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The amount of water-accessible-surface-area, WASA, buried upon protein–protein association is a good measure of the non-covalent complex stability in water; however, the dependence of the binding Gibbs free energy change upon buried WASA proves to be not trivial. We assign a precise physicochemical role to buried WASA in the thermodynamics of non-covalent association and perform close scrutiny of the contributions favoring and those contrasting protein–protein association. The analysis indicates that the decrease in solvent-excluded volume, an entropic effect, described by means of buried WASA, is the molecular driving force of non-covalent association in water.

The amount of water-accessible-surface-area, WASA, buried upon protein–protein association is a good measure of the non-covalent complex stability in water; however, the dependence of the binding Gibbs free energy change upon buried WASA proves to be not trivial. We assign a precise physicochemical role to buried WASA in the thermodynamics of non-covalent association and perform close scrutiny of the contributions favoring and those contrasting protein–protein association. The analysis indicates that the decrease in solvent-excluded volume, an entropic effect, described by means of buried WASA, is the molecular driving force of non-covalent association in water. [ABSTRACT FROM AUTHOR]

Considerable electric fields are present within living cells, and the role of bioelectricity has been well established at the organismal level. Yet much remains to be learned about electric-field effects on protein function. Here, we use phototriggered charge injection from a site-specifically attached ruthenium photosensitizer to directly demonstrate the effect of dynamic charge redistribution within a protein. We find that binding of an antibody to phosphoglycerate kinase (PGK) is increased twofold under illumination. Remarkably, illumination is found to suppress the enzymatic activity of PGK by a factor as large as three. These responses are sensitive to the photosensitizer position on the protein. Surprisingly, left (but not right) circularly polarized light elicits these responses, indicating that the electrons involved in the observed dynamics are spin polarized, due to spin filtration by protein chiral structures. Our results directly establish the contribution of electrical polarization as an allosteric signal within proteins. Future experiments with phototriggered charge injection will allow delineation of charge rearrangement pathways within proteins and will further depict their effects on protein function. [ABSTRACT FROM AUTHOR]

Abstract Background Proteins form various complexes to carry out their versatile functions in cells. The dynamic properties of protein complex formation are mainly characterized by the association rates which measures how fast these complexes can be formed. It was experimentally observed that the association rates span an extremely wide range with over ten orders of magnitudes. Identification of association rates within this spectrum for specific protein complexes is therefore essential for us to understand their functional roles. Results To tackle this problem, we integrate physics-based coarse-grained simulations into a neural-network-based classification model to estimate the range of association rates for protein complexes in a large-scale benchmark set. The cross-validation results show that, when an optimal threshold was selected, we can reach the best performance with specificity, precision, sensitivity and overall accuracy all higher than 70%. The quality of our cross-validation data has also been testified by further statistical analysis. Additionally, given an independent testing set, we can successfully predict the group of association rates for eight protein complexes out of ten. Finally, the analysis of failed cases suggests the future implementation of conformational dynamics into simulation can further improve model. Conclusions In summary, this study demonstrated that a new modeling framework that combines biophysical simulations with bioinformatics approaches is able to identify protein–protein interactions with low association rates from those with higher association rates. This method thereby can serve as a useful addition to a collection of existing experimental approaches that measure biomolecular recognition.

Background: Proteins form various complexes to carry out their versatile functions in cells. The dynamic properties of protein complex formation are mainly characterized by the association rates which measures how fast these complexes can be formed. It was experimentally observed that the association rates span an extremely wide range with over ten orders of magnitudes. Identification of association rates within this spectrum for specific protein complexes is therefore essential for us to understand their functional roles. Results: To tackle this problem, we integrate physics-based coarse-grained simulations into a neural-network-based classification model to estimate the range of association rates for protein complexes in a large-scale benchmark set. The cross-validation results show that, when an optimal threshold was selected, we can reach the best performance with specificity, precision, sensitivity and overall accuracy all higher than 70%. The quality of our cross-validation data has also been testified by further statistical analysis. Additionally, given an independent testing set, we can successfully predict the group of association rates for eight protein complexes out of ten. Finally, the analysis of failed cases suggests the future implementation of conformational dynamics into simulation can further improve model. Conclusions: In summary, this study demonstrated that a new modeling framework that combines biophysical simulations with bioinformatics approaches is able to identify protein–protein interactions with low association rates from those with higher association rates. This method thereby can serve as a useful addition to a collection of existing experimental approaches that measure biomolecular recognition. [ABSTRACT FROM AUTHOR]

