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.^

High performance shift invariant motion estimation and compensation in wavelet domain video compression

The contributions of this dissertation are in the development of two new interrelated approaches to video data compression: (1) A level-refined motion estimation and subband compensation method for the effective motion estimation and motion compensation. (2) A shift-invariant sub-decimation decomposition method in order to overcome the deficiency of the decimation process in estimating motion due to its shift-invariant property of wavelet transform. ^ The enormous data generated by digital videos call for an intense need of efficient video compression techniques to conserve storage space and minimize bandwidth utilization. The main idea of video compression is to reduce the interpixel redundancies inside and between the video frames by applying motion estimation and motion compensation (MEMO) in combination with spatial transform coding. To locate the global minimum of the matching criterion function reasonably, hierarchical motion estimation by coarse to fine resolution refinements using discrete wavelet transform is applied due to its intrinsic multiresolution and scalability natures. ^ Due to the fact that most of the energies are concentrated in the low resolution subbands while decreased in the high resolution subbands, a new approach called level-refined motion estimation and subband compensation (LRSC) method is proposed. It realizes the possible intrablocks in the subbands for lower entropy coding while keeping the low computational loads of motion estimation as the level-refined method, thus to achieve both temporal compression quality and computational simplicity. ^ Since circular convolution is applied in wavelet transform to obtain the decomposed subframes without coefficient expansion, symmetric-extended wavelet transform is designed on the finite length frame signals for more accurate motion estimation without discontinuous boundary distortions. ^ Although wavelet transformed coefficients still contain spatial domain information, motion estimation in wavelet domain is not as straightforward as in spatial domain due to the shift variance property of the decimation process of the wavelet transform. A new approach called sub-decimation decomposition method is proposed, which maintains the motion consistency between the original frame and the decomposed subframes, improving as a consequence the wavelet domain video compressions by shift invariant motion estimation and compensation. ^

Molecular studies in gorgonian alloimmunity : search for gene homologs of the immunoglobulin gene superfamily in Swiftia exserta

Humoral and cells surface molecules of the mammalian immune system, grouped into the Immunoglobulin Gene Superfamily, share protein structure and gene sequence homologies with molecules found among diverse phylogenetic groups. In histocompatibility studies, the gorgonian coral Swiftia exserta has recently demonstrated specific alloimmunity with memory (Salter-Cid and Bigger, 1991. Biological Bulletin Vol 181). In an attempt to shed light on the origins of this gene family and the evolution of the vertebrate immune response, genomic DNA from Swiftia exserta was isolated, purified, and analyzed by Southern blot hybridization with mouse gene probes corresponding to two molecules of the Immunoglobulin Gene Superfamily, the Thy-1 antigen, and the alpha-3 domain of the MHC Class I histocompatibility marker. Hybridizations were conducted under low to non-stringent conditions to allow binding of mismatched homologs that may exist between the mouse gene probes and the Swiftia DNA. Removal of non-specific binding (sequences less than 70% homologous) occurred in washing steps. Results show that with the probes selected, the method chosen, and the conditions applied, no evidence of sequences of 70% or greater homology to the mouse Thy-1 or MHC Class I alpha-3 genes exist in Swiftia exserta genome.

Design strategies for an artificial neural network based algorithm for automatic incident detection on major arterial streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our nation’s highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

Characterization of recombinant chloroperoxidase, and F103A and C29H/C79H/C87H mutants

Mechanistically and structurally chloroperoxidase (CPO) occupies a unique niche among heme containing enzymes. Chloroperoxidase catalyzes a broad range of reactions, such as oxidation of organic substrates, dismutation of hydrogen peroxide, and mono-oxygenation of organic molecules. To expand the synthetic utility of CPO and to appreciate the important interactions that lead to CPO’s exceptional properties, a site-directed mutagenesis study was undertaken. ^ Recombinant CPO and CPO mutants were heterologously expressed in Aspergillus niger. The overall protein structure was almost the same as that of wild type CPO, as determined by UV-vis, NMR and CD spectroscopies. Phenylalanine103, which was proposed to regulate substrate access to the active site by restricting the size of substrates and to control CPO’s enantioselectivity, was mutated to Ala. The ligand binding affinity and most importantly the catalytic activity of F103A was dramatically different from wild type CPO. The mutation essentially eliminated the chlorination and dismutation activities but enhanced, 4-10 fold, the epoxidation, peroxidation, and N-demethylation activities. As expected, the F103A mutant displayed dramatically improved epoxidation activity for larger, more branched styrene derivatives. Furthermore, F103A showed a distinctive enantioselectivity profile: losing enantioselectivity to styrene and cis-β-methylstyrene; having a different configuration preference on α-methylstyrene; showing higher enantioselectivites and conversion rates on larger, more branched substrates. Our results show that F103 acts as a switch box that controls the catalytic activity, substrate specificity, and product enantioselectivity of CPO. Given that no other mutant of CPO has displayed distinct properties, the results with F103A are dramatic. ^ The diverse catalytic activity of CPO has long been attributed to the presence of the proximal thiolate ligand. Surprisingly, a recent report on a C29H mutant suggested otherwise. A new CPO triple mutant C29H/C79H/C87H was prepared, in which all the cysteines were replaced by histidine to eliminate the possibility of cysteine coordinating to the heme. No active form protein was isolated, although, successful transformation and transcription was confirmed. The result suggests that Cys79 and Cys87 are critical to maintaining the structural scaffold of CPO. ^ In vitro biodegradation of nanotubes by CPO were examined by scanning electron microscope method, but little oxidation was observed. ^

