of actions for drug repurposing has gained significant attention in the current era of weak drug pipelines. The present work plan aims at giving new purpose to some well-established FDA-approved drugs. Here, we propose that by combining the literature survey, docking, and manual interpretation altogether, we were able to perform virtual screening on FDA-approved drugs to identify potential PHD inhibitors. Upon screening of 1537 marketed drugs, a final set of six hits were selected for experimental testing. All six drugs were divers, and immuno blotting was carried out to evaluate their ability to upregulate HIF in order to validate our hypothesis. Out of the six, three drugs showed significant upregulation of HIF possibly by inhibiting the PHD. It is believed that the appropriate use of the literature survey, docking, manual interpretation, and experimental validation strategy in the drug design process should improve the ability to identify hits and confirm their potential to serve as basis for drug repurposing.

A combination of 3D-QSAR modeling and molecular docking approach for the discovery of potential HIF prolyl hydroxylase inhibitors.

Suppression of HIF prolyl hydroxylase (PHD) activity by small molecule inhibitors leads to the stabilization of HIF and offers a potential therapeutic option for treating ischemic disorders. In this study, pharmacophore based QSAR modeling, virtual screening and molecular docking approaches were concurrently used to identify target-specific PHD inhibitors with better ADME properties and to readily minimize false positives and false negatives. A 3D-QSAR based method was used to generate a pharmacophore hypothesis (AAAN). The obtained 3D-QSAR model has an excellent correlation coefficient value (r2 = 0.99), Fisher ratio (F = 386) and exhibited good predictive power (q2 = 0.64). The hypothesis was validated and utilized for chemical database screening and the retrieved compounds were subjected to molecular docking for further refinement. Quantitative AAAN hypothesis comprised three H-bond accepter and one negative ionizable group feature and it give good predictive ability because all the QSAR information it was providing matched with the active site information. The hypothesis was validated and used as a 3D query for database screening. After manual selection, molecular docking and further refinement, based on the molecular interactions of inhibitors with the essential amino acids residues, 12 candidates with good ADME and blood brain barrier permeability values were selected as potential PHD inhibitors.

Pharmacophore generation and atom-based 3D-QSAR of N-iso-propyl pyrrole-based derivatives as HMG-CoA reductase inhibitors.

BACKGROUND: Coronary heart disease continues to be the leading cause of mortality and a significant cause of morbidity and account for nearly 30% of all deaths each year worldwide. High levels of cholesterol are an important risk factor for coronary heart disease. The blockage of 3-hydroxy-3-methylglutaryl-coenzyme A (HMG-CoA) reductase activity by small molecule inhibitors has been shown to inhibit hypercholesterolemia. Herein, we describe the development of effective and robust pharmacophore model and the structure-activity relationship studies of 43N-iso-propyl pyrrole-based derivatives previously reported for HMG-CoA reductase inhibition. RESULTS: A 5-point pharmacophore model was developed and the generated pharmacophore model was used to derive a predictive atom-based 3D quantitative structure-activity relationship analysis (3D-QSAR) model for the studied dataset. The obtained 3D-QSAR model has an excellent correlation coefficient value (r2 = 0.96) along with good statistical significance as shown by high Fisher ratio (F = 143.2). The model also exhibited good predictive power confirmed by the high value of cross validated correlation coefficient (q2 = 0.672). Further, pharmacophoric model was employed for virtual screening to identify four potential HMG-CoA reductase inhibitors. CONCLUSIONS: The QSAR model suggests that electron-withdrawing character is crucial for the HMG-CoA reductase inhibitory activity. In addition to the electron-withdrawing character, hydrogen bond--donating groups, hydrophobic and negative ionic groups positively contribute to the HMG-CoA reductase inhibition. These findings provide a set of guidelines for designing compounds with better HMG-CoA reductase inhibitory potential.

Computational identification of novel histone deacetylase inhibitors by docking based QSAR.

