• Bulletin of the Korean Chemical Society
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• v.35 no.7
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• pp.2097-2108
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• 2014

Chemical feature based quantitative pharmacophore models were generated using the HypoGen module implemented in DS2.5. The best hypothesis, Hypo1, which was characterized by the highest correlation coefficient (0.96), the highest cost difference (61.60) and the lowest RMSD (0.74), consisted of one hydrogen bond acceptor, one hydrogen bond donor, one hydrophobic and one ring aromatic. The reliability of Hypo1 was validated on the basis of cost analysis, test set, Fischer's randomization method and GH test method. The validated Hypo1 was used as a 3D search query to identify novel inhibitors. The screened molecules were further refined by employing ADMET, docking studies and visual inspection. Three compounds with novel scaffolds were selected as the most promising candidates for the designing of Mcl-1 antagonists. Finally, a 10 ns molecular dynamics simulation was carried out on the complex of receptor and the retrieved ligand to demonstrate that the binding mode was stable during the MD simulation.

• Bulletin of the Korean Chemical Society
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• v.28 no.4
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• pp.561-566
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• 2007

Adenosine kinase (AK) is a ubiquitous intracellular enzyme, which catalyzes the phosphorylation of adenosine (ADO) to adenosine monophosphate (AMP). AK inhibitors have therapeutic potential as analgesic and antiinflammatory agents. A chemical feature based pharmacophore model has been generated from known AK inhibitors (26 training set compounds) by HypoGen module implemented in CATALYST software. The top ranked hypothesis (Hypo1) contained four features of two hydrogen-bond acceptors (HBA) and two hydrophobic aromatics (Z). Hypo1 was validated by 124 test set molecules with a correlation coefficient of 0.905 between experimental and estimated activity. It was also validated by CatScramble method. Thus, the Hypo1 was exploited for searching new lead compounds over 238,819 chemical compounds in NCI database and then the selected compounds were screened based on restriction estimated activity and Lipinski's rules to evaluate their drug-like properties. Finally we could obtain 72 new lead candidates and the two best compound structures from them were posted.

• Bulletin of the Korean Chemical Society
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• v.29 no.3
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• pp.656-662
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• 2008

Antagonists of the d -opioid receptor are effective in overcoming resistance against analgesic drugs such as morphine. To identify novel antagonists of the d -opioid receptor that display high potency and low resistance, we performed 3D-QSAR analysis using chemical feature-based pharmacophore models. Chemical features for d -opioid receptor antagonists were generated using quantitative (Catalyst/HypoGen) and qualitative (Catalyst/HipHop) approaches. For HypoGen analysis, we collected 16 peptide and 16 non-peptide antagonists as the training set. The best-fit pharmacophore hypotheses of the two antagonist models comprised identical features, including a hydrophobic aromatic (HAR), a hydrophobic (HY), and a positive ionizable (PI) function. The training set of the HipHop model was constructed with three launched opioid drugs. The best hypothesis from HipHop included four features: an HAR, an HY, a hydrogen bond donor (HBD), and a PI function. Based on these results, we confirm that HY, HAR and PI features are essential for effective antagonism of the d -opioid receptor, and determine the appropriate pharmacophore to design such antagonists.

• Bulletin of the Korean Chemical Society
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• v.31 no.11
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• pp.3333-3340
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• 2010

A three dimensional pharmacophore model was generated for the molecules which are responsible for anti-inflammatory activities targeting Interleukin-2 inducible tyrosine kinase (Itk). 16 structurally diverse molecules were selected as training set to generate the hypotheses using Discovery Studio v2.1. The best hypothesis, Hypo1, comprises two hydrogen bond acceptor (HBA), one hydrophobic aromatic (HA), one ring aromatic (RA) and shows high cost difference (63.71), high correlation coefficient (0.97) as well as low RMS deviation (0.81). Hypo1 has been further validated toward a test set, decoy set and Fischer's randomization method. Furthermore, Hypo1 was used to screen NCI and Maybridge databases. Finally, 2 hit molecules were identified as potential leads against Itk, which may be useful for future drug development.

• Bulletin of the Korean Chemical Society
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• v.28 no.2
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• pp.200-206
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• 2007

Pharmacophore models for lymphocyte-specific protein tyrosine kinase (P56 LCK) were developed using CATALYST HypoGen with a training set comprising of 25 different P56 LCK inhibitors. The best quantitative pharmacophore hypothesis comprises of one hydrogen bond acceptor, one hydrogen bond donor, one hydrophobic aliphatic and one ring aromatic features with correlation coefficient of 0.941, root mean square deviation (RMSD) of 0.933 and cost difference (null cost-total cost) of 66.23. The pharmacophore model was validated by two methods and the validated model was further used to search databases for new compounds with good estimated LCK inhibitory activity. These compounds were evaluated for their binding properties at the active site by molecular docking studies using GOLD software. The compounds with good estimated activity and docking scores were evaluated for physiological properties based on Lipinski's rules. Finally 68 compounds satisfied all the properties required to be a successful inhibitor candidate.

• Bulletin of the Korean Chemical Society
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• v.31 no.1
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• pp.52-58
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• 2010

Human histamine H1 receptor (HHR1) is a G protein-coupled receptor and a primary target for antiallergic therapy. Here, the ligand-based three-dimensional pharmacophore models were built from a set of known HHR1 inverse agonists using HypoGen module of CATALYST software. All ten generated pharmacophore models consist of five essential features: hydrogen bond acceptor, ring aromatic, positive ionizable and two hydrophobic functions. Best model had a correlation coefficient of 0.854 for training set compounds and it was validated with an external test set with a high correlation value of 0.925. Using this model Maybridge database containing 60,000 compounds was screened for potential leads. A rigorous screening for drug-like compounds unveiled RH01692 and SPB00834, two novel molecules for HHR1 with good CATALYST fit and estimated activity values. The new lead molecules were docked into the active site of constructed HHR1 homology model based on recently crystallized squid rhodopsin as template. Both the hit compounds were found to have critical interactions with Glu177, Phe432 and other important amino acids. The interpretations of this study may effectively be deployed in designing of novel HHR1 inverse agonists.