The three-dimensional (3-D) structure of gp32*I, a major proteolytic fragment of the DNA helix-destabilizing protein from bacteriophage T4, has been determined at 18 A resolution by electron microscopy of negatively stained crystals and computer image analysis. The crystalline areas processed in 3-D have the symmetry of the space group P2₁, with a = 47 Å, b = 63 Å, c = 65 Å, and α = β = γ = 90°. This P2₁ unit cell contains one gp32*I molecule per asymmetric unit. The molecule is roughly V-shaped, containing two large domains linked by a smaller domain occupying the base of the V. The total length of the molecule is about 110 Å with an average diameter of about 25 Å. Systematic analysis of the symmetry in images of untilted crystals determined that the crystal could display several types of projection symmetry, pgg, pg corresponding to P2₁ symmetry with the screw axis along the a axis of the crystal, and pg corresponding to P2₁ symmetry with the screw axis along the b axis. Among images displaying pg symmetry along the b axis, two types of images with noticeably different appearances were obtained. A hypothesis was formed that explained the different types of symmetry as the result of the growth of the gp32*I crystal in the space group P2₁ 2₁ 2₁, in steps of 1/2 of a unit cell along the thin direction of the crystal. Two different types of 1/2 unit cell thick steps were postulated. Computer simulations were used to generate synthetic images of untilted crystals containing either one, two or three steps of each kind. The results of the simulations prove that the space group of the gp32*I crystal is P2₁ 2₁ 2₁. They suggest that careful analysis of the symmetry in images of untilted gp32*I crystals can provide information about the thickness of the crystals. A strategy is presented for determining the structure of the gp32*I crystal at higher resolution by electron microscopy of frozen, hydrated crystals. This strategy includes the use of symmetry analysis as a tool for determining the thickness of the crystals so that data from crystals of the same thickness can be combined in 3-D. A similar approach may prove useful in the 3-D electron microscopic analysis of other thin, multi-layered crystals.

This study used polyacrylamide gel electrophoresis to study the acid-phenol soluble proteins of five strains (A. vinelandii 12837, A. vinelandii 0, A. chroococcum 8004, A. macrocytogenes 8702, A. tumefaciens) of bacteria grown on Burk's nitrogen-free media, Trypticase Soy Broth, and 0.3% butanol medium. The results showed that the protein patterns can be used for the identification and possibly the taxonomic classification of the Azotobacter. The change of phenotype of the bacteria in different media followed the change of protein quantity and quality. There was no absolute similarity between any two of the species studied and this suggests a genetically heterogenous group of organisms while the amount of common proteins suggests close genetic relationships. Further studies are necessary to confirm the status of A. tumefaciens.

Cell adhesion is a critical process that allows the organisation and functioning of tissues in three-dimensions. However, the replenishing of cells, via cell division, within tissues is equally important for functioning complex life. Both cell adhesion and division are tightly controlled processes and rely on a complex network of signals that, as yet, are not wholly understood. This Thesis presents a structural analysis of several proteins involved in these processes. In the case of cell adhesion, we have made use of high-throughput (HTP) cloning and