Protein-protein etkileşim ağlarının alternatif konformasyonlarla zenginleştirilmesi ve farklı arayüzlerin hızlandırılmış filtrelemesi

The common practice in structural protein-protein interaction (PPI) networks is to investigate just one specific conformation for each protein. Yet it is not a comprehensive representation as it neglects the conformational changes of proteins which may lead to different protein interactions, functions, and downstream signaling. In this dissertation, a new representation is proposed for structural PPI networks which inspects the alternative conformations of proteins. This representation uses a method to get all available structures of proteins from protein data bank (PDB) and clusters them based on their sequence and structural similarities. Then, it investigates the alternative conformations of each protein. A large-scale study is done by creating breast cancer lung and brain metastasis sub-networks and equipping them with alternative conformations of the proteins. PPI network analyses showed novel genes and cellular pathways which play important roles in each sub-network. By examining alternative conformations of proteins, the docking results coverage increased from 54% to 76%. In addition, the effects of conformational changes on specific interactions are shown. The conformational changes of KPNB1 directs it to bind to SNAI1 and SNUPN in the open and close conformations, respectively. Exploring the alternative conformations of CXCL12 shows that a point mutation on the binding surface can inhibit CXCL12 homodimerization, as a complex structure, and alter its functions. PRISM is used for protein docking purposes in the sub-networks. The primary limitations of PRISM are its long running time and restricted interface database. These limitations derive mainly from the all-to-all protein surface and interface structure comparison process which is very time-consuming. So, to speed up this process, a new filtering method is proposed which creates 1D descriptors of protein structures to rapidly filter the dissimilar interface. This method uses a library of non-redundant small protein fragments and Geometric hashing technique to create the protein descriptor vectors. Based on the results, thousands of interface comparisons could be done in seconds using these descriptor vectors. 70%-80% of grossly dissimilar interfaces could be filtered rapidly and the remaining candidate similar interfaces would be compared by an alignment method.