Matching Items (2)
Description
Genomic and proteomic sequences, which are in the form of deoxyribonucleic acid (DNA) and amino acids respectively, play a vital role in the structure, function and diversity of every living cell. As a result, various genomic and proteomic sequence processing methods have been proposed from diverse disciplines, including biology, chemistry, physics, computer science and electrical engineering. In particular, signal processing techniques were applied to the problems of sequence querying and alignment, that compare and classify regions of similarity in the sequences based on their composition. However, although current approaches obtain results that can be attributed to key biological properties, they require pre-processing and lack robustness to sequence repetitions. In addition, these approaches do not provide much support for efficiently querying sub-sequences, a process that is essential for tracking localized database matches. In this work, a query-based alignment method for biological sequences that maps sequences to time-domain waveforms before processing the waveforms for alignment in the time-frequency plane is first proposed. The mapping uses waveforms, such as time-domain Gaussian functions, with unique sequence representations in the time-frequency plane. The proposed alignment method employs a robust querying algorithm that utilizes a time-frequency signal expansion whose basis function is matched to the basic waveform in the mapped sequences. The resulting WAVEQuery approach is demonstrated for both DNA and protein sequences using the matching pursuit decomposition as the signal basis expansion. The alignment localization of WAVEQuery is specifically evaluated over repetitive database segments, and operable in real-time without pre-processing. It is demonstrated that WAVEQuery significantly outperforms the biological sequence alignment method BLAST for queries with repetitive segments for DNA sequences. A generalized version of the WAVEQuery approach with the metaplectic transform is also described for protein sequence structure prediction. For protein alignment, it is often necessary to not only compare the one-dimensional (1-D) primary sequence structure but also the secondary and tertiary three-dimensional (3-D) space structures. This is done after considering the conformations in the 3-D space due to the degrees of freedom of these structures. As a result, a novel directionality based 3-D waveform mapping for the 3-D protein structures is also proposed and it is used to compare protein structures using a matched filter approach. By incorporating a 3-D time axis, a highly-localized Gaussian-windowed chirp waveform is defined, and the amino acid information is mapped to the chirp parameters that are then directly used to obtain directionality in the 3-D space. This mapping is unique in that additional characteristic protein information such as hydrophobicity, that relates the sequence with the structure, can be added as another representation parameter. The additional parameter helps tracking similarities over local segments of the structure, this enabling classification of distantly related proteins which have partial structural similarities. This approach is successfully tested for pairwise alignments over full length structures, alignments over multiple structures to form a phylogenetic trees, and also alignments over local segments. Also, basic classification over protein structural classes using directional descriptors for the protein structure is performed.
ContributorsRavichandran, Lakshminarayan (Author) / Papandreou-Suppappola, Antonia (Thesis advisor) / Spanias, Andreas S (Thesis advisor) / Chakrabarti, Chaitali (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Lacroix, Zoé (Committee member) / Arizona State University (Publisher)
Created2011
Description
Molecular docking serves as an important tool in modeling protein-ligand interactions. Most of the docking approaches treat the protein receptor as rigid and move the ligand in the binding pocket through an energy minimization, which is an incorrect approach as proteins are flexible and undergo conformational changes upon ligand binding. However, modeling receptor backbone flexibility in docking is challenging and computationally expensive due to the large conformational space that needs to be sampled.
A novel flexible docking approach called BP-Dock (Backbone Perturbation docking) was developed to overcome this challenge. BP-Dock integrates both backbone and side chain conformational changes of a protein through a multi-scale approach. In BP-Dock, the residues along a protein chain are perturbed mimicking the binding induced event, with a small Brownian kick, one at a time. The fluctuation response profile of the chain upon these perturbations is computed by Perturbation Response Scanning (PRS) to generate multiple receptor conformations for ensemble docking. To evaluate the performance of BP-Dock, this approach was applied to a large and diverse dataset of unbound structures as receptors. Furthermore, the protein-peptide docking of PICK1-PDZ proteins was investigated. This study elucidates the determinants of PICK1-PDZ binding that plays crucial roles in numerous neurodegenerative disorders. BP-Dock approach was also extended to the challenging problem of protein-glycan docking and applied to analyze the energetics of glycan recognition in Cyanovirin-N (CVN), a cyanobacterial lectin that inhibits HIV by binding to its highly glycosylated envelope protein gp120. This study provide the energetic contribution of the individual residues lining the binding pocket of CVN and explore the effect of structural flexibility in the hinge region of CVN on glycan binding, which are also verified experimentally. Overall, these successful applications of BP-Dock highlight the importance of modeling backbone flexibility in docking that can have important implications in defining the binding properties of protein-ligand interactions.
Finally, an induced fit docking approach called Adaptive BP-Dock is presented that allows both protein and ligand conformational sampling during the docking. Adaptive BP-Dock can provide a faster and efficient docking approach for the virtual screening of novel targets for rational drug design and aid our understanding of protein-ligand interactions.
A novel flexible docking approach called BP-Dock (Backbone Perturbation docking) was developed to overcome this challenge. BP-Dock integrates both backbone and side chain conformational changes of a protein through a multi-scale approach. In BP-Dock, the residues along a protein chain are perturbed mimicking the binding induced event, with a small Brownian kick, one at a time. The fluctuation response profile of the chain upon these perturbations is computed by Perturbation Response Scanning (PRS) to generate multiple receptor conformations for ensemble docking. To evaluate the performance of BP-Dock, this approach was applied to a large and diverse dataset of unbound structures as receptors. Furthermore, the protein-peptide docking of PICK1-PDZ proteins was investigated. This study elucidates the determinants of PICK1-PDZ binding that plays crucial roles in numerous neurodegenerative disorders. BP-Dock approach was also extended to the challenging problem of protein-glycan docking and applied to analyze the energetics of glycan recognition in Cyanovirin-N (CVN), a cyanobacterial lectin that inhibits HIV by binding to its highly glycosylated envelope protein gp120. This study provide the energetic contribution of the individual residues lining the binding pocket of CVN and explore the effect of structural flexibility in the hinge region of CVN on glycan binding, which are also verified experimentally. Overall, these successful applications of BP-Dock highlight the importance of modeling backbone flexibility in docking that can have important implications in defining the binding properties of protein-ligand interactions.
Finally, an induced fit docking approach called Adaptive BP-Dock is presented that allows both protein and ligand conformational sampling during the docking. Adaptive BP-Dock can provide a faster and efficient docking approach for the virtual screening of novel targets for rational drug design and aid our understanding of protein-ligand interactions.
ContributorsBolia, Ashini (Author) / Ozkan, Sefika Banu (Thesis advisor) / Ghirlanda, Giovanna (Thesis advisor) / Beckstein, Oliver (Committee member) / Wachter, Rebekka (Committee member) / Arizona State University (Publisher)
Created2015