A synthetic analog of a spider silk protein (M4) was studied. Langmuir films were made and an inflexion in the isotherm indicated conformational changes upon compression. Deposition onto solid substrates was most successful using a hydrophobic substrate and the Langmuir-Schaeffer method. AFM was used to image the surface, which was mesh like and did not show any indication of order. / Gold nanoparticles were produced in the presence of the protein and protein solutions were added to read made nanoparticles for the purpose of displacing the weak ligands present. CD measurements were performed on the protein solutions to study its conformation. Nanoparticle size information was obtained from TEM images. DLS was used to determine if the protein was affected by the addition of the gold nanoparticles. Precipitation of the protein was shown not to affect the nanoparticles.

No description available.

No description available.

Submitted in fulfillment of the requirements of the Degree of Doctor of Technology: Chemistry, Durban University of Technology, 2011. / Understanding the dynamics and mechanism of protein folding continues to be one of the central problems in molecular biology. Peptide folding experiments characterize the dynamics and molecular mechanisms of the early events of protein folding. However, generally the highly flexible nature of peptides makes their bioactive conformation assessment reasonably difficult as peptides fold at very fast rates experimentally, requiring probing on the nanosecond time resolution. On the other hand, determining the bioactive conformation of biological peptides is a requirement for the design of peptidomimetics in computer-aided drug design. Peptides offer a unique opportunity to bridge the gap between theoretical and experimental understanding of protein folding. Therefore, the present work focuses on the exploration of the conformational space of biologically active neuropeptides with the aim of characterizing their conformational profile. Specifically, bombesin, neuromedin B (NMB) and neuromedin C (NMC), have been chosen for the current investigations. These peptides are widely distributed in the gastrointestinal tract, spinal cord and brain, and are known to elicit various physiological effects, including inhibition of feeding, smooth muscle contraction, exocrine and endocrine secretions, thermoregulation, blood pressure and sucrose regulations and cell growth. These peptides act as a growth factor in a wide range of tumours including carcinomas of the pancreas, stomach, breast, prostate, and colon. This work is intended to get some insight into the performance of different procedures used to explore the configurational space to provide an adequate atomic description of these systems. Different methodological studies involving utilization of molecular dynamics (MD), multicanonical replica exchange molecular dynamics (REMD) and simulate annealing (SA) are undertaken to explore the folding characteristics and thermodynamics of these neuropeptides. MD and REMD calculations on bombesin peptide have revealed its dual conformational behaviour never discovered before and is described in chapter 3. These results explain the known structure-activity studies and open the door to the understanding of the affinity of this peptide to two different receptors: BB1 and BB2. In the case of NMC, REMD calculations are carried out in explicit and implicit solvents, using the Generalized Born (GB) surface area, and are then complemented with two additional MD simulations performed using Langevin and Berendsen thermostats. The results obtained clearly reveal that REMD, performed under explicit solvent conditions, is more efficient and samples preferentially folded conformations with a higher content of  and γ turns. Moreover, these results show good agreement with the experimental results supporting the role of two -turns for its biological action, as reported in the literature. Finally, the results obtained from MD, REMD and SA calculations on NMB reveal that the peptide has a tendency to adopt both turns and helices suggesting its two different receptor recognizing and binding conformations during its biological action. Hence, the present work provides comprehensive information about the conformational preferences of neuropeptides which could lead to a better understanding of their native conformations for future investigations and point the way towards developing their new antagonists.

