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Yasufumi Miyamoto,
Yoshihiro Banno,
Tohru Yamashita,
Tatsuhiko Fujimoto,
Satoru Oi,
Yusuke Moritoh,
Tomoko Asakawa,
Osamu Kataoka,
Hiroaki Yashiro,
Koji Takeuchi, [......],
Takuo Kosaka,
Shigetoshi Tsubotani,
Akiyoshi Tani,
Masako Sasaki,
Miyuki Funami, Michiko Amano,
Yoshio Yamamoto,
Kathleen Aertgeerts,
Jason Yano,
Hironobu Maezaki
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ABSTRACT: Inhibition of dipeptidyl peptidase IV (DPP-4) is an exciting new approach for the treatment of diabetes. To date there has been no DPP-4 chemotype possessing a carboxy group that has progressed into clinical trials. Originating from the discovery of the structurally novel quinoline derivative 1, we designed novel pyridine derivatives containing a carboxy group. In our design, the carboxy group interacted with the targeted amino acid residues around the catalytic region and thereby increased the inhibitory activity. After further optimization, we identified a hydrate of [5-(aminomethyl)-6-(2,2-dimethylpropyl)-2-ethyl-4-(4-methylphenyl)pyridin-3-yl]acetic acid (30c) as a potent and selective DPP-4 inhibitor. The desired interactions with the critical active-site residues, such as a salt-bridge interaction with Arg125, were confirmed by X-ray cocrystal structure analysis. In addition, compound 30c showed a desired preclinical safety profile, and it was encoded as TAK-100.
Journal of Medicinal Chemistry 01/2011; 54(3):831-50. · 4.80 Impact Factor
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Yasufumi Miyamoto,
Yoshihiro Banno,
Tohru Yamashita,
Tatsuhiko Fujimoto,
Satoru Oi,
Yusuke Moritoh,
Tomoko Asakawa,
Osamu Kataoka,
Koji Takeuchi,
Nobuhiro Suzuki,
Koji Ikedo,
Takuo Kosaka,
Shigetoshi Tsubotani,
Akiyoshi Tani,
Miyuki Funami, Michiko Amano,
Yoshio Yamamoto,
Kathleen Aertgeerts,
Jason Yano,
Hironobu Maezaki
[show abstract]
[hide abstract]
ABSTRACT: We have previously discovered nicotinic acid derivative 1 as a structurally novel dipeptidyl peptidase IV (DPP-4) inhibitor. In this study, we obtained the X-ray co-crystal structure between nicotinic acid derivative 1 and DPP-4. From these X-ray co-crystallography results, to achieve more potent inhibitory activity, we targeted Arg125 as a potential amino acid residue because it was located near the pyridine core, and some known DPP-4 inhibitors were reported to interact with this residue. We hypothesized that the guanidino group of Arg125 could interact with two hydrogen-bond acceptors in a bidentate manner. Therefore, we designed a series of 3-pyridylacetamide derivatives possessing an additional hydrogen-bond acceptor that could have the desired bidentate interaction with Arg125. We discovered the dihydrochloride of 1-{[5-(aminomethyl)-2-methyl-4-(4-methylphenyl)-6-(2-methylpropyl)pyridin-3-yl]acetyl}-l-prolinamide (13j) to be a potent and selective DPP-4 inhibitor that could interact with the guanidino group of Arg125 in a unique bidentate manner.
Bioorganic & medicinal chemistry 01/2011; 19(1):172-85. · 2.82 Impact Factor
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ABSTRACT: Conformation generation is a common and key process of computer-aided drug design. The reliability of the docking simulations, pharmacophore development, and 3D-QSAR analyses depends on the accuracy of conformations of small molecules used as input information for each program. Many conformation generators have been developed with the aim of efficiently generating all the putative bound conformations that small molecules adopt when they interact with macromolecules. Conformation generators have been evaluated by whether they can reproduce the experimentally determined bioactive conformations of bound small molecules. These bioactive conformations are usually obtained from publicly available crystal structures of protein-ligand complexes. However, it is difficult to obtain 2 or more than 2 bioactive conformations of one compound because multiple complex structures of a single molecule with various macromolecules are rarely available. Present methods, therefore, simply check whether a set of generated conformations includes the corresponding bioactive conformation. The overall validity of the entire set of generated conformations against bioactive conformation space has never been checked. In this work we developed a novel method for the evaluation of conformation generators, which makes it possible to measure the performance of a conformation generator based on its ability to reproduce the overall bioactive conformation space. We also determined the optimum parameter sets for OMEGA (OpenEye) based on the coverage of bioactive conformation space and computational efficiency. Our evaluation method elucidated that increasing the number of generated conformations is not necessary to obtain better reproducibility of the overall bioactive conformation space. Our method can be applied to the evaluation of the algorithm and/or design of the conformation generator program itself.
Journal of Chemical Information and Modeling 06/2009; 49(6):1377-88. · 4.68 Impact Factor
