Copyright (c) 2009 All rights reserved. http://works.bepress.com/chanin Recent documents in Chanin Nantasenamat en-us Mon, 11 May 2009 09:34:08 PDT 3600 http://works.bepress.com/chanin/19 http://works.bepress.com/chanin/19 Sun, 10 May 2009 07:28:20 PDT A data set comprising of the selectivity index of pentachlorophenol-imprinted polymers against 53 pentachlorophenol and related compounds was obtained from the excellent work of Baggiani et al. Molecular descriptors of the phenol compounds were calculated with E-DRAGON to obtain a total of 1,666 descriptors spanning 20 categories of molecular properties. Multivariate analysis of the data set was performed using multiple linear regression, partial least squares regression, and principal component regression. Partial least squares regression was found to deliver an excellent predictive model and was chosen for further investigation. The descriptor dimension was reduced by the combined use of partial least squares and Unsupervised Forward Selection algorithm. The obtained Quantitative Structure-Property Relationship (QSPR) model based on the smaller subset of the molecular descriptors displayed substantial gain in predictive ability when compared to the model of Baggiani et al. Such QSPR model can help in the computational design of MIPs with predefined selectivity toward template molecules of interest. Chanin Nantasenamat http://works.bepress.com/chanin/18 http://works.bepress.com/chanin/18 Sun, 10 May 2009 07:24:52 PDT Bisphenol A (BPA), a ubiquitous chemical used in industries, has attracted great attention due to its widespread leakage to the environment and foodstuff. This has spurred great interest in the preparation of synthetic polymers capable of selectively sequestering BPA. In this study, theoretical calculation was utilized to confirm the selection of suitable functional monomer capable of strong interaction with BPA. It was found that 4-vinylpyridine was the optimal functional monomer as demonstrated in the literature. A series of molecularly imprinted polymers (MIPs) were prepared by varying the functional monomer, cross-linker, and porogen. After template removal, rebinding with the original template molecule was carried out in acetonitrile, acetonitrile/water (50/50 - 20/80, v/v). 4-vinylpyridine co-polymerized with ethylene glycol dimethacrylate (4VPY-co-EDMA) and 4-vinylpyridine co-polymerized with trimethylolpropane trimethacrylate (4VPY-co-TRIM) were found to exhibit good binding performance towards bisphenol A in acetonitrile. However, only 4VPY-co-EDMA was able to maintain its imprinting effect in acetonitrile/water (50/50 v/v) whereas 4VPY-co-TRIM totally lost its imprinting effect. Chanin Nantasenamat http://works.bepress.com/chanin/17 http://works.bepress.com/chanin/17 Sun, 10 May 2009 07:18:47 PDT Cysteine (a sulfur-based amino acid) has widely been used to aid the biomolecular structure investigation, protein purification, and metal remediation. However, major drawbacks from the difficulty to maintain its reduced state and the tendency to form protein multimerization become obstacles of its applicability. In the present study, significant roles of cysteine residue on the alterations of intrinsic biological activity as well as the expression and localization of chimeric green fluorescent protein (GFP) have been investigated. A series of chimeric GFPs carrying a helical conformation of cysteine-rich peptides (designated as (CXXX)3GFPuv and (CX)3P(HX)3GFPuv) was successfully constructed. The presence of cysteine residues significantly exerted some suppressing effect on the fluorescent emission at both the cellular and protein levels. In addition, the majority of proteins (>95%) was found to be aggregated in the debris fraction. By contrarily, substitution of cysteine with histidine residue rendered the proteins to be more soluble in the cytoplasmic portion. More importantly, enhancement of fluorescent activity up to 2 folds could be detected in the case of chimeric (HXXX)3GFPuv and (HX)3P(HX)3GFPuv. Such prominent effects were experimentally proven to be attributable to the disulfide bond formation. Recovery of both metal-binding capability and the fluorescent activity was more pronounced in the presence of reducing agent. Conclusion can be drawn that the presence of cysteine residue on the biological macromolecules may influence their solubility and functions while exhibiting diverse characteristics in the oxidative and reductive situations. Further investigations, particularly on the use of computational analysis and quantum mechanics, are needed to be performed to gain more understanding on the underlying mechanisms of cysteine in biological system. Chartchalerm Isarankura-Na-Ayudhya http://works.bepress.com/chanin/16 http://works.bepress.com/chanin/16 Sun, 10 May 2009 07:13:02 PDT Quantitative structure-activity relationship (QSAR) modeling pertains to the construction of predictive models of biological