• Bulletin of the Korean Chemical Society
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• v.25 no.12
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• pp.1874-1876
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• 2004

Quantitative structure activity relationship has been probed for spirosuccinimide-fused tetrahydropyrrolo[1,2-a]pyrazine-1,3-dione derivatives acting as aldose reductase inhibitors. While the spirosuccinimide compounds contain a chiral center, the aldose reductase inhibition assay was performed with racemic mixtures in the published work. As the physicochemical descriptors of the QSAR analysis must be evaluated for a definite molecular structure, we devise a new 'racemic' descriptor as the arithmetic mean of the (R)-enantiomer descriptor and the (S)-enantiomer descriptor. The resultant QSAR model derived from the racemic descriptors outperforms the original QSAR models, closely reproducing the observed activity of optically pure enantiomers as well as racemic mixtures.

• Bulletin of the Korean Chemical Society
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• v.25 no.7
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• pp.1046-1050
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• 2004

Six physical properties (enthalpy, density, decomposition temperature, solubility in water, pKa values, and hydronium potential) were examined by molecular modeling techniques. The molecular connectivity index, Wiener distance index, and Ad hoc descriptor are employed as structural parameters to encode information about branching, size, cyclization, unsaturation, heteroatom content, and polarizability. This paper examines the correlation of the molecular modeling techniques parameters and the physicochemical properties of amino acids. As a results, calculated values were in agreement with experimental data in the above six physical properties of amino acids and the molecular connectivity index was superior to the other indices in fitting the calculated data.

• Membrane and Water Treatment
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• v.1 no.3
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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.

• Bulletin of the Korean Chemical Society
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• v.15 no.2
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• pp.106-112
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• 1994

Six physical properties (molecular weight, heat capacity, side chain weight, side chain volume, standard entropy and partial molar volume) of amino acids, peptides and their derivatives were examined by molecular modeling techniques. The molecular connectivity index, Wiener distance index and ad hoc descriptor are employed as structural parameters to encode information about branching, size, cyclization, unsaturation, heteroatom content and polarizability. This paper examines the correlation of the molecular modeling techique's parameters and the physicochemical properties of amino acids and their derivatives. As a result, calculated values were in agreement with experimental data in the above six physical properties of amino acids, peptides and their derivatives and the molecular connectivity index was superior to the other indices in fitting the calculated data.

• Analytical Science and Technology
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• v.28 no.4
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• pp.270-277
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• 2015

Boiling point (BP) is one of the most fundamental physicochemical properties of organic compounds to characterize and identify the thermal characteristics of target compounds. Previously developed QSPR equations, however, still had some limitation for the specific compounds, like high-energy molecules, mainly because of the lack of experimental data and less coverage. A large BP dataset of 5,923 solid organic compounds was finally secured in this study, after dedicated pre-filtration of experimental data from different sources, mostly consisting of compounds not only from common organic molecules but also from some specially used molecules, and those dataset was used to build the new BP prediction model. Various machine learning methods were performed for newly collected data based on meaningful 2D descriptor set. Results of combined check showed acceptable validity and robustness of our models, and consensus approaches of each model were also performed. Applicability domain of BP prediction model was shown based on descriptor of training set.

• Bulletin of the Korean Chemical Society
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• v.33 no.3
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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.