Affinity of disordered protein complexes is modulated by entropy-energy reinforcement.

The association between two intrinsically disordered proteins (IDPs) may produce a fuzzy complex characterized by a high binding affinity, similar to that found in the ultrastable complexes formed between two well-structured proteins. Here, using coarse-grained simulations, we quantified the biophysical forces driving the formation of such fuzzy complexes. We found that the high-affinity complex formed between the highly and oppositely charged H1 and ProTα proteins is sensitive to electrostatic interactions. We investigated 52 variants of the complex by swapping charges between the two oppositely charged proteins to produce sequences whose negatively or positively charged residue content was more homogeneous or heterogenous (i.e., polyelectrolytic or polyampholytic, having higher or lower absolute net charges, respectively) than the wild type. We also changed the distributions of oppositely charged residues within each participating sequence to produce variants in which the charges were segregated or well mixed. Both types of changes significantly affect binding affinity in fuzzy complexes, which is governed by both enthalpy and entropy. The formation of H1-ProTa is supported by an increase in configurational entropy and by entropy due to counterion release. The latter can be twice as large as the former, illustrating the dominance of counterion entropy in modulating the binding thermodynamics. Complexes formed between proteins with greater absolute net charges are more stable, both enthalpically and entropically, indicating that enthalpy and entropy have a mutually reinforcing effect. The sensitivity of the thermodynamics of the complex to net charge and the charge pattern within each of the binding constituents may provide a means to achieve binding specificity between IDPs.

Control of protein activity by photoinduced spin polarized charge reorganization.

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.

PACSAB Server: A Web-Based Tool for the Study of Aggregation and the Conformational Ensemble of Disordered and Folded Proteins.

We present in this article the PACSAB server, which is designed to provide information about the structural ensemble and interactions of both stable and disordered proteins to researchers in the field of molecular biology. The use of this tool does not require any computational skills as the user just needs to upload the structure of the protein to be studied; the server runs a simulation with the PACSAB model, a highly accurate coarse-grained model that is much more efficient than standard molecular dynamics for the exploration of the conformational space of multiprotein systems. The trajectories generated by the simulations based on this model reveal the propensity of the protein under study for aggregation, identify the residues playing a central role in the aggregation process, and reproduce the whole conformational space of disordered proteins. All of this information is shown and can be downloaded from the web page.

Atomic-level characterization of protein-protein association.

Despite the biological importance of protein-protein complexes, determining their structures and association mechanisms remains an outstanding challenge. Here, we report the results of atomic-level 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.

Classification of protein-protein association rates based on biophysical informatics.

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.

Protein association changes in the Hedgehog signaling complex mediate differential signaling strength.

Hedgehog (Hh) is a conserved morphogen that controls cell differentiation and tissue patterning in metazoans. In Drosophila, the Hh signal is transduced from the G protein-coupled receptor Smoothened (Smo) to the cytoplasmic Hh signaling complex (HSC). How activated Smo is translated into a graded activation of the downstream pathway is still not well understood. In this study, we show that the last amino acids of the cytoplasmic tail of Smo, in combination with G protein-coupled receptor kinase 2 (Gprk2), bind to the regulatory domain of Fused (Fu) and highly activate its kinase activity. We further show that this binding induces changes in the association of Fu protein with the HSC and increases the proximity of the Fu catalytic domain to its substrate, the Costal2 kinesin. We propose a new model in which, depending on the magnitude of Hh signaling, Smo and Gprk2 modulate protein association and conformational changes in the HSC, which are responsible for the differential activation of the pathway.

TERIUS: accurate prediction of lncRNA via high-throughput sequencing data representing RNA-binding protein association.

