Subcellular localization and Ser-137 phosphorylation regulate tumor-suppressive activity of profilin-1.

The actin-binding protein profilin-1 (Pfn1) inhibits tumor growth and yet is also required for cell proliferation and survival, an apparent paradox. We previously identified Ser-137 of Pfn1 as a phosphorylation site within the poly-l-proline (PLP) binding pocket. Here we confirm that Ser-137 phosphorylation disrupts Pfn1 binding to its PLP-containing ligands with little effect on actin binding. We find in mouse xenografts of breast cancer cells that mimicking Ser-137 phosphorylation abolishes cell cycle arrest and apoptotic sensitization by Pfn1 and confers a growth advantage to tumors. This indicates a previously unrecognized role of PLP binding in Pfn1 antitumor effects. Spatial restriction of Pfn1 to the nucleus or cytoplasm indicates that inhibition of tumor cell growth by Pfn1 requires its nuclear localization, and this activity is abolished by a phosphomimetic mutation on Ser-137. In contrast, cytoplasmic Pfn1 lacks inhibitory effects on tumor cell growth but rescues morphological and proliferative defects of PFN1 null mouse chondrocytes. These results help reconcile seemingly opposed cellular effects of Pfn1, provide new insights into the antitumor mechanism of Pfn1, and implicate Ser-137 phosphorylation as a potential therapeutic target for breast cancer.

Quantitative assessments of the distinct contributions of polypeptide backbone amides versus side chain groups to chain expansion via chemical denaturation.

In aqueous solutions with high concentrations of chemical denaturants such as urea and guanidinium chloride (GdmCl) proteins expand to populate heterogeneous conformational ensembles. These denaturing environments are thought to be good solvents for generic protein sequences because properties of conformational distributions align with those of canonical random coils. Previous studies showed that water is a poor solvent for polypeptide backbones, and therefore, backbones form collapsed globular structures in aqueous solvents. Here, we ask if polypeptide backbones can intrinsically undergo the requisite chain expansion in aqueous solutions with high concentrations of urea and GdmCl. We answer this question using a combination of molecular dynamics simulations and fluorescence correlation spectroscopy. We find that the degree of backbone expansion is minimal in aqueous solutions with high concentrations of denaturants. Instead, polypeptide backbones sample conformations that are denaturant-specific mixtures of coils and globules, with a persistent preference for globules. Therefore, typical denaturing environments cannot be classified as good solvents for polypeptide backbones. How then do generic protein sequences expand in denaturing environments? To answer this question, we investigated the effects of side chains using simulations of two archetypal sequences with amino acid compositions that are mixtures of charged, hydrophobic, and polar groups. We find that side chains lower the effective concentration of backbone amides in water leading to an intrinsic expansion of polypeptide backbones in the absence of denaturants. Additional dilution of the effective concentration of backbone amides is achieved through preferential interactions with denaturants. These effects lead to conformational statistics in denaturing environments that are congruent with those of canonical random coils. Our results highlight the role of side chain-mediated interactions as determinants of the conformational properties of unfolded states in water and in influencing chain expansion upon denaturation.

Hamiltonian Switch Metropolis Monte Carlo Simulations for Improved Conformational Sampling of Intrinsically Disordered Regions Tethered to Ordered Domains of Proteins.

There is growing interest in the topic of intrinsically disordered proteins (IDPs). Atomistic Metropolis Monte Carlo (MMC) simulations based on novel implicit solvation models have yielded useful insights regarding sequence-ensemble relationships for IDPs modeled as autonomous units. However, a majority of naturally occurring IDPs are tethered to ordered domains. Tethering introduces additional energy scales and this creates the challenge of broken ergodicity for standard MMC sampling or molecular dynamics that cannot be readily alleviated by using generalized tempering methods. We have designed, deployed, and tested our adaptation of the Nested Markov Chain Monte Carlo sampling algorithm. We refer to our adaptation as Hamiltonian Switch Metropolis Monte Carlo (HS-MMC) sampling. In this method, transitions out of energetic traps are enabled by the introduction of an auxiliary Markov chain that draws conformations for the disordered region from a Boltzmann distribution that is governed by an alternative potential function that only includes short-range steric repulsions and conformational restraints on the ordered domain. We show using multiple, independent runs that the HS-MMC method yields conformational distributions that have similar and reproducible statistical properties, which is in direct contrast to standard MMC for equivalent amounts of sampling. The method is efficient and can be deployed for simulations of a range of biologically relevant disordered regions that are tethered to ordered domains.

