Frameworks for understanding long-range intra-protein communication

Deciphering the structural consequences of R83 and R152 methylation on DNA polymerase β using molecular modeling

DNA polymerase β, a member of the X-family of DNA polymerases, undergoes complex regulations both in vitro and in vivo through various posttranslational modifications, including phosphorylation and methylation. The impact of these modifications varies depending on the specific amino acid undergoing alterations. In vitro, methylation of DNA polymerase β with the enzyme protein arginine methyltransferase 6 (PRMT6) at R83 and R152 enhances polymerase activity by improving DNA binding and processivity. Although these studies have shown that methylation improves DNA binding, the underlying mechanism of enhancement of polymerase activity in terms of structure and dynamics remains poorly understood. To address this gap, we modeled the methylated enzyme/DNA complex and conducted a microsecond-long simulation in the presence of Mg ions. Our results revealed significant structural changes induced by methylating both R83 and R152 sites in the enzyme. Specifically, these changes caused the DNA fragment to move closer to the C- and N-subdomains, forming additional hydrogen bonds. Furthermore, the cross-correlation map demonstrated that methylation enhanced long-range correlations within the domains/subdomains of DNA polymerase β, along with an increase in the linear mutual information value between the domains/subdomains and DNA fragments. The graph connectivity network also illustrated that methylation modulates the information pathway and identifies residues exhibiting long-distance coupling with the methylated sites. Our results provide an atomic-level understanding of the structural transition induced by methylation, shedding light on the mechanisms underlying the methylation-induced enhancement of activity in DNA polymerase β.

Investigation of serotonin-receptor interactions, stability and signal transduction pathways via molecular dynamics simulations

Serotonin-receptor binding plays a key role in several neurological and biological processes, including mood, sleep, hunger, cognition, learning, and memory. In this article, we performed molecular dynamics simulation to examine the key residues that play an essential role in the binding of serotonin to the G-protein-coupled 5-HT1B receptor (5HT1BR) via electrostatic interactions. Key residues for electrostatic interactions were identified via bond distance analysis and frustration analysis methods. An end-point free energy calculation method determines the stability of the 5-HT1BR due to serotonin binding. The single-point mutation of the polar/charged amino acid residues (Asp129, Thr134) on the binding sites and the calculation of binding free energy validate the quantitative contribution of these residues to the stability of the serotonin-receptor complex. The principal component analysis reflects that the serotonin-bound 5-HT1BR is more stabilized than the apo-receptor regarding dynamical changes. The difference dynamic cross-correlations map shows the correlation between the transmembranes and mini-Go, which indicates that the signal transduction happens between mini-Go and the receptor. Allosteric pathway analysis reveals the key nodes and key pathways for signal transduction in 5-HT1BR. These results provide useful insights into the study of signal transduction pathways and mutagenesis to regulate the binding and functionality of the complex. The developed protocols can be applied to study local non-covalent interactions and long-range allosteric communications in any protein-ligand system for computer-aided drug design.

Enzyme stabilisation due to incorporation of a fluorinated non-natural amino acid at the protein surface

We have previously engineered E. coli transketolase (TK) enzyme variants that accept new substrates such as aliphatic or aromatic aldehydes, and also with improved thermal stability. Irreversible aggregation is the primary mechanism of deactivation for TK in the buffers used for biocatalysis, and so we were interested in determining the extent to which this remains true in more complex media, crude cell lysates or even in vivo. Such understanding would better guide future protein engineering efforts. NMR offers a potential approach to probe protein structure changes, aggregation, and diffusion, and19F-labelled amino acids are a useful NMR probe for complex systems with little or no background signal from the rest of the protein or their environment. Here we labelled E. coli TK with two different19F probes, trifluoromethyl-L-phenylalanine (tfm-Phe), and 4-fluoro phenylalanine (4 F-Phe), through site specific non-natural amino acid incorporation. We targeted them to residue K316, a highly solvent exposed site located at the furthest point from the enzyme active sites. Characterisation of the19F-labelled TK variants revealed surprising effects of these mutations on stability, and to some extent on activity. While variant TK-tfm-Phe led to a 7.5 °C increase in the thermal transition midpoint (Tm) for denaturation, the TK-4 F-Phe variant largely abolished the aggregation of the enzyme when incubated at 50 °C19. F-NMR revealed different behaviours in response to temperature increases for the two TK variants, displaying opposite temperature gradient chemical shifts, and diverging motion regimes, suggesting that the mutations affected differently both the local environment at this site, and its temperature-induced dynamics. A similar incubation of TK at 40-55 °C is also known to induce higher cofactor-binding affinities, leading to an apparent heat activation under low cofactor concentration conditions. We have hypothesised previously that a heat-inducible conformational change in TK leads to this effect1. H-NMR revealed a temperature-dependent re-structuring of methyl groups, also at 30-50 °C, which may be linked to the heat activation. While our kinetic studies were not expected to observe the heat activation event due to the high cofactor concentrations used, this was not the case for TK-4 F-Phe, which did appear to heat activate slightly at 45 °C. This implied that the mutations at K316 could influence cofactor-binding, despite their location at 47 Å from either active site. Such long-distance effects of mutations are not unprecedented, and indeed we have previously shown how distant mutations can influence active-site loop stability and function in TK, mediated via dynamically coupled networks of residues. Molecular dynamics simulations of the two19F containing variants similarly revealed networks of residues that could couple the changes in dynamics at residue K316, through to changes in active site dynamics. These results independently highlight the sensitivity of active-site function to distant mutations coupled through correlated dynamic networks of residues. They also highlight the potential influence of surface-incorporated probes on protein stability and function, and the need to characterise them well prior to further studies.

G Protein Activation Occurs via a Largely Universal Mechanism

Understanding how signaling proteins like G proteins are allosterically activated is a long-standing challenge with significant biological and medical implications. Because it is difficult to directly observe such dynamic processes, much of our understanding is based on inferences from a limited number of static snapshots of relevant protein structures, mutagenesis data, and patterns of sequence conservation. Here, we use computer simulations to directly interrogate allosteric coupling in six G protein α-subunit isoforms covering all four G protein families. To analyze this data, we introduce automated methods for inferring allosteric networks from simulation data and assessing how allostery is conserved or diverged among related protein isoforms. We find that the allosteric networks in these six G protein α subunits are largely conserved and consist of two pathways, which we call pathway-I and pathway-II. This analysis predicts that pathway-I is generally dominant over pathway-II, which we experimentally corroborate by showing that mutations to pathway-I perturb nucleotide exchange more than mutations to pathway-II. In the future, insights into unique elements of each G protein family could inform the design of isoform-specific drugs. More broadly, our tools should also be useful for studying allostery in other proteins and assessing the extent to which this allostery is conserved in related proteins.

