Prof. Dong-Qing Wei
Project Description and Objectives
Years of exploration and study into cellular, molecular and biochemical biology, structural and biophysical contexts have produced a noteworthy compilation of knowledge on the physiochemical properties and function of individual proteins. Nonetheless, a single protein executing a function alone is very rare and is not often witnessed. The systemic interactions of different proteins in different biological processes, ranging from normal to disease phenotypes, play a significant role. The interface interactions of different proteins ensure the systemic coordination of cellular processes and may lead to different disorders or diseased phenotypes. Many in vitro methods for the investigation of PPI are widely used, such as protein-fragment complementation assay, coimmuno-precipitation, TAP tagging, yeast two-hybrid and X-ray crystallography. Fortunately, the use of in silico protein-protein interaction methods have greatly reduced the costs, time and efforts of wet experimentations. These processes such as structure and sequence-based approaches, in silico two hybrid chromosome vicinity, gene fusion, phylogenetic tree construction and profiling, and microarray gene expression-based methodologies were developed.
The detailed study of PPIs has accelerated the mapping of functional pathways to illustrate the molecular mechanisms of cellular routes and also to identify new drug targets for the treatment of specific diseases. Therefore, this project will thoroughly investigate the interactome of different phenotypes and extract possible information such as:
Identification of key nodes in the DEGs interactome that could act as possible drug targets acting as hub node.
Meta-analysis of large PPI networks to discover universal biomarkers;
Understanding the Gene regulatory network;
Identification of protein-protein interface and their MD study to understand the interaction mechanism of two protein;
Identify the key transcription factors in the disease phenotype;
Targeting identified drug targets for possible discovery of potential inhibitors.
Knowledge of biochemistry, especially about protein structures.
Chemical and physical knowledge of basic types of protein-protein interactions.
Interest and knowledge in mathematical algorithms, statistical modeling, deep learning and programming would be helpful.
Presentation of the research details.
Submission of a research article to a well reputed journal as co-author, if available.