expression screening technologies in the Oxford Protein Production Facility (OPPF) for the study of the Kindlin protein family – a recently discovered set of proteins essential for integrin-mediated cell adhesion. As a direct result of the HTP pipeline used we were able to determine the high resolution crystal structure of a single domain, the Pleckstrin Homology Domain, from the isoform Kindlin-1. Deletion of this domain in the full-length protein resulted in impaired integrin activation in vivo. This structure, in combination with molecular dynamics simulation demonstrated that, unlike other well characterised PH domains, the binding of secondary messenger lipids (phosphoinositides) is dictated by a, previously unseen, salt bridge that occludes the putative binding site. Mutation of the salt bridge alters the binding characteristics of this domain in vitro. In addition to the PH domain, we have also studied and biophysically characterised full-length Kindlin-3, a blood cell specific isoform. By optimising baculovirus-infected Sf9 cell expression systems we were able to obtain, for the first time, sufficient quantities of protein for characterisation. Furthermore, by using small-angle X-ray scattering (SAXS) in solution we were able to determine a low resolution solution structure of Kindlin-3, revealing a linear arrangement of its FERM domain - a novel conformation known only otherwise in talin. We characterised the interaction of full-length Kindlin-3 with β-integrin cytoplasmic tails using nuclear magnetic resonance spectroscopy, which confirmed that a direct interaction with a membrane distal NPxY motif occurs, and demonstrated the importance of a preceding Serine/Threonine rich region in peptide binding. In the case of cell division, we have determined the crystal structure of the cell cycle checkpoint control related protein, Cid1, a terminal uridine tranferase from Schizzosaccharomyces pombe, alone and in complex with UTP. Structural and biochemical analysis of Cid1 identified a novel Uridine selection mechanism that is suggested to be conserved in metazoan ZCCHC enzymes involved in let-7 miRNA biogenesis, which are important for proliferation, differentiation and cell fate. We have also demonstrated that Cid1 is an RNA binding protein, a property essential for activity that employs a novel mechanism of RNA binding in the absence of RNA binding motifs. The structural work undertaken in this thesis has focussed on two distinct, but interwoven, aspects of cell biology and has significantly added to both fields of research. Excitingly, this has opened many new avenues of investigation and, in the case of Cid1, has the strong potential to lead to the development of novel anticancer therapies.

by Chan Wing-yee. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1993. / Includes bibliographical references (leaves 93-95). / ACKNOWLEDGEMENT --- p.i / ABSTRACT --- p.ii / Chapter CHAPTER 1 --- INTRODUCTION --- p.1 / Chapter 1.1 --- General Introduction --- p.1 / Chapter 1.2 --- "Clinical Significance of Fe, Cu and Zn" --- p.2 / Chapter 1.3 --- Alternative Methods of Analysis --- p.5 / Chapter 1.4 --- Principles of Energy Dispersive X-ray Fluorescence Spectrometry --- p.11 / Chapter 1.5 --- Research Plan --- p.20 / Chapter CHAPTER 2 --- EXPERIMENTAL --- p.22 / Chapter 2.1 --- Energy Dispersive X-ray Fluorescence Analysis --- p.22 / Chapter 2.1.1 --- Apparatus --- p.22 / Chapter 2.1.2 --- Reagents --- p.25 / Chapter 2.1.3 --- Procedure --- p.28 / Chapter 2.2 --- Atomic Absorption Spectrometric Analysis --- p.32 / Chapter 2.2.1 --- Apparatus --- p.32 / Chapter 2.2.2 --- Reagents --- p.32 / Chapter 2.2.3 --- Procedure --- p.34 / Chapter CHAPTER 3 --- RESULTS AND DISCUSSION --- p.38 / Chapter 3.1 --- Optimisation of Excitation Conditions --- p.38 / Chapter 3.1.1 --- Effect of Filter --- p.38 / Chapter 3.1.2 --- Effect of Tube Voltage --- p.43 / Chapter 3.1.3 --- Effect of Tube Current --- p.44 / Chapter 3.2 --- Optimisation of Preconcentration Procedure --- p.46 / Chapter 3.2.1 --- Effect of Sample Area and Collimator Size --- p.46 / Chapter 3.2.2 --- Effect of pH --- p.51 / Chapter 3.2.3 --- Effect of Ligand Concentration --- p.54 / Chapter 3.2.4 --- Effect of Mixing Time --- p.57 / Chapter 3.2.5 --- Effect of Standing Time --- p.59 / Chapter 3.2.6 --- Study of Sample Homogeneity --- p.61 / Chapter 3.3 --- Optimisation for Deproteination --- p.63 / Chapter 3.3.1 --- Effect of Different Protein Precipitants --- p.63 / Chapter 3.3.2 --- Effect of Trichloroacetic Acid Concentration --- p.65 / Chapter 3.3.3 --- Effect of Hydrochloric Acid Concentration --- p.67 / Chapter 3.3.4 --- Effect of Temperature --- p.69 / Chapter 3.3.5 --- Effect of Incubation Time --- p.71 / Chapter 3.4 --- Study of Blanks --- p.74 / Chapter 3.5 --- Construction of Calibration Curves --- p.77 / Chapter 3.6 --- Determination of Detection Limit and Sensitivity --- p.84 / Chapter 3.7 --- Accuracy and Reproducibility Tests --- p.86 / Chapter 3.8 --- Parallel Check --- p.89 / Chapter CHAPTER 4 --- CONCLUSION --- p.92 / REFERENCES --- p.93

by Li Leung Wah. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1993. / Includes bibliographical references (leaves 76-81). / Acknowledgements / Abstract / Chapter 1. --- Protein modeling --- p.1 / Chapter 1.1 --- Genetic Engineering --- p.1 / Chapter 1.2 --- Protein Engineering --- p.2 / Chapter 1.2.1 --- The basic concept --- p.2 / Chapter 1.2.2 --- The importance of protein modeling --- p.3 / Chapter 1.2.3 --- Applications --- p.4 / Chapter 1.2.3.1 --- Industry --- p.4 / Chapter 1.2.3.2 --- Medicine --- p.4 / Chapter 1.3 --- The structure of protein molecule --- p.5 / Chapter 2. --- About this thesis --- p.8 / Chapter 2.1 --- Methods on protein tertiary structure prediction --- p.8 / Chapter 2.1.1 --- Energy minimization method --- p.9 / Chapter 2.1.2 --- Sequence homology method --- p.9 / Chapter 2.1.3 --- Hierarchical assembly method --- p.11 / Chapter 2.2 --- Artificial Intelligence and molecular modeling --- p.11 / Chapter 2.3 --- Computer graphics and molecule display --- p.13 / Chapter 2.3.1 --- Molecular model in computer graphics --- p.13 / Chapter 2.3.2 --- Interactive graphic operations --- p.16 / Chapter 2.4 --- The objective of this thesis --- p.17 / Chapter 3. --- Algorithms for protein secondary structure prediction --- p.20 / Chapter 3.1 --- Hydrophobicity --- p.20 / Chapter 3.2 --- Algorithms for protein secondary structure prediction --- p.22 / Chapter 3.2.1 --- The Chou and Fasman method --- p.23 / Chapter 3.2.1.1 --- Method --- p.24 / Chapter 3.2.1.2 --- Results --- p.25 / Chapter 3.2.2 --- The GOR method --- p.26 / Chapter 3.2.2.1 --- Theory --- p.26 / Chapter 3.2.2.2 --- Method and results --- p.26 / Chapter 3.3 --- A proposed algorithm --- p.28 / Chapter 3.3.1 --- Procedure of our algorithm --- p.30 / Chapter 4. --- A protein tertiary structure prediction method --- p.31 / Chapter 4.1 --- The linkage between two amino acids --- p.32 / Chapter 4.2 --- Rotation angle between two peptide planes --- p.34 / Chapter 4.2.1 --- Helical structure --- p.35 / Chapter 4.2.1.1 --- Concept --- p.35 / Chapter 4.2.1.2 --- Procedure --- p.36 / Chapter 4.2.2 --- Sheet structure --- p.37 / Chapter 4.2.3 --- Turn