Structural Insights into Phosphorylation-Mediated Polymerase Function Loss for DNA Polymerase β Bound to Gapped DNA

DNA polymerase β is a member of the X-family of DNA polymerases, playing a critical role in the base excision repair (BER) pathway in mammalian cells by implementing the nucleotide gap-filling step. In vitro phosphorylation of DNA polymerase β with PKC on S44 causes loss in the enzyme's DNA polymerase activity but not single-strand DNA binding. Although these studies have shown that single-stranded DNA binding is not affected by phosphorylation, the structural basis behind the mechanism underlying phosphorylation-induced activity loss remains poorly understood. Previous modeling studies suggested phosphorylation of S44 was sufficient to induce structural changes that impact the enzyme's polymerase function. However, the S44 phosphorylated-enzyme/DNA complex has not been modeled so far. To address this knowledge gap, we conducted atomistic molecular dynamics simulations of pol β complexed with gapped DNA. Our simulations, which used explicit solvent and lasted for microseconds, revealed that phosphorylation at the S44 site, in the presence of Mg ions, induced significant conformational changes in the enzyme. Specifically, these changes led to the transformation of the enzyme from a closed to an open structure. Additionally, our simulations identified phosphorylation-induced allosteric coupling between the inter-domain region, suggesting the existence of a putative allosteric site. Taken together, our results provide a mechanistic understanding of the conformational transition observed due to phosphorylation in DNA polymerase β interactions with gapped DNA. Our simulations shed light on the mechanisms of phosphorylation-induced activity loss in DNA polymerase β and reveal potential targets for the development of novel therapeutics aimed at mitigating the effects of this post-translational modification.

The "violin model": Looking at community networks for dynamic allostery

Allosteric regulation of proteins continues to be an engaging research topic for the scientific community. Models describing allosteric communication have evolved from focusing on conformation-based descriptors of protein structural changes to appreciating the role of internal protein dynamics as a mediator of allostery. Here, we explain a "violin model" for allostery as a contemporary method for approaching the Cooper-Dryden model based on redistribution of protein thermal fluctuations. Based on graph theory, the violin model makes use of community network analysis to functionally cluster correlated protein motions obtained from molecular dynamics simulations. This Review provides the theory and workflow of the methodology and explains the application of violin model to unravel the workings of protein kinase A.

Binding and Functional Folding (BFF): A Physiological Framework for Studying Biomolecular Interactions and Allostery

EF-hand Ca2+-binding proteins (CBPs), such as S100 proteins (S100s) and calmodulin (CaM), are signaling proteins that undergo conformational changes upon increasing intracellular Ca2+. Upon binding Ca2+, S100 proteins and CaM interact with protein targets and induce important biological responses. The Ca2+-binding affinity of CaM and most S100s in the absence of target is weak (CaKD > 1 μM). However, upon effector protein binding, the Ca2+ affinity of these proteins increases via heterotropic allostery (CaKD < 1 μM). Because of the high number and micromolar concentrations of EF-hand CBPs in a cell, at any given time, allostery is required physiologically, allowing for (i) proper Ca2+ homeostasis and (ii) strict maintenance of Ca2+-signaling within a narrow dynamic range of free Ca2+ ion concentrations, [Ca2+]free. In this review, mechanisms of allostery are coalesced into an empirical "binding and functional folding (BFF)" physiological framework. At the molecular level, folding (F), binding and folding (BF), and BFF events include all atoms in the biomolecular complex under study. The BFF framework is introduced with two straightforward BFF types for proteins (type 1, concerted; type 2, stepwise) and considers how homologous and nonhomologous amino acid residues of CBPs and their effector protein(s) evolved to provide allosteric tightening of Ca2+ and simultaneously determine how specific and relatively promiscuous CBP-target complexes form as both are needed for proper cellular function.

Phosphorylation Induced Conformational Transitions in DNA Polymerase β

DNA polymerase β (pol β) is a member of the X- family of DNA polymerases that catalyze the distributive addition of nucleoside triphosphates during base excision DNA repair. Previous studies showed that the enzyme was phosphorylated in vitro with PKC at two serines (44 and 55), causing loss of DNA polymerase activity but not DNA binding. In this work, we have investigated the phosphorylation-induced conformational changes in DNA polymerase β in the presence of Mg ions. We report a comprehensive atomic resolution study of wild type and phosphorylated DNA polymerase using molecular dynamics (MD) simulations. The results are examined via novel methods of internal dynamics and energetics analysis to reveal the underlying mechanism of conformational transitions observed in DNA pol β. The results show drastic conformational changes in the structure of DNA polymerase β due to S44 phosphorylation. Phosphorylation-induced conformational changes transform the enzyme from a closed to an open structure. The dynamic cross-correlation shows that phosphorylation enhances the correlated motions between the different domains. Centrality network analysis reveals that the S44 phosphorylation causes structural rearrangements and modulates the information pathway between the Lyase domain and base pair binding domain. Further analysis of our simulations reveals that a critical hydrogen bond (between S44 and E335) disruption and the formation of three additional salt bridges are potential drivers of these conformational changes. In addition, we found that two of these additional salt bridges form in the presence of Mg ions on the active sites of the enzyme. These results agree with our previous study of DNA pol β S44 phosphorylation without Mg ions which predicted the deactivation of DNA pol β. However, the phase space of structural transitions induced by S44 phosphorylation is much richer in the presence of Mg ions.

Vanilloid-dependent TRPV1 opening trajectory from cryoEM ensemble analysis

Single particle cryo-EM often yields multiple protein conformations within a single dataset, but experimentally deducing the temporal relationship of these conformers within a conformational trajectory is not trivial. Here, we use thermal titration methods and cryo-EM in an attempt to obtain temporal resolution of the conformational trajectory of the vanilloid receptor TRPV1 with resiniferatoxin (RTx) bound. Based on our cryo-EM ensemble analysis, RTx binding to TRPV1 appears to induce intracellular gate opening first, followed by selectivity filter dilation, then pore loop rearrangement to reach the final open state. This apparent conformational wave likely arises from the concerted, stepwise, additive structural changes of TRPV1 over many subdomains. Greater understanding of the RTx-mediated long-range allostery of TRPV1 could help further the therapeutic potential of RTx, which is a promising drug candidate for pain relief associated with advanced cancer or knee arthritis.

Insights of conformational dynamics on catalytic activity in the computational stability design of Bacillus subtilis LipA

In protein engineering, the contributions of individual mutations to designed combinatorial mutants are unpredictable. Screening designed mutations that affect enzyme catalytic activity enables evolutions towards efficient activities. Here, Bacillus subtilis LipA (BSLA) was selected as a model protein for thermostabilization designs, and the circular dichroism measurements showed six combinatorial designs with improved stability (from 5.81 °C to 13.61 °C). Based on molecular dynamic simulations, the conformational dynamics of the mutants revealed that mutations alter the populations of conformational states and the increased ensembles of inactive conformations might lead to a reduction in activity. We further demonstrated that the mutations responsible for the reduced enzyme catalytic activity involved a short dynamic correlation path to disturbing the equilibrium conformation of active sites. By removing N82V, which had a close dynamic correlation to the active sites in mutant D3, the redesigned mutant RD3 had an increased activity of 57.6%. By combining computational simulation with experimental verification, this work established that essential sites to counteract the activity-stability trade-off in multipoint combinatorial mutants could be computationally predicted and thus provide a possible strategy by which to indirectly or directly guide protein design.