activities as a function of structural and molecular information of a compound library. The concept of QSAR has typically been used for drug discovery and development and has gained wide applicability for correlating molecular information with not only biological activities but also with other physicochemical properties, which has therefore been termed quantitative structure-property relationship (QSPR). Typical molecular parameters that are used to account for electronic properties, hydrophobicity, steric effects, and topology can be determined empirically through experimentation or theoretically via computational chemistry. A given compilation of data sets is then subjected to data pre-processing and data modeling through the use of statistical and/or machine learning techniques. This review aims to cover the essential concepts and techniques that are relevant for performing QSAR/QSPR studies through the use of selected examples from our previous work. Chanin Nantasenamat http://works.bepress.com/chanin/15 http://works.bepress.com/chanin/15 Sun, 10 May 2009 07:06:18 PDT Superoxide anions are reactive oxygen species that can attack biomolecules such as DNA, lipids and proteins to cause many serious diseases. This study reports the synthesis of copper complexes of nicotinic acid with related pyridine derivatives. The copper complexes were shown to possess superoxide dismutase (SOD) and antimicrobial activities. The copper complexes exerted SOD activity in range of 49.07-130.23 μM. Particularly, copper complex of nicotinic acid with 2-hydroxypyridine was the most potent SOD mimic with an IC50 of 49.07 μM. In addition, the complexes exhibited antimicrobial activity against Bacillus subtilis ATCC 6633 and Candida albicans ATCC 90028 with MIC range of 128-256 μg/mL. The SOD activities were well correlated with the theoretical parameters as calculated by density functional theory at the B3LYP/LANL2DZ level of theory. Interestingly, the SOD activity of the copper complexes was demonstrated to be inversely correlated with the electron affinity, but was well correlated with both HOMO and LUMO energies. The vitamin-metal complexes described in this report are great examples of the value-added benefits of vitamins for medicinal applications. Thummaruk Suksrichavalit http://works.bepress.com/chanin/14 http://works.bepress.com/chanin/14 Sun, 10 May 2009 06:42:04 PDT Quantitative structure-activity relationship (QSAR) models were constructed for predicting the inhibition of furin-dependent processing of anthrax protective antigen of substituted guanidinylated aryl 2,5-dideoxystreptamines. Molecular descriptors calculated by E-Dragon and RECON were subjected to variable reduction using the Unsupervised Forward Selection (UFS) algorithm. The variables were then used as input for QSAR model generation using partial least squares and back-propagation neural network. Prediction was performed via a two-step approach: (i) perform classification to determine whether the molecule is active or inactive, (ii) develop a QSAR regression model of active molecules. Both classification and regression models yielded good results with RECON providing higher accuracy than that of E-DRAGON descriptors. The performance of the regression model using E-Dragon and RECON descriptors provided a correlation coefficient of 0.807 and 0.923 and root mean square error of 0.666 and 0.304, respectively. Interestingly, it was observed that appropriate representations of the protonation states of the molecules were crucial for good prediction performance, which coincides with the fact that the inhibitors interact with furin via electrostatic forces. The results provide good prospect of using the proposed QSAR models for the rational design of novel therapeutic furin inhibitors toward anthrax and furin-dependent diseases. Chanin Nantasenamat http://works.bepress.com/chanin/13 http://works.bepress.com/chanin/13 Sun, 10 May 2009 06:37:56 PDT Antioxidants play crucial roles in scavenging oxidative damages arising from reactive oxygen species. Bond dissociation enthalpy (BDE) of phenolic O-H bond has well been accepted as an indicator of antioxidant activity since phenols donate the hydrogen atom to the free radicals thereby neutralizing its toxic effect. The BDEs from a data set of 39 antioxidant phenols were modeled using computationally inexpensive quantum chemical descriptors with multiple linear regression (MLR), partial least squares (PLS), and support vector machine (SVM). The molecular descriptors of the phenols were derived from calculations at the following theoretical levels: AM1, HF/3-21g(d), B3LYP/3-21g(d), and B3LYP/6-31g(d). Results indicated that when MLR and PLS were used as the regression methods, B3LYP/3-21g(d) gave the best performance with leave-one-out cross-validated correlation coefficients (r) of 0.917 and 0.921, respectively, while the semiempirical AM1 provided slightly lower r of 0.897 and 