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

• Bulletin of the Korean Chemical Society
• /
• v.33 no.1
• /
• pp.149-152
• /
• 2012

The (S)-(+)-decursin and its analogues are reported as potent inhibitors of melanin production in B16 murine melanoma cells. In order to understand the factors responsible for potency as well as inhibition of potency of (S)-(+)-decursin and its analogues, three-dimensional quantitative structure-activity relationship (3D-QSAR) studies were performed. Since receptor structures are not available, a pharmacophore model was constructed. Using PHASE, we generated 3 different models and selected the seven-site model, which returned excellent statistical values ($r^2$ = 0.9127, $Q^2$ = 0.6878, Pearson-R = 0.9014). Using the generated pharmacophore model, we screened a natural products library and obtained 4'-epi-decursin as the most related compound. 4'-epidecursin is similar to (S)-(+)-decursin, but shows additional interaction possibilities with tyrosinase. The study thus sheds some light on possibility of developing more potent tyrosinase inhibitors.

• Bulletin of the Korean Chemical Society
• /
• v.27 no.2
• /
• pp.273-276
• /
• 2006

Three dimensional quantitative structure-activity relationship studies for a series of isatin derivatives as a nonpeptidyl caspase-3 enzyme inhibitor were investigated using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The first approach of non-peptidyl small molecules by 3D QSAR may be useful in guiding further development of potent caspase-3 inhibitors.

• Molecular & Cellular Toxicology
• /
• v.2 no.3
• /
• pp.216-221
• /
• 2006

The cholinesterase-inhibiting organophosphorous (OP) compounds known as nerve agents are highly toxic. The principal toxic mechanism of OP compounds is the inhibition of acethylcholine esterase (AChE) by phosphorylation of its catalytic site. The reversible competitive inhibition of AChE may prevent the subsequent OP intoxication. In this study, three-dimensional quantitative structure-activity relationship (3D-QSAR) was performed to investigate the relationship between the 29 compounds with structural diversity and their bioactivities against AChE. In particular, predictive models were constructed using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA). The results indicate reasonable model for CoMFA ($q^{2}=0.453,\;r^{2}=0.697$) and CoMSIA ($q^{2}=0.518,\;r^{2}=0.696$). The presence of steric and hydophobic group at naphtyl moiety of the model may lead to the design of improved competitive inhibitors for organophosphorous intoxication.

• Journal of Integrative Natural Science
• /
• v.8 no.1
• /
• pp.40-47
• /
• 2015

Glycogen synthase kinase 3 (GSK-3) is a serine/threonine protein kinase that has recently emerged as a promising target in drug discovery. It is involved in multiple cellular processes and associated with the pathogenesis of several diseases. A three-dimensional quantitative structure-activity relationship (3D-QSAR) analysis was performed on a series of GSK-3 inhibitors to understand the structural basis for inhibitory activity. Comparative molecular field analysis (CoMFA) method was used to derive 3D-QSAR models. A reliable CoMFA model was developed using ligand-based alignment scheme. The model produced statistically acceptable results with a cross-validated correlation coefficient ($q^2$) of 0.594 and a non-cross-validated correlation coefficient ($r^2$) of 0.943. Robustness of the model was checked by bootstrapping and progressive scrambling analysis. This study could assist in the design of novel compounds with enhanced GSK-3 inhibitory activity.

• KSBB Journal
• /
• v.15 no.3
• /
• pp.299-306
• /
• 2000

Concern for the effects of toxic chemicals on the environment leads the search for better bioassay test organisms and test procedures. Photobacterium phosphoreum was used successfully as a test organism and the luminometer detection technique was an effective and simple method for determining the concentration of toxic chemicals. With EC50 a total of 14 chlorine substituted phenols benzenes and ethanes were used for the experiments. The test results showed that the toxicity to P. phosphoreum increased in the order of phenol > benzene > ethane and the toxicity also increased with the number of chlorine substitution. Quantitative structure activity relationship (QSARO) model can be used to predict EC50 to save time and endeavor. Correlation was well established with the QSAR parameters such as log P, log S and solvatochromic parameter(Vi/100 $\pi$, ${\beta}$m and am). The QSAR modeling was used with multi-regression analysis and mono-regression analysis. These analyses resulted in the following QSAR : $log EC_{50} =2.48 + 0.914 log S(n=9 R2=85.5% RE=0.378) log EC_{50}=0.35 - 4.48 Vi/100 + 2.84 \pi^* +9.46{\beta}m-4.48am (n =14 R2=98.2% RE=0.012) log EC_{50} =2.64 -1.66 log P(n=5, R2=98.8% RE=0.16) log EC_{50}=3.44 -1.09 log P(n=9 R2= 80.8% Re=0.207)$

• The Korean Journal of Physiology and Pharmacology
• /
• v.17 no.6
• /
• pp.517-523
• /
• 2013