Despite the biological importance of protein-protein complexes, determining their structures and association mechanisms remains an outstanding challenge. Here, we report the results of atomiclevel simulations in which we observed five protein-protein pairs repeatedly associate to, and dissociate from, their experimentally determined native complexes using a molecular dynamics (MD)-based sampling approach that does not make use of any prior structural information about the complexes. To study association mechanisms, we performed additional, conventional MD simulations, in which we observed numerous spontaneous association events. A shared feature of native association for these five structurally and functionally diverse protein systems was that if the proteins made contact far from the native interface, the native state was reached by dissociation and eventual reassociation near the native interface, rather than by extensive interfacial exploration while the proteins remained in contact. At the transition state (the conformational ensemble from which association to the native complex and dissociation are equally likely), the protein-protein interfaces were still highly hydrated, and no more than 20% of native contacts had formed. [ABSTRACT FROM AUTHOR]

The formation of functionally versatile protein complexes underlies almost every biological process. The estimation of how fast these complexes can be formed has broad implications for unravelling the mechanism of biomolecular recognition. This kinetic property is traditionally quantified by association rates, which can be measured through various experimental techniques. To complement these time-consuming and labor-intensive approaches, we developed a coarse-grained simulation approach to study the physical processes of protein–protein association. We systematically calibrated our simulation method against a large-scale benchmark set. By combining a physics-based force field with a statistically-derived potential in the simulation, we found that the association rates of more than 80% of protein complexes can be correctly predicted within one order of magnitude relative to their experimental measurements. We further showed that a mixture of force fields derived from complementary sources was able to describe the process of protein–protein association with mechanistic details. For instance, we show that association of a protein complex contains multiple steps in which proteins continuously search their local binding orientations and form non-native-like intermediates through repeated dissociation and re-association. Moreover, with an ensemble of loosely bound encounter complexes observed around their native conformation, we suggest that the transition states of protein–protein association could be highly diverse on the structural level. Our study also supports the idea in which the association of a protein complex is driven by a “funnel-like” energy landscape. In summary, these results shed light on our understanding of how protein–protein recognition is kinetically modulated, and our coarse-grained simulation approach can serve as a useful addition to the existing experimental approaches that measure protein–protein association rates.

The hyperactivity of the cyclic dependent kinase 5 (CDK5) induced by the activator protein p25 has been linked to a number of pathologies of the brain. The CDK5-p25 complex has thus emerged as a major therapeutic target for Alzheimer's disease (AD) and other neurodegenerative conditions. Experiments have shown that the peptide p5 reduces the CDK5-p25 activity without affecting the endogenous CDK5-p35 activity, whereas the peptide TFP5, obtained from p5, elicits similar inhibition, crosses the blood-brain barrier, and exhibits behavioral rescue of AD mice models with no toxic side effects. The molecular basis of the kinase inhibition is not currently known, and is here investigated by computer simulations. It is shown that p5 binds the kinase at the same CDK5/p25 and CDK5/p35 interfaces, and is thus a non-selective competitor of both activators, in agreement with available experimental data in vitro. Binding of p5 is enthalpically driven with an affinity estimated in the low µM range. A quantitative description of the binding site and pharmacophore is presented, and options are discussed to increase the binding affinity and selectivity in the design of drug-like compounds against AD. [ABSTRACT FROM AUTHOR]

Many cellular proteins are bound to the surfaces of membranes and participate in various cell signaling responses. Interactions between this group of proteins are in part controlled by the membrane surface to which the proteins are bound. This review focuses on the effects of pressure on membrane-associated proteins. Initially, the effect of pressure on membrane surfaces and how pressure may perturb the membrane binding of proteins is discussed. Next, the effect of pressure on the activity and lateral association of proteins is considered. We then discuss how pressure can be used to gain insight into these types of proteins.

