RESUMEN
The three-dimensional structure of a protein can be treated as a complex network composed of amino acids, and the network properties can help us to understand the relationship between structure and function. Since the amino acid network of a protein is formed in the process of protein folding, it is difficult for general network models to explain its evolving mechanism. Based on the perspective of protein folding, we propose an evolving model for amino acid networks. In our model, the evolution starts from the amino acid sequence of a native protein and it is guided by two generic assumptions: i.e., the neighbor preferential rule and the energy preferential rule. We find that the neighbor preferential rule predominates the general network properties and the energy preferential rule predominates the specific biological structure characteristics. Applied to native proteins, our model mimics the features of amino acid networks well.
Asunto(s)
Aminoácidos/química , Biofisica/métodos , Algoritmos , Simulación por Computador , Modelos Biológicos , Modelos Estadísticos , Modelos Teóricos , Péptidos/química , Conformación Proteica , Pliegue de Proteína , Proteínas/química , Alineación de Secuencia , TermodinámicaRESUMEN
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.
Asunto(s)
Aminoácidos/química , Aminoácidos/metabolismo , Proteínas/química , Proteínas/metabolismo , Unión ProteicaRESUMEN
Human immunodeficiency virus type 1 (HIV-1) integrase (IN) is an essential enzyme in the HIV-1 lifecycle which aids the integration of viral DNA into the host chromosome. Recently synthesized 12-mer peptide EBR28, which can strongly bind to IN, is one of the most potential small peptide leading compounds inhibiting IN binding with viral DNA. However, the binding mode between EBR28 peptide with HIV-1 IN and the inhibition mechanism remain uncertain. In this paper, the binding modes of EBR28 with HIV-1 IN monomer core domain (IN(1)) and dimmer core domain (IN(2)) were investigated by using molecular docking and molecular dynamics (MD) simulation methods. The results indicated that EBR28 bound to the interfaces of the IN(1) and IN(2) systems mainly through the hydrophobic interactions with the beta3, alpha1 and alpha5 regions of the proteins. The binding free energies for IN(1) with a series of EBR28 mutated peptides were calculated with the MM/GBSA model, and the correlation between the calculated and experimental binding free energies is very good (r=0.88). Thus, the validity of the binding mode of IN(1) with EBR28 was confirmed. Based on the binding modes, the inhibition mechanism of EBR28 was explored by analyzing the essential dynamics (ED), energy decomposition and the mobility of EBR28 in the two docked complexes. The proposed inhibition mechanism is represented that EBR28 binds to the interface of IN(1) to form the IN(1)_EBR28 complex and preventes the formation of IN dimmer, finally leads to the partial loss of binding potency for IN with viral DNA. 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.
Asunto(s)
Inhibidores de Integrasa VIH/química , Integrasa de VIH/química , VIH-1/enzimología , Modelos Químicos , Oligopéptidos/química , Sitios de Unión , Simulación por Computador , Humanos , Unión ProteicaRESUMEN
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.
Asunto(s)
Biología Computacional/métodos , Simulación por Computador , Mapeo de Interacción de Proteínas , Proteínas/química , Proteómica/métodos , Algoritmos , Interpretación Estadística de Datos , Bases de Datos de Proteínas , Genómica , Ligandos , Conformación Molecular , Unión Proteica , Conformación Proteica , Programas InformáticosRESUMEN
An efficient biologically enhanced sampling geometric docking method is presented based on the FTDock algorithm to predict the protein-protein binding modes. The active site data from different sources, such as biochemical and biophysical experiments or theoretical analyses of sequence data, can be incorporated in the rotation-translation scan. When discretizing a protein onto a 3-dimensional (3D) grid, a zero value is given to grid points outside a sphere centered on the geometric center of specified residues. In this way, docking solutions are biased toward modes where the interface region is inside the sphere. We also adopt a multiconformational superposition scheme to represent backbone flexibility in the proteins. When these procedures were applied to the targets of CAPRI, a larger number of hits and smaller ligand root-mean-square deviations (RMSDs) were obtained at the conformational search stage in all cases, and especially Target 19. With Target 18, only 1 near-native structure was retained by the biologically enhanced sampling geometric docking method, but this number increased to 53 and the least ligand RMSD decreased from 8.1 A to 2.9 A after performing multiconformational superposition. These results were obtained after the CAPRI prediction deadlines.