Histone deacetylases (HDACs) are enzymes that modify chromatin structure and contribute to aberrant gene expression in cancer. A series compounds with well-assigned HDAC inhibitory activity was used for docking based 3D-QSAR analysis. The 3D-QSAR acquired had excellent correlation coefficient value (q2=0.753) and high Fisher ratio (F=300.2). A validated pharmacophore model (AAAPR) was employed for virtual screening. After manual selection, molecular docking and further refinement, six compounds with good absorption, distribution, metabolism, and excretion (ADME) properties were selected as potential HDAC inhibitors. Further, the molecular interactions of these inhibitors with the HDAC active site residues were discussed in detail.

Pharmacophore generation and atom-based 3D-QSAR of novel quinoline-3-carbonitrile derivatives as Tpl2 kinase inhibitors.

Tumour progression locus-2 (Tpl2) is a serine/threonine kinase, which regulates the expression of tumour necrosis factor α. The article describes the development of a robust pharmacophore model and the investigation of structure-activity relationship analysis of quinoline-3-carbonitrile derivatives reported for Tpl2 kinase inhibition. A five point pharmacophore model (ADRRR) was developed and used to derive a predictive atom-based 3-dimensional quantitative structure activity relationship (3D-QSAR) model. The obtained 3D-QSAR model has an excellent correlation coefficient value (r(2)= 0.96), Fisher ratio (F = 131.9) and exhibited good predictive power (q(2) = 0.79). The QSAR model suggests that the inclusion of hydrophobic substituents will enhance the Tpl2 kinase inhibition. In addition, H-bond donating groups, negative ionic groups and electron withdrawing groups positively contribute to the Tpl2 kinase inhibition. Further, pharmacophoric model was validated by the receiver operating characteristic curve analysis and was employed for virtual screening to identify six potential Tpl2 kinase inhibitors. The findings of this study provide a set of guidelines for designing compounds with better Tpl2 kinase inhibitory potency.

Identification of novel potential HIF-prolyl hydroxylase inhibitors by in silico screening.

Suppression of HIF-prolyl hydroxylase (PHD) activity by small-molecule inhibitors leads to the stabilization of hypoxia inducible factor and has been recognized as promising drug target for the treatment of ischemic diseases. In this study, pharmacophore-based virtual screening and molecular docking approaches were concurrently used with suitable modifications to identify target-specific PHD inhibitors with better absorption, distribution, metabolism, and excretion properties and to readily minimize false positives and false negatives. A customized method based on the active site information of the enzyme was used to generate a pharmacophore hypothesis (AAANR). The hypothesis was validated and utilized for chemical database screening and the retrieved hit compounds were subjected to molecular docking for further refinement. AAANR hypothesis comprised three H-bond acceptor, one negative ionizable group and one aromatic ring feature. The hypothesis was validated using decoy set with a goodness of fit score of 2 and was used as a 3D query for database screening. After manual selection, molecular docking and further refinement based on the molecular interactions of inhibitors with the essential amino acid residues, 18 hits with good absorption, distribution, metabolism, and excretion (ADME) properties were selected as excellent PHD inhibitors. The best pharmacophore hypothesis, AAANR, contains chemical features required for the effective inhibition of PHD. Using AAANR, we have identified 18 potential and diverse virtual leads, which can be readily evaluated for their potency as novel inhibitors of PHD. It can be concluded that the combination of pharmacophore, molecular docking, and manual interpretation approaches can be more successful than the traditional approach alone for discovering more effective inhibitors.

Nanotechnology and nanomedicine: going small means aiming big.

Nanotechnology is an emerging branch of science for designing tools and devices of size 1 to 100 nm with specific function at the cellular, atomic and molecular levels. The concept of employing nanotechnology in biomedical research and clinical practice is best known as nanomedicine. Nanomedicine is an upcoming field that could potentially make a major impact to human health. Nanomaterials are increasingly used in diagnostics, imaging and targeted drug delivery. Nanotechnology will assist the integration of diagnostics/imaging with therapeutics and facilitates the development of personalized medicine, i.e. prescription of specific medications best suited for an individual. This review provides an integrated overview of application of nanotechnology based molecular diagnostics and drug delivery in the development of nanomedicine and ultimately personalized medicine. Finally, we identify critical gaps in our knowledge of nanoparticle toxicity and how these gaps need to be evaluated to enable nanotechnology to transit safely from bench to bedside.