• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2005.09a
• /
• pp.134-138
• /
• 2005

The design of ion channel targeted library is a valuable methodology that can aid in the selection and prioritization of potential ion channel-likeness for ion-channel-targeted bio-screening from large commercial available chemical pool. The differences of property profiling between the 93 ion-channel active compounds from MDDR and CMC database and the ACDSC compounds were classified by suitable descriptors calculated with preADME software. Through the PCA, clustering, and similarity analysis, the compounds capable of ion channel activity were defined in ACDSC compounds pool. The designed library showed a tendency to follow the property profile of ion-channel active compounds and can be implemented with great time and economical efficiencies of ligand-based drug design or virtual high throughput screening from an enormous small molecule space.

• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2004.11a
• /
• pp.210-218
• /
• 2004

Poly(ADP-ribose)polymerase-1 (PARP-1) is a nuclear enzyme involved in various physical functions related to genomic repair, and PARP inhibitors have therapeutic application in a variety of neurological diseases. Docking and the QSAR (quantitative structure-activity relationships) studies for 52 PARP-1 inhibitors were conducted using FlexX algorithm, comparative molecular field analysis (CoMFA), and hologram quantitative structure-activity relationship analysis (HQSAR). The resultant FlexX model showed a reasonable correlation (r$^{2}$ = 0.701) between predicted activity and observed activity. Partial least squares analysis produced statistically significant models with q$^{2}$ values of 0.795 (SDEP=0.690, r$^{2}$=0.940, s=0.367) and 0.796 (SDEP=0.678, r$^{2}$ = 0.919, s=0.427) for CoMFA and HQSAR, respectively. The models for the entire inhibitor set were validated by prediction test and scrambling in both QSAR methods. In this work, combination of docking, CoMFA with 3D descriptors and HQSAR based on molecular fragments provided an improved understanding in the interaction between the inhibitors and the PARP. This can be utilized for virtual screening to design novel PARP-1 inhibitors.

• Bulletin of the Korean Chemical Society
• /
• v.32 no.12
• /
• pp.4341-4346
• /
• 2011

Impact sensitivity, one of the most important screening factors for novel high energy density materials (HEDMs), was predicted by use of quantitative structure-property relationship (QSPR) based on the electrostatic potential (ESP) values calculated on the van der Waals molecular surface (MSEP). Among various 3D descriptors derived from MSEP, we utilized total and positive variance of MSEP, and devised a new QSPR equation by combining three other parameters. We employed 37 HEDMs bearing a benzene scaffold and nitro substituents, which were also utilized by Rice and Hare. All the molecular structures were optimized at the B3LYP/6-31G(d) level of theory and confirmed as minima by the frequency calculations. Our new QSPR equation provided a good result to predict the impact sensitivities of the molecules in the training set including zwitterionic molecules.

• Journal of the Korean Chemical Society
• /
• v.55 no.5
• /
• pp.733-740
• /
• 2011

Multiple regression analysis was used for the calculation of pKa values of 15 substituted benzaldoximes by using various types of descriptors as parameters. These descriptors are based on quantum mechanical treatments. They were derived by employing semi-empirical calculation represented by the PM3 model and an Abinitio method expressed by Hartree-Fock(HF) model performed at the 6-311 G(d, p) level of theory. The parameters tested for their ability to represent the variations observed in the experimental pKa(s) are atomic and structural properties including Muliken charges on the atoms of hydroxyl group and C=N bond, the angle $C_6-C_1-C_7$, and length of O-H bond. Molecular properties are also used like energies of HOMO and LUMO, hardness(${\eta}$), chemical potential(${\mu}$), total energy(TE), dipole of molecule(DM), and electrophilicity index(W). The relation between pKa values and each of these parameters of the studied compounds is investigated. Depending on these relations, two sets of parameters were constructed for comparison between the PM3 and HF methods. The results obtained favor the Abinitio method for such applications although both models proved to have high predictive power and have sufficient reliability to describe the effect of substituents on pKa values of benzaldoxime compounds under consideration which is clear from the values of correlation coefficient $R^2$ obtained and the consistency between the experimental and the calculated values.

• Bulletin of the Korean Chemical Society
• /
• v.33 no.5
• /
• pp.1527-1535
• /
• 2012

Selection of the most informative molecular descriptors from the original data set is a key step for development of quantitative structure activity/property relationship models. Recently, mutual information (MI) has gained increasing attention in feature selection problems. This paper presents an effective mutual information-based feature selection approach, named mutual information maximization by replacing collinear variables (MIMRCV), for nonlinear quantitative structure-property relationship models. The proposed variable selection method was applied to three different QSPR datasets, soil degradation half-life of 47 organophosphorus pesticides, GC-MS retention times of 85 volatile organic compounds, and water-to-micellar cetyltrimethylammonium bromide partition coefficients of 62 organic compounds.The obtained results revealed that using MIMRCV as feature selection method improves the predictive quality of the developed models compared to conventional MI based variable selection algorithms.

