Allosteric signalling in the outer membrane translocation domain of PapC usher

Gating of β-Barrel Protein Pores, Porins, and Channels: An Old Problem with New Facets

β barrels are ubiquitous proteins in the outer membranes of mitochondria, chloroplasts, and Gram-negative bacteria. These transmembrane proteins (TMPs) execute a wide variety of tasks. For example, they can serve as transporters, receptors, membrane-bound enzymes, as well as adhesion, structural, and signaling elements. In addition, multimeric β barrels are common structural scaffolds among many pore-forming toxins. Significant progress has been made in understanding the functional, structural, biochemical, and biophysical features of these robust and versatile proteins. One frequently encountered fundamental trait of all β barrels is their voltage-dependent gating. This process consists of reversible or permanent conformational transitions between a large-conductance, highly permeable open state and a low-conductance, solute-restrictive closed state. Several intrinsic molecular mechanisms and environmental factors modulate this universal property of β barrels. This review article outlines the typical signatures of voltage-dependent gating. Moreover, we discuss recent developments leading to a better qualitative understanding of the closure dynamics of these TMPs.

Allosteric Regulation at the Crossroads of New Technologies: Multiscale Modeling, Networks, and Machine Learning

Allosteric regulation is a common mechanism employed by complex biomolecular systems for regulation of activity and adaptability in the cellular environment, serving as an effective molecular tool for cellular communication. As an intrinsic but elusive property, allostery is a ubiquitous phenomenon where binding or disturbing of a distal site in a protein can functionally control its activity and is considered as the "second secret of life." The fundamental biological importance and complexity of these processes require a multi-faceted platform of synergistically integrated approaches for prediction and characterization of allosteric functional states, atomistic reconstruction of allosteric regulatory mechanisms and discovery of allosteric modulators. The unifying theme and overarching goal of allosteric regulation studies in recent years have been integration between emerging experiment and computational approaches and technologies to advance quantitative characterization of allosteric mechanisms in proteins. Despite significant advances, the quantitative characterization and reliable prediction of functional allosteric states, interactions, and mechanisms continue to present highly challenging problems in the field. In this review, we discuss simulation-based multiscale approaches, experiment-informed Markovian models, and network modeling of allostery and information-theoretical approaches that can describe the thermodynamics and hierarchy allosteric states and the molecular basis of allosteric mechanisms. The wealth of structural and functional information along with diversity and complexity of allosteric mechanisms in therapeutically important protein families have provided a well-suited platform for development of data-driven research strategies. Data-centric integration of chemistry, biology and computer science using artificial intelligence technologies has gained a significant momentum and at the forefront of many cross-disciplinary efforts. We discuss new developments in the machine learning field and the emergence of deep learning and deep reinforcement learning applications in modeling of molecular mechanisms and allosteric proteins. The experiment-guided integrated approaches empowered by recent advances in multiscale modeling, network science, and machine learning can lead to more reliable prediction of allosteric regulatory mechanisms and discovery of allosteric modulators for therapeutically important protein targets.

PySFD: comprehensive molecular insights from significant feature differences detected among many simulated ensembles

Motivation

Many modeling analyses of molecular dynamics (MD) simulations are based on a definition of states that can be (groups of) clusters of simulation frames in a feature space composed of molecular coordinates. With increasing dimension of this feature space (due to the increasing size or complexity of a simulated molecule), it becomes very difficult to cluster the underlying MD data and estimate a statistically robust model. To mitigate this “curse of dimensionality”, one can reduce the feature space, e.g., with principal component or time-lagged independent component analysis transformations, focusing the analysis on the most important modes of transitions. In practice, however, all these reduction strategies may neglect important molecular details that are susceptible to experimental verification.

Results

To recover such molecular details, I have developed PySFD (Significant Feature Differences analyzer for Python), a multi-processing software package that efficiently selects significantly different features of any user-defined feature type among potentially many different simulated state ensembles, such as meta-stable states of a Markov State Model (MSM). Applying PySFD on MSMs of an aggregate of 300 microseconds MD simulations recently performed on the major histocompatibility complex class II (MHCII) protein, I demonstrate how this toolkit can extract and visualize valuable mechanistic information from big MD simulation data, e.g., in form of networks of dynamic interaction changes connecting functionally relevant sites of a protein complex.

Availability and implementation

PySFD is freely available under the L-GPL license at https://github.com/markovmodel/PySFD.

Supplementary information

Supplementary data are available at Bioinformatics online.

