• Title/Summary/Keyword: Quantum molecular descriptors

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Quantitative Structure-Activity Relationships (QSAR) Study on C-7 Substituted Quinolone

  • Lee, Geun U;Gwon, Sun Yeong;Hwang, Seon Gu;Lee, Jae Uk;Kim, Ho Jing
    • Bulletin of the Korean Chemical Society
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    • v.17 no.2
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    • pp.147-152
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    • 1996
  • To see the quantitative relationship between the structures of the C-7 substituted quinolones and their antibacterial activities, theoretical parameters such as the molecular van der Waals volume, surface area and some electrostatic parameters based on the molecular electrostatic potential, which represent lipophilicity, and some quantum mechanical parameters are introduced as descriptors. The sixteen substituted quinolone derivatives and twenty bacteria are used for the study. It is found that the QSARs of C-7 substituted quinolones are obtained for eleven bacteria and our descriptors are more useful for Gram positive organisms than negative ones. It is also shown that molecular surface area (or molecular Waals volume) of the C-7 substituent and net charge of C-7 atom of the quinolones are the descriptors of utmost importance.

Quantitative Structure-Activity Relationship(QSAR) Study of New Fluorovinyloxycetamides

  • Jo, Du Ho;Lee, Seong Gwang;Kim, Beom Tae;No, Gyeong Tae
    • Bulletin of the Korean Chemical Society
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    • v.22 no.4
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    • pp.388-394
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    • 2001
  • Quantitative Structure-Activity Relationship (QSAR) have been established of 57 fluorovinyloxyacetamides compounds to correlate and predict EC50 values. Genetic algorithm (GA) and multiple linear regression analysis were used to select the descriptors and to generate the equations that relate the structural features to the biological activities. This equation consists of three descriptors calculated from the molecular structures with molecular mechanics and quantum-chemical methods. The results of MLR and GA show that dipole moment of z-axis, radius of gyration and logP play an important role in growth inhibition of barnyard grass.

Quantum Chemical Studies of Some Sulphanilamide Schiff Bases Inhibitor Activity Using QSAR Methods

  • Baher, Elham;Darzi, Naser;Morsali, Ali;Beyramabadi, Safar Ali
    • Journal of the Korean Chemical Society
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    • v.59 no.6
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    • pp.483-487
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    • 2015
  • The different calculated quantum chemical descriptors by DFT method were used for prediction of some sulphanilamide Schiff bases inhibitor activity as a binding constant (log K). Multiple linear regression (MLR) and artificial neural network (ANN) were employed for developing the useful quantitative structure activity relationship (QSAR) model. The obtained results presented superiority of ANN model over the MLR one. The offering QSAR model is very easy to computation and Physico-Chemically interpretable. Sensitivity analysis was used to determine the relative importance of each descriptor in ANN model. The order of importance of each descriptor according to this analysis is: molecular volume, molecular weight and dipole moment, respectively. These descriptors appear good information related to different structure of sulphanilamide Schiff bases can participate in their inhibitor activity.

A Comparative QSPR Study of Alkanes with the Help of Computational Chemistry

  • Kumar, Srivastava Hemant
    • Bulletin of the Korean Chemical Society
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    • v.30 no.1
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    • pp.67-76
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    • 2009
  • The development of a variety of methods like AM1, PM3, PM5 and DFT now allows the calculation of atomic and molecular properties with high precision as well as the treatment of large molecules with predictive power. In this paper, these methods have been used to calculate a number of quantum chemical descriptors (like Klopman atomic softness in terms of $E_n^{\ddag}\;and\;E_m^{\ddag}$, chemical hardness, global softness, electronegativity, chemical potential, electrophilicity index, heat of formation, total energy etc.) for 75 alkanes to predict their boiling point values. The 3D modeling, geometry optimization and semiempirical & DFT calculations of all the alkanes have been made with the help of CAChe software. The calculated quantum chemical descriptors have been correlated with observed boiling point by using multiple linear regression (MLR) analysis. The predicted values of boiling point are very close to the observed values. The values of correlation coefficient ($r^2$) and cross validation coefficient ($r_{cv}^2$) also indicates the generated QSPR models are valuable and the comparison of all the methods indicate that the DFT method is most reliable while the addition of Klopman atomic softness $E_n^{\ddag}$ in DFT method improves the result and provides best correlation.

Theoretical Approach for Physicochemical Factors Affecting Human Toxicity of Dioxins (다이옥신의 인체 독성에 영향을 미치는 물리화학적 인자에 대한 이론적 접근)

  • 황인철;박형석
    • Environmental Analysis Health and Toxicology
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    • v.14 no.1_2
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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.

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Statistical Study For The prediction of pKa Values of Substituted Benzaldoxime Based on Quantum Chemicals Methods

  • Al-Hyali, Emad A.S.;Al-Azzawi, Nezar A.;Al-Abady, Faiz M.H.
    • Journal of the Korean Chemical Society
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    • v.55 no.5
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    • pp.733-740
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    • 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.

QM and Pharmacophore based 3D-QSAR of MK886 Analogues against mPGES-1

  • Pasha, F.A.;Muddassar, M.;Jung, Hwan-Won;Yang, Beom-Seok;Lee, Cheol-Ju;Oh, Jung-Soo;Cho, Seung-Joo;Cho, Hoon
    • Bulletin of the Korean Chemical Society
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    • v.29 no.3
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    • pp.647-655
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    • 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.

Theoretical Study of Thiazole Adsorption on the (6,0) zigzag Single-Walled Boron Nitride Nanotube

  • Moradi, Ali Varasteh;Peyghan, Ali Ahmadi;Hashemian, Saeede;Baei, Mohammad T.
    • Bulletin of the Korean Chemical Society
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    • v.33 no.10
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    • pp.3285-3292
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    • 2012
  • The interaction of thiazole drug with (6,0) zigzag single-walled boron nitride nanotube of finite length in gas and solvent phases was studied by means of density functional theory (DFT) calculations. In both phases, the binding energy is negative and presenting characterizes an exothermic process. Also, the binding energy in solvent phase is more than that the gas phase. Binding energy corresponding to adsorption of thiazole on the BNNT model in the gas and solvent phases was calculated to be -0.34 and -0.56 eV, and about 0.04 and 0.06 electrons is transferred from the thiazole to the nanotube in the phases. The significantly changes in binding energies and energy gap values by the thiazole adsorption, shows the high sensitivity of the electronic properties of BNNT towards the adsorption of the thiazole molecule. Frontier molecular orbital theory (FMO) and structural analyses show that the low energy level of LUMO, electron density, and length of the surrounding bonds of adsorbing atoms help to the thiazole adsorption on the nanotube. Decrease in global hardness, energy gap and ionization potential is due to the adsorption of the thiazole, and consequently, in the both phases, stability of the thiazole-attached (6,0) BNNT model is decreased and its reactivity increased. Presence of polar solvent increases the electron donor of the thiazole and the electrophilicity of the complex. This study may provide new insight to the development of functionalized boron nitride nanotubes as drug delivery systems for virtual applications.