0.888, respectively. When SVM was used as the regression method no significant difference in the accuracy was observed for models using B3LYP/3-21g(d) and AM1 as indicated by r of 0.968 and 0.966, respectively. The quantitative structure-property relationship (QSPR) model of BDE discussed in this study offers great potential for the design of novel antioxidant phenols with robust properties. Chanin Nantasenamat http://works.bepress.com/chanin/12 http://works.bepress.com/chanin/12 Sun, 10 May 2009 06:35:55 PDT A quantitative structure-activity relationship (QSAR) study was performed to model the lactonolysis activity of N-acyl-homoserine lactone lactonase. A data set comprising of 20 homoserine lactones and related compounds was taken from the work of Wang et al. Quantum chemical descriptors were calculated using the semiempirical AM1 method. Partial least squares regression was utilized to construct a predictive model. This computational approach reliably reproduced the lactonolysis activity with high accuracy as illustrated by the correlation coefficient in excess of 0.9. It is demonstrated that the combined use of quantum chemical descriptors with partial least squares regression are suitable for modeling the AHL lactonolysis activity. Chanin Nantasenamat http://works.bepress.com/chanin/11 http://works.bepress.com/chanin/11 Sun, 10 May 2009 06:31:52 PDT A novel solvent-exposed analyte channel, generated by F165G substitution, on the surface of green fluorescent protein (designated His6GFPuv/ F165G) was successfully discovered by the aid of molecular modeling software (PyMOL) in conjunction with site-directed mutagenesis. Regarding the high predictive performance of PyMOL, two pore-containing mutants namely His 6GFPuv/H148G and His6GFPuv/H148G/F165G were also revealed. The pore sizes of F165G, H148G, and the double mutant H148G/F165G were in the order of 4, 4.5 and 5.5 Å, respectively. These mutants were subjected to further investigation on the effect of small analytes (e.g. metal ions and hydrogen peroxide) as elucidated by fluorescence quenching experiments. Results revealed that the F165G mutant exhibited the highest metal sensitivity at physiological pH. Meanwhile, the other 2 mutants lacking histidine at position 148 had lower sensitivity against Zn2+ and Cu2+ than those of the template protein (His6GFPuv). Hence, a significant role of this histidine residue in mediating metal transfer toward the GFP chromophore was proposed and evidently demonstrated by testing in acidic condition. Results revealed that at pH 6.5 the order of metal sensitivity was found to be inverted whereby the H148G/F165G became the most sensitive mutant. The dissociation constants (Kd) to metal ions were in the order of 4.88×10 -6 M, 16.67×10-6 M, 25×10-6 M, and 33.33×10-6 M for His6GFPuv/F165G, His 6GFPuv, His6GFPuv/H148G/F165G and His6GFPuv/ H148G, respectively. Sensitivity against hydrogen peroxide was in the order of H148G/F165G > H148G > F165G indicating the crucial role of pore diameters. However, it should be mentioned that H148G substitution caused a markedly decrease in pH- and thermo-stability. Taken together, our findings rendered the novel pore of GFP as formed by F165G substitution to be a high impact channel without adversely affecting the intrinsic fluorescent properties. This opens up a great potential of using F165G mutant in enhancing the sensitivity of GFP in future development of biosensors. Natta Tansila http://works.bepress.com/chanin/10 http://works.bepress.com/chanin/10 Sun, 10 May 2009 06:28:03 PDT The molecular mechanism of ethylenediaminetetraacetic acid (EDTA)-induced membrane destabilization has been studied using a combination of four biophysical techniques on artificial lipid membranes. Data from Langmuir film balance and epifluorescence microscopy revealed the fluidization and expansion effect of EDTA on phase behavior of monolayers of either 1,2-dipalmitoyl-sn- glycero-3-phosphocholine (DPPC) or mixtures of DPPC and metal-chelating lipids, such as Nα, Nα-Bis[carboxymethyl]-N ε-[(dioctadecylamino)succinyl]-L-lysine or 1,2-dioleoyl-sn- glycero-3-[N-(5-amino-1-carboxypentyl iminodiacetic acid) succinyl]. A plausible explanation could be drawn from the electrostatic interaction between negatively charged groups of EDTA and the positively charged choline head group of DPPC. Intercalation of EDTA into the lipid membrane induced membrane curvature as elucidated by atomic force microscopy. Growth in size and shape of the membrane protrusion was found to be time-dependent upon exposure to EDTA. Further loss of material from the lipid membrane surface was monitored in real time using a quartz crystal microbalance. This indicates membrane restabilization by exclusion of the protrusions from the surface. Loss of lipid components facilitates membrane instability, leading to membrane permeabilization and lysis. Virapong Prachayasittikul http://works.bepress.com/chanin/9 http://works.bepress.com/chanin/9 