Homology modelling has matured into an important technique in structural biology, significantly contributing to narrowing the gap between known protein sequences and experimentally determined structures. Fully automated workflows and servers simplify and streamline the homology modelling process, also allowing users without a specific computational expertise to generate reliable protein models and have easy access to modelling results, their visualization and interpretation. Here, we present an update to the SWISS-MODEL server, which pioneered the field of automated modelling 25 years ago and been continuously further developed. Recently, its functionality has been extended to the modelling of homo- and heteromeric complexes. Starting from the amino acid sequences of the interacting proteins, both the stoichiometry and the overall structure of the complex are inferred by homology modelling. Other major improvements include the implementation of a new modelling engine, ProMod3 and the introduction a new local model quality estimation method, QMEANDisCo. SWISS-MODEL is freely available at https://swissmodel.expasy.org.

/pdf/swiss-model-homology-modelling-of-protein-structures-and-dk4p9xtc0o.pdf

SWISS-MODEL: homology modelling of protein structures and complexes.

Using the process of carbon catabolite repression (CCR), bacteria control gene expression and protein activity to preferentially metabolize the carbon sources that are most easily accessible and allow fastest growth. Recent findings have provided new insight into the mechanisms that different bacteria use to control CCR. Most bacteria can selectively use substrates from a mixture of different carbon sources. The presence of preferred carbon sources prevents the expression, and often also the activity, of catabolic systems that enable the use of secondary substrates. This regulation, called carbon catabolite repression (CCR), can be achieved by different regulatory mechanisms, including transcription activation and repression and control of translation by an RNA-binding protein, in different bacteria. Moreover, CCR regulates the expression of virulence factors in many pathogenic bacteria. In this Review, we discuss the most recent findings on the different mechanisms that have evolved to allow bacteria to use carbon sources in a hierarchical manner.

Carbon catabolite repression in bacteria: many ways to make the most out of nutrients

The phosphoenolpyruvate(PEP):carbohydrate phosphotransferase system (PTS) is found only in bacteria, where it catalyzes the transport and phosphorylation of numerous monosaccharides, disaccharides, amino sugars, polyols, and other sugar derivatives. To carry out its catalytic function in sugar transport and phosphorylation, the PTS uses PEP as an energy source and phosphoryl donor. The phosphoryl group of PEP is usually transferred via four distinct proteins (domains) to the transported sugar bound to the respective membrane component(s) (EIIC and EIID) of the PTS. The organization of the PTS as a four-step phosphoryl transfer system, in which all P derivatives exhibit similar energy (phosphorylation occurs at histidyl or cysteyl residues), is surprising, as a single protein (or domain) coupling energy transfer and sugar phosphorylation would be sufficient for PTS function. A possible explanation for the complexity of the PTS was provided by the discovery that the PTS also carries out numerous regulatory functions. Depending on their phosphorylation state, the four proteins (domains) forming the PTS phosphorylation cascade (EI, HPr, EIIA, and EIIB) can phosphorylate or interact with numerous non-PTS proteins and thereby regulate their activity. In addition, in certain bacteria, one of the PTS components (HPr) is phosphorylated by ATP at a seryl residue, which increases the complexity of PTS-mediated regulation. In this review, we try to summarize the known protein phosphorylation-related regulatory functions of the PTS. As we shall see, the PTS regulation network not only controls carbohydrate uptake and metabolism but also interferes with the utilization of nitrogen and phosphorus and the virulence of certain pathogens.

How Phosphotransferase System-Related Protein Phosphorylation Regulates Carbohydrate Metabolism in Bacteria

CAPRI is a communitywide experiment to assess the capacity of protein-docking methods to predict protein-protein interactions. Nineteen groups participated in rounds 1 and 2 of CAPRI and submitted blind structure predictions for seven protein-protein complexes based on the known structure of the component proteins. The predictions were compared to the unpublished X-ray structures of the complexes. We describe here the motivations for launching CAPRI, the rules that we applied to select targets and run the experiment, and some conclusions that can already be drawn. The results stress the need for new scoring functions and for methods handling the conformation changes that were observed in some of the target systems. CAPRI has already been a powerful drive for the community of computational biologists who development docking algorithms. We hope that this issue of Proteins will also be of interest to the community of structural biologists, which we call upon to provide new targets for future rounds of CAPRI, and to all molecular biologists who view protein-protein recognition as an essential process.

