Insight into the Inhibitory Mechanism and Binding Mode Between D77 and HIV-1 Integrase by Molecular Modeling Methods

Prediction and validation of host-pathogen interactions by a versatile inference approach using Aspergillus fumigatus as a case study

Biological networks are characterized by diverse interactions and dynamics in time and space. Many regulatory modules operate in parallel and are interconnected with each other. Some pathways are functionally known and annotated accordingly, e.g., endocytosis, migration, or cytoskeletal rearrangement. However, many interactions are not so well characterized. For reconstructing the biological complexity in cellular networks, we combine here existing experimentally confirmed and analyzed interactions with a protein-interaction inference framework using as basis experimentally confirmed interactions from other organisms. Prediction scoring includes sequence similarity, evolutionary conservation of interactions, the coexistence of interactions in the same pathway, orthology as well as structure similarity to rank and compare inferred interactions. We exemplify our inference method by studying host-pathogen interactions during infection of Mus musculus (phagolysosomes in alveolar macrophages) with Aspergillus fumigatus (conidia, airborne, asexual spores). Three of nine predicted critical host-pathogen interactions could even be confirmed by direct experiments. Moreover, we suggest drugs that manipulate the host-pathogen interaction.

Effective prediction model and determination of binding residues influential for inhibitors targeting HIV-1 integrase-LEDGF/p75 interface by employing solvent accessible surface area energy as key determinant

Development of a highly accurate prediction model for protein-ligand inhibition has been a major challenge in drug discovery. Herein, we describe a novel predictive model for the inhibition of HIV-1 integrase (IN)-LEDGF/p75 protein-protein interaction. The model was constructed using energy parameters approximated from molecular dynamics (MD) simulations and molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations. Chemometric analysis using partial least squares (PLS) regression revealed that solvent accessible surface area energy (ΔG_SASA) is the major determinant parameter contributing greatly to the prediction accuracy. PLS prediction model on the ΔG_SASA values collected from 41 complexes yielded a strong correlation between the predicted and the actual inhibitory activities (R² = 0.9666, RMSEC of pIC₅₀ values = 0.0890). Additionally, for the test set of 14 complexes, the model performed satisfactorily with very low pIC₅₀ errors (Q² = 0.5168, RMSEP = 0.3325). A strong correlation between the buried surface areas on the IN protein, when bound with IN-LEDGF/p75 inhibitors, and the respective ΔG_SASA values was also obtained. Furthermore, the current method could identify 'hot spots'of amino acid residues highly influential to the inhibitory activity prediction. This could present fruitful implications in binding site determination and future inhibitor developments targeting protein-protein interactions.Communicated by Ramaswamy H. Sarma.

Revealing the role of oxidation state in interaction between nitro/amino-derived particulate matter and blood proteins

Surface oxidation states of ultrafine particulate matter can influence the proinflammatory responses and reactive oxygen species levels in tissue. Surface active species of vehicle-emission soot can serve as electron transfer-mediators in mitochondrion. Revealing the role of surface oxidation state in particles-proteins interaction will promote the understanding on metabolism and toxicity. Here, the surface oxidation state was modeled by nitro/amino ligands on nanoparticles, the interaction with blood proteins were evaluated by capillary electrophoresis quantitatively. The nitro shown larger affinity than amino. On the other hand, the affinity to hemoglobin is 10(3) times larger than that to BSA. Further, molecular docking indicated the difference of binding intensity were mainly determined by hydrophobic forces and hydrogen bonds. These will deepen the quantitative understanding of protein-nanoparticles interaction from the perspective of surface chemical state.

Wikstroelide M potently inhibits HIV replication by targeting reverse transcriptase and integrase nuclear translocation

AIM

To evaluate the anti-HIV activity and mechanism of action of wikstroelide M, a daphnane diterpene from Daphne acutiloba Rehder (Thymelaeaceae).

METHODS

The anti-HIV activities of wikstroelide M against different HIV strains were evaluated by cytopathic effect assay and p24 quantification assay with ELISA. The inhibitory effect of wikstroelide M on HIV reverse transcription was analyzed by real-time PCR and ELISA. The effect of wikstroelide M on HIV-1 integrase nuclear translocation was observed with a cell-based imaging assay. The effect of wikstroelide M on LEDGF/p75-IN interaction was assayed by molecular docking.