Electrostatic interaction has long been proposed to be an important factor for stabilizing protein. Charge-charge interaction may especially be important to the thermostability of protein, as having more surface electrostatic interactions is one of the common structural features found in thermophilic proteins when compared to their mesophilic homologues. In order to quantitatively investigate the electrostatic contribution to protein stability, two complementary approaches, namely the double mutant cycle approach and pKa shift approach, were carried out. / In the double mutant cycle approach, the coupling free energies of two salt bridges (E6/R92 and K46/E62) and one a long range ion pair (E90/R92) were estimated by using circular dichroism, to find out the thermodynamic parameters of the protein model Thermococcus celer L30e and its charge-to-neutral mutants. It was found that the coupling free energy was temperature independent and was about 3 kJ mol-1 per salt bridge. By using a novel analysis of double mutant cycle of DeltaC p, it was also found that the interaction of salt bridge plays an important role in the reduction of DeltaCp. The temperature independency of coupling free energy and the effect of reducing DeltaCp could explain the general observation very well that thermophilic proteins have highly up-shifted protein stability curves is due to its elevated electrostatic interactions when compared with their mesophilic homologs. / In the pKa shift approach, the native state pKa values of acidic residues were obtained by fitting the side chain carboxyl 13C chemical shifts to microscopic model or global fitting of titrational event (GloFTE), whereas the denatured state pKa values were obtained by conventional pH titration of terminal protected 5-residue glycine-based model peptide. It was found that the surface charge-charge interactions, either attractive or repulsive, were strong and complicated because of the high surface charge density of T. celer L30e. However, the fact that most of the acidic residues have significantly downshifted native state pK a values indicated the surface charge distribution of T. celer L30e is optimized for stabilizing the protein. In addition, we have shown that temperature has negligible effect on pKa values in both native state and denatured state, therefore temperature can only marginally amplify the stabilizing effect in linear manner. / To overcome the unwanted crystallization problem of wild-type T. celer L30e in the low ionic strength neutral pH NMR conditions, which were essential for the pKa shift approach, a quintuple Arg-to-Lys variant was designed to dramatically improve the crystalline solubility, while the surface charges, as well as the structural, thermodynamic, and electrostatic properties, were conserved. It has also shown that electrostatic interaction played a critical role in crystallization at low ionic strength conditions, and arginine residue was especially important in crystal packing because of its high ability of forming salt bridges and hydrogen bonds. / Wild-type T. celer L30e has also shown to have no observable residual structure in the guanidine HC1-induced denatured state, indicating that denatured state of T. celer L30e should not have large effect on the overall protein stability. / Chan, Chi Ho. / Adviser: Kam Bo Wong. / Source: Dissertation Abstracts International, Volume: 73-01, Section: B, page: . / Thesis (Ph.D.)--Chinese University of Hong Kong, 2010. / Includes bibliographical references (leaves 202-218). / Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web. / Abstract also in Chinese.

Abstract not available

The translocation of a biopolymer through a narrow pore exists in universal cellular processes, such as the translocations of nascent proteins through ribosome and the degradation of protein by ATP-dependent proteases. However, the molecular details of these translocation processes remain unclear. Using computer simulations we study the translocations of a ubiquitin-like protein into a pore. It shows that the mechanism of co-translocational unfolding of proteins through pores depends on the pore diameter, the magnitude of pulling force and on whether the force is applied at the N- or the C-terminus. Translocation dynamics depends on whether or not polymer reversal is likely to occur during translocation. Although it is of interest to compare the timescale of polymer translocation and reversal, there are currently no theories available to estimate the timescale of polymer reversal inside a pore. With computer simulations and approximate theories, we show how the polymer reversal depends on the pore size, r, and the chain length, N. We find that one-dimensional transition state theory (TST) using the polymer extension along the pore axis as a reaction coordinate adequately predicts the exponentially strong dependence of the reversal rate on r and N. Additionally, we find that the transmission factor (the ratio of the exact rate and the TST rate) has a much weaker power law dependence on r and N. Finite-size effects are observed even for chains with several hundred monomers. If metastable states are separated by high energy-barriers, transitions between them will be rare events. Instead of calculating the relative energy by studying those transitions, we can calculate absolute free energy separately to compare their relative stability. We proposed a method for calculating absolute free energy from Monte Carlo or molecular dynamics data. Additionally, the diffusion of a knot in a tensioned polymer is studied using simulations and it can be modeled as a one-dimensional free diffusion problem. The diffusion coefficient is determined by the number of monomers involved in a knot and its tension dependence shows a maximum due to two dominating factors: the friction from solvents and “local friction” from interactions among monomers in a compact knot. / text

