• 한국환경보건학회지
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• 제50권2호
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• pp.113-124
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• 2024

Background: The increasing need to minimize animal testing has sparked interest in alternative methods with more humane, cost-effective, and time-saving attributes. In particular, in silico-based computational toxicology is gaining prominence. Adverse outcome pathway (AOP) is a biological map depicting toxicological mechanisms, composed of molecular initiating events (MIEs), key events (KEs), and adverse outcomes (AOs). To understand toxicological mechanisms, predictive models are essential for AOP components in computational toxicology, including molecular structures. Objectives: This study reviewed the literature and investigated previous research cases related to AOP and in silico methodologies. We describe the results obtained from the analysis, including predictive techniques and approaches that can be used for future in silico-based alternative methods to animal testing using AOP. Methods: We analyzed in silico methods and databases used in the literature to identify trends in research on in silico prediction models. Results: We reviewed 26 studies related to AOP and in silico methodologies. The ToxCast/Tox21 database was commonly used for toxicity studies, and MIE was the most frequently used predictive factor among the AOP components. Machine learning was most widely used among prediction techniques, and various in silico methods, such as deep learning, molecular docking, and molecular dynamics, were also utilized. Conclusions: We analyzed the current research trends regarding in silico-based alternative methods for animal testing using AOPs. Developing predictive techniques that reflect toxicological mechanisms will be essential to replace animal testing with in silico methods. In the future, since the applicability of various predictive techniques is increasing, it will be necessary to continue monitoring the trend of predictive techniques and in silico-based approaches.

• 대한한의학방제학회지
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• 제30권3호
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• pp.205-210
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• 2022

Conventional pharmacology has followed the notion of the reductionist 'single target selective drug paradigm'. Network pharmacology has made conventional pharmacology newer while meeting the challenges of this era. Conventional pharmacological methods have not solved the problems of Korean Medicine. For this reason, Network pharmaco- logy needs urgently and desperately for Korean medicine research. However, the information on drug interactions in herbal medicines is complex and less known. There are still some hurdles before network pharmacology emerges, one factor which constitutes Korean medicine research. There is a need to look for solutions other than inheriting the network pharmacology to solve problems that Korean medicine has before. The way of 'in silico' research should be the best to meet this challenge. With the help of 'in silico' research, there might have been emerged new findings of experimental data in Korean Medicine. If 'herbalomics' has been close to foundation through the 'in silico' method, it will contribute to the formation of modern Korean medicine and, simultaneously, come to a foundation for revitalizing exchanges with orthodox Western medicine. Eventually, it ends with a significant profitable and healthy result for the patients.

• Asian Pacific Journal of Cancer Prevention
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• 제17권4호
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• pp.2291-2295
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• 2016

Small molecule tyrosine kinase inhibitors targeting HER 2 receptors have emerged as an important therapeutic approach in inhibition of downstream proliferation and survival signals for the treatment of breast cancers. Recent drug discovery efforts have demonstrated that naturally occurring polyphenolic compounds like delphinidin have potential to inhibit proliferation and promote apoptosis of breast cancer cells by targeting HER2 receptors. While delphinidin may thus reduce tumour size, it is associated with serious side effects like dysphonia. Owing to the narrow therapeutic window of delphinidin, the present study aimed to identify high affinity compounds targeting HER2 with safer pharmacological profiles than delphinidin through virtual screening approaches. Delphinidin served as the query parent for identification of structurally similar compounds by Tanimoto-based similarity searching with a threshold of 95% against the PubChem database. The compounds retrieved were further subjected to Lipinski and Verber's filters to obtain drug like agents, then further filtered by diversity based screens with a cut off of 0.6. The compound with Pubchem ID: 91596862 was identified to have higher affinity than its parent. In addition it also proved to be non-toxic with a better ADMET profile and higher kinase activity. The compound identified in the study can be put to further in vitro drug testing to complement the present study.

