• 한국환경보건학회지
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• 제45권5호
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• pp.457-464
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• 2019

Objectives: Quantitative structure-activity relationship (QSAR) is one of the effective alternatives to animal testing, but its credibility in terms of toxicity prediction has been questionable. Thus, this work aims to evaluate its predictive capacity and find ways of improving its credibility. Methods: Using $TOPKAT^{(R)}$, OECD toolbox, and $Derek^{(R)}$, all of which have been applied world-wide in the research, industrial, and regulatory fields, an analysis of prediction credibility markers including accuracy (A), sensitivity (S), specificity (SP), false negative (FN), and false positive (FP) was conducted. Results: The multi-application of QSARs elevated the precision credibility relative to individual applications of QSARs. Moreover, we found that the type of chemical structure affects the credibility of markers significantly. Conclusions: The credibility of individual QSAR is insufficient for both the prediction of chemical toxicity and regulation of hazardous chemicals. Thus, to increase the credibility, multi-QSAR application, and compensation of the prediction deviation by chemical structure are required.

• 농약과학회지
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• 제6권1호
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• pp.25-30
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• 2002

새로운 제초성 N-phenyl-3,4-dimethylphthalimide 유도체의 구조변화에 따른 물리-화학 파라미터와 다루어진 바 없는 TOPKAT 프로그램으로 계산된 랫트 및 마우스 등의 급만성 독성에 관한 판별점수(DS) 및 치사율과의 관계(QSTR)를 정량적으로 검토하였다. 그 결과, 발암성은 랫트보다 마우스가 그리고 수컷보다는 암컷이 높은 경향이었다. $R_2$-기만이 변화하는 조건에서 Hansch-Fujita 식을 유도한 결과, 발암성에서 랫트 암컷을 제외한 마우스(암, 수) 및 랫트 수컷은 공통적으로 LUMO 에너지가 영향을 미치는 주 요인이었으며 마우스 암컷과 수컷의 발암성에 관한 선택성 요소는 주로 $R_2$-치환기 길이의 적정값(약 $(L)_{opt.}=5.0{\AA}$)에 의존적이었다. 또한, Free-Wilson 식으로부터 $R_2$-기의 기여도는 랫트 수컷의 경우, 탄화수소로 구성된 치환체가 그리고 그 이외의 경우에는 불소 치환체들의 기여도가 우세한 경향이었다.

• 한국환경성돌연변이발암원학회지
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• 제20권1호
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• pp.21-25
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• 2000

Recently there is increasing interest in the use of structure activity relationships for predicting the biological activity of chemicals. The reasons for the interest include the decrease cost and time per chemical as compared with animal or cell system for identifying toxicological effects of chemicals and the reduction in the use of animals for toxicological testing. This study is to test the validity of the mutagenicity data generated from QSAR (Quantitative Structure Activity Relationship) program. Thirty chemicals, which had been evaluated by Ames test during 1997-1999, were assessed with TOPKAT QSAR mutagenicity prediction module. Among 30chemicals experimented, 28 were negative and 2 were positive for Ames test. On the contrary, 23 chemicals showed the high confidence level indicating high prediction rate in mutagenicity evaluation, and 7 chemicals showed the lsow to moderate confidence level indicating low prediction in mutagenicity evaluation. Overall mutagenicity prediction rate was 77% (23/30). The prediction rates for non-mutagenic chemicals were 79% (22/28) and mutagenic chemicals were 50% (1/2). QSAR could be a useful tool in providing toxicological data for newly introduced chemicals or in furnishing data for MSDS or in determining the dose in toxicity testing for chemicals with no known toxicological data.

• 한국환경보건학회지
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• 제48권3호
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• pp.159-166
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• 2022

Background: A quantitative structure-activity relationship (QSAR) model was adopted in the Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH, EU) regulations as well as the Act on Registration, Evaluation, etc. of Chemicals (AREC, Republic of Korea). It has been previously used in the registration of chemicals. Objectives: In this study, we investigated the correlation between the predicted data provided by three prediction programs using a QSAR model and actual experimental results (acute fish, daphnia magna toxicity). Through this approach, we aimed to effectively conjecture on the performance and determine the most applicable programs when designating toxic substances through the AREC. Methods: Chemicals that had been registered and evaluated in the Toxic Chemicals Control Act (TCCA, Republic of Korea) were selected for this study. Two prediction programs developed and operated by the U.S. EPA - the Ecological Structure-Activity Relationship (ECOSAR) and Toxicity Estimation Software Tool (T.E.S.T.) models - were utilized along with the TOPKAT (Toxicity Prediction by Komputer Assisted Technology) commercial program. The applicability of these three programs was evaluated according to three parameters: accuracy, sensitivity, and specificity. Results: The prediction analysis on fish and daphnia magna in the three programs showed that the TOPKAT program had better sensitivity than the others. Conclusions: Although the predictive performance of the TOPKAT program when using a single predictive program was found to perform well in toxic substance designation, using a single program involves many restrictions. It is necessary to validate the reliability of predictions by utilizing multiple methods when applying the prediction program to the regulation of chemicals.

