Shan Chang

Amino acid network and its scoring application in protein-protein docking

Protein-protein complex, composed of hydrophobic and hydrophilic residues, can be divided into hydrophobic and hydrophilic amino acid network structures respectively. In this paper, we are interested in analyzing these two different types of networks and find that these networks are of small-world properties. Due to the characteristic complementarity of the complex interfaces, protein-protein docking can be viewed as a particular network rewiring. These networks of correct docked complex conformations have much more increase of the degree values and decay of the clustering coefficients than those of the incorrect ones. Therefore, two scoring terms based on the network parameters are proposed, in which the geometric complementarity, hydrophobic-hydrophobic and polar-polar interactions are taken into account. Compared with a two-term energy function, a simple scoring function HPNet which includes the two network-based scoring terms shows advantages in two aspects, not relying on energy considerations and better discrimination. Furthermore, combing the network-based scoring terms with some other energy terms, a new multi-term scoring function HPNet-combine can also make some improvements to the scoring function of RosettaDock.

A holistic molecular docking approach for predicting protein-protein complex structure

A holistic protein-protein molecular docking approach, HoDock, was established, composed of such steps as binding site prediction, initial complex structure sampling, refined complex structure sampling, structure clustering, scoring and final structure selection. This article explains the detailed steps and applications for CAPRI Target 39. The CAPRI result showed that three predicted binding site residues, A191HIS, B512ARG and B531ARG, were correct, and there were five submitted structures with a high fraction of correct receptor-ligand interface residues, indicating that this docking approach may improve prediction accuracy for protein-protein complex structures.

A filter enhanced sampling and combinatorial scoring study for protein docking in CAPRI

Protein–protein docking is usually exploited with a two‐step strategy, i.e., conformational sampling and decoy scoring. In this work, a new filter enhanced sampling scheme was proposed and added into the RosettaDock algorithm to improve the conformational sampling efficiency. The filter term is based on the statistical result that backbone hydrogen bonds in the native protein structures are wrapped by more than nine hydrophobic groups to shield them from attacks of water molecules (Fernandez and Scheraga, Proc Natl Acad Sci USA 2003;100:113–118). A combinatorial scoring function, ComScore, specially designed for the other‐type protein–protein complexes was also adopted to select the near native docked modes. ComScore was composed of the atomic contact energy, van der Waals, and electrostatic interaction energies, and the weight of each item was fit through the multiple linear regression approach. To analyze our docking results, the filter enhanced sampling scheme was applied to targets T12, T20, and T21 after the CAPRI blind test, and improvements were obtained. The ligand least root mean square deviations (L_rmsds) were reduced and the hit numbers were increased. ComScore was used in the scoring test for CAPRI rounds 9–12 with good success in rounds 9 and 11. Proteins 2007.

An Analysis of Protein Conservation Residues Network

Identifying protein interface is crucial for the prediction of protein-protein interactions and for protein functional classification. In this work, the protein structure is modeled as an undirected graph with the conservation amino- acid residues the vertices and all atom contacts between them the edges. We find that the conservation residue networks are characterized by intermediate values of clustering coefficient and characteristic path length, which are the typical property of small-world networks. The residues on the protein interfaces typically have higher degree and lower clustering coefficient values than that of the surface residues. Additionally, it is detected that the spatial clustering of the conservation residues is a general phenomenon, consistent with the cooperative nature of residues in determining the structure and function. These results indicate that the conservation residue network propensities can give us some new parameters in protein-protein interface prediction.

Scoring Function for the Other-type Protein Complexe

Abstract Based on the observation that different complexes have distinctive chemo-physical characters at interfaces, a specific scoring function was designed to select the effective structures in protein-protein docking procedure for the Other-type protein complexes that are difficult to predict. This scoring function was composed of the atomic contact energy (EACE), van der Waals, and electrostatic interaction energies. The weight of each term was obtained by the multiple linear regression approach. The test result on 17 Other-type complexes from CAPRI benchmark 1 demonstrated that the combinatorial scoring function can delineate the interaction feature of the Other-type complexes, reflect the energy change during the complex formation, and have a certain capacity to discriminate effective structures from numbers of the docked modes. Compared with the residue pair potential (RP), the combinatorial score was found to have a higher success rate. Through ranking the predicted models of the two targets in CARPI round 8, the combinatorial score also exhibits a higher degree of accuracy in distinguishing the effective association modes.

A Parallel Molecular Docking Approach Based on Message Passing Interface

Molecular docking technology is an important tool in computer-aided drug discovery and structure prediction for the protein-ligand complex. In this work, based on the analysis of the algorithm of the widely used the docking program AutoDock, we proposed a hybrid parallel method using the message passing interface (MPI) library. The modified programs were applied to dock the small molecule XK263 to its target HIV-1 protease with different number of processors. Docking results indicate that the parallel codes can make a good prediction of the XK263-protease complex structure. The obtained high quality parallel speedup and efficiency show the promising improvement of our method for future applications on structure prediction of protein complex and drug design.

Prediction of the Binding Mode between the Small Peptide Inhibitor EBR28 with Integrase through Molecular Modeling Methods

Human immunodeficiency virus type 1 (HIV-1) integrase (IN), which aids the integration of viral DNA into the host chromosome, is an essential enzyme in the lifecycle of this virus and also an important target for the study of anti-HIV drugs. Recently synthesized 12-mer EBR28 which was identified through the yeast two-hybrid system and could strongly bind to IN is one of the most potential small peptide leading compounds inhibiting IN binding to viral DNA. The binding mode of IN core domain and its peptide inhibitor EBR28 was investigated by using molecular docking and molecular dynamics (MD) simulation and confirmed with a semi-empirical binding free energy calculation method, i.e. MM-GBSA model. The results show that EBR28 binds to the interspace between alpha1 helix and alpha5 helix in the IN core domain mainly through hydrophobic interactions, which impedes the dimerization of the two IN monomers and inhibits IN binding to viral DNA in the end. The correlation between calculated and experimental binding free energies is very good (r = 0.88). All of the above simulation results agree well with experimental data, which provide us with some helpful information for designing anti-HIV small peptide drugs based on the structure of IN.