Variable Speed Limit Strategies to Reduce the Impacts of Traffic Flow Breakdown at Recurrent Freeway Bottlenecks

Variable Speed Limit (VSL) strategies identify and disseminate dynamic speed limits that are determined to be appropriate based on prevailing traffic conditions, road surface conditions, and weather conditions. This dissertation develops and evaluates a shockwave-based VSL system that uses a heuristic switching logic-based controller with specified thresholds of prevailing traffic flow conditions. The system aims to improve operations and mobility at critical bottlenecks. Before traffic breakdown occurrence, the proposed VSL’s goal is to prevent or postpone breakdown by decreasing the inflow and achieving uniform distribution in speed and flow. After breakdown occurrence, the VSL system aims to dampen traffic congestion by reducing the inflow traffic to the congested area and increasing the bottleneck capacity by deactivating the VSL at the head of the congested area. The shockwave-based VSL system pushes the VSL location upstream as the congested area propagates upstream. In addition to testing the system using infrastructure detector-based data, this dissertation investigates the use of Connected Vehicle trajectory data as input to the shockwave-based VSL system performance. Since the field Connected Vehicle data are not available, as part of this research, Vehicle-to-Infrastructure communication is modeled in the microscopic simulation to obtain individual vehicle trajectories. In this system, wavelet transform is used to analyze aggregated individual vehicles’ speed data to determine the locations of congestion. The currently recommended calibration procedures of simulation models are generally based on the capacity, volume and system-performance values and do not specifically examine traffic breakdown characteristics. However, since the proposed VSL strategies are countermeasures to the impacts of breakdown conditions, considering breakdown characteristics in the calibration procedure is important to have a reliable assessment. Several enhancements were proposed in this study to account for the breakdown characteristics at bottleneck locations in the calibration process. In this dissertation, performance of shockwave-based VSL is compared to VSL systems with different fixed VSL message sign locations utilizing the calibrated microscopic model. The results show that shockwave-based VSL outperforms fixed-location VSL systems, and it can considerably decrease the maximum back of queue and duration of breakdown while increasing the average speed during breakdown.

Design Strategies for an Artificial Neural Network Based Algorithm for Automatic Incident Detection on Major Arterial Streets

Traffic incidents are non-recurring events that can cause a temporary reduction in roadway capacity. They have been recognized as a major contributor to traffic congestion on our national highway systems. To alleviate their impacts on capacity, automatic incident detection (AID) has been applied as an incident management strategy to reduce the total incident duration. AID relies on an algorithm to identify the occurrence of incidents by analyzing real-time traffic data collected from surveillance detectors. Significant research has been performed to develop AID algorithms for incident detection on freeways; however, similar research on major arterial streets remains largely at the initial stage of development and testing. This dissertation research aims to identify design strategies for the deployment of an Artificial Neural Network (ANN) based AID algorithm for major arterial streets. A section of the US-1 corridor in Miami-Dade County, Florida was coded in the CORSIM microscopic simulation model to generate data for both model calibration and validation. To better capture the relationship between the traffic data and the corresponding incident status, Discrete Wavelet Transform (DWT) and data normalization were applied to the simulated data. Multiple ANN models were then developed for different detector configurations, historical data usage, and the selection of traffic flow parameters. To assess the performance of different design alternatives, the model outputs were compared based on both detection rate (DR) and false alarm rate (FAR). The results show that the best models were able to achieve a high DR of between 90% and 95%, a mean time to detect (MTTD) of 55-85 seconds, and a FAR below 4%. The results also show that a detector configuration including only the mid-block and upstream detectors performs almost as well as one that also includes a downstream detector. In addition, DWT was found to be able to improve model performance, and the use of historical data from previous time cycles improved the detection rate. Speed was found to have the most significant impact on the detection rate, while volume was found to contribute the least. The results from this research provide useful insights on the design of AID for arterial street applications.

Molecular characterization of GcC8 alpha, the functional homologue of human C8 alpha in the shark, Ginglymostoma cirratum

The focus of this study is to elucidate the components of the nurse shark (Ginglymostoma cirratum) membrane attack complex (MAC), specifically complement component C8a (GcC8u). Nurse shark C8a gene was cloned, sequenced, and analyzed and Western blot analysis performed to identify components of shark MAC. GcC8a consists of 2341 nucleotides that translate into a 589 amino acid sequence that shares 41.1% and 47.4 % identity with human and xenopus C8a, respectively. GcC8a conserves the MAC modular architecture and cysteine-rich backbone characteristic of complement proteins, including the cysteine residue that forms the C8a-y bond as well as the indel that is unique to C8a. Conservation of MAC protein structure is evident from crossreactivity of antihuman-MAC antibodies with shark serum proteins in Western blots which confirmed the presence of C8 and C9-like proteins in shark serum, however, did not resolve the question of whether C6 and/or C7 like proteins are present in shark.