ABSTRACT Understanding factors that drive protein-protein association is of fundamental importance. We show that a single geometric parameter in crystal structures of protein-protein complexes, the angle between the electric dipole of one subunit and the partner-generated electric field at the same subunit, linearly correlates with experimentally determined protein-protein association rates. Imprint of a dynamic kinetic process in a single static geometric parameter, associated with mutual electrostatic orientation of subunits in protein-protein complexes, is elegant and demonstrates the universality of electrostatic steering in attenuating protein-protein association rates. That the essence of a complex phenomenon could be captured by properties of the final crystal structure of the complex implies that the electrostatic orientations of protein subunits in crystal structures and the associated transition states are nearly identical. Further, the cosine of the angle, alone, is shown to be sufficient in predicting association rate constants, with accuracies comparable to currently available predictors that use more intricate methodologies. Our results offer mechanistic insights and could be useful in development of coarse-grained models. Proteins 2015; 83:1557-1562. © 2015 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Recent evidence demonstrated that Lipocalin 2 (LCN2) is garnering interest from a wide spectrum as biomarker. Here, we present an in silico characterization of LCN2 belonging to prominent organisms focusing for their physicochemical and structural differences. We found significant variations in physicochemical properties between organisms and low sequence similarity based on their amino acid properties alone. However, we identified three main structurally distinct motif regions that are conserved among all variants. Further investigation was carried out to understand the functional insights of LCN2. We selected LCN2 sequence from Gallus gallus as an input query to identify unique scoring-framework based on computational tools and confidence scores of various putative associations. Among all ten proteins associated with LCN2; highest confidence of prediction were seen for the associations between LCN2 and metalloproteinase 9 (MMP9) and lipoprotein receptor-related protein 2 (LRP2) which play vital roles in tumor growth and iron transportation, respectively. We attempted to determine binding affinities of LCN2 with MMP9 and LRP2 through molecular modeling and docking. Selected docked models were examined for complex stability by GROMACS. Alteration of binding affinity between LCN2 with MMP9 and LRP2 proteins that we found in this study may provide new direction for future therapeutic targets. [ABSTRACT FROM AUTHOR]

A method is proposed to study protein-ligand binding in a system governed by specific and nonspecific interactions. Strong associations lead to narrow distributions in the proteins configuration space; weak and ultraweak associations lead instead to broader distributions, a manifestation of nonspecific, sparsely populated binding modes with multiple interfaces. The method is based on the notion that a discrete set of preferential first-encounter modes are metastable states from which stable (prerelaxation) complexes at equilibrium evolve. The method can be used to explore alternative pathways of complexation with statistical significance and can be integrated into a general algorithm to study protein interaction networks. The method is applied to a peptide-protein complex. The peptide adopts several low-population conformers and binds in a variety of modes with a broad range of affinities. The system is thus well suited to analyze general features of binding, including conformational selection, multiplicity of binding modes, and nonspecific interactions, and to illustrate how the method can be applied to study these problems systematically. The equilibrium distributions can be used to generate biasing functions for simulations of multiprotein systems from which bulk thermodynamic quantities can be calculated. © 2015 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Calmodulin (CaM) is a primary calcium (Ca2+)-signaling protein that specifically recognizes and activates highly diverse target proteins. We explored the molecular basis of target recognition of CaM with peptides representing the CaM-binding domains from two Ca2+-CaM-dependent kinases, CaMKI and CaMKII, by employing experimentally constrained molecular simulations. Detailed binding route analysis revealed that the two CaM target peptides, although similar in length and net charge, follow distinct routes that lead to a higher binding frustration in the CaM-CaMKII complex than in the CaM-CaMKI complex. We discovered that the molecular origin of the binding frustration is caused by intermolecular contacts formed with the C-domain of CaM that need to be broken before the formation of intermolecular contacts with the N-domain of CaM. We argue that the binding frustration is important for determining the kinetics of the recognition process of proteins involving large structural fluctuations. Copyright © 2015 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

