Towards Quantitative Predictions in Cell Biology Using Chemical Properties of Proteins Michele Vendruscolo and Gian Gaetano Tartaglia*

HIGHLIGHT www.rsc.org/molecularbiosystems | Molecular BioSystems Towards quantitative predictions in cell biology using chemical properties of proteins Michele Vendruscolo and Gian Gaetano Tartaglia*

DOI: 10.1039/b805710a

It has recently been suggested that the concentrations of proteins in the cell are tuned towards their critical values, and that the alteration of this balance often results in misfolding diseases. This concept is intriguing because the in vivo concentrations of proteins are closely regulated by complex cellular processes, while their critical concentrations are primarily determined by the chemical characters of their amino acid sequences. We discuss here how the presence of a link between the upper levels of in vivo concentrations and critical concentrations offers an opportunity to make quantitative predictions in cell biology based on the chemical properties of proteins.

Introduction: protein aggregation rates of the corresponding Solubility and chemical 7 chemistry and cell biology proteins measured in vitro (Fig. 2). properties of proteins In this highlight we explore the oppor- Cellular functions are orchestrated by tunities provided by the relationships be- The solubility of proteins can be defined complex regulatory networks involving tween the upper levels of in vivo in terms of their critical concentration, primarily nucleic acids and proteins.1,2 concentrations and the critical concentra- which is the concentration above which These same cellular functions are also, tions of proteins (Fig. 1) and between they form a condensed phase.9 The solu- however, dependent on the basic chem- mRNA expression levels and aggregation bility depends strongly on the thermo- istry of the molecules that carry them rates of the corresponding proteins (Fig. 2) dynamic conditions, including temperature, out.3–6 Therefore, the ‘‘chemical’’ and to develop strategies to make quantitative pH and ionic strength and on the compo- the ‘‘cellular’’ views of cell biology are predictions in cell biology through the sition of the solvent. Therefore the solu- complementary and closely related. A analysis of the chemical properties of pro- bility under standard in vitro conditions specific link between them emerges from teins. We first describe the advances that might differ from the solubility in the the suggestion that proteins remain so- have been recently made for predicting the highly complex cellular environment.9 luble in the cellular environment only up solubility of proteins8–12 and their propen- Moreover, as the most insoluble regions to the concentrations required for their sity for aggregation.13–20 We then explain of protein sequences are secluded from functions (Fig. 1). This notion follows how the relationship between protein ag- the solvent through the folding process, from the strong correlation that has been gregation rates and mRNA expression the solubility of proteins depends also on recently reported between expression le- levels (Fig. 2) provides a way to use the the stability of their native states.9 vels of human genes in vivo and the chemical properties of proteins to estimate Despite these complications, Wilkinson the expression levels themselves (Fig. 3), and Harrison demonstrated that the solu- and to assess the degree of neuronal dys- bility of proteins in Escherichia coli can be Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, function and degeneration in a Drosophila predicted from their chemical properties, CB2 1EW, UK. E-mail: [email protected] model of Alzheimer’s disease (Fig. 4).21 including charge, propensity for forming

Michele Vendruscolo obtained a Gian Gaetano Tartaglia ob- PhD in condensed matter phy- tained an MPhil in theoretical sics at SISSA in Trieste. He is physics at La Sapienza in now a reader in theoretical che- Rome. He then received his mical biology at the University PhD in biochemistry at the of Cambridge and an EMBO University of Zurich, and he is Young Investigator. His re- currently working as a postdoc- search interests are primarily toral researcher in Cambridge focused on the investigation of in the ﬁeld of protein misfolding the structures and properties of and aggregation. proteins, and their relationship to biological evolution and misfolding diseases. Michele Vendruscolo Gian Gaetano Tartaglia

1170 | Mol. BioSyst., 2008, 4, 1170–1175 This journal is c The Royal Society of Chemistry 2008 proteins whose deposition is associated with specific diseases, but is a generic property of polypeptide chains.24 In 2003, Chiti, Dobson and co-workers reported the existence of a significant correlation between the changes in the aggregation rates resulting from single amino acid substitutions and their effects on the chemical properties of polypeptide chains:13

