Detection of persistent organic pollutants binding modes with androgen receptor ligand binding domain by docking and molecular dynamics.

BACKGROUND: Persistent organic pollutants (POPs) are persistent in the environment after release from industrial compounds, combustion productions or pesticides. The exposure of POPs has been related to various reproductive disturbances, such as reduced semen quality, testicular cancer, and imbalanced sex ratio. Among POPs, dichlorodiphenyldichloroethylene (4,4'-DDE) and polychlorinated biphenyls (PCBs) are the most widespread and well-studied compounds. Recent studies have revealed that 4,4'-DDE is an antagonist of androgen receptor (AR). However, the mechanism of the inhibition remains elusive. CB-153 is the most common congener of PCBs, while the action of CB-153 on AR is still under debate. RESULTS: Molecular docking and molecular dynamics (MD) approaches have been employed to study binding modes and inhibition mechanism of 4,4'-DDE and CB-153 against AR ligand binding domain (LBD). Several potential binding sites have been detected and analyzed. One possible binding site is the same binding site of AR natural ligand androgen 5α-dihydrotestosterone (DHT). Another one is on the ligand-dependent transcriptional activation function (AF2) region, which is crucial for the co-activators recruitment. Besides, a novel possible binding site was observed for POPs with low binding free energy with the receptor. Detailed interactions between ligands and the receptor have been represented. The disrupting mechanism of POPs against AR has also been discussed. CONCLUSIONS: POPs disrupt the function of AR through binding to three possible biding sites on AR/LBD. One of them shares the same binding site of natural ligand of AR. Another one is on AF2 region. The third one is in a cleft near N-terminal of the receptor. Significantly, values of binding free energy of POPs with AR/LBD are comparable to that of natural ligand androgen DHT.

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 ß, 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.

Role of electrostatic interactions for the stability and folding behavior of cold shock protein.

The impacts of three charged-residue-involved mutations, E46A, R3E, and R3E/L66E, on the thermostability and folding behavior of the cold shock protein from the themophile Bacillus caldolyticus (Bc-Csp) were investigated by using a modified Go-like model, in which the nonspecific electrostatic interactions of charged residues were taken into account. Our simulation results show that the wild-type Bc-Csp and its three mutants are all two-sate folders, which is consistent with the experimental observations. It is found that these three mutations all lead to a decrease of protein thermodynamical stability, and the effect of R3E mutation is the strongest. The lower stability of these three mutants is due to the increase of the enthalpy of the folded state and the entropy of the unfolded state. Using this model, we also studied the folding kinetics and the folding/unfolding pathway of the wild-type Bc-Csp as well as its three mutants and then discussed the effects of electrostatic interactions on the folding kinetics. The results indicate that the substitutions at positions 3 and 46 largely decrease the folding kinetics, whereas the mutation of residue 66 only slightly decreases the folding rate. This result agrees well with the experimental observations. It is also found that these mutations have little effects on the folding transition state and the folding pathway, in which the N-terminal beta sheet folds earlier than the C-terminal region. We also investigated the detailed unfolding pathway and found that it is really the reverse of the folding pathway, providing the validity of our simulation results.

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.

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.

Study on the molecular mechanism of inhibiting HIV-1 integrase by EBR28 peptide via molecular modeling approach.

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.

A novel high-throughput format assay for HIV-1 integrase strand transfer reaction using magnetic beads.