Enhanced thermal and alkaline stability of L-lysine decarboxylase CadA by combining directed evolution and computation-guided virtual screening

As an important monomer for bio-based nylons PA5X, cadaverine is mainly produced by enzymatic decarboxylation of L-lysine. A key issue with this process is the instability of L-lysine decarboxylase (CadA) during the reaction due to the dissociation of CadA subunits with the accumulation of alkaline cadaverine. In this work, we attempted to improve the thermal and alkaline stability of CadA by combining directed evolution and computation-guided virtual screening. Interestingly, site 477 residue located at the protein surface and not the decamer interface was found as a hotspot in directed evolution. By combinatorial mutagenesis of the positive mutations obtained by directed evolution and virtual screening with the previously reported T88S mutation, K477R/E445Q/T88S/F102V was generated as the best mutant, delivering 37% improvement of cadaverine yield at 50 ºC and pH 8.0. Molecular dynamics simulations suggested the improved rigidity of regional structures, increased number of salt bridges, and enhancement of hydrogen bonds at the multimeric interface as possible origins of the improved stability of the mutant. Using this four-point mutant, 160.7 g/L of cadaverine was produced from 2.0 M Lysine hydrochloride at 50 °C without pH regulation, with a conversion of 78.5%, whereas the wild type produced 143.7 g/L cadaverine, corresponding to 70% conversion. This work shows the combination of directed evolution and virtual screening as an efficient protein engineering strategy.

Investigating Conformational Dynamics and Allostery in the p53 DNA-Binding Domain Using Molecular Simulations

The p53 tumor suppressor is a multifaceted context-dependent protein, which is involved in multiple cellular pathways, with the ability to either keep the cells alive or to kill them through mechanisms such as apoptosis. To complicate this picture, cancer cells that express mutant p53 becomes addicted to the mutant activity, so that the mutant variant features a myriad of gain-of-function activities, opening different venues for therapy. This makes essential to think outside the box and apply new approaches to the study of p53 structure-(mis)function relationship to find new critical components of its pathway or to understand how known parts are interconnected, compete, or cooperate. In this context, I will here illustrate how to integrate different computational methods to the identification of possible allosteric effects transmitted from the DNA binding interface of p53 to regions for cofactor recruitment. The protocol can be extended to any other cases of study. Indeed, it does not necessarily apply only to the study of DNA-induced effects, but more broadly to the investigation of long-range effects induced by a biological partner that binds to a biomolecule of interest.

Dynamic networks observed in the nucleosome core particles couple the histone globular domains with DNA

The dynamics of eukaryotic nucleosomes are essential in gene activity and well regulated by various factors. Here, we elucidated the internal dynamics at multiple timescales for the human histones hH3 and hH4 in the Widom 601 nucleosome core particles (NCP), suggesting that four dynamic networks are formed by the residues exhibiting larger-scale μs-ms motions that extend from the NCP core to the histone tails and DNA. Furthermore, despite possessing highly conserved structural features, histones in the telomeric NCP exhibit enhanced μs-ms dynamics in the globular sites residing at the identified dynamic networks and in a neighboring region. In addition, higher mobility was observed for the N-terminal tails of hH3 and hH4 in the telomeric NCP. The results demonstrate the existence of dynamic networks in nucleosomes, through which the center of the core regions could interactively communicate with histone tails and DNA to potentially propagate epigenetic changes.

Shi et al. use solid-state nuclear magnetic resonance spectroscopy to reveal the internal dynamics of human histones hH3 and hH4 in the Widom 601 and the telomeric nucleosome core particles. This work has implications for the propagation of epigenetic changes via the center of the nucleosome core communicating with histone tails and DNA.

Fractional-Order Susceptible-Infected Model: Definition and Applications to the Study of COVID-19 Main Protease

We propose a model for the transmission of perturbations across the amino acids of a protein represented as an interaction network. The dynamics consists of a Susceptible-Infected (SI) model based on the Caputo fractional-order derivative. We find an upper bound to the analytical solution of this model which represents the worse-case scenario on the propagation of perturbations across a protein residue network. This upper bound is expressed in terms of Mittag-Leffler functions of the adjacency matrix of the network of inter-amino acids interactions. We then apply this model to the analysis of the propagation of perturbations produced by inhibitors of the main protease of SARS CoV-2. We find that the perturbations produced by strong inhibitors of the protease are propagated far away from the binding site, confirming the long-range nature of intra-protein communication. On the contrary, the weakest inhibitors only transmit their perturbations across a close environment around the binding site. These findings may help to the design of drug candidates against this new coronavirus.

Computation-aided engineering of starch-debranching pullulanase from Bacillus thermoleovorans for enhanced thermostability

Pullulanases are widely used in food, medicine, and other industries because they specifically hydrolyze α-1,6-glycosidic linkages in starch and oligosaccharides. In addition, high-temperature thermostable pullulanase has multiple advantages, including decreasing saccharification solution viscosity accompanied with enhanced mass transfer and reducing microbial contamination in starch hydrolysis. However, thermophilic pullulanase availability remains limited. Additionally, most do not meet starch-manufacturing requirements due to weak thermostability. Here, we developed a computation-aided strategy to engineer the thermophilic pullulanase from Bacillus thermoleovorans. First, three computational design predictors (FoldX, I-Mutant 3.0, and dDFIRE) were combined to predict stability changes introduced by mutations. After excluding conserved and catalytic sites, 17 mutants were identified. After further experimental verification, we confirmed six positive mutants. Among them, the G692M mutant had the highest thermostability improvement, with 3.8 °C increased T_m and 2.1-fold longer half-life than the wild type at 70 °C. We then characterized the mechanism underlying increased thermostability, such as rigidity enhancement, closer conformation, and strengthened motion correlation using root mean square fluctuation (RMSF), principal component analysis (PCA), dynamic cross-correlation map (DCCM), and free energy landscape (FEL) analysis. KEY POINTS: • A computation-aided strategy was developed to engineer pullulanase thermostability. • Seventeen mutants were identified by combining three computational design predictors. • The G692M mutant was obtained with increased T_mand half-life at 70 °C.

Rapid 3-dimensional shape determination of globular proteins by mobility capillary electrophoresis and native mass spectrometry

Established high-throughput proteomics methods provide limited information on the stereostructures of proteins. Traditional technologies for protein structure determination typically require laborious steps and cannot be performed in a high-throughput fashion. Here, we report a new medium throughput method by combining mobility capillary electrophoresis (MCE) and native mass spectrometry (MS) for the 3-dimensional (3D) shape determination of globular proteins in the liquid phase, which provides both the geometric structure and molecular mass information of proteins. A theory was established to correlate the ion hydrodynamic radius and charge state distribution in the native mass spectrum with protein geometrical parameters, through which a low-resolution structure (shape) of the protein could be determined. Our test data of 11 different globular proteins showed that this approach allows us to determine the shapes of individual proteins, protein complexes and proteins in a mixture, and to monitor protein conformational changes. Besides providing complementary protein structure information and having mixture analysis capability, this MCE and native MS based method is fast in speed and low in sample consumption, making it potentially applicable in top–down proteomics and structural biology for intact globular protein or protein complex analysis.