BACKGROUND: LncRNAs are long regulatory non-coding RNAs, some of which are arguably predicted to have coding potential. Despite coding potential classifiers that utilize ribosome profiling data successfully detected actively translated regions, they are less sensitive to lncRNAs. Furthermore, lncRNA annotation can be susceptible to false positives obtained from 3' untranslated region (UTR) fragments of mRNAs. RESULTS: To lower these limitations in lncRNA annotation, we present a novel tool TERIUS that provides a two-step filtration process to distinguish between bona fide and false lncRNAs. The first step successfully separates lncRNAs from protein-coding genes showing enhanced sensitivity compared to other methods. To eliminate 3'UTR fragments, the second step takes advantage of the 3'UTR-specific association with regulator of nonsense transcripts 1 (UPF1), leading to refined lncRNA annotation. Importantly, TERIUS enabled the detection of misclassified transcripts in published lncRNA annotations. CONCLUSIONS: TERIUS is a robust method for lncRNA annotation, which provides an additional filtration step for 3'UTR fragments. TERIUS was able to successfully re-classify GENCODE and miTranscriptome lncRNA annotations. We believe that TERIUS can benefit construction of extensive and accurate non-coding transcriptome maps in many genomes.

Structural requirement of the hydrophobic region of the Bordetella pertussis CyaA-hemolysin for functional association with CyaC-acyltransferase in toxin acylation.

Previously, we demonstrated that the ∼130-kDa CyaA-hemolysin (CyaA-Hly, Met482-Arg1706) from Bordetella pertussis was palmitoylated at Lys983 when co-expressed with CyaC-acyltransferase in Escherichia coli, and thus activated its hemolytic activity. Here, further investigation on a possible requirement of the N-terminal hydrophobic region (HP, Met482-Leu750) for toxin acylation was performed. The ∼100-kDa RTX (Repeat-in-ToXin) fragment (CyaA-RTX, Ala751-Arg1706) containing the Lys983-acylation region (AR, Ala751-Gln1000), but lacking HP, was co-produced with CyaC in E. coli. Hemolysis assay indicated that CyaA-RTX showed no hemolytic activity. Additionally, MALDI-TOF/MS and LC-MS/MS analyses confirmed that CyaA-RTX was non-acylated, although the co-expressed CyaC-acyltransferase was able to hydrolyze its chromogenic substrate-p-nitrophenyl palmitate and acylate CyaA-Hly to become hemolytically active. Unlike CyaA-RTX, the ∼70-kDa His-tagged CyaA-HP/BI fragment which is hemolytically inactive and contains both HP and AR was constantly co-eluted with CyaC during IMAC-purification as the presence of CyaC was verified by Western blotting. Such potential interactions between the two proteins were also revealed by semi-native PAGE. Moreover, structural analysis via electrostatic potential calculations and molecular docking suggested that CyaA-HP comprising α1-α5 (Leu500-Val698) can interact with CyaC through several hydrogen and ionic bonds formed between their opposite electrostatic surfaces. Overall, our results demonstrated that the HP region of CyaA-Hly is conceivably required for not only membrane-pore formation but also functional association with CyaC-acyltransferase, and hence effective palmitoylation at Lys983.

Computational study of the inhibitory mechanism of the kinase CDK5 hyperactivity by peptide p5 and derivation of a pharmacophore.

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.

Protein-protein association rates captured in a single geometric parameter.

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.

Detection and characterization of nonspecific, sparsely populated binding modes in the early stages of complexation.

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.

Conformational frustration in calmodulin-target recognition.

Calmodulin (CaM) is a primary calcium (Ca(2+) )-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 Ca(2+) -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.

Implicit treatment of solvent dispersion forces in protein simulations.

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.

Purine nucleoside phosphorylase activity decline is linked to the decay of the trimeric form of the enzyme.

Homotrimeric mammalian purine nucleoside phosphorylase (PNP) plays a key role in the nucleoside and nucleotide metabolic salvage pathway. Each monomer in the active PNP trimer is composed of a central ß-sheet flanked by several α-helices. We investigated the stability of calf PNP using analytical ultracentrifugation, differential scanning calorimetry, circular dichroism, and UV absorption spectroscopy. The results demonstrate that the activity decline (due to protein aging after isolation from cells) of wild type PNP and its two mutants with point mutations in the region of monomer-monomer interface, is accompanied by a decrease of the population of the trimeric enzyme and an increase of the population of its aggregated forms. The data do not indicate a significant population of either folded or unfolded PNP monomers. The enzyme with specific activity lower than the maximal shows a decrease of the helical structure, which can make it prone to aggregation. The presence of phosphate stabilizes the enzyme but leads to a more pronounced aggregation above the melting temperature. These results suggest that the biological role of packing of the PNP monomers into a trimeric structure is to provide the stability of the enzyme since the monomers are not stable in solution.

