• The Korean Journal of Pesticide Science
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• v.11 no.2
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• pp.72-81
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• 2007

Quantitative structure-activity relationships (QSARs) on the pre-emergency herbicidal activity and reactivity of a series of new O,O-dialkyl-1-phenoxyacetoxy-1-methylphosphonates (S) analogues against seed of cucumber (Cucumus Sativa) were discussed quantitatively using 2D-QSAR and HQSAR methods. The statistical values of HQSAR model were better than that of 2D-QSAR model. From the frontier molecular orbital (FMO) interaction between substrate molecule (S) and $BH^+$ ion (I) in PDH enzyme, the electrophilic reaction was superior in reactivity. From the effect of substituents, $R_2$-groups in substrate molecule (S) contributed to electrophilic reaction with carbonyl oxygen atom while X, Y-groups contributed to nucleophilic reaction with carbonyl carbon atom. And the influence of X,Y-groups was more effective than that of $R_2$-groups. As a results of 2D-QSAR model (I & II) and atomic contribution maps with HQSAR model, the more length of X, Y-groups is longer, the more herbicidal activity tends to increased. And also, the optimal ${\epsilon}LUMO$ energy, $({\epsilon}LUMO)_{opt.}$=-0.479 (e.v.) of substrate molecule is important factor in determining the herbicidal activity. It is predicted that the herbicidal activity proceeds through a nucleophilic reaction. From the analytical results of 2D-QSAR and HQSAR model, it is suggested that the structural distinctions and descriptors that contribute to herbicidal activities will be able to applied new herbicide design.

• The Korean Journal of Pesticide Science
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• v.12 no.1
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• pp.9-17
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• 2008

QSARs (Quantitative structure-activity relationships) between a series of new cyclohexanedione derivatives (5-benzofuryl-2-[1-(alkoxyimino)-alkyl]-3-hydroxycyclohex-2-en-1-ones) and their herbicidal activity against Rice plant (Oryza sativa L.) and Barnyard grass (Echinochloa crus-galli.) were discussed quantitatively using 2D-QSAR and holographic (H) QSAR methods. Generally, the HQSAR models have better predictability and fitness than the 2D-QSAR models. The herbicidal activities against Barnyard grass with 2D-QSAR II model were dependent upon Balaban indice (BI) of molecule and hydrophobicity of $R_1$ and $R_3$ group. And also, the $R_3=ethyl$ group, according to the information of the optimized HQSAR IV model, was more contribute to the herbicidal activities against Rice plant, while the 5-(cyclohex-3-enyl)-2,3-dihydrobenzofuran ring part was not contribute to the herbicidal activities against two plants.

• Journal of Integrative Natural Science
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• v.4 no.3
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• pp.210-215
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• 2011

Holographic quantitative structure-activity relationships (HQSAR) is a useful tool to correlates structures with their biological activities. HQSAR is a two dimensional (2D) QSAR methodology, which generates QSAR equations through 2D fingerprint and correlates it with biological activity. Here, we report a 2D-QSAR model for a series of fifty-one 3,4-dihydroxychalcones derivatives utilizing HQSAR methodology. We developed HQSAR model with 6 optimum numbers of components (ONC), which resulted in cross-validated correlation coefficient ($q^2$) of 0.855 with 0.283 standard error of estimate (SEE). The non-cross-validated correlation coefficient (r2) with 0.966 indicates the model is predictive enough for analysis. Developed HQSAR model was binned in to a hologram length of 257. Atomic contribution map revealed the importance of dihydroxy substitution on phenyl ring.

• Bulletin of the Korean Chemical Society
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• v.25 no.10
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• pp.1513-1520
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• 2004

We investigate a series of synthesized ${\beta}$-methoxyacrylate analogues for their 3D QSAR & HQSAR against Magnaporthe grisea (Rice Blast Disease). We perform the three-dimensional Quantitative Structure-Activity Relationship (3D-QSAR) studies, using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) procedure. In addition, we carry out a two-dimensional Quantitative Structure-Activity Relationship (2D-QSAR) study, using the Hologram QSAR (HQSAR). We perform these studies, using 53 compounds as a training set and 10 compounds as a test set. The predictive QSAR models have conventional $r^2$ values of 0.955 at CoMFA, 0.917 at CoMSIA, and 0.910 at HQSAR respectively; similarly, we obtain cross-validated coefficient $q^2$ values of 0.822 at CoMFA, 0.763 at CoMSIA, and 0.816 at HQSAR, respectively. From these studies, the CoMFA model performs better than the CoMSIA model.

