Pharmacophore Modeling for Protein Tyrosine Phosphatase 1B Inhibitors

Bharatham, Kavitha,Bharatham, Nagakumar,Lee, Keun-Woo 대한약학회 2007 Archives of Pharmacal Research Vol.30 No.5

A three dimensional chemical feature based pharmacophore model was developed for the inhibitors of protein tyrosine phosphatase 1B (PTPIB) using the CATALYST software, which would provide useful knowledge for performing virtual screening to identify new inhibitors targeted toward type II diabetes and obesity. A dataset of 27 inhibitors, with diverse structural properties, and activities ranging from 0.026 to 600 ${\mu}$M, was selected as a training set. Hypo1, the most reliable quantitative four featured pharmacophore hypothesis, was generated from a training set composed of compounds with two H-bond acceptors, one hydrophobic aromatic and ore ring aromatic features. It has a correlation coefficient, RMSD and cost difference (null cost-total cost) of 0.945, 0.840 and 65.731 , respectively. The best hypothesis (Hypo1) was validated using four different methods. Firstly, a cross validation was performed by randomizing the data using the Caf-Scramble technique. The results confirmed that the pharmacophore models generated from the training set were valid. Secondly, a test set of 281 molecules was scored, with a correlation of 0.882 obtained between the experimental and predicted activities. Hypo1 performed well in correctly discriminating the active and inactive molecules. Thirdly, the model was investigated by mapping on two PTP1B inhibitors identified by different pharmaceutical Companies. The Hypo1 model Correctly Predicted these compounds as being highly active. Finally, decking simulations were performed on few compounds to substantiate the role of the pharmacophore features at the birding site of the protein by analyzing their binding conformations. These multiple validation approaches provided confidence in the utility of this phar-macophore model as a 3D query for virtual screening to retrieve new chemical entities showing potential as potent PTP1B inhibitors.

P56 LCK Inhibitor Identification by Pharmacophore Modelling and Molecular Docking

Bharatham, Nagakumar,Bharatham, Kavitha,Lee, Keun-Woo Korean Chemical Society 2007 Bulletin of the Korean Chemical Society Vol.28 No.2

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.

Molecular Docking Study of Aminoacyl-tRNA Synthetases with Ligand Molecules from Four Different Scaffolds

Bharatham, Nagakumar,Bharatham, Kavitha,Lee, Yu-No,Kim, Song-Mi,Lazar, Prettina,Baek, A-Young,Park, Chan-In,Eum, Hee-Sung,Ha, Hyun-Joon,Yun, Sae-Young,Lee, Won-Koo,Kim, Sung-Hoon,Lee, Keun-Woo Korean Chemical Society 2010 Bulletin of the Korean Chemical Society Vol.31 No.3

Aminoacyl-tRNA synthetases (aaRSs) play vital roles in protein biosynthesis of living organisms and are interesting antibacterial drug targets. In order to find out new inhibitor candidate molecules as antibacterial agent, the binding modes of the candidate molecules were investigated at the active sites of aaRSs by molecular docking study. The docking simulations were performed with 48 compounds from four different scaffolds into the eight different aaRSs. The results show that scaffolds 3 and 4 compounds have consistently better binding capabilities, specifically for HisRS (E. coli) and IleRS (S. aureus). The binding modes of the best compounds with the proteins were well compatible with those of two ligands in crystal structures. Therefore, we expect that the final compounds we present may have reasonable aaRS inhibitory activity.

Pharmacophore Modeling for Protein Tyrosine Phosphatase 1B Inhibitors

Kavitha Bharatham,이근우,Nagakumar Bharatham 대한약학회 2007 Archives of Pharmacal Research Vol.30 No.5

A three dimensional chemical feature based pharmacophore model was developed for the inhibitors of protein tyrosine phosphatase 1B (PTP1B) using the CATALYST software, which would provide useful knowledge for performing virtual screening to identify new inhibitors targeted toward type II diabetes and obesity. A dataset of 27 inhibitors, with diverse structural properties, and activities ranging from 0.026 to 600 µM, was selected as a training set. Hypo1, the most reliable quantitative four featured pharmacophore hypothesis, was generated from a training set composed of compounds with two H-bond acceptors, one hydrophobic aromatic and one ring aromatic features. It has a correlation coefficient, RMSD and cost difference (null cost-total cost) of 0.946, 0.840 and 65.731, respectively. The best hypothesis (Hypo1) was validated using four different methods. Firstly, a cross validation was performed by randomizing the data using the Cat-Scramble technique. The results confirmed that the pharmacophore models generated from the training set were valid. Secondly, a test set of 281 molecules was scored, with a correlation of 0.882 obtained between the experimental and predicted activities. Hypo1 performed well in correctly discriminating the active and inactive molecules. Thirdly, the model was investigated by mapping on two PTP1B inhibitors identified by different pharmaceutical companies. The Hypo1 model correctly predicted these compounds as being highly active. Finally, docking simulations were performed on few compounds to substantiate the role of the pharmacophore features at the binding site of the protein by analyzing their binding conformations. These multiple validation approaches provided confidence in the utility of this pharmacophore model as a 3D query for virtual screening to retrieve new chemical entities showing potential as potent PTP1B inhibitors.