Denatured state ensembles with the same radii of gyration can form significantly different long-range contacts.

Defining the structural, dynamic, and energetic properties of the unfolded state of proteins is critical for an in-depth understanding of protein folding, protein thermodynamics, and protein aggregation. Here we analyze long-range contacts and compactness in two apparently fully unfolded ensembles of the same protein: the acid unfolded state of the C-terminal domain of ribosomal protein L9 in the absence of high concentrations of urea as well as the urea unfolded state at low pH. Small angle X-ray scattering reveals that the two states are expanded with values of Rg differing by <7%. Paramagnetic relaxation enhancement (PRE) nuclear magnetic resonance studies, however, reveal that the acid unfolded state samples conformations that facilitate contacts between residues that are distant in sequence while the urea unfolded state ensemble does not. The experimental PRE profiles for the acid unfolded state differ significantly from these predicted using an excluded volume limit ensemble, but these long-range contacts are largely eliminated by the addition of 8 M urea. The work shows that expanded unfolded states can sample very different distributions of long-range contacts yet still have similar radii of gyration. The implications for protein folding and for the characterization of unfolded states are discussed.

A quantitative measure for protein conformational heterogeneity.

Conformational heterogeneity is a defining characteristic of proteins. Intrinsically disordered proteins (IDPs) and denatured state ensembles are extreme manifestations of this heterogeneity. Inferences regarding globule versus coil formation can be drawn from analysis of polymeric properties such as average size, shape, and density fluctuations. Here we introduce a new parameter to quantify the degree of conformational heterogeneity within an ensemble to complement polymeric descriptors. The design of this parameter is guided by the need to distinguish between systems that couple their unfolding-folding transitions with coil-to-globule transitions and those systems that undergo coil-to-globule transitions with no evidence of acquiring a homogeneous ensemble of conformations upon collapse. The approach is as follows: Each conformation in an ensemble is converted into a conformational vector where the elements are inter-residue distances. Similarity between pairs of conformations is quantified using the projection between the corresponding conformational vectors. An ensemble of conformations yields a distribution of pairwise projections, which is converted into a distribution of pairwise conformational dissimilarities. The first moment of this dissimilarity distribution is normalized against the first moment of the distribution obtained by comparing conformations from the ensemble of interest to conformations drawn from a Flory random coil model. The latter sets an upper bound on conformational heterogeneity thus ensuring that the proposed measure for intra-ensemble heterogeneity is properly calibrated and can be used to compare ensembles for different sequences and across different temperatures. The new measure of conformational heterogeneity will be useful in quantitative studies of coupled folding and binding of IDPs and in de novo sequence design efforts that are geared toward controlling the degree of heterogeneity in unbound forms of IDPs.

The denatured state ensemble contains significant local and long-range structure under native conditions: analysis of the N-terminal domain of ribosomal protein L9.

The denatured state ensemble (DSE) represents the starting state for protein folding and the reference state for protein stability studies. Residual structure in the DSE influences the kinetics of protein folding, the propensity to aggregate, and protein stability. The DSE that is most relevant for folding is the ensemble populated under native conditions, but the stability of proteins and the cooperativity of their folding normally prevent direct characterization of this ensemble. Indirect experiments have been used to infer residual structure in the DSE under nondenaturing conditions, but direct characterization is rare. The N-terminal domain of ribosomal protein L9 (NTL9) is a small mixed α-ß domain that folds cooperatively on the millisecond time scale. A destabilized double mutant of NTL9, V3A/I4A-NTL9, populates the DSE in the absence of denaturant and is in slow exchange with the native state on the nuclear magnetic resonance time scale. The DSE populated in buffer was compared to the urea-induced DSE. Analysis of (1)H and (13)C chemical shifts reveals residual secondary structure in the DSE in buffer, which is stabilized by both local and long-range interactions. (15)N R2 relaxation rates deviate from random coil models, suggesting hydrophobic clustering in the DSE. Paramagnetic relaxation enhancement experiments show that there are transient long-range contacts in the DSE in buffer. In contrast, the urea-induced DSE has significantly less residual secondary structure and markedly fewer long-range contacts; however, the urea-induced DSE deviates from a random coil.

Experiments and simulations show how long-range contacts can form in expanded unfolded proteins with negligible secondary structure.

