中文摘要：

Residue networks are constructed by defining the residues as the vertices and atom contacts between them as the edges. The residue network of a protein complex is divided into two types of networks, i.e. the hydrophobic and the hydrophilic residue networks. By analyzing the network parameters, it is found that the correct binding complex conformations are of both higher sum of the interface degree values and lower characteristic path length than those incorrect ones. These features reflect that the correct bind-ing complex conformations have better geometric and/or residue type complementarity, and the correct binding modes are very important for preserving the characteristic path lengths of native protein complexes. In addition, two scoring terms are proposed based on the network parameters, in which the characteristics of the entire complex shape and residue type complementarity are taken into account. These network-based scoring terms have also been used in conjunction with other scoring terms, and the new multi-term scoring HPNCscore is devised in this work. It can improve the discrimination of the combined scoring function of RosettaDock more than 12%. This work might enhance our knowledge of the mechanisms of protein-protein interactions and recognition.

英文摘要：

Residue networks are constructed by defining the residues as the vertices and atom contacts between them as the edges. The residue network of a protein complex is divided into two types of networks, i.e. the hydrophobic and the hydrophilic residue networks. By analyzing the network parameters, it is found that the correct binding complex conformations are of both higher sum of the interface degree values and lower characteristic path length than those incorrect ones. These features reflect that the correct bind-ing complex conformations have better geometric and/or residue type complementarity, and the correct binding modes are very important for preserving the characteristic path lengths of native protein complexes. In addition, two scoring terms are proposed based on the network parameters, in which the characteristics of the entire complex shape and residue type complementarity are taken into account. These network-based scoring terms have also been used in conjunction with other scoring terms, and the new multi-term scoring HPNCscore is devised in this work. It can improve the discrimination of the combined scoring function of RosettaDock more than 12%. This work might enhance our knowledge of the mechanisms of protein-protein interactions and recognition.