A model is proposed for the evaluation of dispersive forces in a continuum solvent representation for use in large-scale computer simulations. The model captures the short- and long-range effects of water-exclusion in conditions of partial and anisotropic hydration. The model introduces three parameters, one of which represents the degree of hydration (water occupancy) at any point in the system, which depends on the solute conformation, and two that represent the strength of water-water and water-solute dispersive interactions. The model is optimized for proteins, using hydration data of a suboptimally hydrated binding site and results from dynamics simulations in explicit water. The model is applied to a series of aliphatic-alcohol/protein complexes and a set of binary and ternary complexes of various sizes. Implications for weak and ultra-weak protein-protein association and for simulation in crowded media are discussed. Published 2014. This article is a U.S. Government work and is in the public domain in the USA [ABSTRACT FROM AUTHOR]

Gene cluster “ ter” conferring high tellurite resistance has been identified in various pathogenic bacteria including Escherichia coli O157:H7. However, the precise mechanism as well as the molecular function of the respective gene products is unclear. Here we describe protein–protein association and localization analyses of four essential Ter proteins encoded by minimal resistance-conferring fragment ( terBCDE) by means of recombinant expression. By using a two-plasmid complementation system we show that the overproduced single Ter proteins are not able to mediate tellurite resistance, but all Ter members play an irreplaceable role within the cluster. We identified several types of homotypic and heterotypic protein–protein associations among the Ter proteins by in vitro and in vivo pull-down assays and determined their cellular localization by cytosol/membrane fractionation. Our results strongly suggest that Ter proteins function involves their mutual association, which probably happens at the interface of the inner plasma membrane and the cytosol. [ABSTRACT FROM AUTHOR]

The human guanylate-binding protein 1 (hGBP1) is a large GTP-binding protein belonging to the dynamin family, a common feature of which is nucleotide-dependent assembly to homotypic oligomers. Assembly leads to stimulation of GTPase activity, which, in the case of dynamin, is responsible for scission of vesicles from membranes. By yeast two-hybrid and biochemical experiments we addressed intermolecular interactions between all subdomains of hGBP1 and identified the C-terminal subdomain, α12/13, as a new interaction site for self-assembly. α12/13 represents a stable subdomain of hGBP1, as shown by CD spectroscopy. In addition to contacts between GTPase domains leading to dimer formation, the interaction between two α12/13 subdomains, in the course of GTP hydrolysis, results in tetramer formation of the protein. With the help of CD spectroscopy we showed coiled-coil formation of two α12/13 subdomains and concentration-dependent measurements allow estimating a value for the dissociation constant of 7.3 μ m. We suggest GTP hydrolysis-driven release of the α12/13 subdomain, making it available for coiled-coil formation. Furthermore, we can demonstrate the biological relevance of hGBP1 tetramer formation in living cells by chemical cross-link experiments. Structured digital abstract and by (), and by (View Interaction: , ), with by (View Interaction: , , ) [ABSTRACT FROM AUTHOR]

Abstract: Regulatory factor X (RFX) is a heterotrimeric protein complex having RFX5, RFXANK and RFXAP as its three subunits. It is involved in the regulation of the transcription of MHCII molecules in antigen presenting cells. The RFX complex binds to X-box DNA, using the DNA binding domain, present in RFX5. The DNA binding domain (DBD) of RFX5 (12kD) and intact RFXANK (35kD) were subcloned, expressed and purified. The associations of RFX5DBD with the X-box DNA and between RFX5DBD and RFXANK were measured in this study. The interaction of RFX5DBD and X-box DNA was studied using steady state fluorescence quenching and circular dichroism. The binding dissociation constant (K d ) of the DNA–protein complex was determined from fluorescence measurements. The van''t Hoff plot was linear over the temperature range 10–25°C and the binding was found to be entropy-driven and enthalpy-favorable. The effect of electrolytes in RFX5DBD–DNA association was also studied. Molecular association between RFX5DBD and RFXANK has been observed by fluorescence resonance energy transfer (FRET) measurements, changes in the ratio of the two vibronic intensities of pyrene labeled RFX5DBD in presence of RFXANK and chemical cross-linking followed by tandem mass spectrometry. Results showed that the two proteins could interact in the absence of the third subunit RFXAP, in vitro with an apparent dissociation constant (K d ) of 128nM. [Copyright &y& Elsevier]