Quantitative Structure-Activity Relationships and Molecular Docking Studies of P56 LCK Inhibitors

Bharatham, Nagakumar,Bharatham, Kavitha,Lee, Keun-Woo Korean Chemical Society 2006 Bulletin of the Korean Chemical Society Vol.27 No.2

Three-dimensional quantitative structure-activity relationship (3D-QSAR) models were developed for 67 molecules of 2-amino-benzothiazole-6-anilide derivatives against lymphocyte-specific protein tyrosine kinase (P56 LCK). The molecular field analysis (MFA) and receptor surface analysis (RSA) were employed for QSAR studies and the predictive ability of the model was validated by 15 test set molecules. Structure-based investigations using molecular docking simulation were performed with the crystal structure of P56 LCK. Good correlation between predicted fitness scores versus observed activities was demonstrated. The results suggested that the nature of substitutions at the 2-amino and 6-anilide positions were crucial in enhancing the activity, thereby providing new guidelines for the design of novel P56 LCK inhibitors.

Molecular Docking Study of Aminoacyl-tRNA Synthetases with Ligand Molecules from Four Different Scaffolds

Nagakumar Bharatham,Kavitha Bharatham,이윤호,Songmi Kim,Prettina Lazar,Ayoung Baek,Chanin Park,엄희성,하현준,Sae Young Yun,이원구,Sunghoon Kim,이근우 대한화학회 2010 Bulletin of the Korean Chemical Society Vol.31 No.3

Aminoacyl-tRNA synthetases (aaRSs) play vital roles in protein biosynthesis of living organisms and are interesting antibacterial drug targets. In order to find out new inhibitor candidate molecules as antibacterial agent, the binding modes of the candidate molecules were investigated at the active sites of aaRSs by molecular docking study. The docking simulations were performed with 48 compounds from four different scaffolds into the eight different aaRSs. The results show that scaffolds 3 and 4 compounds have consistently better binding capabilities, specifically for HisRS (E. coli) and IleRS (S. aureus). The binding modes of the best compounds with the proteins were well compatible with those of two ligands in crystal structures. Therefore, we expect that the final compounds we present may have reasonable aaRS inhibitory activity.

P56 LCK Inhibitor Identification by Pharmacophore Modelling and Molecular Docking

Nagakumar Bharatham,Kavitha Bharatham,이근우 대한화학회 2007 Bulletin of the Korean Chemical Society Vol.28 No.2

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 Lipinskis rules. Finally 68 compounds satisfied all the properties required to be a successful inhibitor candidate.

Quantitative Structure-Activity Relationships and Molecular Docking Studies of P56 LCK Inhibitors

Nagakumar Bharatham,Kavitha Bharatham,이근우 대한화학회 2006 Bulletin of the Korean Chemical Society Vol.27 No.2

Adenosine Kinase Inhibitor Design Based on Pharmacophore Modeling

이윤호,Nagakumar Bharatham,Kavitha Bharatham,이근우 대한화학회 2007 Bulletin of the Korean Chemical Society Vol.28 No.4

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 anti-inflammatory 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 Lipinskis 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.

Urokinase Inhibitor Design Based on Pharmacophore Model Derived from Diverse Classes of Inhibitors

Shui, Liu,Bharatham, Nagakumar,Bharatham, Kavitha,Lee, Keun-Woo Korean Society for Bioinformatics and Systems Biol 2006 Bioinformatics and Biosystems Vol.1 No.2

A three-dimensional pharmacophore model was developed based on 24 currently available inhibitors, which were rationally selected from 472 compounds with diverse molecular structure and bioactivity, for generating pharmacophore of uPA (Urokinase Plasminogen Activator) inhibitors. The best hypothesis (Hypo1) comprised of five features, namely, one positive ionizable group, one hydrogen-bond acceptor group and three hydrophobic aromatic groups. The correlation coefficient, root mean square deviation and cost difference were 0.973, 0.695, and 94.291 respectively, suggesting that a highly predictive pharmacophore model was successfully obtained. The application of the model showed great success in predicting the activities of 251 known uPA inhibitors (test set) with a correlation coefficient of 0.837, and there was also none of the outcome hypotheses that had similar cost difference and RMS deviation (RMSD) with that of the initial hypothesis generated by Cat-Scramble validation test with 95% confidence level. Accordingly, our model should be reliable in identifying structurally diverse compounds with desired biological activity.