Bio-inspired optimization & sampling technique for side-chain packing in MCCE

The prediction of proteins' conformation helps to understand their exhibited functions, allows for modeling and allows for the possible synthesis of the studied protein. Our research is focused on a sub-problem of protein folding known as side-chain packing. Its computational complexity has been proven to be NP-Hard. The motivation behind our study is to offer the scientific community a means to obtain faster conformation approximations for small to large proteins over currently available methods. As the size of proteins increases, current techniques become unusable due to the exponential nature of the problem. We investigated the capabilities of a hybrid genetic algorithm / simulated annealing technique to predict the low-energy conformational states of various sized proteins and to generate statistical distributions of the studied proteins' molecular ensemble for pKa predictions. Our algorithm produced errors to experimental results within .acceptable margins and offered considerable speed up depending on the protein and on the rotameric states' resolution used.

The effects of language complexity in a counterattitudinal appeal to laypeople : an application of the elaboration likelihood model of persuasion to a legal issue

The effects of a complexly worded counterattitudinal appeal on laypeople's attitudes toward a legal issue were examined, using the Elaboration Likelihood Model (ELM) of persuasion as a theoretical framework. This model states that persuasion can result from the elaboration and scrutiny of the message arguments (i.e., central route processing), or can result from less cognitively effortful strategies, such as relying on source characteristics as a cue to message validity (i.e., peripheral route processing). One hundred and sixty-seven undergraduates (85 men and 81 women) listened to eitller a low status or high status source deliver a counterattitudinal speech on a legal issue. The speech was designed to contain strong or weak arguments. These arguments were 'worded in a simple and, therefore, easy to comprehend manner, or in a complex and, therefore, difficult to comprehend manner. Thus, there were three experimental manipulations: argument comprehensibility (easy to comprehend vs. difficult to comprehend), argumel11 strength (weak vs. strong), and source status (low vs. high). After listening to tIle speec.J] participants completed a measure 'of their attitude toward the legal issue, a thought listil1g task, an argument recall task,manipulation checks, measures of motivation to process the message, and measures of mood. As a result of the failure of the argument strength manipulation, only the effects of the comprehel1sibility and source status manipulations were tested. There was, however, some evidence of more central route processing in the easy comprehension condition than in the difficult comprehension condition, as predicted. Significant correlations were found between attitude and favourable and unfavourable thoughts about the legal issue with easy to comprehend arguments; whereas, there was a correlation only between attitude and favourable thoughts 11 toward the issue with difficult to comprehend arguments, suggesting, perhaps, that central route processing, \vhich involves argument scrutiny and elaboration, occurred under conditions of easy comprehension to a greater extent than under conditions of difficult comprehension. The results also revealed, among other findings, several significant effects of gender. Men had more favourable attitudes toward the legal issue than did women, men recalled more arguments from the speech than did women, men were less frustrated while listening to the speech than were ,vomen, and men put more effort into thinking about the message arguments than did women. When the arguments were difficult to comprehend, men had more favourable thoughts and fewer unfavourable thoughts about the legal issue than did women. Men and women may have had different affective responses to the issue of plea bargaining (with women responding more negatively than men), especially in light of a local and controversial plea bargain that occurred around the time of this study. Such pre-existing gender differences may have led to tIle lower frustration, the greater effort, the greater recall, and more positive attitudes for men than for WOlnen. Results· from this study suggest that current cognitive models of persuasion may not be very applicable to controversial issues which elicit strong emotional responses. Finally, these data indicate that affective responses, the controversial and emotional nature ofthe issue, gender and other individual differences are important considerations when experts are attempting to persuade laypeople toward a counterattitudinal position.

Enabling and Measuring Complexity in Evolving Designs using Generative Representations for Artificial Architecture

As the complexity of evolutionary design problems grow, so too must the quality of solutions scale to that complexity. In this research, we develop a genetic programming system with individuals encoded as tree-based generative representations to address scalability. This system is capable of multi-objective evaluation using a ranked sum scoring strategy. We examine Hornby's features and measures of modularity, reuse and hierarchy in evolutionary design problems. Experiments are carried out, using the system to generate three-dimensional forms, and analyses of feature characteristics such as modularity, reuse and hierarchy were performed. This work expands on that of Hornby's, by examining a new and more difficult problem domain. The results from these experiments show that individuals encoded with those three features performed best overall. It is also seen, that the measures of complexity conform to the results of Hornby. Moving forward with only this best performing encoding, the system was applied to the generation of three-dimensional external building architecture. One objective considered was passive solar performance, in which the system was challenged with generating forms that optimize exposure to the Sun. The results from these and other experiments satisfied the requirements. The system was shown to scale well to the architectural problems studied.

