Kwang-Hwi Cho

Detection of the mycotoxin citrinin using silver substrates and Raman spectroscopy.

We detected a trace amount of the mycotoxin citrinin using surface-enhanced Raman scattering (SERS) on silver nanoparticle (Ag NP) surfaces. The SERS substrate on hydrophobic Teflon films was also introduced to observe the citrinin peaks. A broad band at ∼1382cm(-1), which was ascribed to the symmetric carboxylate stretching mode, was observed in addition to an antisymmetric carboxylate stretching mode at ∼1568cm(-1) in the Raman spectra. The spectral feature indicated that citrinin would adsorb on Ag NPs via its carboxylate form. Based on density functional theory (DFT) calculations, vibrational mode analysis was performed to compare the Raman spectra of citrinin. DFT calculations also predicted that a bidentate bridge configuration through O15 and O16 atoms in citrinin would be the most stable on three Ag atoms. After treating with Ag NPs, observation of citrinin peaks was attempted in fungal cells of Penicillium citrinum. This work may provide useful insights into the direct observation of the hazardous citrinin mycotoxin using SERS by understanding its adsorption behaviors on Ag surfaces.

EaMEAD: Activation Energy Prediction of Cytochrome P450 Mediated Metabolism with Effective Atomic Descriptors

In an effort to improve drug design and predictions for pharmacokinetics (PK), an empirical model was developed to predict the activation energies (Ea) of cytochrome P450 (CYP450) mediated metabolism. The model, EaMEAD (Activation energy of Metabolism reactions with Effective Atomic Descriptors), predicts the Ea of four major metabolic reactions of the CYP450 enzyme: aliphatic hydroxylation, N-dealkylation, O-dealkylation, and aromatic hydroxylation. To build and validate the empirical model, the E(a) values of the substrates with diverse chemical structures (394 metabolic sites for aliphatic hydroxylation, 27 metabolic sites for N-dealkylation, 9 metabolic sites for O-dealkylation, and 85 metabolic sites for aromatic hydroxylation) were calculated by AM1 molecular orbital (MO). Empirical equations, Quantitative Structure Activity Relationship (QSAR) models, were derived using effective atomic charge, effective atomic polarizability, and bond dipole moments of the substrates as descriptors. EaMEAD is shown to accurately predict Ea with a correlation coefficient (R) of 0.94 and root-mean-square error (RMSE, unit is kcal/mol) of 0.70 for aliphatic hydroxylation, N-dealkylation, and O-dealkylation, and R of 0.83 and RMSE of 0.80 for aromatic hydroxylation, respectively. Physical origin and the role of the effective atomic descriptors of the models are presented in detail. With this model, the Ea of the metabolism can be rapidly predicted without any experimental parameters or time-consuming QM calculation. Regioselectivity prediction with our model is presented in the case of CYP3A4 metabolism. The reliability and ease of use of this model will greatly facilitate early stage PK predictions and rational drug design. Moreover, the model can be applied to develop the Ea prediction model of various types of chemical reactions.

Adsorption and desorption of tyrosine kinase inhibitor erlotinib on gold nanoparticles

We investigated interfacial behaviors of erlotinib (EL) on gold nanoparticles (AuNPs) by means of Raman spectroscopy. The adsorption reactions and structures of EL on AuNP surfaces were examined by UV-Vis absorption spectroscopy and surface-enhanced Raman scattering (SERS). Density functional theory calculations were performed to estimate the energetic stabilities of the drug-AuNP composites. Among the binding units in EL, the acetylenic C≡C group was calculated to be the most strongly binding on the AuNP cluster atoms, consistent with the SERS spectra. The concentration-dependent SERS spectra indicated that ∼10(-5) M of EL exhibited the highest SERS signals. The attached EL appeared to desorb more efficiently with 2mM glutathione than with cell culture media. The lack of a strong SERS signal of EL in the dark-field microscopy images of AuNP-EL complexes suggested almost complete desorption of EL inside cells.

Calculation of the Solvation Free Energy of Neutral and Ionic Molecules in Diverse Solvents

The solvation free energy density (SFED) model was modified to extend its applicability and predictability. The parametrization process was performed with a large, diverse set of solvation free energies that included highly polar and ionic molecules. The mean absolute error for 1200 solvation free energies of the 379 neutral molecules in 9 organic solvents and water was 0.40 kcal/mol, and for 90 hydration free energies of ions was 1.7 kcal/mol. Overall, the calculated solvation free energies of a wide range of solute functional groups in diverse solvents were consistent with experimental data.

A robust method for searching the smallest set of smallest rings with a path-included distance matrix

The perception of rings in graphs is widely used in many fields of science and engineering. Algorithms developed in the chemistry community, called smallest set of smallest rings (SSSR), applicable only for simple graphs or chemical structures. In contrast, algorithms developed by the computer science community, called minimum cycle basis (MCB) are identical to SSSR yet exhibit greater robustness. MCB-based algorithms can correctly reveal all rings in any complex graph. However, they are slow when applied to large complex graphs due to the inherent limitations of the algorithms used. Here, we suggest a heuristic method called RP-Path. This method is a robust, simple, and fast search method with O(n3) runtime algorithm that correctly identifies the SSSR of all of the test case of complex graphs by using approach different from the MCB-based method. Both the robustness and improvement in speed are achieved by using a path-included distance matrix and describing the characteristic features of rings in the matrix. This method is accurate and faster than any other methods and may find many application in various fields of science and engineering that use complicated graphs with thousands of nodes.