• 한국환경보건학회지
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• 제40권2호
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• pp.105-113
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• 2014

Objectives: It is necessary to apply quantitative structure activity relationship (QSAR) for the various chemicals with insufficient toxicity data that are used in the workplace, based on the precautionary principle. This study aims to find application plan of QSAR software tool for predicting health hazards such as genetic toxicity, and carcinogenicity for some chemicals used in the electronics industries. Methods: Toxicity prediction of 21 chemicals such as 5-aminotetrazole, ethyl lactate, digallium trioxide, etc. used in electronics industries was assessed by Toxicity Prediction by Komputer Assisted Technology (TOPKAT). In order to identify the suitability and reliability of carcinogenicity prediction, 25 chemicals such as 4-aminobiphenyl, ethylene oxide, etc. which are classified as Group 1 carcinogens by the International Agency for Research on Cancer (IARC) were selected. Results: Among 21 chemicals, we obtained prediction results for 5 carcinogens, 8 non-carcinogens and 8 unpredictability chemicals. On the other hand, the carcinogenic potential of 5 carcinogens was found to be low by relevant research testing data and Oncologic TM tool. Seven of the 25 carcinogens (IARC Group 1) were wrongly predicted as non-carcinogens (false negative rate: 36.8%). We confirmed that the prediction error could be improved by combining genetic toxicity information such as mutagenicity. Conclusions: Some compounds, including inorganic chemicals and polymers, were still limited for applying toxicity prediction program. Carcinogenicity prediction may be further improved by conducting cross-validation of various toxicity prediction programs, or application of the theoretical molecular descriptors.

• 농업과학연구
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• 제28권1호
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• pp.33-40
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• 2001

아직까지 시도된 바 없는 살균성 phenylthionocarbamate 유도체들의 phenyl-치환기가 변화함에 따라 TOPKAT 계산으로 예측된 다양한 급성 및 만성 독성값에 미치는 정량적인 분자구조와 독성과의 관계 (QSTRs)를 검토한 결과는 다음과 같다. (1) 기질분자의 구조변화에 따른 독성치와 그의 판별점수 (D.S.) 에 기초하여 분자 중 특정부분 (fragment)이 양 (+)의 값으로 독성에 기여하는 대체적인 순서는 Aro. C=C, -O-, -NH- 및 할로겐 (X) 원자의 순이었다. (2) 대부분의 화합물들은 매우 높은 돌연변이와 발암성이 예측되었으며 특히, 치환기의 위치에 관계없이 fluoro-치환체는 $B_2$상수에 따른 입체효과 ($(B_2)_{opt.}=1.54{\AA}$)에 의하여 모두 100% 돌연변이를 발현한 반면에 trifluorornethyl-치환체는 돌연변이 발현 가능성이 전혀 없었다. (3) 가장 높은 독성 발현조건은 phenyl-치환기에 대한 소정의 적정값으로 돌연변이성에는 $(B_2)_{opt.}=1.54{\AA}$, 발암성에서 수컷 rat와 mouse는$(R)_{opt.}=0.16$ 및 $(\pi)_{opt.}=0.16$ 그리고 rat의 경구독성은 $LD_{50};({\varepsilon}LOMO)_{opt}=-0.52e.v.$, chronic LOAEL; $(B_3){opt.}=1.54{\AA}$, 어독성은 ${LC_50}$; $(logP)_{opt.}=4.25$ 및 물벼룩에 대한 독성은 $EC_{50};({\sigma})_{opt}=-0.68$를 나타내는 경우 이었다. (4) 돌연변이성에는 할로겐 중, fluoro-기를 위시하여 nitro 및 methyl-기 등의 순서로 기여하였고 phenyl 고리 상, 치환기의 위치와 전자 수수관계에는 대체로 무관한 경향을 나타내었다.