Sat, 09 May 2009 09:23:35 PDT Computational approach for evaluating the feasibility of template-monomer complexes has great potential in assisting the selection of appropriate functional monomers for template molecule of interest. A quantitative structure-property relationship (QSPR) study of template-monomer complexes was investigated for the prediction of imprinting factor of molecularly imprinted polymers (MIPs). The data set was based on uniformly-sized MIP particles taken from the literature and was used in our previous study for computing the imprinting factor using molecular descriptors derived from charge density-based electronic properties of molecules. In this study, we examined the feasibility of using quantum chemical descriptors and artificial neural networks for prediction of the imprinting factor. The proposed methodology reliably predicted the imprinting factor of MIPs with correlation coefficient from 0.7083 to 0.8378 albeit to a lesser degree than charge-based descriptors, which yielded correlation coefficient as high as 0.9680. The importance of mobile phase descriptors on the predictive performance of the QSPR model has surprisingly shown that the use of mobile phase descriptors alone was able to predict the imprinting factor with good performance. Chanin Nantasenamat http://works.bepress.com/chanin/8 http://works.bepress.com/chanin/8 Sat, 09 May 2009 09:10:16 PDT The prediction of the excitation and the emission maxima of green fluorescent protein (GFP) chromophores were investigated by a quantitative structure-property relationship study. A data set of 19 GFP color variants and an additional data set consisting of 29 synthetic GFP chromophores were collected from the literature. Artificial neural network implementing the back-propagation algorithm was employed. The proposed computational approach reliably predicted the excitation and the emission maxima of GFP chromophores with correlation coefficient exceeding 0.9. The usefulness of quantum chemical descriptors was revealed by a comparative study with other molecular descriptors. Assignment of appropriate protonation state of the chromophore for the GFP color variants data set was shown to be necessary for good predictive performance. Results suggest that the confinement of the GFP chromophore has no significant influence on the predictive performance of the data set used. A comparative investigation with the traditional modeling methods, particularly multiple linear regression and partial least squares, reveals that artificial neural network is the most suitable modeling approach for the GFP spectral properties. It is anticipated that this methodology has great potential in accelerating the design and engineering of novel GFP color variants of scientific or industrial interest. Chanin Nantasenamat http://works.bepress.com/chanin/7 http://works.bepress.com/chanin/7 Sat, 09 May 2009 09:06:09 PDT Nicotinic acid (also known as vitamin B3) is a dietary element essential for physiological and antihyperlipidemic functions. This study reports the synthesis of novel mixed ligand complexes of copper with nicotinic and other select carboxylic acids (phthalic, salicylic and anthranilic acids). The tested copper complexes exhibited superoxide dismutase (SOD) mimetic activity and antimicrobial activity against Bacillus subtilis ATCC 6633, with a minimum inhibition concentration of 256 μg/mL. Copper complex of nicotinic-phthalic acids (CuNA/Ph) was the most potent with a SOD mimetic activity of IC 50 34.42 μM. The SOD activities were observed to correlate well with the theoretical parameters as calculated using density functional theory (DFT) at the B3LYP/LANL2DZ level of theory. Interestingly, the SOD activity of the copper complex CuNA/Ph was positively correlated with the electron affinity (EA) value. The two quantum chemical parameters, highest occupied molecular orbital (HOMO) and lowest unoccupied molecular orbital (LUMO), were shown to be appropriate for understanding the mechanism of the metal complexes as their calculated energies show good correlation with the SOD activity. Moreover, copper complex with the highest SOD activity were shown to possess the lowest HOMO energy. These findings demonstrate a great potential for the development of value-added metallovitamin-based therapeutics. Thummaruk Suksrichavalit Medicinal Chemistry http://works.bepress.com/chanin/6 http://works.bepress.com/chanin/6 Sat, 09 May 2009 09:06:08 PDT Molecular imprinting is one of the most efficient methods for preparing synthetic receptors that possess user defined recognition properties. Despite general success of non-covalent imprinting for a large variety of templates, some groups of compounds remain difficult to tackle due to their structural complexity. In this study we investigate preparation of molecularly imprinted polymers that can bind sulfonamide compounds, which represent important drug candidates. Compared