Experimental and Computational Studies on Copper and Hydrobenzoin Derivatives in Catalytic Asymmetric Reactions

The use of theory to understand and facilitate catalytic enantioselective organic transformations involving copper and hydrobenzoin derivatives is reported. Section A details the use of theory to predict, facilitate, and understand a copper promoted amino oxygenation reaction reported by Chemler et al. Using Density Functional Theory (DFT), employing the hybrid B3LYP functional and a LanL2DZ/6-31G(d) basis set, the mechanistic details were studied on a N-tosyl-o-allylaniline and a [alpha]-methyl-[gamma]-alkenyl sulfonamide substrate. The results suggest the N-C bond formation proceeds via a cisaminocupration, and not through a radical-type mechanism. Additionally, the origin of diastereoselection observed with [alpha]-methyl-[gamma]-alkenyl sulfonamide arises from avoidance of unfavourable steric interactions between the methyl substituent and the N -protecting group. Section B details the computationally guided, experimental investigation of two hydrobenzoin derivatives as ligands/ catalysts, as well as the attempted synthesis of a third hydrobenzoin derivative. The bis-boronic acid derived from hydrobenzoin was successful as a Lewis acid catalyst in the Bignielli reaction and the Conia ene reaction, but provided only racemic products. The chiral diol derived from hydrobenzoin successfully increased the rate of the addition of diethyl zinc to benzaldehyde in the presence of titanium tetraisopropoxide, however poor enantioinduction was obseverved. Notably, the observed reactivity was successfully predicted by theoretical calculations.

Towards reverse engineering of Photosystem II: Synergistic Computational and Experimental Approaches

ABSTRACT Photosystem II (PSII) of oxygenic photosynthesis has the unique ability to photochemically oxidize water, extracting electrons from water to result in the evolution of oxygen gas while depositing these electrons to the rest of the photosynthetic machinery which in turn reduces CO2 to carbohydrate molecules acting as fuel for the cell. Unfortunately, native PSII is unstable and not suitable to be used in industrial applications. Consequently, there is a need to reverse-engineer the water oxidation photochemical reactions of PSII using solution-stable proteins. But what does it take to reverse-engineer PSII’s reactions? PSII has the pigment with the highest oxidation potential in nature known as P680. The high oxidation of P680 is in fact the driving force for water oxidation. P680 is made up of a chlorophyll a dimer embedded inside the relatively hydrophobic transmembrane environment of PSII. In this thesis, the electrostatic factors contributing to the high oxidation potential of P680 are described. PSII oxidizes water in a specialized metal cluster known as the Oxygen Evolving Complex (OEC). The pathways that water can take to enter the relatively hydrophobic region of PSII are described as well. A previous attempt to reverse engineer PSII’s reactions using the protein scaffold of E. coli’s Bacterioferritin (BFR) existed. The oxidation potential of the pigment used for the BFR ‘reaction centre’ was measured and the protein effects calculated in a similar fashion to how P680 potentials were calculated in PSII. The BFR-RC’s pigment oxidation potential was found to be 0.57 V, too low to oxidize water or tyrosine like PSII. We suggest that the observed tyrosine oxidation in BRF-RC could be driven by the ZnCe6 di-cation. In order to increase the efficiency of iii tyrosine oxidation, and ultimately oxidize water, the first potential of ZnCe6 would have to attain a value in excess of 0.8 V. The results were used to develop a second generation of BFR-RC using a high oxidation pigment. The hypervalent phosphorous porphyrin forms a radical pair that can be observed using Transient Electron Paramagnetic Resonance (TR-EPR). Finally, the results from this thesis are discussed in light of the development of solar fuel producing systems.

Modeling Metal Protein Complexes from Experimental Extended X-ray Absorption Fine Structure using Computational Intelligence

Experimental Extended X-ray Absorption Fine Structure (EXAFS) spectra carry information about the chemical structure of metal protein complexes. However, pre- dicting the structure of such complexes from EXAFS spectra is not a simple task. Currently methods such as Monte Carlo optimization or simulated annealing are used in structure refinement of EXAFS. These methods have proven somewhat successful in structure refinement but have not been successful in finding the global minima. Multiple population based algorithms, including a genetic algorithm, a restarting ge- netic algorithm, differential evolution, and particle swarm optimization, are studied for their effectiveness in structure refinement of EXAFS. The oxygen-evolving com- plex in S1 is used as a benchmark for comparing the algorithms. These algorithms were successful in finding new atomic structures that produced improved calculated EXAFS spectra over atomic structures previously found.

Optimizing Computational Frameworks to Study the Influence of the Protein Environment on the Individual Site Energies of Chromophores in Photosystem II of Photosynthesis

Photosynthesis is a process in which electromagnetic radiation is converted into chemical energy. Photosystems capture photons with chromophores and transfer their energy to reaction centers using chromophores as a medium. In the reaction center, the excitation energy is used to perform chemical reactions. Knowledge of chromophore site energies is crucial to the understanding of excitation energy transfer pathways in photosystems and the ability to compute the site energies in a fast and accurate manner is mandatory for investigating how protein dynamics ef-fect the site energies and ultimately energy pathways with time. In this work we developed two software frameworks designed to optimize the calculations of chro-mophore site energies within a protein environment. The first is for performing quantum mechanical energy optimizations on molecules and the second is for com-puting site energies of chromophores in a fast and accurate manner using the polar-izability embedding method. The two frameworks allow for the fast and accurate calculation of chromophore site energies within proteins, ultimately allowing for the effect of protein dynamics on energy pathways to be studied. We use these frame-works to compute the site energies of the eight chromophores in the reaction center of photosystem II (PSII) using a 1.9 Å resolution x-ray structure of photosystem II. We compare our results to conflicting experimental data obtained from both isolat-ed intact PSII core preparations and the minimal reaction center preparation of PSII, and find our work more supportive of the former.