Vibrio parahaemolyticus has two sets of type III secretion systems that are major pathogenic factors: T3SS1 (cytotoxicity) and T3SS2 (enterotoxicity). V. parahaemolyticus mainly colonizes the distal small intestine after oral infection and may be exposed to carbon-limiting stress due to the lack of readily available carbohydrates in this environment. Catabolite activator protein (CAP), a transcription factor involved in carbon-limiting metabolism in many Gram-negative bacteria, is well known to be involved in the regulation of the expression of many virulence factors. In this study, we determined the effects of CAP on the expression of T3SSs in this bacterium. Based on a lactate dehydrogenase-based cytotoxicity assay, CAP was found to have a greater contribution to the expression of T3SS2-dependent cytotoxicity than to that of T3SS1. Reverse transcription quantitative PCR revealed decreased expression of many T3SS2-related genes, including vpa1348, in the cap gene deletion mutant compared to the parent strain. CAP was demonstrated to bind near the T-rich elements within the vpa1348 promoter region in an electrophoretic mobility shift assay and DNase I footprinting. CAP also enhanced the expression of vpa1348 in a β-galactosidase reporter assay. Collectively, these results suggest that CAP is involved in T3SS2-mediated virulence by regulating the expression of vpa1348 in V. parahaemolyticus.

In this study, we utilize Protein Residue Networks (PRNs), constructed using Local Spatial Pattern (LSP) alignment, to explore the dynamic behavior of Catabolite Activator Protein (CAP) upon the sequential binding of cAMP. We employed the Degree Centrality of these PRNs to investigate protein dynamics on a sub-nanosecond time scale, hypothesizing that it would reflect changes in CAP\'s entropy related to its thermal motions. We show that the binding of the first cAMP led to an increase in stability in the Cyclic-Nucleotide Binding Domain A (CNBD-A) and destabilization in CNBD-B, agreeing with previous reports explaining the negative cooperativity of cAMP binding in terms of an entropy-driven allostery. LSP-based PRNs also allow for the study of Betweenness Centrality, another graph-theoretical characteristic of PRNs, providing insights into global residue connectivity within CAP. Using this approach, we were able to correctly identify amino acids that were shown to be critical in mediating allosteric interactions in CAP. The agreement between our studies and previous experimental reports validates our method, particularly with respect to the reliability of Degree Centrality as a proxy for entropy related to protein thermal dynamics. Because LSP-based PRNs can be easily extended to include dynamics of small organic molecules, polynucleotides, or other allosteric proteins, the methods presented here mark a significant advancement in the field, positioning them as vital tools for a fast, cost-effective, and accurate analysis of entropy-driven allostery and identification of allosteric hotspots.

The transcription mechanism of genetic information from DNA to RNA is efficiently controlled by regulatory proteins, such as catabolite activator protein (CAP), and their ligands. When cyclic AMP (cAMP) binds to CAP, the complex forms a dimer and binds specifically to DNA to activate the transcription mechanism. On the other hand, when cyclic GMP (cGMP) binds to CAP, the complex has no marked effect on the mechanism. In our previous study, based on molecular dynamics (MD) and ab initio fragment molecular orbital (FMO) methods, we elucidated which residues of CAP are important for the specific interactions between CAP and DNA in the CAP-monomer+DNA + cAMP complex. However, this monomer model for CAP cannot describe real interactions between the CAP-dimer and DNA because CAPs form a dimer before binding to DNA. Accordingly, here, we investigated stable structures and their electronic states for the CAP-dimer+DNA complex with cAMP or cGMP ligand, to clarify the influence of ligand-binding on the interactions between CAP-dimer and DNA. The MD simulations elucidated that the DNA-binding domains of CAP-dimer behave differently depending on the ligand bound to the CAP-dimer. In addition, FMO calculations revealed that the binding energy between CAP-dimer and DNA for the CAP-dimer+DNA + cAMP complex is larger than that for the CAP-dimer+DNA + cGMP complex, being consistent with experiments. It was also highlighted that the Arg185 and Lys188 residues of CAP-dimer are important for the binding between CAP-dimer and DNA. These results provide useful information for proposing new compounds that efficiently control the transcription mechanism.

Normal mode analysis (NMA) can facilitate quick and systematic investigation of protein dynamics using data from the Protein Data Bank (PDB). We developed an elastic network model-based NMA program using dihedral angles as independent variables. Compared to the NMA programs that use Cartesian coordinates as independent variables, key attributes of the proposed program are as follows: (1) chain connectivity related to the folding pattern of a polypeptide chain is naturally embedded in the model; (2) the full-atom system is acceptable, and owing to a considerably smaller number of independent variables, the PDB data can be used without further manipulation; (3) the number of variables can be easily reduced by some of the rotatable dihedral angles; (4) the PDB data for any molecule besides proteins can be considered without coarse-graining; and (5) individual motions of constituent subunits and ligand molecules can be easily decomposed into external and internal motions to examine their mutual and intrinsic motions. Its performance is illustrated with an example of a DNA-binding allosteric protein, a catabolite activator protein. In particular, the focus is on the conformational change upon cAMP and DNA binding, and on the communication between their binding sites remotely located from each other. In this illustration, NMA creates a vivid picture of the protein dynamics at various levels of the structures, i.e., atoms, residues, secondary structures, domains, subunits, and the complete system, including DNA and cAMP. Comparative studies of the specific protein in different states, e.g., apo- and holo-conformations, and free and complexed configurations, provide useful information for studying structurally and functionally important aspects of the protein.