Using native mass spectrometry and mobility capillary electrophoresis, the ellipsoid dimensions of globular proteins or protein complexes could be measured efficiently.

The Pierced Lasso Topology Leptin has a Bolt on Dynamic Domain Composed by the Disordered Loops I and III

Leptin is an important signaling hormone, mostly known for its role in energy expenditure and satiety. Furthermore, leptin plays a major role in other proteinopathies, such as cancer, marked hyperphagia, impaired immune function, and inflammation. In spite of its biological relevance in human health, there are no NMR resonance assignments of the human protein available, obscuring high-resolution characterization of the soluble protein and/or its conformational dynamics, suggested as being important for receptor interaction and biological activity. Here, we report the nearly complete backbone resonance assignments of human leptin. Chemical shift-based secondary structure prediction confirms that in solution leptin forms a four-helix bundle including a pierced lasso topology. The conformational dynamics, determined on several timescales, show that leptin is monomeric, has a rigid four-helix scaffold, and a dynamic domain, including a transiently formed helix. The dynamic domain is anchored to the helical scaffold by a secondary hydrophobic core, pinning down the long loops of leptin to the protein body, inducing motional restriction without a well-defined secondary or tertiary hydrogen bond stabilized structure. This dynamic region is well suited for and may be involved in functional allosteric dynamics upon receptor binding.

Clustering of atomic displacement parameters in bovine trypsin reveals a distributed lattice of atoms with shared chemical properties

Low-frequency vibrations are crucial for protein structure and function, but only a few experimental techniques can shine light on them. The main challenge when addressing protein dynamics in the terahertz domain is the ubiquitous water that exhibit strong absorption. In this paper, we observe the protein atoms directly using X-ray crystallography in bovine trypsin at 100 K while irradiating the crystals with 0.5 THz radiation alternating on and off states. We observed that the anisotropy of atomic displacements increased upon terahertz irradiation. Atomic displacement similarities developed between chemically related atoms and between atoms of the catalytic machinery. This pattern likely arises from delocalized polar vibrational modes rather than delocalized elastic deformations or rigid-body displacements. The displacement correlation between these atoms were detected by a hierarchical clustering method, which can assist the analysis of other ultra-high resolution crystal structures. These experimental and analytical tools provide a detailed description of protein dynamics to complement the structural information from static diffraction experiments.

A Molecular Dynamics Approach to Explore the Intramolecular Signal Transduction of PPAR-α

Dynamics and functions of the peroxisome proliferator-activated receptor (PPAR)-α are modulated by the types of ligands that bind to the orthosteric sites. While several X-ray crystal structures of PPAR-α have been determined in their agonist-bound forms, detailed structural information in their apo and antagonist-bound states are still lacking. To address these limitations, we apply unbiased molecular dynamics simulations to three different PPAR-α systems to determine their modulatory mechanisms. Herein, we performed hydrogen bond and essential dynamics analyses to identify the important residues involved in polar interactions and conformational structural variations, respectively. Furthermore, betweenness centrality network analysis was carried out to identify key residues for intramolecular signaling. The differences observed in the intramolecular signal flow between apo, agonist- and antagonist-bound forms of PPAR-α will be useful for calculating maps of information flow and identifying key residues crucial for signal transductions. The predictions derived from our analysis will be of great help to medicinal chemists in the design of effective PPAR-α modulators and additionally in understanding their regulation and signal transductions.

Coupled molecular dynamics mediate long- and short-range epistasis between mutations that affect stability and aggregation kinetics

Multiple mutations are typically required to significantly improve protein stability or aggregation kinetics. However, when several substitutions are made in a single protein, the mutations can potentially interact in a nonadditive manner, resulting in epistatic effects, which can hamper protein-engineering strategies to improve thermostability or aggregation kinetics. Here, we have examined the role of protein dynamics in mediating epistasis between pairs of mutations. With Escherichia coli transketolase (TK) as a model, we explored the epistatic interactions between two single variants H192P and A282P, and also between the double-mutant H192P/A282P and two single variants, I365L or G506A. Epistasis was determined for several measures of protein stability, including the following: the free-energy barrier to kinetic inactivation, ∆∆G ^‡; thermal transition midpoint temperatures, T _m; and aggregation onset temperatures, T _agg Nonadditive epistasis was observed between neighboring mutations as expected, but also for distant mutations located in the surface and core regions of different domains. Surprisingly, the epistatic behaviors for each measure of stability were often different for any given pairwise recombination, highlighting that kinetic and thermodynamic stabilities do not always depend on the same structural features. Molecular-dynamics simulations and a pairwise cross-correlation analysis revealed that mutations influence the dynamics of their local environment, but also in some cases the dynamics of regions distant in the structure. This effect was found to mediate epistatic interactions between distant mutations and could therefore be exploited in future protein-engineering strategies.

Understanding G Protein-Coupled Receptor Allostery via Molecular Dynamics Simulations: Implications for Drug Discovery

Unraveling the mystery of protein allostery has been one of the greatest challenges in both structural and computational biology. However, recent advances in computational methods, particularly molecular dynamics (MD) simulations, have led to its utility as a powerful and popular tool for the study of protein allostery. By capturing the motions of a protein's constituent atoms, simulations can enable the discovery of allosteric hot spots and the determination of the mechanistic basis for allostery. These structural and dynamic studies can provide a foundation for a wide range of applications, including rational drug design and protein engineering. In our laboratory, the use of MD simulations and network analysis assisted in the elucidation of the allosteric hotspots and intracellular signal transduction of G protein-coupled receptors (GPCRs), primarily on one of the adenosine receptor subtypes, A_2A adenosine receptor (A_2AAR). In this chapter, we describe a method for calculating the map of allosteric signal flow in different GPCR conformational states and illustrate how these concepts have been utilized in understanding the mechanism of GPCR allostery. These structural studies will provide valuable insights into the allosteric and orthosteric modulations that would be of great help to design novel drugs targeting GPCRs in pathological states.

Quantifying Allosteric Communication via Both Concerted Structural Changes and Conformational Disorder with CARDS

Allosteric (i.e., long-range) communication within proteins is crucial for many biological processes, such as the activation of signaling cascades in response to specific stimuli. However, the physical basis for this communication remains unclear. Existing computational methods for identifying allostery focus on the role of concerted structural changes, but recent experimental work demonstrates that disorder is also an important factor. Here, we introduce the Correlation of All Rotameric and Dynamical States (CARDS) framework for quantifying correlations between both the structure and disorder of different regions of a protein. To quantify disorder, we draw inspiration from methods for quantifying "dynamic heterogeneity" from chemical physics to classify segments of a dihedral's time evolution as being in either ordered or disordered regimes. To demonstrate the utility of this approach, we apply CARDS to the Catabolite Activator Protein (CAP), a transcriptional activator that is regulated by Cyclic Adenosine MonoPhosphate (cAMP) binding. We find that CARDS captures allosteric communication between the two cAMP-Binding Domains (CBDs). Importantly, CARDS reveals that this coupling is dominated by disorder-mediated correlations, consistent with NMR experiments that establish allosteric coupling between the CBDs occurs without a concerted structural change. CARDS also recapitulates an enhanced role for disorder in the communication between the DNA-Binding Domains (DBDs) and CBDs in the S62F variant of CAP. Finally, we demonstrate that using CARDS to find communication hotspots identifies regions of CAP that are in allosteric communication without foreknowledge of their identities. Therefore, we expect CARDS to be of great utility for both understanding and predicting allostery.