• Mass Spectrometry Letters
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• 제10권3호
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• pp.93-101
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• 2019

Algorithms and software for predicting tandem mass spectra have been developed in recent years. In this work, we explore how distinct in silico $MS^2$ spectra are predicted for isomers, i.e. compounds having the same formula and similar molecular structures, to differentiate between them. We used the CFM-ID 2.0/3.0 predictor with regard to (a) test compounds, whose experimental mass spectra had been randomly sampled from the MassBank of North America (MoNA) collection, and to (b) the most widespread isomers of test compounds searched in the PubChem database. In the first validation test, in silico mass spectra constitute a reference library, and library searches are performed for test experimental spectra of "unknowns". The searches led to the true positive rate (TPR) of ($46-48{\pm}10$)%. In the second test, in silico and experimental spectra were interchanged and this resulted in a TPR of ($58{\pm}10$)%. There were no significant differences between results obtained with different metrics of spectral similarity and predictor versions. In a comparison of test compounds vs. their isomers, a statistically significant correlation between mass spectral data and structural features was observed. The TPR values obtained should be regarded as reasonable results for predicting tandem mass spectra of related chemical structures.

• Bulletin of the Korean Chemical Society
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• 제28권3호
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• pp.379-385
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• 2007

Receptor-oriented pharmacophore-based in silico screening is a powerful tool for rapidly screening large number of compounds for interactions with a given protein. Inhibition of the enzyme catechol-Omethyltransferase (COMT) offers a novel possibility for treating Parkinson's disease. Bisubstrate inhibitors of COMT containing the adenine of S-adenosylmethionine (SAM) and a catechol moiety are a new class of potent and selective inhibitor. In the present study, we used receptor-oriented pharmacophore-based in silico screening to examine the interactions between the active site of human COMT and bisubstrate inhibitors. We generated 20 pharmacophore maps, of which 4 maps reproduced the docking model of hCOMT and a bisubstrate inhibitor. Only one of these four, pharmacophore map I, effectively described the common features of a series of bisubstrate inhibitors. Pharmacophore map I consisted of one hydrogen bond acceptor (to Mg2+), three hydrogen bond donors (to Glu199, Glu90, and Gln120), and one hydrophobic feature (an active site region surrounded by several aromatic and hydrophobic residues). This map represented the most essential pharmacophore for explaining interactions between hCOMT and a bisubstrate inhibitor. These results revealed a pharmacophore that should help in the development of new drugs for treating Parkinson's disease.

• Asian Pacific Journal of Cancer Prevention
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• 제16권12호
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• pp.5005-5006
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• 2015

Gastric cancer as one of the most common cancers worldwide has various genetic and environmental risk factors including Helicobacter pylori (H.pylori) infection. Recently, loss of a tumor suppressor gene named promyelocytic leukemia (PML) has been identified in gastric cancer. However, no mutation has been found in this gene in gastric cancer samples. Cag A H.pylori protein has been shown to exert post transcriptional regulation of some tumor suppressor genes. In order to assess such a mechanism for PML degradation, we performed in silico analyses to establish any interaction between PML and Cag A proteins. In silico interaction and docking studies showed that these two proteins may have stable interactions. In addition, we showed that imatinib kinase inhibitor can restore PML function by inhibition of casein kinase 2.

• 제어로봇시스템학회논문지
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• 제11권10호
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• pp.823-829
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• 2005

We have newly constructed an in silico model of fermentative metabolism for Lactococcus lactis in order to analyze the characteristics of metabolite flux for dynamic network. A rigorous mathematical model for metabolic flux has been developed and simulation researches have been performed by using GEPASI program. In this simulation task, we were able to predict the whole flux distribution trend for lactate metabolism and analyze the flux ratio on the pyruvate branch point by using metabolic flux analysis(MFA). And we have studied flux control coefficients of key reaction steps in the model by using metabolic control analysis(MCA). The role of pyruvate branch seems to be essential for the secretion of lactate and other organic byproducts. Then we have made an effort to elucidate its metabolic regulation characteristics and key reaction steps, and find an optimal condition for the production of lactate.

• Journal of Microbiology and Biotechnology
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• 제13권4호
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• pp.571-577
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• 2003

The intracellular metabolic fluxes can be calculated by metabolic flux analysis, which uses a stoichiometric model for the intracellulal reactions along with mass balances around the intracellular metabolites. In this study, metabolic flux analyses were carried out to estimate flux distributions for the maximum in silico yields of various metabolites in Escherichia coli. The maximum in silico yields of acetic acid and lactic acid were identical to their theoretical yields. On the other hand, the in silico yields of succinic acid and ethanol were only 83% and 6.5% of their theoretical yields, respectively. The lower in silico yield of succinic acid was found to be due to the insufficient reducing power. but this lower yield could be increased to its theoretical yield by supplying more reducing power. The maximum theoretical yield of ethanol could be achieved, when a reaction catalyzed by pyruvate decarboxylase was added in the metabolic network. Futhermore, optimal metabolic pathways for the production of various metabolites could be proposed, based on the results of metabolic flux analyses. In the case of succinic acid production, it was found that the pyruvate carboxylation pathway should be used for its optimal production in E. coli rather than the phosphoenolpyruvate carboxylation pathway.

