Structural insight into protein–protein interactions between intestinal microbiome and host

Protein–protein interactions between the microbiome and host organism play an important role in shaping host health. These host-modulating proteins have therapeutic potential in treating microbiome-linked disorders such as inflammatory bowel disease and obesity. Structural analysis of interacting proteins provides highly mechanistic insight into the domains driving these interactions and the resulting influence on host cell processes. Here, we briefly review recent publication of microbiome protein structures involved in host binding interactions, the effects of these interactions on host physiology, and the need for further study to increase the ability to detect proteins with therapeutic potential.     

Characterization of protein–protein interactions between rice viruses and vector insects

Planthoppers are the most notorious rice pests, because they transmit various rice viruses in a persistent-propagative manner. Protein–protein interactions (PPIs) between virus and vector are crucial for virus transmission by vector insects. However, the number of known PPIs for pairs of rice viruses and planthoppers is restricted by low throughput research methods. In this study, we applied DeNovo, a virus-host sequence-based PPI predictor, to predict potential PPIs at a genome-wide scale between three planthoppers and five rice viruses. PPIs were identified at two different confidence thresholds, referred to as low and high modes. The number of PPIs for the five planthopper-virus pairs ranged from 506 to 1985 in the low mode and from 1254 to 4286 in the high mode. After eliminating the “one-too-many” redundant interacting information, the PPIs with unique planthopper proteins were reduced to 343–724 in the low mode and 758–1671 in the high mode. Homologous analysis showed that 11 sets and 31 sets of homologous planthopper proteins were shared by all planthopper-virus interactions in the two modes, indicating that they are potential conserved vector factors essential for transmission of rice viruses. Ten PPIs between small brown planthopper and rice stripe virus (RSV) were verified using glutathione-S-transferase (GST)/His-pull down or co-immunoprecipitation assay. Five of the ten PPIs were proven positive, and three of the five SBPH proteins were confirmed to interact with RSV. The predicted PPIs provide new clues for further studies of the complicated relationship between rice viruses and their vector insects.     

Mating systems and protein–protein interactions determine evolutionary rates of primate sperm proteins

To assess the relative impact of functional constraint and post-mating sexual selection on sequence evolution of reproductive proteins, we examined 169 primate sperm proteins. In order to recognize potential genome-wide trends, we additionally analysed a sample of altogether 318 non-reproductive (brain and postsynaptic) proteins. Based on cDNAs of eight primate species (Anthropoidea), we observed that pre-mating sperm proteins engaged in sperm composition and assembly show significantly lower incidence of site-specific positive selection and overall lower non-synonymous to synonymous substitution rates (d_N/d_S) across sites as compared with post-mating sperm proteins involved in capacitation, hyperactivation, acrosome reaction and fertilization. Moreover, database screening revealed overall more intracellular protein interaction partners in pre-mating than in post-mating sperm proteins. Finally, post-mating sperm proteins evolved at significantly higher evolutionary rates than pre-mating sperm and non-reproductive proteins on the branches to multi-male breeding species, while no such increase was observed on the branches to unimale and monogamous species. We conclude that less protein–protein interactions of post-mating sperm proteins account for lowered functional constraint, allowing for stronger impact of post-mating sexual selection, while the opposite holds true for pre-mating sperm proteins. This pattern is particularly strong in multi-male breeding species showing high female promiscuity.     

Protein backbone motions viewed by intraresidue and sequential HN–Hα residual dipolar couplings

Triple resonance E.COSY-based techniques were used to measure intra-residue and sequential H(N)-H(alpha) residual dipolar couplings (RDCs) for the third IgG-binding domain of protein G (GB3), aligned in Pf1 medium. Measurements closely correlate with values predicted on the basis of an NMR structure, previously determined on the basis of a large number of one-bond backbone RDCs measured in five alignment media. However, in particular the sequential H(N)-H(alpha) RDCs are smaller than predicted for a static structure, suggesting a degree of motion for these internuclear vectors that exceeds that of the backbone amide N-H vectors. Of all experimentally determined GB3 structures available, the best correlation between experimental (1)H-(1)H couplings is observed for a GB3 ensemble, previously derived to generate a realistic picture of the conformational space sampled by GB3 (Clore and Schwieters, J Mol Biol 355:879-886, 2006). However, for both NMR and X-ray-derived structures the (1)H-(1)H couplings are found to be systematically smaller than expected on the basis of alignment tensors derived from (15)N-(1)H amide RDCs, assuming librationally corrected N-H bond lengths of 1.041 A.     