ln(nwt/nmut)=aDH + b(DDGcoil-a + DDGb-coil)+gDC (2) Fig. 1 Schematic illustration of the expected relationship between the in vivo concentrations and the critical concentrations of proteins under physiological conditions. The amino acid In this equation, ln(nmut/nwt) is the loga- sequences of proteins have evolved to remain soluble at the upper levels of abundance required rithm in base 10 of the ratio between nwt, 25–27 by the cell during their cycles. As random mutations tend to destabilize their native folds the aggregation rate of the wild type and increase their propensities to aggregate,28 proteins slowly drift towards the toxic region of protein, and nmut, the aggregation rate low solubility (shown in red). Evolutionary selection prevents them from entering this region and of its mutational variant. DH, DDG stops the drift at the boundary between the toxic and the non-toxic regions (the latter shown in coil-a + DDG , and DC represent the green). This boundary is rather sharp (yellow band) and therefore causes the high correlation b-coil between aggregation rates and expression levels reported in Fig. 2. change in hydrophobicity, secondary structure propensity and charge upon mutation, respectively. Eqn (2) repro- duces to a remarkable extent the changes in the aggregation rates observed experimentally in vitro for single amino acid substitutions for series of peptide and proteins, including those associated with disease.13 This initial observation was then de- veloped into an approach in which en- vironmental conditions are also taken into account in order to predict the over- all aggregation propensities of peptides and proteins from the knowledge of their amino acid sequences and of the conditions used experimentally to monitor the aggregation process, including the pH, Fig. 2 Relationship between mRNA expression levels and aggregation rates for 11 human the ionic strength and the protein con- proteins for which the latter have been measured in vitro under near-physiological conditions.7 centration of the solution in which ag- The coefficient of correlation between these two quantities is 0.97. gregation occurs.16 The parameters corresponding to all these terms were turns, hydrophilicity and length of the dataset of 81 proteins, the simple mathe- estimated by fitting the elongation rates sequence.8 The degree of solubility of a matical model given by eqn (1) was pro- of a dataset of proteins compiled protein, cv, was estimated as: posed for the identification of soluble through an extensive literature search.16 eukaryotic targets in E. coli.22 After The same approach was also shown to N þ G þ P þ S cv ¼ a this initial work, several other studies have lead to accurate predictions of the n increased our understanding of the regions of the sequence of a peptide or R þ K D E þ b þ g ð1Þ relationship between the chemical proper- a protein that are most important n ties of amino acid sequences and their in determining the aggregation solubility.10–12 process.16,17,19,20 In this equation, n is the number of amino acids in the protein, a and b are two parameters describing, respectively, the Aggregation and chemical A link between protein electrostatic charge and the propensity to properties of proteins chemistry and cell biology form turns, and g is a constant; furthermore N, G, P,andS are the number of It is well known that proteins have a By considering together the results Asn, Gly, Pro, and Ser residues and R, K, strong tendency to aggregate into inso- described in the previous two sections, D,andE the number of Arg, Lys, Asp, luble assemblies,23 and that the ability to we observe that the same chemical para- and Glu residues, respectively. Using a form aggregates is not restricted to the meters used for predicting the solubility

This journal is c The Royal Society of Chemistry 2008 Mol. BioSyst., 2008, 4, 1170–1175 | 1171 between aggregation rates measured in vitro and concentrations detected in vivo. By investigating the nature of this link, we have reported a strong relationship between in vivo mRNA expression levels and in vitro protein aggregation rates7 (Fig. 2). We suggested that this correlation is the consequence of an evolutionary pressure acting to decrease the risk of aggregation in the cell.7 This evolutionary pressure is exerted since failure of proteins to fold correctly can give rise to cellular malfunctions and diseases. Ran- dom amino acid mutations have a strong tendency to destabilize the native fold of a protein25–27 and enhance the propen- Fig. 3 Relationship between gene expression levels and the chemical properties of the sity to aggregate.28 Since protein concen- corresponding protein sequences. High expression levels are associated with protein sequences trations and mRNA expression levels are with large numbers of polar (D, E, N, R, Q, and H) and hydrophilic (T, K, C, G, A, and R) correlated in E. coli,29 the relationship amino acids. Low expression levels are observed for protein sequences with large numbers of that we identiﬁed indicates a close corre- amino acids with high hydrophobicity (F, M, I, L, V, Y, and P), and high b-sheet propensity lation between concentrations and solu- (V, I, F, W, L, Y, and T). These results were obtained by sorting the expression levels of about bility of proteins (Fig. 1). 2000 E. coli genes (http://redpoll.pharmacy.ualberta.ca/CCDB/) and by selecting the 50 top- Since the aggregation propensities of ranked and 50 bottom-ranked genes. The horizontal line represents the average value for the two datasets taken together. Chemical propensities are deﬁned following a consensus of experimental proteins can be predicted from their che- 8–20 scales (http://expasy.org/tools/protscale.html). mical properties. and the aggregation propensities themselves are correlated to of proteins in E. coli8–12,22 are also em- pensities of proteins in vitro.13–20 These the in vivo concentrations,7 it should also ployed for predicting aggregation pro- results hint at the existence of a link be possible to make predictions about a

