Research On Interaction Mechanism Of Biological Macromolecules

Protein-protein and protein-RNA interactionsplay a central role in various biologicalprocesses, such as signal transduction, protein synthesis, mRNA processing and generegulation. To sufficiently understand these biological processes, we need to figure out themechanism of biomolecular association. Molecular recognition before forming complex isthe first step of interaction. The molecular recognition mechanism is one of the mainproblems of the life science and is important to biomolecular interaction prediction,treatment of diseases and regulation of life process.Former studies show that electrostatic interaction plays a crucial role inpre-orientation of subunits and speeding up the formation of protein-protein complexes.Accordingly, due to the negative charges from phosphate groups in RNA, we believe thatelectrostatic interaction is even more vital in protein-RNA recognition than inprotein-protein recognition. It could make it easier for protein and RNA to find each otherin their free states. Here, we study pre-orientation of RNA and protein separated at adistance of5-7just before they form contacts and only interact electrostatically., Wepropose a long-range electrostatic docking-like method using FFT-based sampling,LEDock,to study our problem. Our results show that the orientations between RNA andprotein are very different from the random ones at a distance of5-7and are much closerto those in their native complexes. Meanwhile, electrostatic funnels are found around theRNA-binding sites of the proteins in62out of78bound protein-RNA complexes. Besides,LEDock is also used to find RNA-binding residues and it outperforms BindN Serverslightly for23unbound protein-RNA complexes.Protein-protein interaction has been studied for decades. Based on the analysis ofprotein interfaces, a number of approaches have been developed to predict the bindingsites of protein-protein interaction. Most of these methods are based on physicochemicalproperties of the interfaces, such as H-bond, hydrophobicity, interface propensity,geometric properties or evolutionary conservation of residues. Here, we expand theLEDock and develop a method of protein binding sites prediction based on the long-rangeelectrostatic interaction. This approach does not have any adjustable parameter and is not depend on the training set. We test this method on benchmark4.0and get acceptableresults.Leukemia is a disease hardly to be cured. Most of the chemotherapy drugs usedcurrently are aiming at leukemia cells in the proliferation, but can not deal with leukemiastem cells (LSCs) in stationary phase. If we start from the source which causes leukemia,we can find a new way to treat leukemia. Experimental data show that HERG1K+channel proteins express in leukemia cells and leukemia stem cells and do not express inthe normal hematopoietic stem cells or white blood cells. The concentration of SDF-1inbone marrow stromal cells of leukemia patients is significantly higher than that of healthyindividuals. Besides, SDF-1enhances electric current of HERG1K+channel. Based onthese experimental evidences, we suppose that there is direct interaction between SDF-1and HERG1K+channel. So, we use our LEDock and Rosetta program to predict thecomplex of SDF-1and HERG K+channel protein. the analysis of results shows that theprediction structure is in line with experimental evidence and the result provide is atheoretical basis and reference for future experiments.