AIM: To develop a novel high-throughput format assay to monitor the integrase (IN) strand transfer (ST) reaction in vitro and apply it to a reaction character study and the identification of antiviral drugs. METHODS: The donor DNA duplex, with a sequence identical to the U5 end of HIV-1 long terminal repeats, is labeled at its 5' end with biotin (BIO). The target DNA duplex is labeled at its 3' end with digoxin (DIG). IN mediates the integration of donor DNA into target DNA and results in a 5' BIO and 3' DIG-labeled duplex DNA product. Streptavidin-coated magnetic beads were used to capture the product, and the amount of DIG was measured as the ST reaction product. The assay was optimized in 96-well microplate format for high-throughput screening purpose. Moreover, the assay was applied in a ST reaction character study, and the efficiency of the assay in the identification of antiviral compounds was tested. RESULTS: The end-point values, measured as absorbance at 405 nm was approximately 1.5 for the IN-mediated ST reaction as compared with no more than 0.05 of background readings. The ST reaction character and the half maximal inhibitory concentration (IC50) values of 2 known IN inhibitors obtained in our assay were similar to previously reported results using other assays. The evaluation parameter Z' factor for this assay ranged from 0.6 to 0.9. CONCLUSION: The assay presented here has been proven to be rapid, sensitive, and specific for the detection of IN ST activity, the reaction character study, as well as for the identification of antiviral drugs targeting IN.

Evolving model of amino acid networks.

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.

Prediction of the binding mode between BMS-378806 and HIV-1 gp120 by docking and molecular dynamics simulation.

BMS-378806 is a newly discovered small molecule that effectively blocks the binding of CD4 with gp120. The binding mode of this kind of inhibitor remains unknown. In this paper, AutoDock 3.0 in conjunction with molecular dynamics simulation, accommodating the receptor's flexibility, was used to explore the binding mode between BMS-378806 and gp120. Two structures, Mode I and Mode II, with the lowest docking energy were selected as different representative binding modes. The analysis of the results from the molecular dynamics simulation indicated that the binding of BMS-348806 in Mode II is more stable. The average structure of Mode II was analyzed and compared with the experimental data. The conclusion was that BMS-378806 inserts the azaindole ring deeply into the PHE43 cavity and makes contact with a number of residues in the cavity, on the cavity and near the cavity. This study benefits the understanding of the mechanism of this kind of inhibitor and may provide useful information for rational drug design.

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.

Complex-type-dependent scoring functions in protein-protein docking.

A major challenge in the field of protein-protein docking is to discriminate between the many wrong and few near-native conformations, i.e. scoring. Here, we introduce combinatorial complex-type-dependent scoring functions for different types of protein-protein complexes, protease/inhibitor, antibody/antigen, enzyme/inhibitor and others. The scoring functions incorporate both physical and knowledge-based potentials, i.e. atomic contact energy (ACE), the residue pair potential (RP), electrostatic and van der Waals' interactions. For different type complexes, the weights of the scoring functions were optimized by the multiple linear regression method, in which only top 300 structures with ligand root mean square deviation (L_RMSD) less than 20 A from the bound (co-crystallized) docking of 57 complexes were used to construct a training set. We employed the bound docking studies to examine the quality of the scoring function, and also extend to the unbound (separately crystallized) docking studies and extra 8 protein-protein complexes. In bound docking of the 57 cases, the first hits of protease/inhibitor cases are all ranked in the top 5. For the cases of antibody/antigen, enzyme/inhibitor and others, there are 17/19, 5/6 and 13/15 cases with the first hits ranked in the top 10, respectively. In unbound docking studies, the first hits of 9/17 protease/inhibitor, 6/19 antibody/antigen, 1/6 enzyme/inhibitor and 6/15 others' complexes are ranked in the top 10. Additionally, for the extra 8 cases, the first hits of the two protease/inhibitor cases are ranked in the top for the bound and unbound test. For the two enzyme/inhibitor cases, the first hits are ranked 1st for bound test, and the 119th and 17th for the unbound test. For the others, the ranks of the first hits are the 1st for the bound test and the 12th for the 1WQ1 unbound test. To some extent, the results validated our divide-and-conquer strategy in the docking study, which might hopefully shed light on the prediction of protein-protein interactions.

Construction and application of the weighted amino acid network based on energy.

