Cun Xin Wang

A new residue‐nucleotide propensity potential with structural information considered for discriminating protein‐RNA docking decoys

Understanding the key factors that influence the preferences of residue‐nucleotide interactions in specific protein‐RNA interactions has remained a research focus. We propose an effective approach to derive residue‐nucleotide propensity potentials through considering both the types of residues and nucleotides, and secondary structure information of proteins and RNAs from the currently largest nonredundant and nonribosomal protein‐RNA interaction database. To test the validity of the potentials, we used them to select near‐native structures from protein‐RNA docking poses. The results show that considering secondary structure information, especially for RNAs, greatly improves the predictive power of pair potentials. The success rate is raised from 50.7 to 65.5% for the top 2000 structures, and the number of cases in which a near‐native structure is ranked in top 50 is increased from 7 to 13 out of 17 cases. Furthermore, the exclusion of ribosomes from the database contributes 8.3% to the success rate. In addition, some very interesting findings follow: (i) the protein secondary structure element π‐helix is strongly associated with RNA‐binding sites; (ii) the nucleotide uracil occurs frequently in the most preferred pairs in which the unpaired and non‐Watson‐Crick paired uracils are predominant, which is probably significant in evolution. The new residue‐nucleotide potentials can be helpful for the progress of protein‐RNA docking methods, and for understanding the mechanisms of protein‐RNA interactions. Proteins 2012;

Protein Unfolding Behavior Studied by Elastic Network Model

Experimental and theoretical studies have showed that the native-state topology conceals a wealth of information about protein folding/unfolding. In this study, a method based on the Gaussian network model (GNM) is developed to study some properties of protein unfolding and explore the role of topology in protein unfolding process. The GNM has been successful in predicting atomic fluctuations around an energy minimum. However, in the GNM, the normal mode description is linear and cannot be accurate in studying protein folding/unfolding, which has many local minima in the energy landscape. To describe the nonlinearity of the conformational changes during protein unfolding, a method based on the iterative use of normal mode calculation is proposed. The protein unfolding process is mimicked through breaking the native contacts between the residues one by one according to the fluctuations of the distance between them. With this approach, the unfolding processes of two proteins, CI2 and barnase, are simulated. It is found that the sequence of protein unfolding events revealed by this method is consistent with that obtained from thermal unfolding by molecular dynamics and Monte Carlo simulations. The results indicate that this method is effective in studying protein unfolding. In this method, only the native contacts are considered, which implies that the native topology may play an important role in the protein unfolding process. The simulation results also show that the unfolding pathway is robust against the introduction of some noise, or stochastic characters. Furthermore, several conformations selected from the unfolding process are studied to show that the denatured state does not behave as a random coil, but seems to have highly cooperative motions, which may help and promote the polypeptide chain to fold into the native state correctly and speedily.

Biologically enhanced sampling geometric docking and backbone flexibility treatment with multiconformational superposition

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 Å to 2.9 Å after performing multiconformational superposition. These results were obtained after the CAPRI prediction deadlines. Proteins 2005;60:319–323.

Identification of key residues for protein conformational transition using elastic network model

Proteins usually undergo conformational transitions between structurally disparate states to fulfill their functions. The large-scale allosteric conformational transitions are believed to involve some key residues that mediate the conformational movements between different regions of the protein. In the present work, a thermodynamic method based on the elastic network model is proposed to predict the key residues involved in protein conformational transitions. In our method, the key functional sites are identified as the residues whose perturbations largely influence the free energy difference between the protein states before and after transition. Two proteins, nucleotide binding domain of the heat shock protein 70 and human/rat DNA polymerase β, are used as case studies to identify the critical residues responsible for their open-closed conformational transitions. The results show that the functionally important residues mainly locate at the following regions for these two proteins: (1) the bridging point at the interface between the subdomains that control the opening and closure of the binding cleft; (2) the hinge region between different subdomains, which mediates the cooperative motions between the corresponding subdomains; and (3) the substrate binding sites. The similarity in the positions of the key residues for these two proteins may indicate a common mechanism in their conformational transitions.

