• 대한화학회지
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• 제45권5호
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• pp.422-428
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• 2001

기체 크로마토그래피에서 PAH와 그것의 유도체들의 상대적 용리시간을 인공신경망분석과 다변량 선형 회귀분석을 사용하여 학습한 후, 시험세트들의 상대적 용리시간을 예측하였다. QSRR에서 PAH와 그것의 유도체의 주요한 설명인자는 분자량의 제곱근, 분자의 연결지수($^1{\chi}_v$), 분자 쌍극자모멘트 및 분자의 길이와 폭의 비율(L/B)이었다. 다변량선형회귀분석에 의하면 큰 분자일수록 용리시간은 길어지며 또한 L/B의 값이 커지면 용리시간이 증가하는 것으로 보아 슬롯이론을 따르고 있음을 알 수 있었다. 반면에 설명인자 사이의 선형 독립성에 영향을 받지 않는 인공신경망 분석결과에 의하면 분자량과 분자 쌍극자 모멘트가 주요한 인자로 작용하고 있었다. 시험세트의 예측 정확도를 나타내는 분산은 선형회귀분석에서는 1.860, 인공신경망분석법에서 0.206으로서 인공신경망 분석법이 다변량회귀분석보다 더 좋은 예측방법임을 알 수 있었다.

• 대한화학회지
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• 제60권4호
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• pp.225-234
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• 2016

The activity of 34 sulfonamide derivatives has been estimated by means of multiple linear regression (MLR), artificial neural network (ANN), simulated annealing (SA) and genetic algorithm (GA) techniques. These models were also utilized to select the most efficient subsets of descriptors in a cross-validation procedure for non-linear -log (IC50) prediction. The results obtained using GA-ANN were compared with MLR-MLR, MLR-ANN, SA-ANN and GA-ANN approaches. A high predictive ability was observed for the MLR-MLR, MLR-ANN, SA-ANN and MLR-GA models, with root mean sum square errors (RMSE) of 0.3958, 0.1006, 0.0359, 0.0326 and 0.0282 in gas phase and 0.2871, 0.0475, 0.0268, 0.0376 and 0.0097 in solvent, respectively (N=34). The results obtained using the GA-ANN method indicated that the activity of derivatives of sulfonamides depends on different parameters including DP03, BID, AAC, RDF035v, JGI9, TIE, R7e+, BELM6 descriptors in gas phase and Mor 32u, ESpm03d, RDF070v, ATS8m, MATS2e and R4p, L1u and R3m in solvent. In conclusion, the comparison of the quality of the ANN with different MLR models showed that ANN has a better predictive ability.

• Molecular & Cellular Toxicology
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• 제5권1호
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• pp.14-22
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• 2009

In vitro cytotoxicity of 23 alkyl phenols (APs) on human cervical cancer cell lines (HeLa) was determined using the lactate dehydrogenase (LDH) cytotoxicity assay. Two different sets of descriptors were used to construct the calibration model based on Genetic Algorithm-Multiple Linear Regression (GA-MLR) based on the experimental data. A statistically robust Structure-Activity Relationships (QSAR) model was achieved ($R^2$=95.05%, $Q^2_{LOO}$=91.23%, F=72.02 and SE= 0.046) using three Dragon descriptors based on Me (0D-Constitutional descriptor), BELp8 (2D-Burden eigenvalue descriptor) and HATS8p (3D-GETAWAY descriptor). However, external validation could not fully prove its validity of the selected QSAR in characterization of the cytotoxicity of APs towards HeLa cells. Nevertheless, the cytotoxicity profiles showed a finding that 4-n-octylphenol (4-NOP), 4-tert-octyl-phenol (4-TOP), 4-n-nonylphenol (4-NNP) had a more potent cytotoxic effect than other APs tested, inferring that increased length and molecular bulkiness of the substituent had important influence on the LDH cytotoxicity.

• Environmental Analysis Health and Toxicology
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• 제14권1_2호
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• pp.65-73
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• 1999

Dioxins refer to a family of chemicals comprising 75 polychlorinated dibenzo-p-dioxin (PCDD) and 135 polychlorinated dibenzo-p-furan (PCDF) congeners, which may cause skin disorder, human immune system disruption, birth defects, severe hormonal imbalance, and cancer. The effects of exposure of dioxin-like compounds such as PCBs are mediated by binding to the aryl hydrocarbon receptor (AHR), which is a ligand-activated transcription factor. To grasp physicochemical factors affecting human toxicity of dioxins, six geometrical and topological indices, eleven thermodynamic variables, and quantum mechanical descriptors including ESP (electrostatic potential) were analyzed using QSAR and semi-empirical AM1 method. Planar dioxins with high lipophilicity and large surface tension show the probability that negative electrostatic potential in the lateral oxygen may make hydrogen bonding with DNA bases to be a carcinogen.