Naphthyridine compounds are important, because they exhibit various biological activities including anticancer, antimicrobial, and anti-inflammatory activity. Some naphthyridines have antimitotic effects or demonstrate anticancer activity by inhibiting topoisomerase II. These compounds have been investigated as potential anticancer agents, and several compounds are now part of clinical trials. A series of naphthyridine derivatives were evaluated for their in vitro cytotoxic activities against human cervical cancer (HeLa), leukemia (HL-60), and prostate cancer (PC-3) cell lines using an MTT assay. Some compounds (14, 15, and 16) were more potent than colchicine against all three human cancer cell lines and compound (16) demonstrated potency with $IC_{50}$ values of 0.7, 0.1, and $5.1{\mu}M$, respectively. Comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) were used for quantitative structure-activity relationship (QSAR) molecular modeling of these compounds. We obtained accurate and predictive three-dimensional QSAR (3D-QSAR) models as indicated by the high PLS parameters of the HeLa ($q^2$, 0.857; $r^2$, 0.984; $r^2\;_{pred}$, 0.966), HL-60 ($q^2$, 0.777; $q^2$, 0.937; $r^2\;_{pred}$, 0.913), and PC-3 ($q^2$, 0.702; $q^2$, 0.983; $r^2\;_{pred}$, 0.974) cell lines. The 3D-QSAR contour maps suggested that the C-1 NH and C-4 carbonyl group of the naphthyridine ring and the C-2 naphthyl ring were important for cytotoxicity in all three human cancer cell lines.

• Genomics & Informatics
• /
• v.5 no.1
• /
• pp.24-29
• /
• 2007

Computational virtual screening has become an essential platform of drug discovery for the efficient identification of active candidates. Moleculardocking, a key technology of receptor-centric virtual screening, is commonly used to predict the binding affinities of chemical compounds on target receptors. Despite the advancement and extensive application of these methods, substantial improvement is still required to increase their accuracy and time-efficiency. Here, we evaluate several advanced structure-based virtual screening approaches for elucidating the rank-order activity of chemical libraries, and the quantitative structureactivity relationship (QSAR). Our results show that the ensemble-average free energy estimation, including implicit solvation energy terms, significantly improves the hit enrichment of the virtual screening. We also demonstrate that the assignment of quantum mechanical-polarized (QM-polarized) partial charges to docked ligands contributes to the reproduction of the crystal pose of ligands in the docking and scoring procedure.

• Korean Chemical Engineering Research
• /
• v.61 no.4
• /
• pp.523-541
• /
• 2023

As accessibility to 3D printers increases, there is a growing frequency of exposure to chemicals associated with 3D printing. However, research on the toxicity and harmfulness of chemicals generated by 3D printing is insufficient, and the performance of toxicity prediction using in silico techniques is limited due to missing molecular structure data. In this study, quantitative structure-activity relationship (QSAR) model based on data-centric AI approach was developed to predict the toxicity of new 3D printing materials by imputing missing values in molecular descriptors. First, MissForest algorithm was utilized to impute missing values in molecular descriptors of hazardous 3D printing materials. Then, based on four different machine learning models (decision tree, random forest, XGBoost, SVM), a machine learning (ML)-based QSAR model was developed to predict the bioconcentration factor (Log BCF), octanol-air partition coefficient (Log Koa), and partition coefficient (Log P). Furthermore, the reliability of the data-centric QSAR model was validated through the Tree-SHAP (SHapley Additive exPlanations) method, which is one of explainable artificial intelligence (XAI) techniques. The proposed imputation method based on the MissForest enlarged approximately 2.5 times more molecular structure data compared to the existing data. Based on the imputed dataset of molecular descriptor, the developed data-centric QSAR model achieved approximately 73%, 76% and 92% of prediction performance for Log BCF, Log Koa, and Log P, respectively. Lastly, Tree-SHAP analysis demonstrated that the data-centric-based QSAR model achieved high prediction performance for toxicity information by identifying key molecular descriptors highly correlated with toxicity indices. Therefore, the proposed QSAR model based on the data-centric XAI approach can be extended to predict the toxicity of potential pollutants in emerging printing chemicals, chemical process, semiconductor or display process.

• Proceedings of the Korean Society for Bioinformatics Conference
• /
• 2005.09a
• /
• pp.249-255
• /
• 2005

Angiotensin-converting enzyme (ACE) is primarily responsible for human hypertension. Current ACE drugs show serious cough and angiodema health problems due to the un-specific activity of the drug to ACE protein. The availability of ACE crystal structure (1UZF) provided the plausible biological orientation of inhibitors to ACE active site (C-domain). Three-dimensional quantitative structure-activity relationship (3D-QSAR) models have been constructed using the comparative molecula. field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) for a series of 28 ACE inhibitors. Alignment for CoMFA obtained by docking ligands to 1UZF protein using FlexX program showed better statistical model as compared to superposition of corresponding atoms. The statistical parameters indicate reasonable models for both CoMFA (q$^2$ = 0.530, r$^2$ = 0.998) and CoMSIA (q$^2$= 0.518, r$^2$ = 0.990). The 3D-QSAR analyses provide valuable information for the design of ACE inhibitors with potent activity towards C-domain of ACE. The group substitutions involving the phenyl ring and carbon chain at the propionyl and sulfonyl moieties of captopril are essential for specific activity to ACE.