to the biological system that utilizes metal coordinated interaction, the imprinted polymer provided pronounced selectivity when hydrogen bond interaction was employed in an organic solvent. Computer simulation of the interaction between the sulfonamide template and functional monomers pointed out that although methacrylic acid had strong interaction energy with the template, it also possessed high non-specific interaction with the solvent molecules of tetrahydrofuran as well as being prone to self-complexation. On the other hand, 1-vinyl-imidazole was suitable for imprinting sulfonamides as it did not cross-react with the solvent molecules or engage in self-complexation structures. Chartchalerm Isarankura-Na-Ayudhya Polymer Chemistry http://works.bepress.com/chanin/5 http://works.bepress.com/chanin/5 Sat, 09 May 2009 09:04:54 PDT Superoxide dismutase (SOD) activities of various metallobacitracin complexes were evaluated using the riboflavin-methionine-nitro blue tetrazolium assay. The radical scavenging activity of various metallobacitracin complexes was shown to be higher than those of the negative controls, e.g., free transition metal ions and metal-free bacitracin. The SOD activity of the complex was found to be in the order of Mn(II) > Cu(II) > Co(II) > Ni(II). Furthermore, the effect of bacitracin and their complexation to metals on various microorganisms was assessed by antibiotic susceptibility testing. Moreover, molecular modeling and quantum chemical calculation of the metallobacitracin complex was performed to evaluate the correlation of electrostatic charge of transition metal ions on the SOD activity. © 2006 Elsevier Inc. All rights reserved. Chanin Nantasenamat http://works.bepress.com/chanin/4 http://works.bepress.com/chanin/4 Sat, 09 May 2009 08:26:53 PDT Successful recognition of splice junction sites of human DNA sequences was achieved via three machine learning approaches. Both unsupervised (Kohonen's Self-Organizing Map, KSOM) and supervised (Back-propagation Neural Network, BNN; and Support Vector Machine, SVM) machine learning techniques were used for the classification of sequences from the testing set into one of three categories: transition from exon to intron, transition from intron to exon, and no transition. The dataset used in this study is comprised of 1,424 DNA sequences obtained from the National Center for Bioinformatics Information (NCBI). Performance of the machine learning approaches were assessed by the construction of learning models from 1,000 sequences of the training set and evaluated on the 424 sequences of the testing set that is unknown to the learning model. Each sequence is a window of 32 nucleotides long with regions comprising -15 to +15 nucleotides from the dinucleotide splice site. Since the nucleotides (A, C, G, and T) are represented by four digit binary code (e.g. 0001, 0010, 0100, and 1000) the number of descriptors increased from 32 to 128. The performance of machine learning techniques in order of increasing accuracy are as follows SVM > BNN > KSOM, suggesting that SVM is a robust method in the identification of unknown splice site. Although KSOM gave lower prediction accuracy than the two supervised methods, it is fascinating that it was able to make such prediction based only on knowledge of the input whereas the supervised method requires that the output be known during training. It is expected that the Support Vector Machine method can provide a powerful computational tool for predicting the splice junction sites of uncharacterized DNA. Chanin Nantasenamat http://works.bepress.com/chanin/3 http://works.bepress.com/chanin/3 Sat, 09 May 2009 08:16:31 PDT Artificial neural network (ANN) implementing the back-propagation algorithm was applied for the calculation of the imprinting factors (IF) of molecularly imprinted polymers (MIP) as a function of the computed molecular descriptors of template and functional monomer molecules and mobile phase descriptors. The dataset used in our study were obtained from the literature and classified into two distinctive datasets on the basis of the polymer's morphology, irregularly sized MIP and uniformly sized MIP datasets. Results revealed that artificial neural network was able to perform well on datasets derived from uniformly sized MIP (n=23, r=0.946, RMS=2.944) while performing poorly on datasets derived from irregularly sized MIP (n=75, r=0.382, RMS=6.123). The superior performance of the uniformly sized MIP dataset over the irregularly sized MIP dataset could be attributed to its more predictable nature owing to the consistency of MIP particles, uniform number and association constant of binding sites, and minimal deviation of the imprinted polymers. The ability to predict the imprinting factor of imprinted polymer prior to performing actual experimental work provide great insights on the feasibility of the interaction between template-functional monomer pairs. Chanin Nantasenamat