IIIT Hyderabad Publications |
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Density Functional Theory-Based Studies on Gold Clusters and their Complexes with BiomoleculesAuthor: Sandhya Rai Date: 2016-03-16 Report no: IIIT/TH/2016/12 Advisor:Harjinder Singh,U Deva Priyakumar AbstractInteresting physiochemical properties of gold nanoclusters have attracted the scientific community towards their extensive applications in catalysis, biosensing, protein engineering, gene technology, etc. The role of gold clusters as catalysts has been of intense interest in recent years, being regarded as new generation of catalysts due to their unusually high catalytic performance. The nontoxic and biocompatible nature of gold nanoclusters has put them on the center stage for designing therapeutic drug delivery vehicles and efficient biosensors. In the present work, computational studies based on density functional theory (DFT) was performed to study the electronic structure modulation on increasing the size of the gold cluster and how the biomolecular tagging effects the electronic structure and properties of these gold clusters. These modulations exhibit great potential in influencing the catalytic properties and biosensing mechanism of the gold nanoclusters. In order to choose a reliable level of theory, an extensive benchmarking of DFT functionals was done, based on which PBE0 functional was employed for carrying out all the calculations related to geometry and electronic modulation of small gold clusters on increasing the system size and also tagging them with natural/synthetic biomolecules. The work demonstrates how the quantum size effects play an instrumental role in tuning the catalytic potential of these clusters, in case of CO oxidation. An even-odd oscillation is found in the fragmentation energy of clusters indicating a preferentially higher stability for even numbered clusters. A correlation between the electronic properties of the clusters and the activation energy barrier was established, suggesting that modulating the electronic structure is the key to fine-tune the catalytic properties of the cluster. The catalytic properties of the gold clusters can also be modulated by tagging them with biomolecules. In this respect, complexes of nucleobases (natural/size-expanded) tagged to gold cluster (Au3) are studied. The CO oxidation reaction on the nucleobase-tagged gold cluster indicates an interesting implication of tagging the cluster to a nucleobase resulting in a mechanistic crossover which is responsible for making nucleobase tagged gold clusters a better catalyst in comparison to pristine Au3 cluster. The results open up prospect of using these as building blocks of new nanoscale catalysts with tailored properties and having wider technological applications. Interaction between metal nanoparticles and biomolecules is important from the view point of developing and designing biosensors. In this respect, studies on proline tagged with gold nanoclusters of varying size are reported. DNA and RNA molecules tagged to gold nanoparticles, have been shown to exhibit potential applications in designing and fabrication of novel electronic nano-devices. Complexes of RNA with gold nanoparticles are known to exhibit potential application in gene silencing and as siRNA delivery vehicles which find application in developing novel therapeutic and diagnostic modalities. However, the binding mechanism between gold nanoparticles and these molecules and its implications are not completely understood. Hence, a comprehensive study to examine the effect of structural perturbations offered to DNA and RNA base pairs in terms of adsorption on a gold cluster (Au3) has been done. Geometric and electronic features of these complexes provide evidences for distortion of certain base pairs depending on the binding site of the cluster. This study demonstrates the possibility of combining structural modifications to DNA and RNA base pairs and subsequent binding to gold nanoparticles to modulate and achieve molecular systems with desired optoelectronic properties. Full thesis: pdf Centre for Computational Natural Sciences and Bioinformatics |
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