一般认为生物大分子的“折叠(folding)”和“结合(binding)”是两类截然不同生物学过程。先前我们提出了一种跨越折叠和结合之间的生物分子现象，称为“自结合肽”，它一方面与特定蛋白发生特异性识别、结合和解离来动态行使生物职能，另一方面又与该蛋白在一级序列上连为一个整体。由于（1）自结合肽常常作为其所在蛋白质的功能调节元件，进而参与到诸多疾病相关细胞信号网络当中；（2）自结合肽多以较弱的化学力与蛋白受体发生短暂可逆的相互作用，因此我们认为它非常适合作为一类新型药物靶标加以分子干预。在该项目中，我们拟在结构水平对自结合肽的热力学性质和动力学行为开展系统研究，阐明决定自结合肽生物学功能的分子机制。在此基础上，重点针对两类原癌蛋白（c-Src激酶和TIM蛋白）理性设计靶向自结合肽的小分子和多肽药物。此外，我们还将使用荧光光谱、酶活检测和肿瘤细胞毒性试验测试设计分子的活性。

It is known that 'folding' and 'binding' are two distinct strategies used by biomolecules to fulfill their biological functions. In fact, however, there is an exception we called 'self-binding peptides (SBPs) that span between the folding and binding; that is, a peptide segment, on the one hand, specifically recognizes and interacts with its target to establish a dynamic balance between the bound complex and unbound members, on the other hand, the segment is integrated into the target in primary sequence via a flexible polypeptide linker. Considering that the SBPs (i) are found to serve commonly as functional mediator of their parent proteins within disease-related cell signaling networks, and (ii) can bind to their cognate targets in a transient, reversible manner through weak chemical forces, it is suggested that the SBPs would be promising as a kind of new therapeutic targets that can be readily interfered with drug molecules. Here, we attempt to deploy a fold of structure-based studies around the SBPs; first, the thermodynamic property and dynsmic behavior are elucidated to understand the molecular mechnism and biological implication underlying SBPs. On this basis, we will then focus on the rational drug design of small-molecule compounds and peptide aptamers to target the SBP regions of two oncogenic proteins, i.e. the non-receptor tyrosine kinase c-Src and the guanine nucleotide exchange factor TIM. In addition, we will also perform fluorescence spectroscopy analysis, enzyme activity assay and tumor cytotoxicity experiment to test, verify, and correct the theoretical protocols and designed molecular enetities arising from computational efforts.