/pdf/capri-a-critical-assessment-of-predicted-interactions-d7a3cmrerj.pdf

CAPRI: A Critical Assessment of PRedicted Interactions

Cellular processes often depend on interactions between proteins and the formation of macromolecular complexes. The impairment of such interactions can lead to deregulation of pathways resulting in disease states, and it is hence crucial to gain insights into the nature of macromolecular assemblies. Detailed structural knowledge about complexes and protein-protein interactions is growing, but experimentally determined three-dimensional multimeric assemblies are outnumbered by complexes supported by non-structural experimental evidence. Here, we aim to fill this gap by modeling multimeric structures by homology, only using amino acid sequences to infer the stoichiometry and the overall structure of the assembly. We ask which properties of proteins within a family can assist in the prediction of correct quaternary structure. Specifically, we introduce a description of protein-protein interface conservation as a function of evolutionary distance to reduce the noise in deep multiple sequence alignments. We also define a distance measure to structurally compare homologous multimeric protein complexes. This allows us to hierarchically cluster protein structures and quantify the diversity of alternative biological assemblies known today. We find that a combination of conservation scores, structural clustering, and classical interface descriptors, can improve the selection of homologous protein templates leading to reliable models of protein complexes.

/pdf/modeling-protein-quaternary-structure-of-homo-and-hetero-2g0611gik0.pdf

Modeling protein quaternary structure of homo- and hetero-oligomers beyond binary interactions by homology

Traditional approaches to protein–protein docking sample the binding modes with no regard to similar experimentally determined structures (templates) of protein–protein complexes. Emerging template-based docking approaches utilize such similar complexes to determine the docking predictions. The docking problem assumes the knowledge of the participating proteins’ structures. Thus, it provides the possibility of aligning the structures of the proteins and the template complexes. The progress in the development of template-based docking and the vast experience in template-based modeling of individual proteins show that, generally, such approaches are more reliable than the free modeling. The key aspect of this modeling paradigm is the availability of the templates. The current common perception is that due to the difficulties in experimental structure determination of protein–protein complexes, the pool of docking templates is insignificant, and thus a broad application of template-based docking is possible only at some future time. The results of our large scale, systematic study show that, surprisingly, in spite of the limited number of protein–protein complexes in the Protein Data Bank, docking templates can be found for complexes representing almost all the known protein–protein interactions, provided the components themselves have a known structure or can be homology-built. About one-third of the templates are of good quality when they are compared to experimental structures in test sets extracted from the Protein Data Bank and would be useful starting points in modeling the complexes. This finding dramatically expands our ability to model protein interactions, and has far-reaching implications for the protein docking field in general.

https://www.pnas.org/content/pnas/109/24/9438.full.pdf

Templates are available to model nearly all complexes of structurally characterized proteins

In most Gram-positive bacteria, serine-46-phosphorylated HPr (P-Ser-HPr) controls the expression of numerous catabolic genes (≈10% of their genome) by acting as catabolite corepressor. HPr kinase/phosphorylase (HprK/P), the bifunctional sensor enzyme for catabolite repression, phosphorylates HPr, a phosphocarrier protein of the sugar-transporting phosphoenolpyruvate/glycose phosphotransferase system, in the presence of ATP and fructose-1,6-bisphosphate but dephosphorylates P-Ser-HPr when phosphate prevails over ATP and fructose-1,6-bisphosphate. We demonstrate here that P-Ser-HPr dephosphorylation leads to the formation of HPr and pyrophosphate. HprK/P, which binds phosphate at the same site as the β phosphate of ATP, probably uses the inorganic phosphate to carry out a nucleophilic attack on the phosphoryl bond in P-Ser-HPr. HprK/P is the first enzyme known to catalyze P-protein dephosphorylation via this phospho–phosphorolysis mechanism. This reaction is reversible, and at elevated pyrophosphate concentrations, HprK/P can use pyrophosphate to phosphorylate HPr. Growth of Bacillus subtilis on glucose increased intracellular pyrophosphate to concentrations (≈6 mM), which in in vitro tests allowed efficient pyrophosphate-dependent HPr phosphorylation. To effectively dephosphorylate P-Ser-HPr when glucose is exhausted, the pyrophosphate concentration in the cells is lowered to 1 mM. In B. subtilis, this might be achieved by YvoE. This protein exhibits pyrophosphatase activity, and its gene is organized in an operon with hprK.

https://www.pnas.org/content/pnas/99/21/13442.full.pdf

JoÃ«l Janin

Papers

Templates are available to model nearly all complexes of structurally characterized proteins

Pyrophosphate-producing protein dephosphorylation by HPr kinase/phosphorylase: a relic of early life?