The function of a protein is largely dictated by its natural shape called the "native conformation." Since the native conformation and the global minimum energy configuration highly correlate, predicting this conformation is a global optimization known as the "protein folding problem." It is computationally intensive due to the high-dimensional and complex energy landscape. Typical conformation algorithms combine a probabilistic search with analytical optimization. The analytical portion typically takes longer than the probabilistic part since more function evaluations are required, which are algorithm bottlenecks. To reduce the computational cost, this research studies the effects of exponential energy landscaping (XEL) on three analytical optimization algorithms: Newton's method, a quasi-Newton algorithm (QNA), and the Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm. The XEL changes the heights and the depths of the extrema but keeps their location the same, which eliminates the troublesome process of remapping minima onto the original landscape. The Newton-XEL is found to have a similar convergence property as Newton's method by showing that their error residues are of the same order. Found by observation, stability and convergence are improved when the error residue is bounded. While XEL is found to have no effect on the similarity of resulting configurations to the native conformation, results show that the XEL can improve the speed in terms of average iterations in the QNA by 47% and in the BFGS by 41%. In terms of the average score improvement, which indicates how the energy of the resulting configuration is compared to that of the initial configuration, the XEL can improve the quality of resulting configurations in the QNA by 12% and in the BFGS by 10%. Since both results were not achieved simultaneously, the adaptive exponential energy landscaping (AXEL) is developed. The results lead to the conclusion that a trade-off between quality and speed must be considered when XEL is implemented. To improve speed by 15% to 47% and efficiency by 13% to 75%, XEL with n within 2⁻⁹-2⁻⁵ should be used and to improve quality by 4% to 7%, AXEL with Scheme E that keeps the error residue bounded should be used.

Proteins are composed of a unique sequence of amino acids, whose order guides a protein to adopt its particular fold and perform a specific function. It has been shown that a protein's 3-dimensional structure is embedded within its primary sequence. The problem that remains elusive to biochemists is how a protein's primary sequence directs the folding to adopt such a specific conformation. In an attempt to gain a better understanding of protein folding, my research tests a novel model of protein packing using protein design. The model defines the knob-socket construct as the fundamental unit of packing within protein structure. The knob-socket model characterizes packing specificity in terms of amino acid preferences for sockets in different environments: sockets filled with a knob are involved in inter-helical interactions and free sockets are involved in intra-helical interactions. Equipped with this knowledge, I sought to design a unique protein, Ksα1.1, completely de novo. The sequence was selected to induce helix formation with a predefined tertiary packing interface. Circular dichroism showed that Ksα1.1 formed α-helical secondary structure as intended. The nuclear magnetic resonance studies demonstrated formation of a high order oligomer with increased protein concentration. These results and analysis prove that the knob-socket model is a predictive model for all α-helical protein packing. More importantly, the knob-socket model introduces a new protein design method that can potentially hold a solution to the folding problem.