Abstract: Studies on the nature and function of intrinsically disordered proteins (IDP) over the past 10years have demonstrated the importance of IDPs in normal cellular function. Although many proteins predicted to be IDPs have been experimentally characterized on an individual basis, the conservation of disorder between homologous proteins from different organisms has not been fully studied. We now demonstrate that the FlgM protein from the thermophile Aquifex aeolicus exhibits a more ordered conformation at 20°C than the previously characterized FlgM protein from Salmonella typhimurium. FlgM is an inhibitor of the RNA transcription factor σ 28, which is involved in regulation of the late-stage genes involved in flagella synthesis. Previous work has shown that the S. typhimurium FlgM protein is an intrinsically disordered protein, though the C-terminus becomes ordered when bound to σ 28 or under crowded solution conditions. In this work, we demonstrate that at 20°C the A. aeolicus FlgM protein exhibits alpha-helical character in circular dichroism (CD) experiments, though the percentage of alpha-helical content decreases with increased temperature, consistent with the FlgM assuming a less folded conformation. We also show that the A. aeolicus FlgM exhibits cooperativity in chemical denaturation experiments, consistent with a globular nature. Furthermore, we use the fluorescent probe FlAsH to show that the H2 helix is ordered, even in the unbound state and that the H1 and H2 helices appear to be associated with each other in the absence of the σ 28 protein. Finally, we demonstrate that the H2 helix assumes an extended conformation at 85°C. Based on our results, we propose that at 20°C the A. aeolicus FlgM assumes a four-helix bundle-like conformation that becomes a more extended conformation at the A. aeolicus'' physiological temperature of 85°C. [Copyright &y& Elsevier]

Unveiling sequence-stability and structure-stability relationships is a major goal of protein chemistry and structural biology. Despite the enormous efforts devoted, answers to these issues remain elusive. In principle, collagen represents an ideal system for such investigations due to its simplified sequence and regular structure. However, the definition of the molecular basis of collagen triple helix stability has hitherto proved to be a difficult task. Particularly puzzling is the decoding of the mechanism of triple helix stabilization/destabilization induced by imino acids. Although the propensity-based model, which correlates the propensities of the individual imino acids with the structural requirements of the triple helix, is able to explicate most of the experimental data, it is unable to predict the rather high stability of peptides embedding Gly-Hyp-Hyp triplets. Starting from the available X-ray structures of this polypeptide, we carried out an extensive quantum chemistry analysis of the mutual interactions established by hydroxyproline residues located at the X and Y positions of the Gly-X-Y motif. Our data clearly indicate that the opposing rings of these residues establish significant van der Waals and dipole-dipole interactions that play an important role in triple helix stabilization. These findings suggest that triple helix stabilization can be achieved by distinct structural mechanisms. The interplay of these subtle but recurrent effects dictates the overall stability of this widespread structural motif. [ABSTRACT FROM AUTHOR]

Sensitivity of the electron paramagnetic resonance (CW EPR) to molecular tumbling provides potential means for studying processes of molecular association. It uses spin-labeled macromolecules, whose CW EPR spectra may change upon binding to other macromolecules. When a spin-labeled molecule is mixed with its liganding partner, the EPR spectrum constitutes a linear combination of spectra of the bound and unbound ligand (as seen in our example of spin-labeled cytochrome c 2 interacting with cytochrome bc 1 complex). In principle, the fraction of each state can be extracted by the numerical decomposition of the spectrum; however, the accuracy of such decomposition may often be compromised by the lack of the spectrum of the fully bound ligand, imposed by the equilibrium nature of molecular association. To understand how this may affect the final estimation of the binding parameters, such as stoichiometry and affinity of the binding, a series of virtual titration experiments was conducted. Our non-linear regression analysis considered a case in which only a single class of binding sites exists, and a case in which classes of both specific and non-specific binding sites co-exist. The results indicate that in both models, the error due to the unknown admixture of the unbound ligand component in the EPR spectrum causes an overestimation of the bound fraction leading to the bias in the dissociation constant. At the same time, the stoichiometry of the binding remains relatively unaffected, which overall makes the decomposition of the EPR spectrum an attractive method for studying protein–protein interactions in equilibrium. Our theoretical treatment appears to be valid for any spectroscopic techniques dealing with overlapping spectra of free and bound component. [ABSTRACT FROM AUTHOR]