Scoring functions for protein–protein interactions

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Characterizing weak protein–protein complexes by NMR residual dipolar couplings

Protein–protein interactions occur with a wide range of affinities from tight complexes characterized by femtomolar dissociation constants to weak, and more transient, complexes of millimolar affinity. Many of the weak and transiently formed protein–protein complexes have escaped characterization due to the difficulties in obtaining experimental parameters that report on the complexes alone without contributions from the unbound, free proteins. Here, we review recent developments for characterizing the structures of weak protein–protein complexes using nuclear magnetic resonance spectroscopy with special emphasis on the utility of residual dipolar couplings.     

Comparative mapping of host–pathogen protein–protein interactions

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Peptide-based covalent inhibitors of protein–protein interactions

Protein–protein interactions (PPI) are involved in all cellular processes and many represent attractive therapeutic targets. However, the frequently rather flat and large interaction areas render the identification of small molecular PPI inhibitors very challenging. As an alternative, peptide interaction motifs derived from a PPI interface can serve as starting points for the development of inhibitors. However, certain proteins remain challenging targets when applying inhibitors with a competitive mode of action. For that reason, peptide-based ligands with an irreversible binding mode have gained attention in recent years. This review summarizes examples of covalent inhibitors that employ peptidic binders and have been tested in a biological context.     

Molecular glues to stabilise protein–protein interactions

Targeting protein–protein interactions (PPIs) has become a common approach to tackle various diseases whose pathobiology is driven by their mis-regulation in important signalling pathways. Modulating PPIs has tremendous untapped therapeutic potential and different approaches can be used to modulate PPIs. Initially, therapeutic effects were mostly sought by inhibiting PPIs. However, by gaining insight in the mode of action of certain therapeutic compounds, it became clear that stabilising (i.e. enhancing) PPIs can also be useful. The latter strategy is recently gaining a lot of attention, as stabilising physiologic, or even inducing novel interactions of a target protein with E3 ubiquitin ligases forms the basis of the targeted protein degradation (TPD) approach. An emerging additional example for drug discovery based on PPI stabilisation are the 14-3-3 proteins, a family of regulatory proteins, which engages in many protein–protein interactions, some of which might become therapeutical targets.     

Probing membrane protein–lipid interactions

Structure determination of membrane proteins has highlighted the many roles played by lipids in influencing overall protein architecture. It is now widely accepted that lipids surrounding membrane proteins play crucial roles by modulating their conformational, structural, and functional properties. Capturing often transient lipid interactions and defining their chemical identity, however, remains challenging. Recent advances in mass spectrometry have resolved questions concerning lipid interactions by providing the molecular composition of intact complexes in association with lipids. Together with other biophysical tools, a picture is emerging of the dynamic nature of lipid-mediated interactions and their effects on conformation, interactions, and signaling.     

Predicting protein–protein interactions from protein sequences using meta predictor

A novel method is proposed for predicting protein–protein interactions (PPIs) based on the meta approach, which predicts PPIs using support vector machine that combines results by six independent state-of-the-art predictors. Significant improvement in prediction performance is observed, when performed on Saccharomyces cerevisiae and Helicobacter pylori datasets. In addition, we used the final prediction model trained on the PPIs dataset of S. cerevisiae to predict interactions in other species. The results reveal that our meta model is also capable of performing cross-species predictions. The source code and the datasets are available at