• Animal Bioscience
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• 제37권3호
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• pp.522-535
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• 2024

Objective: Transition period is considered from 3 weeks prepartum to 3 weeks postpartum, characterized with dramatic events (endocrine, metabolic, and physiological) leading to occurrence of production diseases (negative energy balance/ketosis, milk fever etc). The objectives of our study were to analyze the periodic concentration of serum beta-hydroxy butyric acid (BHBA), glucose and oxidative markers along with identification, and validation of the putative markers of negative energy balance in buffaloes using in-silico and quantitative real time-polymerase chain reaction (qRT-PCR) assay. Methods: Out of 20 potential markers of ketosis identified by in-silico analysis, two were selected and analyzed by qRT-PCR technique (upregulated; acetyl serotonin o-methyl transferase like and down regulated; guanylate cyclase activator 1B). Additional two sets of genes (carnitine palmotyl transferase A; upregulated and Insulin growth factor; downregulated) that have a role of hepatic fatty acid oxidation to maintain energy demands via gluconeogenesis were also validated. Extracted cDNA (complementary deoxyribonucleic acid) from the blood of the buffaloes were used for validation of selected genes via qRTPCR. Concentrations of BHBA, glucose and oxidative stress markers were identified with their respective optimized protocols. Results: The analysis of qRT-PCR gave similar trends as shown by in-silico analysis throughout the transition period. Significant changes (p<0.05) in the levels of BHBA, glucose and oxidative stress markers throughout this period were observed. This study provides validation from in-silico and qRT-PCR assays for potential markers to be used for earliest diagnosis of negative energy balance in buffaloes. Conclusion: Apart from conventional diagnostic methods, this study improves the understanding of putative biomarkers at the molecular level which helps to unfold their role in normal immune function, fat synthesis/metabolism and oxidative stress pathways. Therefore, provides an opportunity to discover more accurate and sensitive diagnostic aids.

• 한국산학기술학회논문지
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• 제22권4호
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• pp.483-492
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• 2021

곽향은 식욕부진, 메스꺼움 등의 치료에 사용될 뿐만 아니라 최근에는 항당뇨 효능도 알려졌다. 본 연구에서는 곽향의 항산화력과 주요 성분들을 조사한 다음, in-silico 방법론을 적용하여 타겟 단백질들을 예측하였다. 먼저 메탄올 추출물의 DPPH와 ABTS 라디칼 소거능의 EC50 값은 각각 78.6 ㎍/mL과 31.0 ㎍/mL이었다. 이것은 ascorbic acid의 값(9.9 ㎍/mL, 5.2 ㎍/mL)과 비교할 때 항산화력이 뛰어나다고 할 수 있다. HPLC-PDA-MS/MS를 이용하여 성분들을 정성 분석한 결과, 추출물의 주요 화합물로 rosmarinic acid, tilianin, agastachoside 그리고 acacetin을 확인하였다. 이들 성분들의 항당뇨 작용 타겟 단백질을 DIA-DB 서버를 사용하여 구조 유사도와 inverse doking 방법론을 적용하여 예측하였다. 본 가상 탐색 결과, 주요 타겟 단백질들은 PPAR-γ, DPP IV, glucokinase, α-glucosidase, SGLT2, aldose reductase, corticosteroid 11-beta-dehydrogenase로 예측되었다. 그리고 이들 단백질들 중 일부는 이미 실험적으로 검증된 타겟 단백질이었다. 따라서 in silico 검색 방법이 유효하다고 생각할 수 있다. 마지막으로 활성성분들의 최적의 추출 조건을 결정하기 위하여 여러 추출 용매들로 곽향을 추출하였다. 여러 유기 용매들 중에는 메탄올이 그리고 에탄올-물 혼합용매에서는 80% 에탄올이 가장 효과적인 추출 용매로 확인되었다.