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Dive into the research topics where Ji Guo Su is active.

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Featured researches published by Ji Guo Su.


Proteins | 2012

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

Chun Hua Li; Li Bin Cao; Ji Guo Su; Yong Xiao Yang; Cun Xin Wang

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;


Biophysical Journal | 2008

Protein Unfolding Behavior Studied by Elastic Network Model

Ji Guo Su; Chun Hua Li; Rui Hao; Wei Zu Chen; Cun Xin Wang

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.


Journal of Chemical Physics | 2011

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

Ji Guo Su; Xianjin Xu; Chun Hua Li; Wei Zu Chen; Cun Xin Wang

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.


Biophysical Chemistry | 2008

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

Ming Liu; Ji Guo Su; Ren Kong; Ting Guang Sun; Jian Jun Tan; Wei Zu Chen; Cun Xin Wang

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.


Journal of Biomolecular Structure & Dynamics | 2011

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

Ji Guo Su; Xianjin Xu; Chun Hua Li; Wei Zu Chen; Cun Xin Wang

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.


Journal of Biomolecular Structure & Dynamics | 2013

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

Chun Hua Li; Zhi Cheng Zuo; Ji Guo Su; Xianjin Xu; Cun Xin Wang

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.


Journal of Biomolecular Structure & Dynamics | 2016

Analysis of conformational motions and related key residue interactions responsible for a specific function of proteins with elastic network model.

Ji Guo Su; Xiao Ming Han; Xiao Zhang; Yan Xue Hou; Jian Zhuo Zhu; Yi Dong Wu

Protein collective motions play a critical role in many biochemical processes. How to predict the functional motions and the related key residue interactions in proteins is important for our understanding in the mechanism of the biochemical processes. Normal mode analysis (NMA) of the elastic network model (ENM) is one of the effective approaches to investigate the structure-encoded motions in proteins. However, the motion modes revealed by the conventional NMA approach do not necessarily correspond to a specific function of protein. In the present work, a new analysis method was proposed to identify the motion modes responsible for a specific function of proteins and then predict the key residue interactions involved in the functional motions by using a perturbation approach. In our method, an internal coordinate that accounts for the specific function was introduced, and the Cartesian coordinate space was transformed into the internal/Cartesian space by using linear approximation, where the introduced internal coordinate serves as one of the axes of the coordinate space. NMA of ENM in this internal/Cartesian space was performed and the function-relevant motion modes were identified according to their contributions to the specific function of proteins. Then the key residue interactions important for the functional motions of the protein were predicted as the interactions whose perturbation largely influences the fluctuation along the internal coordinate. Using our proposed methods, the maltose transporter (MalFGK2) from E. Coli was studied. The functional motions and the key residue interactions that are related to the channel-gating function of this protein were successfully identified.


Biopolymers | 2014

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

Chun Hua Li; Yong Xiao Yang; Ji Guo Su; Bin Liu; Jian Jun Tan; Xiaoyi Zhang; Cun Xin Wang

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.


Journal of Physical Chemistry B | 2013

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

Ji Guo Su; Hui Jing Du; Rui Hao; Xianjin Xu; Chun Hua Li; Wei Zu Chen; Cun Xin Wang

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.


Proteins | 2015

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

Xiao Lu Xie; Chun Hua Li; Yong Xiao Yang; Lu Jin; Jian Jun Tan; Xiaoyi Zhang; Ji Guo Su; Cun Xin Wang

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.

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Cun Xin Wang

Beijing University of Technology

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Chun Hua Li

Beijing University of Technology

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Wei Zu Chen

Beijing University of Technology

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Xianjin Xu

University of Missouri

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Jian Jun Tan

Beijing University of Technology

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Yong Xiao Yang

Beijing University of Technology

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Ming Liu

Beijing University of Technology

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Ting Guang Sun

Beijing University of Technology

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