Investigation of a Catenane with a Responsive Noncovalent Network: Mimicking Long-Range Responses in Proteins

We report a functional synthetic model for studying the noncovalent networks (NCNs) required for complex protein functions. The model [2]-catenane is self-assembled from dipeptide building blocks and contains an extensive network of hydrogen bonds and aromatic interactions. Perturbations to the catenane cause compensating changes in the NCNs structure and dynamics, resulting in long-distance changes reminiscent of a protein. Key findings include the notion that NCNs require regions of negative cooperativity, or "frustrated" noncovalent interactions, as a source of potential energy for driving the response. We refer to this potential energy as latent free energy and describe a mechanistic and energetic model for responsive systems.

Dynamically Coupled Residues within the SH2 Domain of FYN Are Key to Unlocking Its Activity

Src kinase activity is controlled by various mechanisms involving a coordinated movement of kinase and regulatory domains. Notwithstanding the extensive knowledge related to the backbone dynamics, little is known about the more subtle side-chain dynamics within the regulatory domains and their role in the activation process. Here, we show through experimental methyl dynamic results and predicted changes in side-chain conformational couplings that the SH2 structure of Fyn contains a dynamic network capable of propagating binding information. We reveal that binding the phosphorylated tail of Fyn perturbs a residue cluster near the linker connecting the SH2 and SH3 domains of Fyn, which is known to be relevant in the regulation of the activity of Fyn. Biochemical perturbation experiments validate that those residues are essential for inhibition of Fyn, leading to a gain of function upon mutation. These findings reveal how side-chain dynamics may facilitate the allosteric regulation of the different members of the Src kinase family.

Solution NMR Spectroscopy for the Study of Enzyme Allostery

Allostery is a ubiquitous biological regulatory process in which distant binding sites within a protein or enzyme are functionally and thermodynamically coupled. Allosteric interactions play essential roles in many enzymological mechanisms, often facilitating formation of enzyme-substrate complexes and/or product release. Thus, elucidating the forces that drive allostery is critical to understanding the complex transformations of biomolecules. Currently, a number of models exist to describe allosteric behavior, taking into account energetics as well as conformational rearrangements and fluctuations. In the following Review, we discuss the use of solution NMR techniques designed to probe allosteric mechanisms in enzymes. NMR spectroscopy is unequaled in its ability to detect structural and dynamical changes in biomolecules, and the case studies presented herein demonstrate the range of insights to be gained from this valuable method. We also provide a detailed technical discussion of several specialized NMR experiments that are ideally suited for the study of enzymatic allostery.

From Binding-Induced Dynamic Effects in SH3 Structures to Evolutionary Conserved Sectors

Src Homology 3 domains are ubiquitous small interaction modules known to act as docking sites and regulatory elements in a wide range of proteins. Prior experimental NMR work on the SH3 domain of Src showed that ligand binding induces long-range dynamic changes consistent with an induced fit mechanism. The identification of the residues that participate in this mechanism produces a chart that allows for the exploration of the regulatory role of such domains in the activity of the encompassing protein. Here we show that a computational approach focusing on the changes in side chain dynamics through ligand binding identifies equivalent long-range effects in the Src SH3 domain. Mutation of a subset of the predicted residues elicits long-range effects on the binding energetics, emphasizing the relevance of these positions in the definition of intramolecular cooperative networks of signal transduction in this domain. We find further support for this mechanism through the analysis of seven other publically available SH3 domain structures of which the sequences represent diverse SH3 classes. By comparing the eight predictions, we find that, in addition to a dynamic pathway that is relatively conserved throughout all SH3 domains, there are dynamic aspects specific to each domain and homologous subgroups. Our work shows for the first time from a structural perspective, which transduction mechanisms are common between a subset of closely related and distal SH3 domains, while at the same time highlighting the differences in signal transduction that make each family member unique. These results resolve the missing link between structural predictions of dynamic changes and the domain sectors recently identified for SH3 domains through sequence analysis.

Small protein domains as Src Homology 3 often act as docking sites and serve as regulatory elements. To understand their role in the regulation of a protein’s activity, one needs to understand how their backbone and sidechain dynamics are affected when binding to peptides. We have therefore computationally analyzed eight different SH3 domain structures, predicting dynamical effects induced by binding through our MCIT approach that has been shown to correlate well with experimental data. We show first that binding the Src SH3 domain triggers a particular cascade of dynamic effects, which are compatible with an induced fit mechanism reported before. We then combined the predictions for the eight SH3 domains into different consensus models, with the aim of analyzing, for the first time from a structural perspective, commonalities and differences in the transduction mechanisms among these SH3 domains. These consensus results are, on one hand, in agreement with the domain sectors recently identified for the entire family of SH3 domains. On the other hand, they reveal also that differences exist between the different subgroups that were studied here, requiring extensive experimental investigations of the importance of these differences for the proteins wherein these SH3 domains can be found.

Concurrent Increases and Decreases in Local Stability and Conformational Heterogeneity in Cu, Zn Superoxide Dismutase Variants Revealed by Temperature-Dependence of Amide Chemical Shifts

The chemical shifts of backbone amide protons in proteins are sensitive reporters of local structural stability and conformational heterogeneity, which can be determined from their readily measured linear and nonlinear temperature-dependences, respectively. Here we report analyses of amide proton temperature-dependences for native dimeric Cu, Zn superoxide dismutase (holo pWT SOD1) and structurally diverse mutant SOD1s associated with amyotrophic lateral sclerosis (ALS). Holo pWT SOD1 loses structure with temperature first at its periphery and, while having extremely high global stability, nevertheless exhibits extensive conformational heterogeneity, with ∼1 in 5 residues showing evidence for population of low energy alternative states. The holo G93A and E100G ALS mutants have moderately decreased global stability, whereas V148I is slightly stabilized. Comparison of the holo mutants as well as the marginally stable immature monomeric unmetalated and disulfide-reduced (apo(2SH)) pWT with holo pWT shows that changes in the local structural stability of individual amides vary greatly, with average changes corresponding to differences in global protein stability measured by differential scanning calorimetry. Mutants also exhibit altered conformational heterogeneity compared to pWT. Strikingly, substantial increases as well as decreases in local stability and conformational heterogeneity occur, in particular upon maturation and for G93A. Thus, the temperature-dependence of amide shifts for SOD1 variants is a rich source of information on the location and extent of perturbation of structure upon covalent changes and ligand binding. The implications for potential mechanisms of toxic misfolding of SOD1 in disease and for general aspects of protein energetics, including entropy-enthalpy compensation, are discussed.

