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  • 03월 02일 17시 이후 : 초록수정 불가능, 일정확인 및 검색만 가능

제117회 대한화학회 학술발표회, 총회 및 기기전시회 안내 Development of QNTR (Quantitative Nanostructure-Toxicity Relationships) models to predict cytotoxicity of metal/metal oxide nanoparticles

2016년 2월 24일 17시 11분 51초
ENVR.P-508 이곳을 클릭하시면 발표코드에 대한 설명을 보실 수 있습니다.
4월 22일 (금요일) 13:00~14:30
저자 및
신현길, 김광연1, 박준우2, 노경태*
연세대학교 생명공학과, Korea
1(사)분자설계연구소 환경정보팀, Korea
2안전성평가연구소 경남환경독성본부 미래환경연구센터, Korea
Nanotechnology brought various benefits to our society. Throughout the human history, many promising technologies have been disappeared due to the adverse effects on the human health and on the environment; therefore deeper understanding on the relationship between properties and toxicity of nanomaterials is required to keep utilizing the benefits of nanotechnology. Hazard of manufactured nanoparticles (MNPs) are studied through various researches; however, there are still information gaps on the toxicity induced by MNPs. Computational approaches have been widely applied to compensate experimental study, and to understand toxicity of chemicals. In toxicity of MNPs, this approach also can be beneficial to fill data gaps, and to give insights on further experimental study. Quantitative nanostructure-toxicity relationships (QNTR) are a statistical approach to correlate nanostructure with toxicity. QNTR is different from classical QSAR due to the molecular structure of NPs. In this study, structure of NP is represented by metal (Me) and metal oxide (MeOx) cluster generated from their crystal information. Descriptors for Me/MeOx NPs are calculated based on the cluster structure and metal cation information. QNTR models with the descriptors from the cluster structures show good performance to predict cytotoxicity of Me/MeOx NPs.