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Higo J.,Osaka University | Dasgupta B.,Osaka University | Mashimo T.,Technology Research Association for Next Generation Natural Products Chemistry | Mashimo T.,Mathematical Science and Bioinformatics Co. | And 3 more authors.
Journal of Computational Chemistry | Year: 2015

A novel enhanced conformational sampling method, virtual-system-coupled adaptive umbrella sampling (V-AUS), was proposed to compute 300-K free-energy landscape for flexible molecular docking, where a virtual degrees of freedom was introduced to control the sampling. This degree of freedom interacts with the biomolecular system. V-AUS was applied to complex formation of two disordered amyloid-β (Aβ30-35) peptides in a periodic box filled by an explicit solvent. An interpeptide distance was defined as the reaction coordinate, along which sampling was enhanced. A uniform conformational distribution was obtained covering a wide interpeptide distance ranging from the bound to unbound states. The 300-K free-energy landscape was characterized by thermodynamically stable basins of antiparallel and parallel β-sheet complexes and some other complex forms. Helices were frequently observed, when the two peptides contacted loosely or fluctuated freely without interpeptide contacts. We observed that V-AUS converged to uniform distribution more effectively than conventional AUS sampling did. © 2015 Wiley Periodicals, Inc. Source

Fukunishi Y.,Japan National Institute of Advanced Industrial Science and Technology | Fukunishi Y.,Technology Research Association for Next Generation Natural Products Chemistry | Kurosawa T.,Technology Research Association for Next Generation Natural Products Chemistry | Kurosawa T.,Hitachi Solutions | And 3 more authors.
Journal of Chemical Information and Modeling | Year: 2014

A compound's synthetic accessibility (SA) is an important aspect of drug design, since in some cases computer-designed compounds cannot be synthesized. There have been several reports on SA prediction, most of which have focused on the difficulties of synthetic reactions based on retro-synthesis analyses, reaction databases and the availability of starting materials. We developed a new method of predicting SA using commercially available compound databases and molecular descriptors. SA was estimated from the probability of existence of substructures consisting of the compound in question, the number of symmetry atoms, the graph complexity, and the number of chiral centers of the compound. The probabilities of the existence of given substructures were estimated based on a compound library. The predicted SA results reproduced the expert manual assessments with a Pearson correlation coefficient of 0.56. Since our method required a compound database and not a reaction database, it should be easy to customize the prediction for compound vendors. The correlation between the sales price of approved drugs and the SA values was also examined and found to be weak. The price most likely depends on the total cost of development and other factors. © 2014 American Chemical Society. Source

Yamashita Y.,Keio University | Tanaka K.-I.,Keio University | Asano T.,Keio University | Yamakawa N.,Keio University | And 11 more authors.
Bioorganic and Medicinal Chemistry | Year: 2014

Chronic obstructive pulmonary disease (COPD) is characterized by abnormal inflammatory responses and airflow limitations. We recently proposed that the muscarinic antagonist mepenzolate bromide (mepenzolate) would be therapeutically effective against COPD due to its muscarinic receptor-dependent bronchodilatory activity as well as anti-inflammatory properties. Mepenzolate has an asymmetric carbon atom, thus providing us with the opportunity to synthesize both of its enantiomers ((R)- and (S)-mepenzolate) and to examine their biochemical and pharmacological activities. (R)- or (S)-mepenzolate was synthesized by condensation of benzilic acid with (R)- or (S)-alcohol, respectively, followed by quaternization of the tertiary amine. As predicted by computational simulation, a filter-binding assay in vitro revealed that (R)-mepenzolate showed a higher affinity for the muscarinic M3 receptor than (S)-mepenzolate. In vivo, the bronchodilatory activity of (R)-mepenzolate was superior to that of (S)-mepenzolate, whereas anti-inflammatory activity was indistinguishable between the two enantiomers. We confirmed that each mepenzolate maintained its original stereochemistry in the lung when administered intratracheally. These results suggest that (R)-mepenzolate may have superior properties to (S)-mepenzolate as a drug to treat COPD patients given that the former has more potent bronchodilatory activity than the latter. © 2014 Elsevier Ltd. All rights reserved. Source

Fukunishi Y.,Japan National Institute of Advanced Industrial Science and Technology | Yamasaki S.,Technology Research Association for Next Generation Natural Products Chemistry | Yasumatsu I.,Technology Research Association for Next Generation Natural Products Chemistry | Yasumatsu I.,Daiichi Sankyo | And 4 more authors.
Molecular Informatics | Year: 2016

In order to improve docking score correction, we developed several structure-based quantitative structure activity relationship (QSAR) models by protein-drug docking simulations and applied these models to public affinity data. The prediction models used descriptor-based regression, and the compound descriptor was a set of docking scores against multiple (∼600) proteins including nontargets. The binding free energy that corresponded to the docking score was approximated by a weighted average of docking scores for multiple proteins, and we tried linear, weighted linear and polynomial regression models considering the compound similarities. In addition, we tried a combination of these regression models for individual data sets such as IC50, Ki, and %inhibition values. The cross-validation results showed that the weighted linear model was more accurate than the simple linear regression model. Thus, the QSAR approaches based on the affinity data of public databases should improve docking scores. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Source

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