Ligand-Binding-Site Structure Shapes Allosteric Signal Transduction and the Evolution of Allostery in Protein Complexes

The structure of ligand-binding sites has been shown to profoundly influence the evolution of function in homomeric protein complexes. Complexes with multichain binding sites (MBSs) have more conserved quaternary structure, more similar binding sites and ligands between homologs, and evolve new functions slower than homomers with single-chain binding sites (SBSs). Here, using in silico analyses of protein dynamics, we investigate whether ligand-binding-site structure shapes allosteric signal transduction pathways, and whether the structural similarity of binding sites influences the evolution of allostery. Our analyses show that: 1) allostery is more frequent among MBS complexes than in SBS complexes, particularly in homomers; 2) in MBS homomers, semirigid communities and critical residues frequently connect interfaces and thus they are characterized by signal transduction pathways that cross protein-protein interfaces, whereas SBS homomers usually not; 3) ligand binding alters community structure differently in MBS and SBS homomers; and 4) except MBS homomers, allosteric proteins are more likely to have homologs with similar binding site than nonallosteric proteins, suggesting that binding site similarity is an important factor driving the evolution of allostery.

Atomistic Modeling of the ABL Kinase Regulation by Allosteric Modulators Using Structural Perturbation Analysis and Community-Based Network Reconstruction of Allosteric Communications

In this work, we have examined the molecular mechanisms of allosteric regulation of the ABL tyrosine kinase at the atomic level. Atomistic modeling of the ABL complexes with a panel of allosteric modulators has been performed using a combination of molecular dynamics simulations, structural residue perturbation scanning, and a novel community analysis of the residue interaction networks. Our results have indicated that allosteric inhibitors and activators may exert a differential control on allosteric signaling between the kinase binding sites and functional regions. While the inhibitor binding can strengthen the closed ABL state and induce allosteric communications directed from the allosteric pocket to the ATP binding site, the DPH activator may induce a more dynamic open form and activate allosteric couplings between the ATP and substrate binding sites. By leveraging a network-centric theoretical framework, we have introduced a novel community analysis method and global topological parameters that have unveiled the hierarchical modularity and the intercommunity bridging sites in the residue interaction network. We have found that allosteric functional hotspots responsible for the kinase regulation may serve the intermodular bridges in the global interaction network. The central conclusion from this analysis is that the regulatory switch centers play a fundamental role in the modular network organization of ABL as the unique intercommunity bridges that connect the SH2 and SH3 domains with the catalytic core into a functional kinase assembly. The hierarchy of network organization in the ABL regulatory complexes may allow for the synergistic action of dense intercommunity links required for the robust signal transfer in the catalytic core and sparse network bridges acting as the regulatory control points that orchestrate allosteric transitions between the inhibited and active kinase forms.

Reaching the End of the Line: Urinary Tract Infections

Urinary tract infections (UTIs) cause a substantial health care burden. UTIs (i) are most often caused by uropathogenic Escherichia coli (UPEC), (ii) primarily affect otherwise healthy females (50% of women will have a UTI), (iii) are associated with significant morbidity and economic impact, (iv) can become chronic, and (v) are highly recurrent. A history of UTI is a significant risk factor for a recurrent UTI (rUTI). In otherwise healthy women, an acute UTI leads to a 25 to 50% chance of rUTI within months of the initial infection. Interestingly, rUTIs are commonly caused by the same strain of E. coli that led to the initial infection, arguing that there exist host-associated reservoirs, like the gastrointestinal tract and underlying bladder tissue, that can seed rUTIs. Additionally, catheter-associated UTIs (CAUTI), caused by Enterococcus and Staphylococcus as well as UPEC, represent a major health care concern. The host's response of depositing fibrinogen at the site of infection has been found to be critical to establishing CAUTI. The Drug Resistance Index, an evaluation of antibiotic resistance, indicates that UTIs have become increasingly difficult to treat since the mid-2000s. Thus, UTIs are a "canary in the coal mine," warning of the possibility of a return to the preantibiotic era, where some common infections are untreatable with available antibiotics. Numerous alternative strategies for both the prevention and treatment of UTIs are being pursued, with a focus on the development of vaccines and small-molecule inhibitors targeting virulence factors, in the hopes of reducing the burden of urogenital tract infections in an antibiotic-sparing manner.

Self-organization, entropy and allostery

Allostery is a fundamental regulatory mechanism in biology. Although generally accepted that it is a dynamics-driven process, the exact molecular mechanism of allosteric signal transmission is hotly debated. We argue that allostery is as a part of a bigger picture that also includes fractal-like properties of protein interior, hierarchical protein folding and entropy-driven molecular recognition. Although so far all these phenomena were studied separately, they stem from the same common root: self-organization of polypeptide chains and, thus, has to be studied collectively. This merge will allow the cross-referencing of a broad spectrum of multi-disciplinary data facilitating progress in all these fields.

Stochastic Gating as a Novel Mechanism for Channel Selectivity

An ideal channel, responsible for metabolite fluxes in and out of the cells and cellular compartments, is supposed to be selective for a particular set of molecules only. However, such a channel has to be wide enough to accommodate relatively large metabolites, and, therefore, it allows passage of smaller solutes, for example, sodium, potassium, and chloride ions, thus compromising membrane's barrier function. Here we show that stochastic gating is able to provide a mechanism for the selectivity of wide channels in favor of large metabolites. Specifically, applying our recent theory of the stochastic gating effect on channel-facilitated transport, we demonstrate that under certain conditions gating hinders translocation of fast-diffusing small solutes to a significantly higher degree than that of large solutes that diffuse much slower. We hypothesize that this can be used by Nature to minimize the shunting effect of wide channels with respect to small solutes.

