Chun Hua Li

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.

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.

The interactions and recognition of cyclic peptide mimetics of Tat with HIV-1 TAR RNA: a molecular dynamics simulation study

The interaction of HIV-1 trans-activator protein Tat with its cognate trans-activation response element (TAR) RNA is critical for viral transcription and replication. Therefore, it has long been considered as an attractive target for the development of antiviral compounds. Recently, the conformationally constrained cyclic peptide mimetics of Tat have been tested to be a promising family of lead peptides. Here, we focused on two representative cyclic peptides termed as L-22 and KP-Z-41, both of which exhibit excellent inhibitory potency against Tat and TAR interaction. By means of molecular dynamics simulations, we obtained a detailed picture of the interactions between them and HIV-1 TAR RNA. In results, it is found that the binding modes of the two cyclic peptides to TAR RNA are almost identical at or near the bulge regions, whereas the binding interfaces at the apical loop exhibit large conformational heterogeneity. In addition, it is revealed that electrostatic interaction energy contributes much more to KP-Z-41 complex formation than to L-22 complex, which is the main source of energy that results in a higher binding affinity of KP-Z-41 over-22 for TAR RNA. Furthermore, we identified a conserved motif RRK (Arg-Arg-Lys) that is shown to be essential for specific binding of this class of cyclic peptides to TAR RNA. This work can provide a useful insight into the design and modification of cyclic peptide inhibitors targeting the association of HIV-1 Tat and TAR RNA.

Allosteric transitions of the maltose transporter studied by an elastic network model

The maltose transporter from Escherichia coli is one of the ATP‐binding cassette (ABC) transporters that utilize the energy from ATP hydrolysis to translocate substrates across cellular membranes. Until 2011, three crystal structures have been determined for maltose transporter at different states in the process of transportation. Here, based on these crystal structures, the allosteric pathway from the resting state (inward‐facing) to the catalytic intermediate state (outward‐facing) is studied by applying an adaptive anisotropic network model. The results suggest that the allosteric transitions proceed in a coupled way. The closing of the nucleotide‐binding domains occurs first, and subsequently this conformational change is propagated to the transmembrane domains (TMD) via the EAA and EAS loops, and then to the maltose‐binding protein, which facilitates the translocation of the maltose. It is also found that there exist nonrigid‐body and asymmetric movements in the TMD. The cytoplasmic gate may only play the role of allosteric propagation during the transition from the pretranslocation to outward‐facing states. In addition, the results show that the movment of the helical subdomain towards the RecA‐like subdomain mainly occurs in the earlier stages of the transition. These results can provide some insights into the understanding of the mechanism of ABC transporters.

Identification of functionally key residues in AMPA receptor with a thermodynamic method.

AMPA receptor mediates the fast excitatory synaptic transmission in the central nervous system, and it is activated by the binding of glutamate that results in the opening of the transmembrane ion channel. In the present work, the thermodynamic method developed by our group was improved and then applied to identify the functionally key residues that regulate the glutamate-binding affinity of AMPA receptor. In our method, the key residues are identified as those whose perturbation largely changes the ligand binding free energy of the protein. It is found that besides the ligand binding sites, other residues distant from the binding cleft can also influence the glutamate binding affinity through a long-range allosteric regulation. These allosteric sites include the hinge region of the ligand binding cleft, the dimer interface of the ligand binding domain, the linkers between the ligand binding domain and the transmembrane domain, and the interface between the N-terminal domain and the ligand binding domain. Our calculation results are consistent with the available experimental data. The results are helpful for our understanding of the mechanism of long-range allosteric communication in the AMPA receptor and the mechanism of channel opening triggered by glutamate binding.

Allosteric transitions of ATP-binding cassette transporter MsbA studied by the adaptive anisotropic network model

The transporter MsbA is a kind of multidrug resistance ATP‐binding cassette transporter that can transport lipid A, lipopolysaccharides, and some amphipathic drugs from the cytoplasmic to the periplasmic side of the inner membrane. In this work, we explored the allosteric pathway of MsbA from the inward‐ to outward‐facing states during the substrate transport process with the adaptive anisotropic network model. The results suggest that the allosteric transitions proceed in a coupled way. The large‐scale closing motions of the nucleotide‐binding domains occur first, accompanied with a twisting motion at the same time, which becomes more obvious in middle and later stages, especially for the later. This twisting motion plays an important role for the rearrangement of transmembrane helices and the opening of transmembrane domains on the periplasmic side that mainly take place in middle and later stages respectively. The topological structure plays an important role in the motion correlations above. The conformational changes of nucleotide‐binding domains are propagated to the transmembrane domains via the intracellular helices IH1 and IH2. Additionally, the movement of the transmembrane domains proceeds in a nonrigid body, and the two monomers move in a symmetrical way, which is consistent with the symmetrical structure of MsbA. These results are helpful for understanding the transport mechanism of the ATP‐binding cassette exporters. Proteins 2015; 83:1643–1653.