Abstract: The process of protein–protein association starts with their random collision, which may develop into an encounter complex followed by a transition state and final complex formation. Here we aim to experimentally characterize the nature of the transition state of protein–protein association for three different protein–protein interactions; Barnase-Barstar, TEM1-BLIP and IFNα2-IFNAR2, and use the data to model the transition state structures. To model the transition state, we determined inter-protein distance-constraints of the activated complex by using double mutant cycles (DMC) assuming that interacting residues are spatially close. Significant ΔΔG ‡ int values were obtained only between residues on Barnase and Barstar. However, introducing specific mutations that optimize the charge complementarity between BLIP and TEM1 resulted in the introduction of significant ΔΔG ‡ int values also between residues of these two proteins. While electrostatic interactions make major contributions towards stabilizing the transition state, we show two examples where steric hindrance exerts an effect on the transition state as well. To model the transition-state structures from the experimental ΔΔG ‡ int values, we introduced a method for structure perturbation, searching for those inter-protein orientations that best support the experimental ΔΔG ‡ int values. Two types of transition states were found, specific as observed for Barnase-Barstar and the electrostatically optimized TEM1-BLIP mutants, and diffusive as shown for wild-type TEM1-BLIP and IFNα2-IFNAR2. The specific transition states are characterized by defined inter-protein orientations, which cannot be modeled for the diffusive transition states. Mutations introduced through rational design can change the transition state from diffusive to specific. Together, these data provide a structural view of the mechanism allowing rates of association to differ by five orders of magnitude between different protein complexes. [Copyright &y& Elsevier]

Computational techniques are becoming increasingly important in structural and functional biology, in particular as tools to aid the interpretation of experimental results and the design of new systems. This review reports on recent studies employing a variety of computational approaches to unravel the microscopic details of the structure-function relationships in plastocyanin and other proteins belonging to the blue copper superfamily. Aspects covered include protein recognition, electron transfer and protein-solvent interaction properties of the blue copper protein family. The relevance of integrating diverse computational approaches to address the analysis of a complex protein system, such as a cupredoxin metalloprotein, is emphasized. [ABSTRACT FROM AUTHOR]

Here, we present a diverse, structurally nonredundant data set of two-chain protein-protein interfaces derived from the PDB. Using a sequence order-independent structural comparison algorithm and hierarchical clustering, 3799 interface clusters are obtained. These yield 103 clusters with at least five nonhomologous members. We divide the clusters into three types. In Type I clusters, the global structures of the chains from which the interfaces are derived are also similar. This cluster type is expected because, in general, related proteins associate in similar ways. In Type II, the interfaces are similar; however, remarkably, the overall structures and functions of the chains are different. The functional spectrum is broad, from enzymes/inhibitors to immunoglobulins and toxins. The fact that structurally different monomers associate in similar ways, suggests 'good' binding architectures. This observation extends a paradigm in protein science: It has been well known that proteins with similar structures may have different functions. Here, we show that it extends to interfaces. In Type III clusters, only one side of the interface is similar across the cluster. This structurally nonredundant data set provides rich data for studies of protein-protein interactions and recognition, cellular networks and drug design. In particular, it may be useful in addressing the difficult question of what are the favorable ways for proteins to interact. (The data set is available at and .) [ABSTRACT FROM AUTHOR]