• Bulletin of the Korean Chemical Society
• /
• v.32 no.11
• /
• pp.3865-3872
• /
• 2011

A quantitative structure-property relationship (QSPR) study was performed for the prediction of the absorption maxima of azobenzene dyes. The entire set of 191 azobenzenes was divided into a training set of 150 azobenzenes and a test set of 41 azobenzenes according to Kennard and Stones algorithm. A seven-descriptor model, with squared correlation coefficient ($R^2$) of 0.8755 and standard error of estimation (s) of 14.476, was developed by applying stepwise multiple linear regression (MLR) analysis on the training set. The reliability of the proposed model was further illustrated using various evaluation techniques: leave-many-out crossvalidation procedure, randomization tests, and validation through the test set.

• Journal of the Korean Chemical Society
• /
• v.44 no.6
• /
• pp.501-506
• /
• 2000

Some previous linear equations to predict hydrocarbon heats of formation are generalized. The basic molecular descriptors used for the QSPR analysis are atoms and chemcal bonds. This particular choice makes the method extremely simple and quite inexpensive. The predictions for a set of 19 alkenes yield deviations which are similar to experimental uncertainties. Some possible extensions of the method are pointed out.

• Bulletin of the Korean Chemical Society
• /
• v.24 no.12
• /
• pp.1757-1762
• /
• 2003

The interrelation between retention factors of several L-amino acids and their physico-chemical and structural properties can be determined in chromatographic research. In this paper we describe a predictor for retention factors with various properties of the L-amino acids. Eighteen L-amino acids are included in this study, and retention factors are measured experimentally by RP-HPLC. Binding energy ($E_b$), hydrophobicity (log P), molecular refractivity (MR), polarizability (${\alpha}$), total energy ($E_t$), water solubility (log S), connectivity index (${\chi}$) of different orders and Wiener index (w) are theoretically calculated. Relationships between these properties and retention factors are established, and their predictive and interpretive ability are evaluated. The equation of the relationship between retention factors and various descriptors of L-amino acids is suggested as linear and multiple linear form, and the correlation coefficients estimated are relatively higher than 0.90.

• Journal of the Korean Chemical Society
• /
• v.54 no.4
• /
• pp.363-373
• /
• 2010

Computational studies were carried out on the opiates morphine, heroin, codeine, pentazocine, and buprenorphine, under the density functional theory. The geometric parameters of the pharmacophore and substituents were evaluated at the B3LYP/6-31+G(d) level of theory. The electronic structure calculations were performed using the same hybrid functional at the B3LYP/6-311++G (d,p) level of theory. The atomic charges were obtained by Mulliken population analysis. Given the reported biological activity, calculated partition coefficients, and electronic and geometric analysis, pentazocine and buprenorphine were chosen as models for proposed analogues. These analogues were then studied and compared with the model molecules. The study reveals that the geometry and electronic structure of the pharmacophore remains consistent in the presence of different substituents. Because the proposed analogues preserve the studied properties of the model molecules, it is likely that these analogues display biological activity.

• Bulletin of the Korean Chemical Society
• /
• v.29 no.3
• /
• pp.647-655
• /
• 2008

Microsomal prostaglandin E2 synthase (mPGES-1) is a potent target for pain and inflammation. Various QSAR (quantitative structure activity relationship) analyses used to understand the factors affecting inhibitory potency for a series of MK886 analogues. We derived four QSAR models utilizing various quantum mechanical (QM) descriptors. These QM models indicate that steric, electrostatic and hydrophobic interaction can be important factors. Common pharmacophore hypotheses (CPHs) also have studied. The QSAR model derived by best-fitted CPHs considering hydrophobic, negative group and ring effect gave a reasonable result (q2 = 0.77, r2 = 0.97 and Rtestset = 0.90). The pharmacophore-derived molecular alignment subsequently used for 3D-QSAR. The CoMFA (Comparative Molecular Field Analysis) and CoMSIA (Comparative Molecular Similarity Indices Analysis) techniques employed on same series of mPGES-1 inhibitors which gives a statistically reasonable result (CoMFA; q2 = 0.90, r2 = 0.99. CoMSIA; q2 = 0.93, r2 = 1.00). All modeling results (QM-based QSAR, pharmacophore modeling and 3D-QSAR) imply steric, electrostatic and hydrophobic contribution to the inhibitory activity. CoMFA and CoMSIA models suggest the introduction of bulky group around ring B may enhance the inhibitory activity.