• Membrane and Water Treatment
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• 제1권3호
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• pp.181-192
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• 2010

A linear quantitative structure-property relationship (QSPR) model is presented for the prediction of rejection in permeation through membrane. The model was produced by using the multiple linear regression (MLR) technique on the database consisting of retention data of 25 pesticides in 4 different membrane separation experiments. Among the 3224 different physicochemical, topological and structural descriptors that were considered as inputs to the model only 50 were selected using several criteria of elimination. The physical meaning of chosen descriptor is discussed in detail. The accuracy of the proposed MLR models is illustrated using the following evaluation techniques: leave-one-out cross validation procedure, leave-many-out cross validation procedure and Y-randomization.

• Interdisciplinary Bio Central
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• 제2권2호
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• pp.6.1-6.5
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• 2010

Fragment molecular orbital (FMO) method provides a novel tool for ab initio calculations of large biomolecules. This method overcomes the size limitation difficulties in conventional molecular orbital methods and has several advantages compared to classical force field approaches. While there are many features in this method, we here focus on explaining the issues related to protein-ligand binding: FMO method provides useful interaction-analysis tools such as IFIE, CAFI and FILM. FMO calculations can provide not only binding energies, which are well correlated with experimental binding affinity, but also QSAR descriptors. In addition, FMO-derived charges improve the descriptions of electrostatic properties and the correlations between docking scores and experimental binding affinities. These calculations can be performed by the ABINIT-MPX program and the calculation results can be visualized by its proper BioStation Viewer. The acceleration of FMO calculations on various computer facilities is ongoing, and we are also developing methods to deal with cytochrome P450, which belongs to the family of drug metabolic enzymes.

• Journal of Plant Biotechnology
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• 제46권2호
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• pp.61-70
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• 2019

There is vast genetic diversity of Myanmar Mangoes. This study mainly focused on indigenous thirteen different mango landraces cultivated in central area of Myanmar, Kyauk-se District and their fruit characteristics by 18 descriptors together with genetic relationship among them by 12 SSR markers. Based on the morpho-physical characters, a wide variation among accessions was found. Genetic characterization of thirteen mango genotypes resulted in the detection of 302 scorable polymorphic bands with an average of 4.33 alleles per locus and an average polymorphism information content (PIC) of 0.7. All the genotypes were grouped into two major clusters by UPGMA cluster analysis and a genetic similarity was observed in a range of 61 ~ 85%. This study may somehow contribute insights into the identification of regional mango diversity in Myanmar and would be useful for future mango breeding program.

• Bulletin of the Korean Chemical Society
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• 제33권2호
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• pp.613-619
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• 2012

We applied several machine learning methods for developing QSAR models for prediction of acute toxicity to fathead minnow. The multiple linear regression (MLR) and artificial neural network (ANN) method were applied to predict 96 h $LC_{50}$ (median lethal concentration) of 555 chemical compounds. Molecular descriptors based on 2D chemical structure were calculated by PreADMET program. The recursive partitioning (RP) model was used for grouping of mode of actions as reactive or narcosis, followed by MLR method of chemicals within the same mode of action. The MLR, ANN, and two RP-MLR models possessed correlation coefficients ($R^2$) as 0.553, 0.618, 0.632, and 0.605 on test set, respectively. The consensus model of ANN and two RP-MLR models was used as the best model on training set and showed good predictivity ($R^2$=0.663) on the test set.

• Bulletin of the Korean Chemical Society
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• 제26권1호
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• pp.85-90
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• 2005

MX and its analogs are synthesized and modeled by quantitative structure activity relationship (QSAR) study including comparative molecular field analysis (CoMFA). As a result, factors affecting this class of compounds have been found to be steric and electrostatic effects. Because hologram quantitative structure activity relationship (HQSAR) technique is based on the 2-dimensional descriptors, this is free of ambiguity of conformational selection and molecular alignment. In this study we tried to include all the data available from the literature, and modeled with the HQSAR technique. Among the parameters affecting fragmentation, connectivity was the most important one for the whole compounds, giving good statistics. Considering additional parameters such as bond specification only slightly improved the model. Therefore connectivity has been found to be the most appropriate to explain the mutagenicity for this class of compounds.

• Bulletin of the Korean Chemical Society
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• 제33권3호
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• pp.855-861
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• 2012

A pioneering version of an on-line management system for high-energy molecules (MS-HEMs) was developed by the ADD and BMDRC in Korea. The current system can manage the physicochemical and explosive properties of virtual and existing HEMs. The on-line MS-HEMs consist of three main routines: management, calculation, and search. The management routine contains a user-friendly interface to store and manage molecular structures and other properties of the new HEMs. The calculation routine automatically calculates a number of compositional and topological molecular descriptors when a new HEM is stored in the MS-HEMs. Physical properties, such as the heat of formation and density, can also be calculated using group additivity methods. In addition, the calculation routine for the impact sensitivity can be used to obtain the safety nature of new HEMs. The impact sensitivity was estimated in a knowledge-based manner using in-house neural network code. The search routine enables general users to find an exact HEM and its properties by sketching a 2D chemical structure, or to retrieve HEMs and their properties by giving a range of properties. These on-line MS-HEMs are expected be powerful tool for deriving novel promising HEMs.