分子標的薬アファチニブの薬効予測を実現するシミュレーション解析と数理モデル

Sugano, Aki (Principal Investigator)
Takaoka, Yutaka (Co-Investigator(Kenkyū-buntansha))
Ota, Mika (Co-Investigator(Kenkyū-buntansha))

Outline of Research at the Start

本研究では、肺がん分子標的薬の第２世代のアファチニブを対象に変異型EGFRへの薬効予測を実現する分子シミュレーション解析手法と数理モデル系を確立する。

Status	Finished
Effective start/end date	2022/04/01 → 2025/03/31

Funding

Japan Society for the Promotion of Science: ¥4,030,000.00

Keywords

分子シミュレーション
薬効予測

Access Project

https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-22K12261/

2 Article

In silico binding affinity of the spike protein with ACE2 and the relative evolutionary distance of S gene may be potential factors rapidly obtained for the initial risk of SARS-CoV-2
Sugano, A., Murakami, J., Kataguchi, H., Ohta, M., Someya, Y., Kimura, S., Kanno, A., Maniwa, Y., Tabata, T., Tobe, K. & Takaoka, Y., 2023/12, In: Microbial Risk Analysis. 25, 100278.
Research output: Contribution to journal › Article › peer-review

Open Access
2 Scopus citations
SARS-CoV-2 Omicron BA.2.75 Variant May Be Much More Infective than Preexisting Variants Based on In Silico Model
Sugano, A., Takaoka, Y., Kataguchi, H., Ohta, M., Kimura, S., Araki, M., Morinaga, Y. & Yamamoto, Y., 2022/10, In: Microorganisms. 10, 10, 2090.
Research output: Contribution to journal › Article › peer-review

Open Access
3 Scopus citations