Molecular dynamics of copper plastocyanin: simulations of structure and dynamics as a function of hydration

Abstract Molecular dynamics simulations of copper plastocyanin were carried out to study protein structure and dynamics as a function of hydration. The simulations of plastocyanin were performed at 300 K in the presence of 44, 80, 228, 682, 2516 water molecules, respectively. For each different hydrated system, the simulation covered 110 ps; the trajectories of the last 80 ps were used for analysis. Structural and dynamical properties of the protein are considerably altered upon addition of water. The gyration ratio value indicates that the most compact structure is obtained in the presence of 80 water molecules. Both the RMS deviations from the initial structure and the fluctuations of the protein atoms depend significantly on the number of hydration water molecules. The largest RMS deviations are obtained at intermediate hydration level, while the smallest value is recorded at full hydration. The RMS fluctuations are minimized in the presence of 80 water molecules and maximized at high hydration level. The interplay among protein dynamics, hydration water and the aminoacid residue properties is discussed.

HYDROGEN BOND ANALYSIS BY MD SIMULATION OF COPPER PLASTOCYANIN AT DIFFERENT HYDRATION LEVELS

Abstract Hydrogen bond interactions in copper plastocyanin aqueous solutions have been investigated in details by computer simulation. Molecular dynamics simulations of the protein in the presence of a different number of water molecules (80, 228, 682, 2516) have been performed for 110 picoseconds. Intraprotein hydrogen bonds occurring on the MD simulations are investigated and compared to the hydrogen bonds detected in the crystal structure as obtained from X-ray data. Protein-water hydrogen bonds are analyzed in terms of the average number of hydrogen bonds formed by each aminoacid residue and in terms of the number of different water molecules forming hydrogen bonds with each amino-acid residue during the simulation time. A strong influence on the protein-solvent interface of the electrical character of the aminoacid residues involved in the protein-water hydrogen bonds is evidenced. The results point out the crucial role played by the hydration level on the organization of the hydrogen bond network surrounding a protein molecule and on the protein-solvent coupling. The behaviour of the protein-solvent hydrogen bonds is discussed in connection with the protein dynamics.

Molecular dynamics simulations of the bacterial periplasmic heme binding proteins ShuT and PhuT.

ShuT and PhuT are two periplasmic heme binding proteins that shuttle heme between the outer and inner membranes of the Gram-negative bacteria. Periplasmic binding proteins (PBPs) generally exhibit considerable conformational changes during the ligand binding process, whereas ShuT and PhuT belong to a class of PBPs that do not show such behavior based on their apo and holo crystal structures. By employing a series of molecular dynamic simulations on the ShuT and the PhuT, the dynamics and functions of the two PBPs were investigated. Through monitoring the distance changes between the two conserved glutamates of ShuT and PhuT, it was found the two PBPs were more flexible than previously assumed, exhibiting obvious opening-closing motions which were more remarkable in the apo runs of ShuT. Based on the results of the domain motion analysis, large scale conformational transitions were found in all apo runs of ShuT and PhuT, hinting that the domain motions of the two PBPs may be intrinsic. On the basis of the results of the principle component analysis, distinct opening-closing and twisting motion tendencies were observed not only in the apo, but also in the holo simulations of the two PBPs. The Gaussian network model was applied in order to analyze the hinge bending regions. The most important bending regions of ShuT and PhuT are located around the midpoints of their respective connecting helixes. Finally, the flexibilities and the details of the simulations of ShuT and PhuT were discussed. Characterized by the remarkably large flexibilities, the loop constituted by Ala 169, Gly170 and Gly171 of ShuT and the beta-turn constituted by Ala176, Gly177 and Gly178 of PhuT may be important for the functions of the two PBPs. Furthermore, the Asn254 of ShuT and the Arg228 of PhuT may be indispensable for the binding or unbinding of heme, since it is involved in the important hydrogen bonding to the propionate side-chains of heme.

Study on the inhibitory mechanism and binding mode of the hydroxycoumarin compound NSC158393 to HIV-1 integrase by molecular modeling.

