Proton nuclear magnetic resonance investigation of the native and modified active site structure of heme proteins

Hemoproteins are a very important class of enzymes in nature sharing the essentially same prosthetic group, heme, and are good models for exploring the relationship between protein structure and function. Three important hemoproteins, chloroperoxidase (CPO), horseradish peroxidase (HRP), and cytochrome P450cam (P450cam), have been extensively studied as archetypes for the relationship between structure and function. In this study, a series of 1D and 2D NMR experiments were successfully conducted to contribute to the structural studies of these hemoproteins. ^ During the epoxidation of allylbenzene, CPO is converted to an inactive green species with the prosthetic heme modified by addition of the alkene plus an oxygen atom forming a five-membered chelate ring. Complete assignment of the NMR resonances of the modified porphyrin extracted and demetallated from green CPO unambiguously established the structure of this porphyrin as an NIII-alkylated product. A novel substrate binding motif of CPO was proposed from this concluded regiospecific N-alkylation structure. ^ Soybean peroxidase (SBP) is considered as a more stable, more abundant and less expensive substitute of HRP for industrial applications. A NMR study of SBP using 1D and 2D NOE methods successfully established the active site structure of SBP and consequently fills in the blank of the SBP NMR study. All of the hyperfine shifts of the SBP-CN- complex are unambiguously assigned together with most of the prosthetic heme and all proximal His170 resonances identified. The active site structure of SBP revealed by this NMR study is in complete agreement with the recombinant SBP crystal structure and is highly similar to that of the HRP with minor differences. ^ The NMR study of paramagnetic P450cam had been greatly restricted for a long time. A combination of 2D NMR methods was used in this study for P450cam-CN - complexes with and without camphor bound. The results lead to the first unequivocal assignments of all heme hyperfine-shifted signals, together with certain correlated diamagnetic resonances. The observed alternation of the assigned novel proximal cysteine β-CH2 resonances induced by camphor binding indicated a conformational change near the proximal side.^

Development, validation and uncertainty analysis of quantitative structure and activity relationship models for Log P of disinfection by -products

Hydrophobicity as measured by Log P is an important molecular property related to toxicity and carcinogenicity. With increasing public health concerns for the effects of Disinfection By-Products (DBPs), there are considerable benefits in developing Quantitative Structure and Activity Relationship (QSAR) models capable of accurately predicting Log P. In this research, Log P values of 173 DBP compounds in 6 functional classes were used to develop QSAR models, by applying 3 molecular descriptors, namely, Energy of the Lowest Unoccupied Molecular Orbital (ELUMO), Number of Chlorine (NCl) and Number of Carbon (NC) by Multiple Linear Regression (MLR) analysis. The QSAR models developed were validated based on the Organization for Economic Co-operation and Development (OECD) principles. The model Applicability Domain (AD) and mechanistic interpretation were explored. Considering the very complex nature of DBPs, the established QSAR models performed very well with respect to goodness-of-fit, robustness and predictability. The predicted values of Log P of DBPs by the QSAR models were found to be significant with a correlation coefficient R2 from 81% to 98%. The Leverage Approach by Williams Plot was applied to detect and remove outliers, consequently increasing R 2 by approximately 2% to 13% for different DBP classes. The developed QSAR models were statistically validated for their predictive power by the Leave-One-Out (LOO) and Leave-Many-Out (LMO) cross validation methods. Finally, Monte Carlo simulation was used to assess the variations and inherent uncertainties in the QSAR models of Log P and determine the most influential parameters in connection with Log P prediction. The developed QSAR models in this dissertation will have a broad applicability domain because the research data set covered six out of eight common DBP classes, including halogenated alkane, halogenated alkene, halogenated aromatic, halogenated aldehyde, halogenated ketone, and halogenated carboxylic acid, which have been brought to the attention of regulatory agencies in recent years. Furthermore, the QSAR models are suitable to be used for prediction of similar DBP compounds within the same applicability domain. The selection and integration of various methodologies developed in this research may also benefit future research in similar fields.