• 대한화학회지
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• 제53권6호
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• pp.653-662
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• 2009

흡수, 분포, 대사, 배설 특성 및 독성을 예측하기 위한 효과적인 툴을 개발하는 것은 신약개발의 초기단계에서 NCE(new chemical entity)에 대한 가장 중요한 업무 중의 하나이다. 최근에 이런 시도중의 하나로서 ADME/T(absorption, distribution, metabolism, excretion, toxicity)관련 성질들의 예측에 support vector machine(SVM)을 이용하고 있다. 그리고 SVM은 ADME/T 성질들을 정확하게 예측하는데 많이 사용 되고 있다. 그러나 SVM 모델링에 두 가지 문제가 있다. 특성 선택(feature selection) 과 매개변수 설정(parameter setting)은 여전히 해결해야 할 과제이다. 이 두 가지 문제들은 SVM 분류의 효율성과 정확도에 결정적인 영향을 끼친다. 특히 특성 선택과 최적화된 SVM 변수의 설정은 서로 영향을 주기 때문에 동시에 다루어져야 한다. 여기서 우리는 genetic algorithm(GA) – 특성 선택에 사용 – 과 grid search(GS) method– 변수최적화에 사용 – 두 가지를 통합하는 효과적인 해결책을 제시하였다. ADME/T관련 성질 중 하나인 심장부정맥을 야기시키는 hERG 이온채널 저해제 분류 모델이 여기서 제안된 GA-GS-SVM을 위해 할당되고 테스트 되었다. 1891개의 화합물을 가지는 트레이닝 셋으로 단일 모델 3개, 앙상블 모델 3개, 총 6개의 모델을 만들었고 175개의 외부 데이터를 테스트 셋으로 사용하여 검증하였다. 데이터의 불균형 문제를 해결하기 위하여 GA-GS-SVM 단일 모델에 의한 예측 정확도와 GA-GS-SVM 앙상블 모델 예측 정확도를 비교하였으며, 앙상블모델을 사용하여 예측의 정확도를 높일 수 있었다.

• 한국유전체학회:학술대회논문집
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• 한국유전체학회 2002년도 The 11th Korea Genome Conference
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• pp.46.1-46.1
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• 2002

• 한국미생물생명공학회소식지:생물산업
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• 제15권3호
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• pp.16-19
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• 2002

• 한국유전체학회:학술대회논문집
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• 한국유전체학회 2005년도 The 14th Korea Genome Conference
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• pp.45-45
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• 2005

• 통합자연과학논문집
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• 제15권4호
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• pp.153-161
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• 2022

c-Jun N-terminal kinases (JNKs) are members of MAPK family. Many genes can relay signals that promote inflammation, cell proliferation, or cell death which causes several diseases have been associated to mutations in the JNK gene family. The JNK2 gene is significantly more important in cancer development than the JNK1 and JNK3 genes. There are several different ways in which JNK2 contributes to breast cancer, and one of these is through its role in cell migration. As a result, this study's primary objective was to employ computational strategies to identify promising leads that potentially target the JNK2 protein in a strategy to alleviate breast cancer. We have derived these anticancer compounds from marine brown seaweed called Turbinaria conoides. We have identified compounds Ethane, 1, 1-diethoxy- and Butane, 2-ethoxy as promising anti-cancer drugs by molecular docking, DFT, and ADME study.

• 약학회지
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• 제57권6호
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• pp.412-419
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• 2013

Drug discovery and development processes are time consuming and costly endeavors. It has been reported that on average it takes 10 to 15 years and costs more than $ 1billion to bring a molecule from discovery to market. Compounds fail for various reasons but one of the significant reasons that accounts for failures in clinical trials is poor prediction/understanding of pharmacokinetics and drug metabolism in human. In an effort to improve the number of compounds that exhibit optimal absorption, distribution, metabolism, elimination (ADME), and pharmacokinetic properties in human, drug metabolism, pharmacokinetic scientists have been continually developing new technologies and compound screening strategies. Over the last few years, accelerator mass spectrometry (AMS) and its applications to preclinical/clinical pharmacokinetics and ADME studies have significantly increased, particularly for new chemical/biological entities that are difficult to support with conventional radiolabel studies. In this review, the application of AMS for micro-dosing, micro-tracer absolute bioavailability, mass balance and metabolite profiling studies will be discussed.