Human immunodeficiency virus type 1 integrase (IN) is an essential enzyme in the life cycle of this virus and also an important target for the study of anti‐HIV drugs. In this work, the binding modes of the wild type IN core domain and the two mutants, that is, W132G and C130S, with the 4‐hydroxycoumarin compound NSC158393 were evaluated by using the “relaxed complex” molecular docking approach combined with molecular dynamics (MD) simulations. Based on the monomer MD simulations, both of the two substitutions affect not only the stability of the 128–136 peptides, but also the flexibility of the functional 140s loop. In principle, NSC158393 binds the 128–136 peptides of IN; however, the specific binding modes for the three systems are various. According to the binding mode of NSC158393 with WT, NSC158393 can effectively interfere with the stability of the IN dimer by causing a steric hindrance around the monomer interface. Additionally, through the comparative analysis of the MD trajectories of the wild type IN and the IN‐NSC158393 complex, we found that NSC15893 may also exert its inhibitory function by diminishing the mobility of the function loop of IN. Three key binding residues, that is, W131, K136, and G134, were discovered by energy decomposition calculated with the Molecular Mechanics Generalized Born Surface Area method. Characterized by the largest binding affinity, W131 is likely to be indispensable for the ligand binding. All the above results are consistent with experiment data, providing us some helpful information for understanding the mechanism of the coumarin‐based inhibitors.

A soft docking algorithm for predicting the structure of antibody-antigen complexes.

An efficient soft docking algorithm is described for predicting the mode of binding between an antibody and its antigen based on the three‐dimensional structures of the molecules. The basic tools are the “simplified protein” model and the docking algorithm of Wodak and Janin. The side‐chain flexibility of Arg, Lys, Asp, Glu, and Met residues on the protein surface is taken into account. A combined filtering technique is used to select candidate binding modes. After energy minimization, we calculate a scoring function, which includes electrostatic and desolvation energy terms. This procedure was applied to targets 04, 05, and 06 of CAPRI, which are complexes of three different camelid antibody VHH variable domains with pig α‐amylase. For target 06, two native‐like structures with a root‐mean‐square deviation < 4.0 Å relative to the X‐ray structure were found within the five top ranking structures. For targets 04 and 05, our procedure produced models where more than half of the antigen residues forming the epitope were correctly predicted, albeit with a wrong VHH domain orientation. Thus, our soft docking algorithm is a promising tool for predicting antibody‐antigen recognition. Proteins 2003;52:47–50.

An Analysis of the Influence of Protein Intrinsic Dynamical Properties on its Thermal Unfolding Behavior

Abstract The influence of the protein topology-encoded dynamical properties on its thermal unfolding motions was studied in the present work. The intrinsic dynamics of protein topology was obtained by the anisotropic network model (ANM). The ANM has been largely used to investigate protein collective functional motions, but it is not well elucidated if this model can also reveal the preferred large-scale motions during protein unfolding. A small protein barnase is used as a typical case study to explore the relationship between protein topology- encoded dynamics and its unfolding motions. Three thermal unfolding simulations at 500 K were performed for barnase and the entire unfolding trajectories were sampled and partitioned into several windows. For each window, the preferred unfolding motions were investigated by essential dynamics analysis, and then associated with the intrinsic dynamical properties of the starting conformation in this window, which is detected by ANM. The results show that only a few slow normal modes imposed by protein structure are sufficient to give a significant overlap with the preferred unfolding motions. Especially, the large amplitude unfolding movements, which imply that the protein jumps out of a local energy basin, can be well described by a single or several ANM slow modes. Besides the global motions, it is also found that the local residual fluctuations encoded in protein structure are highly correlated with those in the protein unfolding process. Furthermore, we also investigated the relationship between protein intrinsic flexibility and its unfolding events. The results show that the intrinsic flexible regions tend to unfold early. Several early unfolding events can be predicted by analysis of protein structural flexibility. These results imply that protein structure-encoded dynamical properties have significant influences on protein unfolding motions.