• Bulletin of the Korean Chemical Society
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• v.33 no.9
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• pp.2930-2936
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• 2012

A three-dimensional pharmacophore hypothesis was developed for atypical antipsychotics in order to map common structural features of highly active compounds by using HipHop in CATALYST program. The pharmacophore hypotheses were generated using 12 compounds as training set and validated using 11 compounds as test set. The most predictive hypothesis (Hypo1) comprises five features viz. two hydrophobic regions, two hydrogen bond acceptor lipid and one aromatic ring. In the absence of information like crystallized structure of 5-$HT_{2A}$ receptor and binding mode of antipsychotics with 5-$HT_{2A}$ receptor, this hypothesis will serve as a potentially valuable tool in the design of novel atypical antipsychotics acting primarily at 5-$HT_{2A}$ and $D_2$ receptors.

• 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.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.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.34 no.7
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• pp.1972-1984
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• 2013

Microtubules play an important role in intracellular transport, mobility, and particularly mitosis. Paclitaxel (Taxol$^{TM}$) and paclitaxel-like compounds have been shown to be anti-tumor agents useful for various human tumors. Paclitaxel-like compounds operate by stabilizing microtubules through interface binding at the interface between two ${\beta}$-tubulin monomers in adjacent protofilaments. In this paper we present the elucidation of the structural features of paclitaxel and paclitaxel-like compounds (e.g., epothilones) with microtubule stabilizing activities, and relate their activities to spatial and chemical features of the molecules. CATALYST program was used to generate three-dimensional quantitative structure activity relationships (3D-QSARs) resulting in 3D pharmacophore models of epothilone- and paclitaxel-derivatives. Pharmacophore models were generated from diverse conformers of these compounds resulting in a high correlation between experimental and predicted biological activities (r = 0.83 and 0.91 for epothilone and paclitaxel derivatives, respectively). On the basis of biological activities of the training sets, five- and four-feature pharmacophore hypotheses were generated in the epothilone and paclitaxel series. The validation of generated hypotheses was achieved by using twelve epothilones and ten paclitaxels, respectively, which are not in the training sets. The clustering (grouping) and merging techniques were used in order to supplement spatial restrictions of each of hypothesis and to develop more comprehensive models. This approach may be of use in developing novel inhibitor candidates as well as contributing a better understanding of structural characters of many compounds useful as anticancer agents targeting microtubules.

• Bulletin of the Korean Chemical Society
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• v.30 no.5
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• pp.1152-1156
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• 2009

Silent information regulator 2 (Sir2) or sirtuins are NAD(+)-dependent deacetylases, which hydrolyze the acetyllysine residues. In mammals, sirtuins are classified into seven different classes (SIRT1-7). SIRT1 was reported to be involved in age related disorders like obesity, metabolic syndrome, type II diabetes mellitus and Parkinson’s disease. Activation of SIRT1 is one of the promising approaches to treat these age related diseases. In this study, we have used HipHop module of CATALYST to identify a series of pharmacophore models to screen SIRT1 enhancing molecules. Three molecules from Sirtris Pharmaceuticals were selected as training set and 607 sirtuin activator molecules were used as test set. Five different hypotheses were developed and then validated using the training set and the test set. The results showed that the best pharmacophore model has four features, ring aromatic, positive ionization and two hydrogen-bond acceptors. The best hypothesis from our study, Hypo2, screened high number of active molecules from the test set. Thus, we suggest that this four feature pharmacophore model could be helpful to screen novel SIRT1 activator molecules. Hypo2-virtual screening against Maybridge database reveals seven molecules, which contains all the critical features. Moreover, two new scaffolds were identified from this study. These scaffolds may be a potent lead for the SIRT1 activation.