structure --- p.38 / Chapter 4.2.4 --- Anti-parallel sheet and turn structure --- p.40 / Chapter 4.3 --- Random factor in rotation angle of peptide planes --- p.41 / Chapter 4.4 --- Atomic size --- p.41 / Chapter 4.5 --- Tertiary structure prediction algorithm --- p.42 / Chapter 5. --- Implementation --- p.45 / Chapter 5.1 --- Hardware --- p.45 / Chapter 5.2 --- User-defined data types and data structures --- p.46 / Chapter 5.3 --- Technique in molecule displaying --- p.48 / Chapter 5.4 --- Image processing --- p.50 / Chapter 5.5 --- Options in our program --- p.52 / Chapter 5.6 --- Steps in protein tertiary structure prediction --- p.54 / Chapter 6. --- Results --- p.59 / Chapter 6.1 --- The results of protein secondary structure prediction --- p.59 / Chapter 6.2 --- The results of protein tertiary structure prediction --- p.66 / Chapter 7. --- Conclusion --- p.70 / Chapter 7.1 --- Comments on protein secondary structure prediction algorithm --- p.70 / Chapter 7.1.1 --- Advantages and disadvantages --- p.70 / Chapter 7.1.2 --- Further development --- p.71 / Chapter 7.2 --- Discussion on X-ray crystallographic data --- p.72 / Chapter 7.3 --- Comments on the protein tertiary structure prediction algorithm --- p.73 / Chapter 7.3.1 --- Advantages and disadvantages --- p.73 / Chapter 7.3.2 --- Further development --- p.74 / Chapter 7.3.2.1 --- Rotation angle between two peptide planes --- p.74 / Reference --- p.76 / Glossary --- p.82 / Appendix A An algorithm to determine hydrophobic value --- p.83 / Appendix B Chou and Fasman algorithm --- p.84 / Appendix C GOR algorithm --- p.87 / Appendix D Shading algorithm --- p.88

Integral Membrane Proteins (IMPs) are an important and scientifically interesting class of protein which span the lipid bilayer surrounding cells, cell compartments and many viruses. Molecular Dynamics (MD) simulation has revealed intimate and often highly specific relationships between membrane lipids and IMPs critical to many metabolic and signalling pathways. Meanwhile, the use of Coarse-Grained (CG) MD techniques has extended capabilities of biomolecular simulation to larger proteins over longer time periods. Several tools and resources for biomolecular simulations of IMPs are presented here, as well as two MD studies of specific IMPs. The previously developed MemProtMD pipeline automates the setup of MD simulations of IMPs; major extensions to this are presented here with the MemProtMD database and web server, automating the analysis of IMP simulations. The results of this can be viewed using the MemProtMD web server, an interactive, searchable online resource containing data from simulations of over 3000 experimentally determined IMP structures in explicit lipid bilayers. Using data from analysis of the entire MemProtMD database, MemProtMetrics has been developed to automate identification and orientation of IMP structures from Protein DataBank (PDB) depositions. This is shown to effectively predict membrane protein orientations seen in MD simulations. A tool for identification and classification of membrane lipids is also described, and used to identify over 500 IMPs structures with resolved lipids. CGMD simulations have also been used to assess dependence on side-chain ionisation state of interactions between lipids and two IMPs observed in mass spectrometry experiments. The simulations reveal similar trends to those seen in experiments. Finally, using multi-scale simulations, and through the development of a novel method for altering membrane composition in MD simulations, lipid-specific scramblase activity was shown for a novel structure of the TMEM16K scramblase IMP.