Physiological media constitutes a crowded environment that serves as the field of action for protein–protein interaction in vivo. Measuring protein–protein interaction in crowded solutions can mimic this environment. In this work we follow the process of protein–protein association and its rate constants (kon) of the β-lactamase (TEM)–β-lactamase inhibitor protein (BLIP) complex in crowded solution using both low and high molecular mass crowding agents. In all crowded solutions (0–40% (w/w) of ethylene glycol (EG), poly(ethylene glycol) (PEG) 200, 1000, 3350, 8000 Da Ficoll-70 and Haemaccel the measured absolute kon, but not koff values, were found to be slower as compared to buffer. However, there is a fundamental difference between low and high mass crowding agents. In the presence of low mass crowding agents and Haemaccel kon depends inversely on the solution viscosity. In high mass polymer solutions kon changes only slightly, even at viscosities 12-fold higher than water. The border between low and high molecular mass polymers is sharp and is dictated by the ratio between the polymer length (L) and its persistence length (Lp). Polymers that are long enough to form a flexible coil (L/Lp>2) behave as high molecular mass polymers and those who are unable to do so (L/Lp<2) behave as low molecular mass polymers. We concluded that although polymers solution are crowded, this property is not uniform; i.e. there are areas in the solution that contain bulk water, and in these areas proteins can diffuse and associate almost as if they were in diluted environment. This porous medium may be taken as mimicking some aspects of the cellular environment, where many of the macromolecules are organized along membranes and the cytoskeleton. To determine the contribution of electrostatic attraction between proteins in crowded milieu, we followed kon of wt-TEM and three BLIP analogs with up to 100-fold increased values of kon due to electrostatic steering. Faster associating BLIP variants keep their relative advantage in all crowded solutions, including Haemaccel. This result suggests that faster associating protein complexes keep their advantage also in complex environment. [Copyright &y& Elsevier]

The chemotaxis system of Escherichia coli makes use of an extended two-component sensory response pathway in which CheA, an autophosphorylating protein histidine kinase (PHK) rapidly passes its phosphoryl group to CheY, a phospho-accepting response regulator protein (RR). The CheA→CheY phospho-transfer reaction is 100–1000 times faster than the His→Asp phospho-relays that operate in other (non-chemotaxis) two-component regulatory systems, suggesting that CheA and CheY have unique features that enhance His→Asp phospho-transfer kinetics. One such feature could be the P2 domain of CheA. P2 encompasses a binding site for CheY, but an analogous RR-binding domain is not found in other PHKs. In previous work, we removed P2 from CheA, and this decreased the catalytic efficiency of CheA→CheY phospho-transfer by a factor of 50–100. Here we examined the kinetics of the binding interactions between CheY and P2. The rapid association reaction (kassn∼108 M−1 s−1 at 25 °C and μ=0.03 M) exhibited a simple first-order dependence on P2 concentration and appeared to be largely diffusion-limited. Ionic strength (μ) had a moderate effect on kassn in a manner predictable based on the calculated electrostatic interaction energy of the protein binding surfaces and the expected Debye–Hu¨ckel shielding. The speed of binding reflects, in part, electrostatic interactions, but there is also an important contribution from the inherent plasticity of the complex and the resulting flexibility that this allows during the process of complex formation. Our results support the idea that the P2 domain of CheA contributes to the overall speed of phospho-transfer by promoting rapid association between CheY and CheA. However, this alone does not account for the ability of the chemotaxis system to operate much more rapidly than other two-component systems: kcat differences indicate that CheA and CheY also achieve the chemical events of phospho-transfer more rapidly than do PHK–RR pairs of slower systems. [Copyright &y& Elsevier]