Single molecule compression reveals intra-protein forces drive cytotoxin pore formation

Perfringolysin O (PFO) is a prototypical member of a large family of pore-forming proteins that undergo a significant reduction in height during the transition from the membrane-assembled prepore to the membrane-inserted pore. Here, we show that targeted application of compressive forces can catalyze this conformational change in individual PFO complexes trapped at the prepore stage, recapitulating this critical step of the spontaneous process. The free energy landscape determined from these measurements is in good agreement with that obtained from molecular dynamics simulations showing that an equivalent internal force is generated by the interaction of the exposed hydrophobic residues with the membrane. This hydrophobic force is transmitted across the entire structure to produce a compressive stress across a distant, otherwise stable domain, catalyzing its transition from an extended to compact conformation. Single molecule compression is likely to become an important tool to investigate conformational transitions in membrane proteins.

DOI:http://dx.doi.org/10.7554/eLife.08421.001

Proteins are made up of chains of amino acids that need to fold into intricate three-dimensional shapes to work correctly. But some proteins also have to change their shape drastically when they work. Mechanical forces that change the shape of a protein can therefore be used to determine how a protein folds and how it changes its structure when working.

Although researchers have developed techniques to analyze the effect of force on single proteins, most studies carried out so far have investigated the effect of stretching (or tensile forces) to understand structural changes that naturally involve an extension within the protein. However, many proteins undergo structural changes that involve a compaction in their shape. How these changes occur remains poorly understood because, for these, methods to apply compressive forces to single proteins are required.

Perfringolysin O (PFO for short) is a protein that is made by a bacterium that causes food poisoning in humans. PFO makes pores in the membrane that surrounds cells. This causes the cell’s contents to leak out, killing the cell. When inserting into the membrane, PFO changes from an elongated “prepore” state to a compact pore-forming state.

Czajkowsky et al. now use a combination of single molecule techniques and computer simulations to investigate how PFO undergoes this compaction. Previous work had identified a mutant PFO protein that arrests at the prepore state. Applying a compressive force to the top of this prepore-trapped PFO as it sits on the membrane transmitted forces across the entire PFO protein. This ultimately produced a compressive force across a distant part of the protein that caused the protein to change from the elongated prepore state to the compact, pore-like shape. If a compressive force was not applied, the PFO protein remained in the prepore state. Czajkowsky et al. further found that this compressive force is naturally produced by distant water-repellent parts of the naturally occurring protein interacting with the cell membrane. Therefore, internal forces can transmit across proteins to drive shape changes in distant regions.

In the future, the methods developed in this study could be applied to analyze other naturally occurring changes in proteins where shape compaction happens when working.

DOI:http://dx.doi.org/10.7554/eLife.08421.002

Integrating atomistic molecular dynamics simulations, experiments, and network analysis to study protein dynamics: strength in unity

In the last years, we have been observing remarkable improvements in the field of protein dynamics. Indeed, we can now study protein dynamics in atomistic details over several timescales with a rich portfolio of experimental and computational techniques. On one side, this provides us with the possibility to validate simulation methods and physical models against a broad range of experimental observables. On the other side, it also allows a complementary and comprehensive view on protein structure and dynamics. What is needed now is a better understanding of the link between the dynamic properties that we observe and the functional properties of these important cellular machines. To make progresses in this direction, we need to improve the physical models used to describe proteins and solvent in molecular dynamics, as well as to strengthen the integration of experiments and simulations to overcome their own limitations. Moreover, now that we have the means to study protein dynamics in great details, we need new tools to understand the information embedded in the protein ensembles and in their dynamic signature. With this aim in mind, we should enrich the current tools for analysis of biomolecular simulations with attention to the effects that can be propagated over long distances and are often associated to important biological functions. In this context, approaches inspired by network analysis can make an important contribution to the analysis of molecular dynamics simulations.

The Tipper-Strominger Hypothesis and Triggering of Allostery in Penicillin-Binding Protein 2a of Methicillin-Resistant Staphylococcus aureus (MRSA)

The transpeptidases involved in the synthesis of the bacterial cell wall (also known as penicillin-binding proteins, PBPs) have evolved to bind the acyl-D-Ala-D-Ala segment of the stem peptide of the nascent peptidoglycan for the physiologically important cross-linking of the cell wall. The Tipper-Strominger hypothesis stipulates that β-lactam antibiotics mimic the acyl-D-Ala-D-Ala moiety of the stem and, thus, are recognized by the PBPs with bactericidal consequences. We document that this mimicry exists also at the allosteric site of PBP2a of methicillin-resistant Staphylococcus aureus (MRSA). Interactions of different classes of β-lactam antibiotics, as mimics of the acyl-D-Ala-D-Ala moiety at the allosteric site, lead to a conformational change, across a distance of 60 Å to the active site. We directly visualize this change using an environmentally sensitive fluorescent probe affixed to the protein loops that frame the active site. This conformational mobility, documented in real time, allows antibiotic access to the active site of PBP2a. Furthermore, we document that this allosteric trigger enables synergy between two different β-lactam antibiotics, wherein occupancy at the allosteric site by one facilitates occupancy by a second at the transpeptidase catalytic site, thus lowering the minimal-inhibitory concentration. This synergy has important implications for the mitigation of facile emergence of resistance to these antibiotics by MRSA.

Principles of allosteric interactions in cell signaling

Linking cell signaling events to the fundamental physicochemical basis of the conformational behavior of single molecules and ultimately to cellular function is a key challenge facing the life sciences. Here we outline the emerging principles of allosteric interactions in cell signaling, with emphasis on the following points. (1) Allosteric efficacy is not a function of the chemical composition of the allosteric pocket but reflects the extent of the population shift between the inactive and active states. That is, the allosteric effect is determined by the extent of preferred binding, not by the overall binding affinity. (2) Coupling between the allosteric and active sites does not decide the allosteric effect; however, it does define the propagation pathways, the allosteric binding sites, and key on-path residues. (3) Atoms of allosteric effectors can act as "driver" or "anchor" and create attractive "pulling" or repulsive "pushing" interactions. Deciphering, quantifying, and integrating the multiple co-occurring events present daunting challenges to our scientific community.

The ensemble nature of allostery

Allostery is the process by which biological macromolecules (mostly proteins) transmit the effect of binding at one site to another, often distal, functional site, allowing for regulation of activity. Recent experimental observations demonstrating that allostery can be facilitated by dynamic and intrinsically disordered proteins have resulted in a new paradigm for understanding allosteric mechanisms, which focuses on the conformational ensemble and the statistical nature of the interactions responsible for the transmission of information. Analysis of allosteric ensembles reveals a rich spectrum of regulatory strategies, as well as a framework to unify the description of allosteric mechanisms from different systems.