Allostery is fundamentally thermodynamic in nature. Long-range communication in proteins may be mediated not only by changes in the mean conformation with enthalpic contribution but also by changes in dynamic fluctuations with entropic contribution. The important role of protein motions in mediating allosteric interactions has been established by NMR spectroscopy. By using CAP as a model system, we have shown how changes in protein structure and internal dynamics can allosterically regulate protein function and activity. The results indicate that changes in conformational entropy can give rise to binding enhancement, binding inhibition, or have no effect in the expected affinity, depending on the magnitude and sign of enthalpy-entropy compensation. Moreover, allosteric interactions can be regulated by the modulation a low-populated conformation states that serve as on-pathway intermediates for ligand binding. Taken together, the interplay between fast internal motions, which are intimately related to conformational entropy, and slow internal motions, which are related to poorly populated conformational states, can regulate protein activity in a way that cannot be predicted on the basis of the protein\'s ground-state structure.

The related concepts of protein dynamics, conformational ensembles and allostery are often difficult to study with molecular dynamics (MD) due to the timescales involved. We present ExProSE (Exploration of Protein Structural Ensembles), a distance geometry-based method that generates an ensemble of protein structures from two input structures. ExProSE provides a unified framework for the exploration of protein structure and dynamics in a fast and accessible way. Using a dataset of apo/holo pairs it is shown that existing coarse-grained methods often cannot span large conformational changes. For T4-lysozyme, ExProSE is able to generate ensembles that are more native-like than tCONCOORD and NMSim, and comparable with targeted MD. By adding additional constraints representing potential modulators, ExProSE can predict allosteric sites. ExProSE ranks an allosteric pocket first or second for 27 out of 58 allosteric proteins, which is similar and complementary to existing methods. The ExProSE source code is freely available.

Allostery is a fundamental process by which ligand binding to a protein alters its activity at a distant site. There is considerable evidence that allosteric cooperativity can be communicated by the modulation of protein dynamics without conformational change. The Catabolite Activator Protein (CAP) of Escherichia coli is an important experimental exemplar for entropically driven allostery. Here we discuss recent experimentally supported theoretical analysis that highlights the role of global low-frequency dynamics in allostery in CAP and identify how allostery arises as a natural consequence of changes in global low-frequency protein fluctuations on ligand binding.

The crystal structure of cyclic AMP-catabolite activator protein (CAP) from Escherichia coli containing cobalt(II) chloride and ammonium sulfate is reported at 1.97 Å resolution. Each of the two CAP subunits in the asymmetric unit binds one cobalt(II) ion, in each case coordinated by N-terminal domain residues His19, His21 and Glu96 plus an additional acidic residue contributed via a crystal contact. The three identified N-terminal domain cobalt-binding residues are part of a region of CAP that is important for transcription activation at class II CAP-dependent promoters. Sulfate anions mediate additional crystal lattice contacts and occupy sites corresponding to DNA backbone phosphate positions in CAP-DNA complex structures.

Synthetic biology is the design and construction of new biological parts, devices and circuits not existing in nature. It provides a novel solution to imminent challenges in a wide variety of fields, including the discovery of new drugs, production chemicals, renewable biofuels, value-added products and cellular reprogramming. Many efforts have been made to design and characterize synthetic genetic parts, including promoter, transcription factors, RBS, degradation tags and transcriptional terminators, among others. These genetic parts have been assembled for construction of a number of synthetic devices and circuits like oscillators, toggle switches, amplifiers and biologic gates; they play a vital role in cell reprogramming for better understanding of cellular mechanisms and control of biological process. They are also useful for the periodic and tunable production of drugs, fine chemicals, vaccines and much more. It is the goal of this review to aid and accelerate future research in synthetic biology.

The structures of the same protein, determined under different conditions, provide clues toward understanding the role of structural changes in the protein\'s function. Structural changes are usually identified as rigid-body motions, which are defined using a particular threshold of rigidity, such as domain motions. However, each protein actually undergoes motions with various size and magnitude ranges. In this study, to describe protein structural changes more comprehensively, we propose a method based on hierarchical clustering. This method enables the illustration of a wide range of protein motions in a single tree diagram, named the \"Motion Tree\". We applied the method to 432 proteins exhibiting large structural changes and classified their Motion Trees in terms of the characteristic indices of the trees. This classification of the Motion Trees revealed clear relationships to their protein functions. Especially, complex structural changes are significantly correlated with multi-step protein functions.