The sizes of unfolded proteins under highly denaturing conditions scale as N(0.59) with chain length. This suggests that denaturing conditions mimic good solvents, whereby the preference for favorable chain-solvent interactions causes intrachain interactions to be repulsive, on average. Beyond this generic inference, the broader implications of N(0.59) scaling for quantitative descriptions of denatured state ensembles (DSEs) remain unresolved. Of particular interest is the degree to which N(0.59) scaling can simultaneously accommodate intrachain attractions and detectable long-range contacts. Here we present data showing that the DSE of the N-terminal domain of the L9 (NTL9) ribosomal protein in 8.3 M urea lacks detectable secondary structure and forms expanded conformations in accord with the expected N(0.59) scaling behavior. Paramagnetic relaxation enhancements, however, indicate the presence of detectable long-range contacts in the denatured-state ensemble of NTL9. To explain these observations we used atomistic thermal unfolding simulations to identify ensembles whose properties are consistent with all of the experimental observations, thus serving as useful proxies for the DSE of NTL9 in 8.3 M urea. Analysis of these ensembles shows that residual attractions are present under mimics of good solvent conditions, and for NTL9 they result from low-likelihood, medium/long-range contacts between hydrophobic residues. Our analysis provides a quantitative framework for the simultaneous observation of N(0.59) scaling and low-likelihood long-range contacts for the DSE of NTL9. We propose that such low-likelihood intramolecular hydrophobic clusters might be a generic feature of DSEs that play a gatekeeping role to protect against aggregation during protein folding.

Describing sequence-ensemble relationships for intrinsically disordered proteins.

Intrinsically disordered proteins participate in important protein-protein and protein-nucleic acid interactions and control cellular phenotypes through their prominence as dynamic organizers of transcriptional, post-transcriptional and signalling networks. These proteins challenge the tenets of the structure-function paradigm and their functional mechanisms remain a mystery given that they fail to fold autonomously into specific structures. Solving this mystery requires a first principles understanding of the quantitative relationships between information encoded in the sequences of disordered proteins and the ensemble of conformations they sample. Advances in quantifying sequence-ensemble relationships have been facilitated through a four-way synergy between bioinformatics, biophysical experiments, computer simulations and polymer physics theories. In the present review we evaluate these advances and the resultant insights that allow us to develop a concise quantitative framework for describing the sequence-ensemble relationships of intrinsically disordered proteins.

Opposing effects of glutamine and asparagine govern prion formation by intrinsically disordered proteins.

Sequences rich in glutamine (Q) and asparagine (N) residues often fail to fold at the monomer level. This, coupled to their unusual hydrogen-bonding abilities, provides the driving force to switch between disordered monomers and amyloids. Such transitions govern processes as diverse as human protein-folding diseases, bacterial biofilm assembly, and the inheritance of yeast prions (protein-based genetic elements). A systematic survey of prion-forming domains suggested that Q and N residues have distinct effects on amyloid formation. Here, we use cell biological, biochemical, and computational techniques to compare Q/N-rich protein variants, replacing Ns with Qs and Qs with Ns. We find that the two residues have strong and opposing effects: N richness promotes assembly of benign self-templating amyloids; Q richness promotes formation of toxic nonamyloid conformers. Molecular simulations focusing on intrinsic folding differences between Qs and Ns suggest that their different behaviors are due to the enhanced turn-forming propensity of Ns over Qs.

Thermodynamics of beta-sheet formation in polyglutamine.

The role of beta-sheets in the early stages of protein aggregation, specifically amyloid formation, remains unclear. Interpretations of kinetic data have led to a specific model for the role of beta-sheets in polyglutamine aggregation. According to this model, monomeric polyglutamine, which is intrinsically disordered, goes through a rare conversion into an ordered, metastable, beta-sheeted state that nucleates aggregation. It has also been proposed that the probability of forming the critical nucleus, a specific beta-sheet conformation for the monomer, increases with increasing chain length. Here, we test this model using molecular simulations. We quantified free energy profiles in terms of beta-content for monomeric polyglutamine as a function of chain length. In accord with estimates from experimental data, the free energy penalties for forming beta-rich states are in the 10-20 kcal/mol range. However, the length dependence of these free energy penalties does not mirror interpretations of kinetic data. In addition, although homodimerization of disordered molecules is spontaneous, the imposition of conformational restraints on polyglutamine molecules does not enhance the spontaneity of intermolecular associations. Our data lead to the proposal that beta-sheet formation is an attribute of peptide-rich phases such as high molecular weight aggregates rather than monomers or oligomers.