競爭性內源核糖核酸(ceRNA) 假設最近已成為生物訊息學研究中最熱門的話題之一。Cell 是在生物科學界上經常被引用的學術期刊，早前亦有一班學者在Cell 2011年同一期成功發佈四篇關於ceRNA 假設的學術文章。跟據有關ceRNA 假設的學術文章，大部份學者均以不同的個別例子成功驗證假定，可是，欠缺一個大規模的及全面性的分析。 / 在我兩年碩士的研究中，我引入了一個新的概念微核糖核酸及其目標對向聚類(MTB) 運用了ceRNA 的假設，還提出算法，成功從微核糖核酸與信使核糖核酸的相互數據中找出一系列的MTB' 還利用GENCODE 項目上大量的微核糖核酸及信使核糖核酸的表達數據去驗証MTB 的概念。一方面，我從大量的表達數據中成功推斷出微核糖核酸與信使核糖核酸之間的相反關連、信使核糖核酸之間的正面關運和微核糖核酸之間的正面關連;另一方面，這些關連進一步肯定ceRNA 假設的真實性。此外，我提出一個從大量基因組中找出基因功能分析的方法，並在大量的MTB 的基因組中找出重要的基因註解。最後，我提出另一個MTB 概念的應用一新算法來預測微核糖核酸與信使核糖核酸的相互影響。總括而吉， MTB 概念從複雜且混亂的微核糖核酸與信使核糖核酸網絡中定義簡單且穩固的模姐，提供一個系統生物學分析微核糖核酸調節能力的方法。 / The competing Endogenous RNA (ceRNA) hypothesis has become one of the hottest topics in bioinformatics research recently. Four papers related to the ceRNA hypothesis were published simultaneously in Cell in 2011, a top journal in life sciences. For most papers related to the ceRNA hypothesis, the corresponding studies have successfully validated the hypothesis with different individual examples, without a large-scale and comprehensive analysis. / In my Master of Philosophy study, a novel concept, called mi-RNA Target Bicluster (MTB), is introduced to model the ceRNA hypothesis. The MTBs are identified computationally from validated and/or predicted miRNA-mRNA interaction pairs. The MTB models were tested with the mRNAs and miRNAs expression data from the GENCODE Project. Statistically significant miRNA-mRNA anti-correlation, mRNA-mRNA correlation and miRNA-miRNA correlation in expression data are found, verifying the correlation relations among mRNAs and miRNAs stated in the ceRNA hypothesis with large-scale data support. Moreover, a novel large-scale functional enrichment analysis is performed, and the mRNAs selected by the MTBs are found to be biologically relevant. Besides, some new target prediction algorithms are suggested, as another application of the MTBs, are suggested. Overall, the concept of MTB defines simple and robust modules from the complex and noisy miRNA-mRNA network, suggesting ways for system biology analyses in miRNA-mediated regulations. / Detailed summary in vernacular field only. / Detailed summary in vernacular field only. / Yip, Kit Sang Danny. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2013. / Includes bibliographical references (leaves [117]-126). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstracts also in Chinese. / Abstract --- p.i / Acknowledgement --- p.iv / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Contributions --- p.1 / Chapter 1.2 --- Thesis Outline --- p.2 / Chapter 2 --- Background --- p.3 / Chapter 2.1 --- Bioinformatics --- p.3 / Chapter 2.2 --- Biological Background --- p.7 / Chapter 2.2.1 --- The Central Dogma of Molecular Biology . --- p.7 / Chapter 2.2.2 --- RNAs --- p.8 / Chapter 2.2.3 --- Competing Endogenous RNA (ceRNA) hypothesis --- p.9 / Chapter 2.2.4 --- Biological Considerations in Functional Enrichment Analysis --- p.11 / Chapter 2.3 --- Computational Background --- p.12 / Chapter 2.3.1 --- miRNA Genomic Annotation Prediction --- p.13 / Chapter 2.3.2 --- miRNA Target Interaction Prediction --- p.14 / Chapter 2.3.3 --- Applying Computational Algorithms on Related Problems --- p.16 / Chapter 2.3.4 --- Algorithms in Functional Enrichment Analysis --- p.16 / Chapter 2.4 --- Experiments and Data --- p.17 / Chapter 2.4.1 --- miRNA Target Interactions --- p.17 / Chapter 2.4.2 --- Expression Data --- p.18 / Chapter 2.4.3 --- Annotation Datasets --- p.19 / Chapter 2.5 --- Research Motivations --- p.20 / Chapter 3 --- Definitions of miRNA Target Biclusters (MTB) --- p.22 / Chapter 3.1 --- Representations --- p.22 / Chapter 3.1.1 --- Binary Association Matrix Representation --- p.23 / Chapter 3.1.2 --- Bipartite Graph Representation --- p.23 / Chapter 3.1.3 --- Mathematical Representation --- p.24 / Chapter 3.2 --- Concept of MTB --- p.24 / Chapter 3.2.1 --- MTB Restrictive Type (Type R) --- p.27 / Chapter 3.2.2 --- MTB Restrictive Type on miRNA (Type Rmi) --- p.31 / Chapter 3.2.3 --- MTB Restrictive Type on mRNA (Type Rm) --- p.34 / Chapter 3.2.4 --- MTB Restrictive and General Type (Type Rgen) --- p.37 / Chapter 3.2.5 --- MTB Loose Type (Type L) --- p.44 / Chapter 3.2.6 --- MTB Loose Type but restricts on miRNA (Type Lmi) --- p.47 / Chapter 3.2.7 --- MTB Loose Type but restricts on mRNA (Type Lm) --- p.50 / Chapter 3.2.8 --- MTB Loose and General Type (Type Lgen) --- p.53 / Chapter 3.2.9 --- A General Definition on all Eight Types --- p.58 / Chapter 3.2.10 --- Discussions --- p.60 / Chapter 4 --- MTB Workflow in Checking Correlation Relations --- p.61 / Chapter 4.1 --- MTB Workflow in Checking Correlation Relations --- p.61 / Chapter 4.1.1 --- MTB Identification --- p.62 / Chapter 4.1.2 --- Correlation Coefficients --- p.63 / Chapter 4.1.3 --- Scoring Scheme --- p.64 / Chapter 4.1.4 --- Background Construction --- p.65 / Chapter 4.1.5 --- Wilcoxon Rank-sum Test --- p.66 / Chapter 4.1.6 --- Preliminary Studies --- p.67 / Chapter 4.2 --- miRNA-mRNA Anti-correlation in Expression Data --- p.68 / Chapter 4.2.1 --- Interaction Datasets --- p.69 / Chapter 4.2.2 --- Expression Datasets --- p.72 / Chapter 4.2.3 --- Independence of the Choices of Datasets --- p.73 / Chapter 4.2.4 --- Independence of the Types of MTBs --- p.76 / Chapter 4.2.5 --- Independence of the Choices of Correlation Coefficients --- p.78 / Chapter 4.2.6 --- Dependence on the Way to Score --- p.79 / Chapter 4.2.7 --- Independence of theWay to Construct Background --- p.81 / Chapter 4.2.8 --- Independence of Natural Bias in Datasets --- p.82 / Chapter 4.3 --- mRNA-mRNA Correlation in Expression Data --- p.84 / Chapter 4.3.1 --- Variations in the Analysis --- p.85 / Chapter 4.3.2 --- Discussions --- p.87 / Chapter 4.4 --- miRNA-miRNA Correlation in Expression Data --- p.88 / Chapter 4.4.1 --- Variations in the Analysis --- p.89 / Chapter 4.4.2 --- Discussions --- p.92 / Chapter 5 --- Target Prediction Aided by MTB --- p.94 / Chapter 5.1 --- Workflow in Target Prediction --- p.94 / Chapter 5.2 --- Contingency Table Approach --- p.96 / Chapter 5.2.1 --- One-tailed Hypothesis Testing --- p.97 / Chapter 5.3 --- Ranked List Approach --- p.98 / Chapter 5.3.1 --- Wilcoxon Signed Rank Test --- p.99 / Chapter 5.4 --- Results and Discussions --- p.99 / Chapter 6 --- Large-scale Functional Enrichment Analysis --- p.102 / Chapter 6.1 --- Principles in Functional Enrichment Analysis --- p.102 / Chapter 6.1.1 --- Annotation Files --- p.104 / Chapter 6.1.2 --- Functional Enrichment Analysis on a gene --- p.set105 / Chapter 6.1.3 --- Functional Enrichment Analysis on many gene sets --- p.106 / Chapter 6.2 --- Results and Discussions --- p.107 / Chapter 7 --- Future Perspectives and Conclusions --- p.112 / Chapter 7.1 --- Applying MTB definition on other problems --- p.112 / Chapter 7.2 --- Matrix Definitions and Optimization Problems --- p.113 / Chapter 7.3 --- Non-binary association matrix problem settings --- p.114 / Chapter 7.4 --- Limitations --- p.114 / Chapter 7.5 --- Conclusions --- p.116 / Bibliography --- p.117 / Chapter A --- Publications --- p.127 / Chapter A.1 --- Publications --- p.127

published_or_final_version / Chemistry / Master / Master of Philosophy

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