• 방사선산업학회지
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• 제7권2_3호
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• pp.209-219
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• 2013

RI-Biomics field comes into the limelight as a new fusion radiation technology. These rapid development of RI-Biomics cause the necessity of establishment of a new methodical education program model for consistent training of professional manpower in RI-ADME, Biomics field. But domestic current status is not satisfied to training human resource development in RI-Biomics. Actually domestic educational organization related to RI-Biomics just run educational programs oriented basic theory, so practical and fusion education are not existed nowadays for preliminary RI-Biomics expert. Therefore we established a new education program model for educate of the expert in RI-Biomics field to overcome current problem about the route of knowledge that has more monotonous and concentrated tendency and non-professional education. To improve universality and practicality, we conduct education-training model survey about domestic and foreign country. This new human resource development model will contribute to fostering new expert in RI-Biomics field.

• Journal of Pharmaceutical Investigation
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• 제38권3호
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• pp.183-189
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• 2008

The present study compared the feasibility of Caco-2 and MDCK cells as an efficient in-vitro model for the drug classification based on Biopharmaceutics Classification System (BCS) as well as an in-vitro model for drug interactions mediated by P-gp inhibition or P-gp induction. Thirteen model drugs were selected to cover BCS Class I{\sim}IV$ and their membrane permeability values were evaluated in both Caco-2 and MDCK cells. P-gp inhibition studies were conducted by using vinblastine and verapamil in MDCK cells. P-gp induction studies were also performed in MDCK cells using rifampin and the P-gp expression level was determined by western blot analysis. Compared to Caco-2 cells, MDCK cells required shorter period of time to culture cells before running the transport study. Both Caco-2 and MDCK cells exhibited the same rank order relationship between in-vitro permeability values and human permeability values of all tested model compounds, implying that those in-vitro models may be useful in the prediction of human permeability (rank order) of new chemical entities at the early drug discovery stage. However, in the case of BCS drug classification, Caco-2 cells appeared to be more suitable than MDCK cells. P-gp induction by rifampin was negligible in MDCK-cells while MDCK cells appeared to be feasible for P-gp inhibition studies. Taken all together, the present study suggests that Caco-2 cells might be more applicable to the BCS drug classification than MDCK-cells, although MDCK cells may provide some advantage in terms of capacity and speed in early ADME screening process.

• 방사선산업학회지
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• 제7권2_3호
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• pp.221-224
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• 2013

RI-Biomics is a new compound word of radiation technology and Biomics related to the study of life. RI-Biomics is high radiation fusion technology by combining evaluation of pharmacokinetics in vivo (RI-ADME) of new drugs and medical materials using radioisotope and molecular imaging technology using nuclear medicine equipments. RI-Biomics fields are emerging with the increasing usage of radioisotopes (RI). In this paper, we investigated the latest trends of radioisotope using in RI-Biomics fields. The representative radioisotopes are $^{14}C$, $^3H$ and $^{32}P$ for the optimization and the selection of candidates in the development process of new drugs among the RI-Biomics fields. As shown in the status of accumulated income of radioisotopes, using amounts of radioisotopes are showing a tendency to increase every year. $^{14}C$ is 61.6% increase of accumulated income growth rate and $^3H$ increased by 58.8% and $^{32}P$ increased by 33.9% in 2012 compared to 2007. These isotopes are used in a variety of fields as using of $^{14}C$ for microdosing test, development of [$^3H$]cholesterol absorption inhibitors, study of [$^{131}I$]pyronaridine tetraphosphate for malaria therapy. These are going on in vivo test sucessfully. So, clinical research step is expected to begin soon. Therefore, usages of radioisotopes are necessary and need for the evaluation of pharmacokinetics, optimization and the selection of new drug candidates in the development process of new drugs among the RI-Biomics fields. So, using of radioisotopes is predict to increase continuously except for primarily used $^{14}C$, $^3H$.

• 방사선산업학회지
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• 제11권1호
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• pp.7-11
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• 2017

RI-Biomics는 방사성동위원소를 이용한 신약 및 물질의 흡수, 분포, 대사 및 배설(RI-ADME)과 같은 생체 내 역학을 평가하기 위한 최첨단 방사선 융합 기술이다. 현재 RI-Biomics 기술정보는 RI-Biomics 기술정보시스템인 'RIBio-Info'로 제공되고 있으며, 본 연구에서는 최근 빅 데이터 기술 동향을 검토하여 RIBio-Info의 개선사항을 도출하였다. RI Biomics 정보 시스템에서 빅데이터를 적용하기 위해 실현되어야 할 구성 요소로 자원, 기술 및 인력에 대해 각각 검토하였다. 첫째 활용할 수 있는 외부 빅데이터를 찾고, 두번째로 빅데이터 활용 실현을 위한 인프라를 확충하고, 마지막으로 대용량 정보분석이 가능한 데이터 사이언티스트를 양성해야 한다. 이러한 환경 하에 비정형 대용량 데이터에 대한 다양한 분석이 가능한 원천기술이 개발될 것이며, RI-Biomics 분야의 새로운 가치를 창출할 수 있는 기반이 구축될 것이다.