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Now showing items 1-9 of 9

Sparse Topological Pharmacophore Graphs for Interpretable Scaffold Hopping

Nakano, Hiroshi; Miyao, Tomoyuki; Swarit, Jasial; Funatsu, Kimito (American Chemical Society, 2021-07-15)

The aim of scaffold hopping (SH) is to find compounds consisting of different scaffolds from those in already known active compounds, giving an opportunity for unexplored regions of chemical space. We previously demonstrated ...
Prediction of Reaction Yield for Buchwald-Hartwig Cross-coupling Reactions Using Deep Learning

Sato, Akinori; Miyao, Tomoyuki; Funatsu, Kimito (Wiley-VCH Verlag, 2021-09-29)

Chemical reaction yield is one of the most important factors for determining reaction conditions. Recently, several machine learning-based prediction models using high-throughput experiment (HTE) data sets were reported ...
Ligand-based Activity Cliff Prediction Models with Applicability Domain

Tamura, Shunsuke; Miyao, Tomoyuki; Funatsu, Kimito (Wiley-VCH Verlag, 2020-12-01)

Activity cliffs (ACs) are formed by pairs of structurally similar compounds with large differences in potency. Predicting ACs is of high interest in lead optimization for drug discovery. Previous AC prediction models that ...
Comparing predictive ability of QSAR/QSPR models using 2D and 3D molecular representations

Sato, Akinori; Miyao, Tomoyuki; Jasial, Swarit; Funatsu, Kimito (Springer, 2021-01-04)

Quantitative structure–activity relationship (QSAR) and quantitative structure–property relationship (QSPR) models predict biological activity and molecular property based on the numerical relationship between chemical ...
Exploring Topological Pharmacophore Graphs for Scaffold Hopping

Nakano, Hiroshi; Miyao, Tomoyuki; Funatsu, Kimito (American Chemical Society, 2020-04-27)

The primary goal of ligand-based virtual screening is to identify active compounds consisting of a core scaffold that is not found in the current active compound pool. Scaffold hopping is the term used for this purpose. ...
Soft Sensor Modeling for Identifying Significant Process Variables with Time Delays

Hikosaka, Tatsuya; Aoshima, Shinichiro; Miyao, Tomoyuki; Funatsu, Kimito (American Chemical Society, 2020-07-01)

Soft sensors have been widely employed in industrial processes to estimate process variables that are difficult to measure in real time. Taking into account process dynamics in soft sensor models is important not only for ...
Interpretation of Ligand-Based Activity Cliff Prediction Models Using the Matched Molecular Pair Kernel

Tamura, Shunsuke; Jasial, Swarit; Miyao, Tomoyuki; Funatsu, Kimito (MDPI, 2021-08-13)

Activity cliffs (ACs) are formed by two structurally similar compounds with a large difference in potency. Accurate AC prediction is expected to help researchers’ decisions in the early stages of drug discovery. Previously, ...
最先端をリードする国際連携推進に向けて～人と科学と技術の国際交流～

三宅, 雅人 (日本化学会, 2016)
IRE1–XBP1 pathway regulates oxidative proinsulin folding in pancreatic β cells

Tsuchiya, Yuichi; Saito, Michiko; Kadokura, Hiroshi; Miyazaki, Jun-ichi; Tashiro, Fumi; Imagawa, Yusuke; Iwawaki, Takao; Kohno, Kenji (Rockefeller University Press, 2018-03-05)

In mammalian pancreatic β cells, the IRE1α–XBP1 pathway is constitutively and highly activated under physiological conditions. To elucidate the precise role of this pathway, we constructed β cell–specific Ire1α conditional ...

Now showing items 1-9 of 9

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