yaInChI: Modified InChI string scheme for line notation of chemical structures

A modified InChI (International Chemical Identifier) string scheme, yaInChI (yet another InChI), is suggested as a method for including the structural information of a given molecule, making it straightforward and more easily readable. The yaInChI theme is applicable for checking the structural identity with higher sensitivity and generating three-dimensional (3-D) structures from the one-dimensional (1-D) string with less ambiguity than the general InChI method. The modifications to yaInChI provide non-rotatable single bonds, stereochemistry of organometallic compounds, allene and cumulene, and parity of atoms with a lone pair. Additionally, yaInChI better preserves the original information of the given input file (SDF) using the protonation information, hydrogen count +1, and original bond type, which are not considered or restrictively considered in InChI and SMILES. When yaInChI is used to perform a duplication check on a 3D chemical structure database, Ligand.Info, it shows more discriminating power than InChI. The structural information provided by yaInChI is in a compact format, making it a promising solution for handling large chemical structure databases.

Development of Surface-SFED Models for Polar Solvents

We developed surface grid-based solvation free energy density (Surface-SFED) models for 36 commonly used polar solvents. The parametrization was performed with a large and diverse set of experimental solvation free energies mainly consisting of combinations of polar solvent and multipolar solute. Therefore, the contribution of hydrogen bonds was dominant in the model. In order to increase the accuracy of the model, an elaborate version of a previous hydrogen bond acidity and basicity prediction model was introduced. We present two parametrizations for use with experimentally determined (Surface-SFED/HB(exp)) and empirical (Surface-SFED/HB(cal)) hydrogen bond acidity and basicity values. Our computational results agreed well with experimental results, and inaccuracy of empirical hydrogen bond acidity and basicity values was the main source of error in Surface-SFED/HB(cal). The mean absolute errors of Surface-SFED/HB(exp) and Surface-SFED/HB(cal) were 0.49 and 0.54 kcal/mol, respectively.

PXR ligand classification model with SFED-weighted WHIM and CoMMA descriptors

Understanding which type of endogenous and exogenous compounds serve as agonists for the nuclear pregnane X receptor (PXR) would be valuable for drug discovery and development, because PXR regulates a large number of genes related to xenobiotic metabolism. Although several models have been proposed to classify human PXR activators and non-activators, models with better predictability are necessary for practical purposes in drug discovery. Grid-weighted holistic invariant molecular (G-WHIM) and comparative molecular moment analysis (G-CoMMA) type 3D descriptors that contain information about the solvation free energy of target molecules were developed. With these descriptors, prediction models built using decision tree (DT)-, support vector machine (SVM)-, and Kohonen neural network (KNN)-based models exhibited better predictability than previously proposed models. Solvation free energy density-weighted G-WHIM and G-CoMMA descriptors reveal new insights into PXR ligand classification, and incorporation with machine learning methods (DT, SVM, KNN) exhibits promising results, especially SVM and KNN. SVM- and KNN-based models exhibit accuracy around 0.90, and DT-based models exhibit accuracy around 0.8 for both the training and test sets.

Energetic stabilities of thiolated pyrimidines on gold nanoparticles investigated by Raman spectroscopy and density functional theory calculations

The adsorption structures of 2-thiocytosine (2TC) on gold surfaces were examined by means of vibrational Raman spectroscopy and quantum mechanical density functional theory calculations. The 1H-thione-amino form was calculated to be most stable among the six examined tautomers. The three plausible binding geometries of sulfur, pyrimidine nitrogen, and amino group binding modes were calculated to estimate the binding energies of the 1H-thione-amino form with six gold cluster atoms. Thiouracils including 2-thiouracil (2TU), 4-thiouracil (4TU), and 6-methyl-2-thiouracil (6M2TU) were also studied to compare their relative binding energies on gold atoms. The intracellular localization of a DNA base analog of 2TC on gold nanoparticles (AuNPs) in HeLa cells was identified by means of surface-enhanced Raman scattering. AuNPs were modified with 2TC by self-assembly. Our dark-field microscopy and z-depth-dependent confocal Raman spectroscopy indicated that 2TC-assembled AuNPs could be found inside cancer cells. On the other hand, we did not observe noticeably strong Raman peaks in the cases of thiouracils including 2TU, 4TU, and 6M2TU. This may be due to the additional amino group of 2TC, which can lead to a stronger binding of adsorbates on AuNPs.

Mutational analysis of human tumor necrosis factor-α

To understand the structure-function relationship of human tumor necrosis factor-α (TNF-α), mutational analysis was carried out on the lower regions (regions 1–6) of the molecule. The muteins were prepared as a soluble form by using a chaperonin co-expression system and the cytotoxic activities of the purified muteins were evaluated on TNF-sensitive murine fibrosarcoma L929 cells. Three regions (regions 1, 2 & 4) were found where mutations significantly influenced the bioactivity. In region 1 (residues 1–10), the number of deleted residues and the positioning of positive charges are important to achieve a maximum activity and in region 4 (residues 84–88), introduction of charged residues in one of the positions 86–88 significantly increased the cytotoxic activity. On the other hand, any mutation introduced in region 2 (residues 37–41) had a deleterious effect. The present study provides a structural basis for the design of highly potent TNF-α as a therapeutic agent.