Most proteins function by interacting with other proteins or acting sequentially. The interactions between proteins play critical roles in various biological phenomena such as controlling enzymatic activities, molecule signaling, and gene expression, specificity determination of bacterial and viral infection, immune response and the like in living organisms. Therefore, it is crucial to understand interaction between proteins to clarify biological functions of novel genes and therefore discover novel drug candidates. The interaction between proteins or sequential action of proteins takes part in metabolism for survival of a living body by forming a network in an organism (FIG. 1). FIG. 1 shows a view of protein network modeling for E. coli or H. pylori [1]. The modeling method of the protein network is disclosed in Korean Patent Laid-Open Publication No. 10-2003-48974.
The interaction network between proteins existing in a living body is very complicated, even in relatively simple organisms such as bacteria. Some network factors are not critical and thus, even when they are interrupted, do not affect the viability of the organism. However, other factors existing in the center of the protein network are associated with various metabolisms and thus, when they are interrupted, the survival of the organism can be threatened [2˜4]. For example, when the protein network and various metabolisms related to the growth of an organism is operated normally through normal protein interaction, i.e., between the growth hormones and the growth hormone receptors, the organism may show normal growth patterns. However, if interference within the network is present, various problems including abnormal growth patterns can be induced. Also, in case of arthritis, for example, due to excessive expression of TNF protein, the interaction between the TNF receptor and TNF activates a protein network related to inflammation response, which develops arthritis symptoms.
It is possible to predict the protein network through bioinformatics. By experimentally validating the predicted results, it is possible to identify essential proteins or essential network factors of the subject organism [5˜7]. For this purpose, the biological change of an organism was observed after the protein network was blocked by mutation induction of the subject protein at gene level to knock-out the function of the protein.
Meanwhile, it is possible to identify an essential protein and its function by introducing a protein in an organism and examining the growth pattern through observation of morphological changes and cell spectroscopy [8˜10].
It is known that specific sites within the protein called domains, rather than the whole protein molecule, are involved in the interaction between two or more proteins [11˜14]. As shown in FIGS. 2A and 2B, for the interaction between protein A and protein B, domain a1 and domain b1 should bind. Therefore, if a protein has domain b1 which can bind to the domain a1, it can bind to protein A. In FIG. 2A is a schematic view of a specific domain for protein interaction and FIG. 2B is a schematic view of two proteins bound through domain interaction.
Conventionally, attempts were made to use a product obtained by chemically simulating an active part of an enzyme or antibody. However, many cases have shown that the simulated structures seldom performed the same function as the actual protein itself [15˜17].
As a reference, RNAi (Ribonucleic acid interference) technology which is similar to this has been applied in development of new drugs [18˜20]. In this technique, RNA oligomers designed to complementarily bind to a specific type of RNA molecules are introduced into an organism to nullify the function of a specific RNA. Therefore, the specific protein is not produced as a result. Based on this property, the method of removal of a protein required for pathogenic bacterial activity or possible induction of a disease is applied in treatment of the disease.
If a method for understanding the protein network and interrupting the important network factor of a microorganism or animal and plant cell system is provided, it is possible to develop bioactive substances such as novel antibiotic agents targeting a specific protein.
Accordingly, the present inventors have made efforts to develop a method for screening drug candidates and found that if a protein domain interacting with a specific protein can block the action network of the specific protein, the protein domain can be utilized as a bioactive substance such as a drug candidate. Based on this finding, the present invention has been completed.