A method is proposed to construct the weighted amino acid network. The weight of the link is based on the contact energy between residues. For the 197 proteins with low homology, the "small-world" property was studied based on this method. Additionally, analyses were carried out for the statistic characteristics of the network parameters, the influence of the weight on the network parameters, the network parameter difference of amino acids, and the links between the hydrophobic and hydrophilic residues. Using this method, we studied the network parameter change for the protein chymotrypsin inhibitor 2 (CI2) on its high-temperature unfolding pathway. It is found that the unfolding of the protein is mainly exhibited as the derogation of the hydrophobic core and the shortest path length rise in the unfolding process. This work is helpful for studies of protein folding and the relationship between structure and function using complex network theory.

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 A to 2.9 A after performing multiconformational superposition. These results were obtained after the CAPRI prediction deadlines.

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 alpha-amylase. For target 06, two native-like structures with a root-mean-square deviation < 4.0 A 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.

Protein molecular dynamics with electrostatic force entirely determined by a single Poisson-Boltzmann calculation.

The electrostatic force including the intramolecular Coulombic interactions and the electrostatic contribution of solvation effect were entirely calculated by using the finite difference Poisson-Boltzmann method (FDPB), which was incorporated into the GROMOS96 force field to complete a new finite difference stochastic dynamics procedure (FDSD). Simulations were performed on an insulin dimer. Different relative dielectric constants were successively assigned to the protein interior; a value of 17 was selected as optimal for our system. The simulation data were analyzed and compared with those obtained from 500-ps molecular dynamics (MD) simulation with explicit water and a 500-ps conventional stochastic dynamics (SD) simulation without the mean solvent force. The results indicate that the FDSD method with GROMOS96 force field is suitable to study the dynamics and structure of proteins in solution if used with the optimal protein dielectric constant.

A soft docking algorithm for predicting the structures of protein-protein complexes.

An efficient soft docking algorithm is described to predict the mode of binding between two proteins based on the three-dimensional structures of molecules. The molecular model used in this work was grounded on the "simplified protein" model used in Janin's docking algorithm. The side chain flexibility of the amino acid residues Arg, Lys, Asp, Glu and Met at the protein surface was considered through softening the molecular surface. A double filtering technique was used to eliminate most of the unlike binding modes. The energy minimization was performed on the retained structures, and then these structures were evaluated with the scoring function which included electrostatic, desolvation and van der Waals energy terms. The 26 complexes were used to test this docking algorithm and good results were obtained. The native-like conformations of all the complexes were all found, of which 20 were ranked in the top 10.

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.

An analysis of the influence of protein intrinsic dynamical properties on its thermal unfolding behavior.

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.

Insight into the inhibitory mechanism and binding mode between D77 and HIV-1 integrase by molecular modeling methods.

Integrase is an essential enzyme in the life cycle of Human immunoficiency virus type 1 (HIV-1) and also an important target for designing integrase inhibitors. In this paper, the binding modes between the wild type integrase core domain (ICD) and the W131A mutant ICD with the benzoic acid derivative--D77 were investigated using the molecular docking combined with molecular dynamics (MD) simulations. The result of MD simulations showed that the W131A substitution affected the flexibility of the region 150-167 in both the monomer A and B of the mutant type ICD. In principle, D77 interacted with the residues around the Lens Epithelium-Derived Growth Factor (LEDGF/p75) binding site which is nearby the HIV-1 integrase dimer interface. However, the specific binding modes for D77-wild type integrase and D77-mutant integrase systems are various. According to the binding mode of D77 with the wild type ICD, D77 can effectively intervene with the binding of LEDGF/p75 to integrase due to a steric hindrance effect around the LEDGF/p75 binding site. In addition, we found that D77 might also affect its inhibitory action by reducing the flexibility of the region 150-167 of integrase. Through energy decomposition calculated with the Molecular Mechanics Generalized Born Surface Area approach to estimate the binding affinity, it seems likely that W131 and E170 are indispensable for the ligand binding, as characterized by the largest binding affinity. All the above results are consistent with the experimental data, providing us with some helpful information not only for the understanding of the mechanism of this kind of inhibitor but also for the rational drug design.

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.