RESULTS

Wikstroelide M potently inhibited different HIV-1 strains, including HIV-1IIIB, HIV-1A17, and HIV-19495, induced a cytopathic effect, with EC50 values ranging from 3.81 to 15.65 ng·mL⁻¹. Wikstroelide M also had high inhibitory activities against HIV-2ROD and HIV-2CBL-20-induced cytopathic effects with EC50 values of 18.88 and 31.90 ng·mL⁻¹. The inhibitory activities of wikstroelide M on the three HIV-1 strains were further confirmed by p24 quantification assay, with EC50 values ranging from 15.16 to 35.57 ng·mL⁻¹. Wikstroelide M also potently inhibited HIV-1IIIB induced cytolysis in MT-4 cells, with an EC50 value of 9.60 ng·mL⁻¹. The mechanistic assay showed that wikstroelide M targeted HIV-1 reverse transcriptase and nuclear translocation of integrase through disrupting the interaction between integrase and LEDGF/p75.

CONCLUSION

Wikstroelide M may be a potent HIV-1 and HIV-2 inhibitor, the mechanisms of action may include inhibition of reverse trascriptase activity and inhibition of integrase nuclear translocation through disrupting the interaction between integrase and LEDGF/p75.

Study on the interactions between diketo-acid inhibitors and prototype foamy virus integrase-DNA complex via molecular docking and comparative molecular dynamics simulation methods

Human immunodeficiency virus type 1 (HIV-1) integrase (IN) is an important drug target for anti-acquired immune deficiency disease (AIDS) treatment and diketo-acid (DKA) inhibitors are potent and selective inhibitors of HIV-1 IN. Due to lack of three-dimensional structures including detail interactions between HIV-1 IN and its substrate viral DNA, the drug design and screening platform remains incompleteness and deficient. In addition, the action mechanism of DKA inhibitors with HIV-1 IN is not well understood. In view of the high homology between the structure of prototype foamy virus (PFV) IN and that of HIV-1 IN, we used PFV IN as a surrogate model for HIV-1 IN to investigate the inhibitory mechanism of raltegravir (RLV) and the binding modes with a series of DKA inhibitors. Firstly, molecular dynamics simulations of PFV IN, IN-RLV, IN-DNA, and IN-DNA-RLV systems were performed for 10 ns each. The interactions and inhibitory mechanism of RLV to PFV IN were explored through overall dynamics behaviors, catalytic loop conformation distribution, and hydrogen bond network analysis. The results show that the coordinated interactions of RLV with IN and viral DNA slightly reduce the flexibility of catalytic loop region of IN, and remarkably restrict the mobility of the CA end of viral DNA, which may lead to the partial loss of the inhibitory activity of IN. Then, we docked a series of DKA inhibitors into PFV IN-DNA receptor and obtained the IN-DNA-inhibitor complexes. The docking results between PFV IN-DNA and DKA inhibitors agree well with the corresponding complex of HIV-1 IN, which proves the dependability of PFV IN-DNA used for the anti-AIDS drug screening. Our study may help to make clear some theoretical questions and to design anti-AIDS drug based on the structure of IN.

The effect of fucoidan on tyrosinase: computational molecular dynamics integrating inhibition kinetics

Fucoidan is a complex sulfated polysaccharide extracted from brown seaweed and has a wide variety of biological activities. In this study, we investigated the inhibitory effect of fucoidan on tyrosinase via a combination of inhibition kinetics and computational simulations. Fucoidan reversibly inhibited tyrosinase in a mixed-type manner. Time-interval kinetics showed that the inhibition was processed as first order with biphasic processes. For further insight, we simulated dockings with various sizes of molecular models (monomer to decamer) of fucoidan and showed that the best binding energy change results were obtained from the pentamer (-1.89 kcal/mol) and the hexamer (-1.97 kcal/mol) models of AutoDock Vina. The molecular dynamics simulation confirmed the binding mechanisms between tyrosinase and fucoidan and suggested that fucoidan mostly interacts with several residues including copper ions located in the active site. Our study suggests that fucoidan might be a potential natural antipigment agent.