Multiple conformational selection and induced fit events take place in allosteric propagation

The fact that we observe a single conformational selection event during binding does not necessarily mean that only a single conformational selection event takes place, even though this is the common assumption. Here we suggest that conformational selection takes place not once in a given binding/allosteric event, but at every step along the allosteric pathway. This view generalizes conformational selection and makes it applicable also to other allosteric events, such as post-translational modifications (PTMs) and photon absorption. Similar to binding, at each step along a propagation pathway, conformational selection is coupled with induced fit which optimizes the interactions. Thus, as in binding, the allosteric effects induced by PTMs and light relate not only to population shift; but to conformational selection as well. Conformational selection and population shift take place conjointly.

Allosteric conformational barcodes direct signaling in the cell

The cellular network is highly interconnected. Pathways merge and diverge. They proceed through shared proteins and may change directions. How are cellular pathways controlled and their directions decided, coded, and read? These questions become particularly acute when we consider that a small number of pathways, such as signaling pathways that regulate cell fates, cell proliferation, and cell death in development, are extensively exploited. This review focuses on these signaling questions from the structural standpoint and discusses the literature in this light. All co-occurring allosteric events (including posttranslational modifications, pathogen binding, and gain-of-function mutations) collectively tag the protein functional site with a unique barcode. The barcode shape is read by an interacting molecule, which transmits the signal. A conformational barcode provides an intracellular address label, which selectively favors binding to one partner and quenches binding to others, and, in this way, determines the pathway direction, and, eventually, the cell's response and fate.

The spatial structure of cell signaling systems

The spatial structure of the cell is highly organized at all levels: from small complexes and assemblies, to local nano- and microclusters, to global, micrometer scales across and between cells. We suggest that this multiscale spatial cell organization also organizes signaling and coordinates cellular behavior. We propose a new view of the spatial structure of cell signaling systems. This new view describes cell signaling in terms of dynamic allosteric interactions within and among distinct, spatially organized transient clusters. The clusters vary over time and space and are on length scales from nanometers to micrometers. When considered across these length scales, primary factors in the spatial organization are cell membrane domains and the actin cytoskeleton, both also highly dynamic. A key challenge is to understand the interplay across these multiple scales, link it to the physicochemical basis of the conformational behavior of single molecules and ultimately relate it to cellular function. Overall, our premise is that at these scales, cell signaling should be thought of not primarily as a sequence of diffusion-controlled molecular collisions, but instead transient, allostery-driven cluster re-forming interactions.

A mechanism for localized dynamics-driven affinity regulation of the binding of von Willebrand factor to platelet glycoprotein Ibα

Binding of the A1 domain of von Willebrand factor (vWF) to glycoprotein Ibα (GPIbα) results in platelet adhesion, activation, and aggregation that initiates primary hemostasis. Both the elevated shear stress and the mutations associated with type 2B von Willebrand disease enhance the interaction between A1 and GPIbα. Through molecular dynamics simulations for wild-type vWF-A1 and its eight gain of function mutants (R543Q, I546V, ΔSS, etc.), we found that the gain of function mutations destabilize the N-terminal arm, increase a clock pendulum-like movement of the α2-helix, and turn a closed A1 conformation into a partially open one favoring binding to GPIbα. The residue Arg(578) at the α2-helix behaves as a pivot in the destabilization of the N-terminal arm and a consequent dynamic change of the α2-helix. These results suggest a localized dynamics-driven affinity regulation mechanism for vWF-GPIbα interaction. Allosteric drugs controlling this intrinsic protein dynamics may be effective in blocking the GPIb-vWF interaction.

Allostery in disease and in drug discovery

Allostery is largely associated with conformational and functional transitions in individual proteins. This concept can be extended to consider the impact of conformational perturbations on cellular function and disease states. Here, we clarify the concept of allostery and how it controls physiological activities. We focus on the challenging questions of how allostery can both cause disease and contribute to development of new therapeutics. We aim to increase the awareness of the linkage between disease symptoms on the cellular level and specific aberrant allosteric actions on the molecular level and to emphasize the potential of allosteric drugs in innovative therapies.

Structural and energetic basis of allostery

Allostery is a biological phenomenon of fundamental importance in regulation and signaling, and efforts to understand this process have led to the development of numerous models. In spite of individual successes in understanding the structural determinants of allostery in well-documented systems, much less success has been achieved in identifying a set of quantitative and transferable ground rules that provide an understanding of how allostery works. Are there organizing principles that allow us to relate structurally different proteins, or are the determinants of allostery unique to each system? Using an ensemble-based model, we show that allosteric phenomena can be formulated in terms of conformational free energies of the cooperative elements in a protein and the coupling interactions between them. Interestingly, the resulting allosteric ground rules provide a framework to reconcile observations that challenge purely structural models of site-to-site coupling, including (a) allostery in the absence of pathways of structural distortions, (b) allostery in the absence of any structural change, and (c) the ability of allosteric ligands to act as agonists under some circumstances and antagonists under others. The ensemble view of allostery that emerges provides insights into the energetic prerequisites of site-to-site coupling and thus into how allostery works.

The underappreciated role of allostery in the cellular network

Allosteric propagation results in communication between distinct sites in the protein structure; it also encodes specific effects on cellular pathways, and in this way it shapes cellular response. One example of long-range effects is binding of morphogens to cell surface receptors, which initiates a cascade of protein interactions that leads to genome activation and specific cellular action. Allosteric propagation results from combinations of multiple factors, takes place through dynamic shifts of conformational ensembles, and affects the equilibria of macromolecular interactions. Here, we (a) emphasize the well-known yet still underappreciated role of allostery in conveying explicit signals across large multimolecular assemblies and distances to specify cellular action; (b) stress the need for quantitation of the allosteric effects; and finally, (c) propose that each specific combination of allosteric effectors along the pathway spells a distinct function. The challenges are colossal; the inspiring reward will be predicting function, misfunction, and outcomes of drug regimes.

Phosphatidylserine-induced factor Xa dimerization and binding to factor Va are competing processes in solution

A soluble, short chain phosphatidylserine, 1,2-dicaproyl-sn-glycero-3-phospho-l-serine (C6PS), binds to discrete sites on FXa, FVa, and prothrombin to alter their conformations, to promote FXa dimerization (K(d) ~ 14 nM), and to enhance both the catalytic activity of FXa and the cofactor activity of FVa. In the presence of calcium, C6PS binds to two sites on FXa, one in the epidermal growth factor-like (EGF) domain and one in the catalytic domain; the latter interaction is sensitive to Na(+) binding and probably represents a protein recognition site. Here we ask whether dimerization of FXa and its binding to FVa in the presence of C6PS are competitive processes. We monitored FXa activity at 5, 20, and 50 nM FXa while titrating with FVa in the presence of 400 μM C6PS and 3 or 5 mM Ca(2+) to show that the apparent K(d) of FVa-FXa interaction increased with an increase in FXa concentration at 5 mM Ca(2+), but the K(d) was only slightly affected at 3 mM Ca(2+). A mixture of 50 nM FXa and 50 nM FVa in the presence of 400 μM C6PS yielded both Xa homodimers and Xa·Va heterodimers, but no FXa dimers bound to FVa. A mutant FXa (R165A) that has reduced prothrombinase activity showed both weakened dimerization (K(d) ~ 147 nM) and weakened FVa binding (apparent K(d) values of 58, 92, and 128 nM for 5, 20, and 50 nM R165A FXa, respectively). Native gel electrophoresis showed that the GLA-EGF(NC) fragment of FXa (lacking the catalytic domain) neither dimerized nor formed a complex with FVa in the presence of 400 μM C6PS and 5 mM Ca(2+). Our results demonstrate that the dimerization site and FVa-binding site are both located in the catalytic domain of FXa and that these sites are linked thermodynamically.