Structure-Activity Relationship in TLR4 Mutations: Atomistic Molecular Dynamics Simulations and Residue Interaction Network Analysis

Toll-like receptor 4 (TLR4), a vital innate immune receptor present on cell surfaces, initiates a signaling cascade during danger and bacterial intrusion. TLR4 needs to form a stable hexamer complex, which is necessary to dimerize the cytoplasmic domain. However, D299G and T399I polymorphism may abrogate the stability of the complex, leading to compromised TLR4 signaling. Crystallography provides valuable insights into the structural aspects of the TLR4 ectodomain; however, the dynamic behavior of polymorphic TLR4 is still unclear. Here, we employed molecular dynamics simulations (MDS), as well as principal component and residue network analyses, to decipher the structural aspects and signaling propagation associated with mutations in TLR4. The mutated complexes were less cohesive, displayed local and global variation in the secondary structure, and anomalous decay in rotational correlation function. Principal component analysis indicated that the mutated complexes also exhibited distinct low-frequency motions, which may be correlated to the differential behaviors of these TLR4 variants. Moreover, residue interaction networks (RIN) revealed that the mutated TLR4/myeloid differentiation factor (MD) 2 complex may perpetuate abnormal signaling pathways. Cumulatively, the MDS and RIN analyses elucidated the mutant-specific conformational alterations, which may help in deciphering the mechanism of loss-of-function mutations.

Effect of chaperone-adhesin complex on plug release by the PapC usher

The P pilus of uropathogenic Escherichia coli is a multisubunit fiber assembled at the outer membrane in a defined sequence by a chaperone/usher secretion system, comprising a periplasmic chaperone and a beta-barrel outer membrane protein, the PapC usher. To gain insight into the pilus biogenesis mechanism, we used patch clamp electrophysiology to investigate the effect of the initiating adhesin subunit, as it is delivered to PapC in a complex with the chaperone. We show that the chaperone-adhesin complex facilitates opening of the PapC pore and appears to engage within the PapC lumen, in agreement with prior biochemical and structural data.

Electrostatic networks control plug stabilization in the PapC usher

The PapC usher, a β-barrel pore in the outer membrane of uropathogenic Escherichia coli, is used for assembly of the P pilus, a key virulence factor in bacterial colonization of human kidney cells. Each PapC protein is composed of a 24-stranded β-barrel channel, flanked by N- and C-terminal globular domains protruding into the periplasm, and occluded by a plug domain (PD). The PD is displaced from the channel towards the periplasm during pilus biogenesis, but the molecular mechanism for PD displacement remains unclear. Two structural features within the β-barrel, an α-helix and β5-6 hairpin loop, may play roles in controlling plug stabilization. Here we have tested clusters of residues at the interface of the plug, barrel, α-helix and hairpin, which participate in electrostatic networks. To assess the roles of these residues in plug stabilization, we used patch-clamp electrophysiology to compare the activity of wild-type and mutant PapC channels containing alanine substitutions at these sites. Mutations interrupting each of two salt bridge networks were relatively ineffective in disrupting plug stabilization. However, mutation of two pairs of arginines located at the inner and the outer surfaces of the PD resulted in an enhanced propensity for plug displacement. One arginine pair involved in a repulsive interaction between the linkers that tether the plug to the β-barrel was particularly sensitive to mutation. These results suggest that plug displacement, which is necessary for pilus assembly and translocation, may require a weakening of key electrostatic interactions between the plug linkers, and the plug and the α-helix.

Computational approaches to detect allosteric pathways in transmembrane molecular machines

Many of the functions of transmembrane proteins involved in signal processing and transduction across the cell membrane are determined by allosteric couplings that propagate the functional effects well beyond the original site of activation. Data gathered from breakthroughs in biochemistry, crystallography, and single molecule fluorescence have established a rich basis of information for the study of molecular mechanisms in the allosteric couplings of such transmembrane proteins. The mechanistic details of these couplings, many of which have therapeutic implications, however, have only become accessible in synergy with molecular modeling and simulations. Here, we review some recent computational approaches that analyze allosteric coupling networks (ACNs) in transmembrane proteins, and in particular the recently developed Protein Interaction Analyzer (PIA) designed to study ACNs in the structural ensembles sampled by molecular dynamics simulations. The power of these computational approaches in interrogating the functional mechanisms of transmembrane proteins is illustrated with selected examples of recent experimental and computational studies pursued synergistically in the investigation of secondary active transporters and GPCRs. This article is part of a Special Issue entitled: Membrane Proteins edited by J.C. Gumbart and Sergei Noskov.

Lifting the lid on pilus assembly

A combination of computer simulations, evolutionary analysis and graph theory has provided new insights into the assembly of pili on the surface of bacteria.