Leung Ka-Kit. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2002. / Includes bibliographical references (leaves 129-131). / Abstracts in English and Chinese. / Abstract --- p.1 / Chapter CHAPTER 1. --- introduction --- p.14 / Chapter 1.1 --- Preamble --- p.14 / Chapter 1.2 --- Biological background --- p.14 / Chapter CHAPTER 2. --- previous related work --- p.18 / Chapter 2.1 --- Protein functionality analysis --- p.18 / Chapter 2.1.1 --- Analysis from primary structure --- p.18 / Chapter 2.1.2 --- Analysis from tertiary structure --- p.20 / Chapter 2.2 --- Secondary structure prediction --- p.21 / Chapter 2.3 --- Motivation - Challenges from protein complexity --- p.22 / Chapter CHAPTER 3. --- mathematical representations for protein properties and sequence alignment --- p.24 / Chapter 3.1 --- Secondary structure sequence model --- p.24 / Chapter 3.2 --- Substitution matrix --- p.26 / Chapter 3.3 --- Gap --- p.26 / Chapter 3.4 --- Similarity measurement --- p.27 / Chapter 3.5 --- Geometric Model for Protein --- p.28 / Chapter CHAPTER 4. --- overall system design --- p.30 / Chapter 4.1 --- System architecture and design --- p.30 / Chapter 4.2 --- System environment --- p.32 / Chapter 4.3 --- Experimental data --- p.32 / Chapter CHAPTER 5. --- adaptive dynamic programming (adp)- general global alignment consideration --- p.35 / Chapter 5.1 --- t-triangles cutting --- p.35 / Chapter 5.1.1 --- Theoretical time and memory requirements of ADP with z-triangles cutting --- p.43 / Chapter 5.1.1.1 --- Study of parameters affecting h in case 1 --- p.44 / Chapter 5.1.1.2 --- Study of parameters affecting h in case 2 --- p.45 / Chapter 5.1.2 --- Experimental results of ADP with z-triangles cutting --- p.46 / Chapter 5.2 --- Constructing the path matrix by expansion --- p.51 / Chapter 5.2.1 --- Time and memory requirements of EXPAND --- p.57 / Chapter 5.2.2 --- Experimental results and discussions --- p.58 / Chapter CHAPTER 6. --- adp - global alignment of sequences with consecutive repeated characters --- p.65 / Chapter 6.1 --- Estimation of similarity upper bound (Ba) --- p.65 / Chapter 6.1.1 --- Sequence composition (SC) consideration --- p.65 / Chapter 6.1.2 --- Implementation of SC --- p.67 / Chapter 6.1.3 --- Experimental results --- p.69 / Chapter 6.1.4 --- Overall trend of change of structures (OTCS) --- p.74 / Chapter 6.1.5 --- Uninformed search --- p.76 / Chapter 6.2 --- Short-cut --- p.80 / Chapter 6.2.1 --- Time and memory requirements --- p.86 / Chapter 6.2.2 --- Experimental results and discussions --- p.86 / Chapter CHAPTER 7. --- ga based topology discovery --- p.87 / Chapter 7.1 --- Chromosome encoding --- p.87 / Chapter 7.2 --- Non-sequential order penalty --- p.88 / Chapter 7.3 --- Fitness function --- p.88 / Chapter 7.4 --- Genetic operators --- p.88 / Chapter 7.4.1 --- Hop operator --- p.89 / Chapter 7.4.2 --- Inverse operator --- p.89 / Chapter 7.4.3 --- Shift operator --- p.90 / Chapter 7.4.4 --- Selection pressure --- p.90 / Chapter 7.5 --- Selection of progeny --- p.91 / Chapter 7.6 --- Implementation --- p.91 / Chapter 7.6.1 --- Size of population and generation --- p.91 / Chapter 7.6.2 --- Parallelization --- p.91 / Chapter 7.6.3 --- Crowding Handling --- p.92 / Chapter 7.6.4 --- Selection of progeny --- p.92 / Chapter 7.7 --- Results of alignment with GA exploration on topological order --- p.93 / Chapter CHAPTER 8. --- FILTERING OF FALSE POSITIVES --- p.103 / Chapter 8.1 --- Alignment Segments to Gap Ratio (ASGR) --- p.103 / Chapter 8.2 --- Tolerance --- p.104 / Chapter 8.3 --- Overall trend of change of structures (OTCS) --- p.104 / Chapter 8.4 --- Results and discussions --- p.105 / Chapter CHAPTER 9. --- SECONDARY STRUCTURE PREDICTION --- p.111 / Chapter 9.1 --- 3-STATE SECONDARY STRUCTURE PREDICTION IMPROVEMENT --- p.111 / Chapter 9.2 --- 8-state secondary structure prediction --- p.117 / Chapter 9.3 --- Iterative Subordinate Voting (IS V) --- p.117 / Chapter 9.4 --- ISV Results and discussion --- p.119 / Chapter CHAPTER 10. --- CONCLUSIONS --- p.123 / Chapter 10.1 --- Contributions --- p.123 / Chapter 10.2 --- Future Work --- p.126 / Chapter 10.2.1 --- Using database indexing --- p.126 / Chapter 10.2.2 --- 3-state secondary structure prediction improvement --- p.127 / appendix --- p.128 / Chapter ´Ø --- Interpretation on the dp一filter results --- p.128