Accurate prediction of the dynamical changes within the second PDZ domain of PTP1e

Experimental NMR relaxation studies have shown that peptide binding induces dynamical changes at the side-chain level throughout the second PDZ domain of PTP1e, identifying as such the collection of residues involved in long-range communication. Even though different computational approaches have identified subsets of residues that were qualitatively comparable, no quantitative analysis of the accuracy of these predictions was thus far determined. Here, we show that our information theoretical method produces quantitatively better results with respect to the experimental data than some of these earlier methods. Moreover, it provides a global network perspective on the effect experienced by the different residues involved in the process. We also show that these predictions are consistent within both the human and mouse variants of this domain. Together, these results improve the understanding of intra-protein communication and allostery in PDZ domains, underlining at the same time the necessity of producing similar data sets for further validation of thses kinds of methods.

Intra-protein communication has recently attracted an increasing interest from the scientific community, because of its important functional consequences: allostery and signalling. Unravelling how information is processed and transferred within a protein structure requires the study of the dynamical effects of, for instance, binding events, which may be captured experimentally by NMR relaxation experiments. Given the complexity of this experimental analysis, computational approaches, often based on molecular dynamics simulations, have been proposed for predicting these dynamical effects, using protein structural information as input. We examine here the accuracy of these predictors in the context of a well-studied domain, i.e. the second PSD95/Disc-large/ZO-1 domain (or PDZ domain) of PTP1e, and compare it to our approach that combines Monte-Carlo sampling of the conformational space of the side-chains and an information theoretical analysis. The results we discuss in this manuscript show clearly that the latter method provides very accurate predictions when compared to the experimental results, and has a better predictive quality compared to other computational approaches. The predictions, which are consistent between closely related structures, and the global network perspective provided by this approach, improve our understanding of intra-protein communication and allostery in these domains.

Convergent transmission of RNAi guide-target mismatch information across Argonaute internal allosteric network

In RNA interference, a guide strand derived from a short dsRNA such as a microRNA (miRNA) is loaded into Argonaute, the central protein in the RNA Induced Silencing Complex (RISC) that silences messenger RNAs on a sequence-specific basis. The positions of any mismatched base pairs in an miRNA determine which Argonaute subtype is used. Subsequently, the Argonaute-guide complex binds and silences complementary target mRNAs; certain Argonautes cleave the target. Mismatches between guide strand and the target mRNA decrease cleavage efficiency. Thus, loading and silencing both require that signals about the presence of a mismatched base pair are communicated from the mismatch site to effector sites. These effector sites include the active site, to prevent target cleavage; the binding groove, to modify nucleic acid binding affinity; and surface allosteric sites, to control recruitment of additional proteins to form the RISC. To examine how such signals may be propagated, we analyzed the network of internal allosteric pathways in Argonaute exhibited through correlations of residue-residue interactions. The emerging network can be described as a set of pathways emanating from the core of the protein near the active site, distributed into the bulk of the protein, and converging upon a distributed cluster of surface residues. Nucleotides in the guide strand "seed region" have a stronger relationship with the protein than other nucleotides, concordant with their importance in sequence selectivity. Finally, any of several seed region guide-target mismatches cause certain Argonaute residues to have modified correlations with the rest of the protein. This arises from the aggregation of relatively small interaction correlation changes distributed across a large subset of residues. These residues are in effector sites: the active site, binding groove, and surface, implying that direct functional consequences of guide-target mismatches are mediated through the cumulative effects of a large number of internal allosteric pathways.

Local motifs in proteins combine to generate global functional moves

Literature on the topological properties of folded proteins that has emerged as a field in its own right in the past decade is reviewed. Physics-based construction of coarse-grained models of proteins from knowledge of all-atom coordinates of the average structure is discussed. Once network is thus obtained with the node and link information, local motifs provide plethora of information on protein function. The hierarchical structure of the proteins manifested in the interrelations of local motifs is emphasized. Motifs are also related to modularity of the structure, and they quantify shifts in the landscapes upon conformational changes induced by, e.g. ligand binding. Redundancy emerges as a balance between local and global network descriptors and is related to the collectivity of the protein motions. Introducing weight on links followed by sequential removal of least cohesive contacts allows interactions in proteins to be represented as the superposition of essential and redundant sets. Lack of the former makes the network non-functional, while the latter ensures robust functioning under a wide range of perturbation scenarios.

Allosteric inhibition of individual enzyme molecules trapped in lipid vesicles

Enzymatic inhibition by product molecules is an important and widespread phenomenon. We describe an approach to study product inhibition at the single-molecule level. Individual HRP molecules are trapped within surface-tethered lipid vesicles, and their reaction with a fluorogenic substrate is probed. While the substrate readily penetrates into the vesicles, the charged product (resorufin) gets trapped and accumulates inside the vesicles. Surprisingly, individual enzyme molecules are found to stall when a few tens of product molecules accumulate. Bulk enzymology experiments verify that the enzyme is noncompetitively inhibited by resorufin. The initial reaction velocity of individual enzyme molecules and the number of product molecules required for their complete inhibition are broadly distributed and dynamically disordered. The two seemingly unrelated parameters, however, are found to be substantially correlated with each other in each enzyme molecule and over long times. These results suggest that, as a way to counter disorder, enzymes have evolved the means to correlate fluctuations at structurally distinct functional sites.

Network-based models as tools hinting at nonevident protein functionality

Network-based models of proteins are popular tools employed to determine dynamic features related to the folded structure. They encompass all topological and geometric computational approaches idealizing proteins as directly interacting nodes. Topology makes use of neighborhood information of residues, and geometry includes relative placement of neighbors. Coarse-grained approaches efficiently predict alternative conformations because of inherent collectivity in the protein structure. Such collectivity is moderated by topological characteristics that also tune neighborhood structure: That rich residues have richer neighbors secures robustness toward random loss of interactions/nodes due to environmental fluctuations/mutations. Geometry conveys the additional information of force balance to network models, establishing the local shape of the energy landscape. Here, residue and/or bond perturbations are critically evaluated to suggest new experiments, as network-based computational techniques prove useful in capturing domain movements and conformational shifts resulting from environmental alterations. Evolutionarily conserved residues are optimally connected, defining a subnetwork that may be utilized for further coarsening.