Initiation of protein association in tofu formation by metal ions.

Magnesium and calcium ions are important factors in making tofu. However, the molecular role of these ions remains unclear in tofu formation. We have previously shown that magnesium chloride concentration-dependent produced silken tofu-like (SP) and regular tofu-like (RP) precipitates, but was an inconsequential factor for the retention of tofu. We investigated in this present study, the effect of various metal chlorides on the metal chloride concentration-dependent changes in tofu formation. These changes occurred in a similar manner to that of the magnesium ion, in which SP formation was followed by RP formation. It is interesting that the midpoint concentration for the formation of SP and RP represented a good correlation with the stability constant of EDTA. This correlation demonstrated the possibility that metal ions would interact with the carboxyl groups of soy proteins. We consider from these results that metal ions were the initiators of protein association in tofu formation.

Uptake of a cyanotoxin, ß-N-methylamino-L-alanine, by wheat (Triticum aestivum).

In order to study the uptake of the cyanobacterial neurotoxin ß-N-methylamino-l-alanine (BMAA) into the crop plant Triticum aestivum during germination and primary growth imbibed grains and 7-day-old seedlings were irrigated with 100 and 1000µg l(-1) BMAA for 4 days and 100µg l(-1) BMAA for 28 days. Content of derivatized free and protein-associated BMAA in seedlings, root and shoot tissue, respectively, were analyzed by LC-MS/MS. Free BMAA was only detected in seedlings exposed to 1000µg l(-1) BMAA, whereas protein-associated BMAA was found at both exposure concentrations. Irrigation with 100µgl(-1) BMAA led to an uptake of the neurotoxin into roots and shoots and to immediate protein-association. In roots, protein-associated BMAA was detectable after 5 days with peaking amounts after 14 days. Longer exposure did not cause further accumulation in roots. In contrast, protein-associated BMAA was detected in shoot samples after only 1 day. In shoots the highest amounts of protein-associated BMAA were found after 28 days. In turn, in both plant compartments free BMAA was below the measurable concentration.

Using the concept of transient complex for affinity predictions in CAPRI rounds 20-27 and beyond.

Predictions of protein-protein binders and binding affinities have traditionally focused on features pertaining to the native complexes. In developing a computational method for predicting protein-protein association rate constants, we introduced the concept of transient complex after mapping the interaction energy surface. The transient complex is located at the outer boundary of the bound-state energy well, having near-native separation and relative orientation between the subunits but not yet formed most of the short-range native interactions. We found that the width of the binding funnel and the electrostatic interaction energy of the transient complex are among the features predictive of binders and binding affinities. These ideas were very promising for the five affinity-related targets (T43-45, 55, and 56) of CAPRI rounds 20-27. For T43, we ranked the single crystallographic complex as number 1 and were one of only two groups that clearly identified that complex as a true binder; for T44, we ranked the only design with measurable binding affinity as number 4. For the nine docking targets, continuing on our success in previous CAPRI rounds, we produced 10 medium-quality models for T47 and acceptable models for T48 and T49. We conclude that the interaction energy landscape and the transient complex in particular will complement existing features in leading to better prediction of binding affinities.

Integration of various protein similarities using random forest technique to infer augmented drug-protein matrix for enhancing drug-disease association prediction.

Identifying new therapeutic indications for existing drugs is a major challenge in drug repositioning. Most computational drug repositioning methods focus on known targets. Analyzing multiple aspects of various protein associations provides an opportunity to discover underlying drug-associated proteins that can be used to improve the performance of the drug repositioning approaches. In this study, machine learning models were developed based on the similarities of diversified biological features, including protein interaction, topological network, sequence alignment, and biological function to predict protein pairs associating with the same drugs. The crucial set of features was identified, and the high performances of protein pair predictions were achieved with an area under the curve (AUC) value of more than 93%. Based on drug chemical structures, the drug similarity levels of the promising protein pairs were used to quantify the inferred drug-associated proteins. Furthermore, these proteins were employed to establish an augmented drug-protein matrix to enhance the efficiency of three existing drug repositioning techniques: a similarity constrained matrix factorization for the drug-disease associations (SCMFDD), an ensemble meta-paths and singular value decomposition (EMP-SVD) model, and a topology similarity and singular value decomposition (TS-SVD) technique. The results showed that the augmented matrix helped to improve the performance up to 4% more in comparison to the original matrix for SCMFDD and EMP-SVD, and about 1% more for TS-SVD. In summary, inferring new protein pairs related to the same drugs increase the opportunity to reveal missing drug-associated proteins that are important for drug development via the drug repositioning technique.