• Journal of Applied Biological Chemistry
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• v.50 no.2
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• pp.52-57
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• 2007

Quantitative structure-activity relationships (QSARs) on the inhibition activities by oleanolic acid analogues (1-19) as a potent inhibitor against protein tyrosine phosphatase-1B were studied quantitatively using 2D-QSAR and HQSAR methodologies. The inhibition activity was dependent on the variations of $R_{4-}$substituent, and as shown in 2D-QSAR model ($r^2=0.928$), it has a tendency to increase as the negative Randic Indice (RI) goes up. The size of the molecular fragments used in HQSAR varied from five to eight. The fragment distinctions had the best statistic value, whose predictability is $q^2=0.785$ and correlation coefficient is $r^2=0.970$, on condition of connections. From the atomic contribution maps, the factor that contributes to the inhibition activities is the $C_{15}{\sim}C_{17}$ bond in the D ring. From the analysis result of these two the models, the structural distinctions and descriptors that contribute to the inhibition activities were obtained.

• Bulletin of the Korean Chemical Society
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• v.30 no.11
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• pp.2739-2748
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• 2009

Hologram and three dimensional quantitative structure activity relationship (3D QSAR) studies for a series of anilinobipyridine JNK3 inhibitors were performed using various alignment-based comparative molecular field analysis (COMFA) and comparative molecular similarity indices analysis (CoMSIA). The in vitro JNK3 inhibitory activity exhibited a strong correlation with steric and electrostatic factors of the molecules. Using four different types of alignments, the best model was selected based on the statistical significance of CoMFA ($q_2\;=\;0.728,\;r_2\;=\;0.865$), CoMSIA ($q_2\;=\;0.706,\;r_2\;=\;0.960$) and Hologram QSAR (HQSAR: $q_2\;=\;0.838,\;r_2\;=\;0.935$). The graphical analysis of produced CoMFA and CoMSIA contour maps in the active site indicated that steric and electrostatic interactions with key residues are crucial for potency and selectivity of JNK3 inhibitors. The HQSAR analysis showed a similar qualitative conclusion. We believe these findings could be utilized for further development of more potent and selective JNK3 inhibitors.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2004.11a
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• pp.210-218
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• 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
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• v.31 no.10
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• pp.2761-2770
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• 2010

In this study, we have developed QSAR models for a series of 38 piperidine-4-carboxamide CCR5 antagonists using CoMFA, CoMSIA and HQSAR methods. Developed models showed good statistics in terms of $q^2$ and $r^2$ values. Best predictions obtained with standard CoMFA model ($r^2$ = 0.888, $q^2$ = 0.651) and combined CoMSIA model ($r^2$ = 0.892, $q^2$ = 0.665) with electrostatics and H-bond acceptor parameter. The validity of developed models was assessed by test set of 9 compounds, which showed good predictive correlation coefficient for CoMFA (0.804) and CoMSIA (0.844). Bootstrapped analysis showed statistically significant and robust CoMFA (0.968) and CoMSIA (0.936) models. Best HQSAR model was obtained with a $q^2$ of 0.662 and $r^2$ of 0.936 using atom, connection, hydrogen, donor and acceptor as parameters and fragment size (7-10) with optimum number of 6 components. Predictive power of developed HQSAR model was proved by test set and it was found to be 0.728.

• Journal of Integrative Natural Science
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• v.8 no.1
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• pp.1-12
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• 2015

CRTh2 receptor is an important mediator of the inflammatory effects and act as beneficial target for the treatment of asthma, COPD, allergic rhinitis and atopic dermatitis. In the present work, Hologram QSAR studies were conducted on a series of 50 training set CRTh2 antagonists (2-(2-(benzylthio)-1H-benzo[d]imidazol-1-yl acetic acids). The best HQSAR model was obtained using atoms, bonds, connections and donor/acceptor as fragment distinction parameter using hologram length 257 and 6 components with fragment size of minimum 7 and maximum 10. Significant cross-validated correlation coefficient ($q^2=0.786$) and non cross-validated correlation coefficients ($r^2=0.954$) were obtained. The model was then used to evaluate the 15 external test compounds which are not included in the training set and the predicted values were in good agreement with the experimental results ($r^2_{pred}=0.739$). Contribution map show that presence of C ring and its substituents makes big contributions for activities. The HQSAR model and analysis from the contribution map could be useful for further design of novel structurally related CRTh2 antagonists.

• Journal of Integrative Natural Science
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• v.10 no.3
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• pp.141-147
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• 2017

Vascular endothelial growth factor (VEGF) is an important signaling protein involved in angiogenesis, which is the formation of new blood vessels from pre-existing vessels. Consequently, blocking of the vascular endothelial growth factor receptor (VEGFR-2) by small molecule inhibitors leads to the inhibition of cancer induced angiogenesis. In this study, we performed a two dimensional quantitative structure activity relationship (2D-QSAR) study of 38 N-Phenyl-N'-{4-(4-quinolyloxy) phenyl} urea derivatives as VEGFR-2 inhibitors based on hologram quantitative structure-activity (HQSAR). The model developed showed reasonable $q^2=0.521$ and $r^2=0.932$ values indicating good predictive ability and reliability. The atomic contribution map analysis of most active compound (compound 7) indicates that hydrogen and oxygen atoms in the side chain of ring A and oxygen atom in side chain of ring C contributes positively to the activity of the compounds. The HQSAR model developed and the atomic contribution map can serve as a guideline in designing new compounds for VEGFR-2 inhibition.