| 학회 | 한국공업화학회 |
| 학술대회 | 2020년 가을 (10/28 ~ 10/30, 광주 김대중컨벤션센터(Kimdaejung Convention Center)) |
| 권호 | 24권 1호 |
| 발표분야 | 포스터-화학물질안전·위해성 |
| 제목 | In silico method of endocrine-disrupting chemicals (EDCs) prediction in chemical space |
| 초록 | Endocrine-disrupting chemicals (EDCs) are compounds that interfere with hormonal systems and disrupt normal endocrine function. EDCs can lead to an adverse health effect in exposed humans or other organisms. Recently, many experimental data of EDCs were reported, but it is not enough to understand to identify the EDCs. Therefore, the in silico methods were used as an alternative approach to identifying the EDCs. The in silico methods such as QSAR models and molecular docking were developed to predict endocrine-disrupting activity from environmental chemicals. However, the QSAR method had a limited applicability domain of chemicals in each model. Also, molecular docking was accurate, but it was time-consuming about large numbers of compounds. To overcome this, we clustered EDCs using the physicochemical properties and biological information of EDCs and constructed EDCs space. All chemicals with industry can be predicted whether a compound is EDCs or not in EDCs space. |
| 저자 | 서명원, 김선미, 최지원, 나민주, 김종운 |
| 소속 | 한국화학(연) |
| 키워드 | In silico; endorine-disrupting chemicals; EDCs; chemical space; physicochemical similarity |