Molecular insights into the heat shock proteins of the human parasitic blood fluke Schistosoma mansoni.

BACKGROUND: Heat shock proteins (HSPs) are evolutionarily conserved proteins, produced by cells in response to hostile environmental conditions, that are vital to organism homeostasis. Here, we undertook the first detailed molecular bioinformatic analysis of these important proteins and mapped their tissue expression in the human parasitic blood fluke, Schistosoma mansoni, one of the causative agents of the neglected tropical disease human schistosomiasis. METHODS: Using bioinformatic tools we classified and phylogenetically analysed HSP family members in schistosomes, and performed transcriptomic, phosphoproteomic, and interactomic analysis of the S. mansoni HSPs. In addition, S. mansoni HSP protein expression was mapped in intact parasites using immunofluorescence. RESULTS: Fifty-five HSPs were identified in S. mansoni across five HSP families; high conservation of HSP sequences were apparent across S. mansoni, Schistosoma haematobium and Schistosoma japonicum, with S. haematobium HSPs showing greater similarity to S. mansoni than those of S. japonicum. For S. mansoni, differential HSP gene expression was evident across the various parasite life stages, supporting varying roles for the HSPs in the different stages, and suggesting that they might confer some degree of protection during life stage transitions. Protein expression patterns of HSPs were visualised in intact S. mansoni cercariae, 3 h and 24 h somules, and adult male and female worms, revealing HSPs in the tegument, cephalic ganglia, tubercles, testes, ovaries as well as other important organs. Analysis of putative HSP protein-protein associations highlighted proteins that are involved in transcription, modification, stability, and ubiquitination; functional enrichment analysis revealed functions for HSP networks in S. mansoni including protein export for HSP 40/70, and FOXO/mTOR signalling for HSP90 networks. Finally, a total of 76 phosphorylation sites were discovered within 17 of the 55 HSPs, with 30 phosphorylation sites being conserved with those of human HSPs, highlighting their likely core functional significance. CONCLUSIONS: This analysis highlights the fascinating biology of S. mansoni HSPs and their likely importance to schistosome function, offering a valuable and novel framework for future physiological investigations into the roles of HSPs in schistosomes, particularly in the context of survival in the host and with the aim of developing novel anti-schistosome therapeutics.

Multiscale modelling of claudin-based assemblies: A magnifying glass for novel structures of biological interfaces.

Claudins (Cldns) define a family of transmembrane proteins that are the major determinants of the tight junction integrity and tissue selectivity. They promote the formation of either barriers or ion-selective channels at the interface between two facing cells, across the paracellular space. Multiple Cldn subunits form complexes that include cis- (intracellular) interactions along the membrane of a single cell and trans- (intercellular) interactions across adjacent cells. The first description of Cldn assemblies was provided by electron microscopy, while electrophysiology, mutagenesis and cell biology experiments addressed the functional role of different Cldn homologs. However, the investigation of the molecular details of Cldn subunits and complexes are hampered by the lack of experimental native structures, currently limited to Cldn15. The recent implementation of computer-based techniques greatly contributed to the elucidation of Cldn properties. Molecular dynamics simulations and docking calculations were extensively used to refine the first Cldn multimeric model postulated from the crystal structure of Cldn15, and contributed to the introduction of a novel, alternative, arrangement. While both these multimeric assemblies were found to account for the physiological properties of some family members, they gave conflicting results for others. In this review, we illustrate the major findings on Cldn-based systems that were achieved by using state-of-the-art computational methodologies. The information provided by these results could be useful to improve the characterization of the Cldn properties and help the design of new efficient strategies to control the paracellular transport of drugs or other molecules.