A hydrophobic folding unit cutting algorithm, originally developed for dissecting single-chain proteins, has been applied to a dataset of dissimilar two-chain protein-protein interfaces. Rather than consider each individual chain separately, the two-chain complex has been treated as a single chain. The two-chain parsing results presented in this work show hydrophobicity to be a critical attribute of two-state versus three-state protein-protein complexes. The hydrophobic folding units at the interfaces of two-state complexes suggest that the cooperative nature of the two-chain protein folding is the outcome of the hydrophobic effect, similar to its being the driving force in a single-chain folding. In analogy to the protein-folding process, the two-chain, two-state model complex may correspond to the formation of compact, hydrophobic nuclei. On the other hand, the three-state model complex involves binding of already folded monomers, similar to the association of the hydrophobic folding units within a single chain. The similarity between folding entities in protein cores and in two-state protein-protein interfaces, despite the absence of some chain connectivities in the latter, indicates that chain linkage does not necessarily affect the native conformation. This further substantiates the notion that tertiary, non-local interactions play a critical role in protein folding. These compact, hydrophobic, two-chain folding units, derived from structurally dissimilar protein-protein interfaces, provide a rich set of data useful in investigations of the role played by chain connectivity and by tertiary interactions in studies of binding and of folding. Since they are composed of non-contiguous pieces of protein backbones, they may also aid in defining folding nuclei. [ABSTRACT FROM AUTHOR]

The formation of functionally versatile protein complexes underlies almost every biological process. The estimation of how fast these complexes can be formed has broad implications for unravelling the mechanism of biomolecular recognition. This kinetic property is traditionally quantified by association rates, which can be measured through various experimental techniques. To complement these time-consuming and labor-intensive approaches, we developed a coarse-grained simulation approach to study the physical processes of protein–protein association. We systematically calibrated our simulation method against a large-scale benchmark set. By combining a physics-based force field with a statistically-derived potential in the simulation, we found that the association rates of more than 80% of protein complexes can be correctly predicted within one order of magnitude relative to their experimental measurements. We further showed that a mixture of force fields derived from complementary sources was able to describe the process of protein–protein association with mechanistic details. For instance, we show that association of a protein complex contains multiple steps in which proteins continuously search their local binding orientations and form non-native-like intermediates through repeated dissociation and re-association. Moreover, with an ensemble of loosely bound encounter complexes observed around their native conformation, we suggest that the transition states of protein–protein association could be highly diverse on the structural level. Our study also supports the idea in which the association of a protein complex is driven by a "funnel-like" energy landscape. In summary, these results shed light on our understanding of how protein–protein recognition is kinetically modulated, and our coarse-grained simulation approach can serve as a useful addition to the existing experimental approaches that measure protein–protein association rates. [ABSTRACT FROM AUTHOR]

To elicit apoptosis, BAX metamorphoses from an inert cytosolic monomer into homo-oligomers that permeabilize the mitochondrial outer membrane (MOM). A long-standing puzzle is that BH3 domains apparently activate BAX by not only its canonical groove but also a proposed site involving helices α1 and α6. Our mutagenesis studies reveal that late steps like oligomerization require activation through the groove but probably not earlier steps like MOM association. Conversely, α1 or α6 obstruction and alanine mutagenesis scanning implicate these helices early in BAX activation. The α1 and α6 mutations lowered BH3 binding, altered the BAX conformation, and reduced its MOM translocation and integration; their exposure of the BAX α1-α2 loop allosterically sequestered its α9 membrane anchor in the groove. The crystal structure of an α6 mutant revealed additional allosteric effects. The results suggest that the α1 and α6 region drives MOM association and integration, whereas groove binding favors subsequent steps toward oligomerization., (Copyright © 2019 The Author(s). Published by Elsevier Inc. All rights reserved.)

Conventional cytotoxic therapies for synovial sarcoma provide limited benefit. Drugs specifically targeting the product of its driver translocation are currently unavailable, in part because the SS18-SSX oncoprotein functions via aberrant interactions within multiprotein complexes. Proximity ligation assay is a recently-developed method that assesses protein-protein interactions in situ. Here we report use of the proximity ligation assay to confirm the oncogenic association of SS18-SSX with its co-factor TLE1 in multiple human synovial sarcoma cell lines and in surgically-excised human tumor tissue. SS18-SSX/TLE1 interactions are disrupted by class I HDAC inhibitors and novel small molecule inhibitors. This assay can be applied in a high-throughput format for drug discovery in fusion-oncoprotein associated cancers where key effector partners are known., Competing Interests: The authors disclose no potential conflicts of interest.