Fig. 4 The toxicity of mutational variants of the Ab peptide can be better predicted using the propensities to form protofibrillar assemblies rather than the propensities to form fibrillar aggregates.21 (a) Correlation between aggregation propensity and neurotoxicity in Drosophila of Ab mutational variants. The Zyggregator algorithm19,20 (http://www-vendruscolo.ch.cam.ac.uk/zyggregator.php) was used to rationally design 17 variants of the Ab peptide on the basis of their aggregation propensities. The toxicity of the variants, measured as deficiencies in the locomotor activity, shows a correlation of 75% with the predicted aggregation propensities.21 Mutants of the E22G ’’Arctic’’ variant (red circles) diverge from the trend defined by the mutants of the wild-type Ab (black circles). Notably, different fibril morphologies are associated with the E22G variants, which aggregate into low molecular weight protofibrils. Taken together, these results show that the algorithm used for predicting aggregation propensities, while capable of predicting the in vitro aggregation rates of all the mutants considered, including those on the E22G background,21 is unable to fully capture their toxic effects. (b) Correlation between the predictions of the propensities to form protofibrillar aggregates and toxicities measured in vivo in transgenic Drosophila.21 The toxicity of the variants, measured as deficiencies in the locomotor activity, shows a correlation of 83% with the predicted protofibrillar propensities, which is significantly higher than the one obtained using the aggregation propensities. In particular, mutations on the E22G background (red circles) do not diverge significantly from the trend given by the wild type mutants (black circles).

1172 | Mol. BioSyst., 2008, 4, 1170–1175 This journal is c The Royal Society of Chemistry 2008 variety of cellular processes by using the of all the possible 798 single-point muta- I31E/E22G variants suggests that non- chemical properties of the proteins in- tions of the Ab peptide were predicted. toxic proteins can be expressed at higher volved in them. In the next two sections Thirteen non-naturally occurring var- levels without impairing cellular pro- we provide two examples that show how iants were then selected according to cesses, which strongly supports our ob- this idea can be applied. such propensities for expression in the servation of a link between aggregation central nervous system of Drosophila.In rates and expression levels. addition, four mutational variants of the In order to rationalize the deviations Relationship between gene E22G (‘‘Arctic’’) form of the Ab peptide, of some of the mutants that we observed, expression levels and amino which leads to early onset of Alzheimer’s we considered the series of experimental acid composition of the disease in humans,34 were designed to studies that have shown for a range of corresponding proteins modulate its aggregation propensity. It peptides and proteins that amyloid fibril has been shown by in vitro experiments formation is preceded by the appearance We first illustrate the close connection that the E22G mutant forms aggregates of organized molecular assemblies usual- between protein chemistry and cell bio- and fibrils at much lower concentrations ly termed protofibrils.37,38 Interest in logy by showing that gene expression (o2.5 mM) than the wild type (12.5 mM).35 these low molecular weight oligomers levels and the amino acid compositions At the same concentration, the aggrega- has increased since these species have of the corresponding protein sequences tion process occurs more rapidly for been detected in the brains of patients are linked in E. coli (Fig. 3). Highly- the E22G mutant compared with the suffering from Alzheimer’s disease.39,40 expressed genes are associated with wild type protein and amyloid fibrils In fact, at different stages of Ab assem- protein sequences with high charge and hy- appear about four days earlier after the bly, Ab oligomers and fibrils are ob- drophilicity, while genes with low levels onset of sample incubation without served that differ in structure as well as of expression are associated with protein seeding.36 toxic function. In particular, earlier oli- sequences with high hydrophobicity and Using the Drosophila longevity to gomeric assemblies have been found to propensity to form b-sheets (Fig. 3). quantify the effect of Ab variants, a be toxic to cells in cell cultures and in a Consistent with these results, proteins correlation of 75% was found between transgenic mouse model.41,42 Hence, we with many polar amino acids represent the predicted propensities to aggregate investigated the relationship between an optimal target for heterologous ex- and the severity of neurodegeneration neurodegenerative effects of the Ab var- pression in E. coli.30 In addition, mem- (Fig. 4a). Although the transcription le- iants and their associated protofibrillar brane proteins, which are characterized vels of the wild type Ab and of the E22G propensities.21 In order to build a pre- by the presence of several extended hydro- variant were found to be practically the dictor for protofibrillar propensities, we phobic regions, show very low levels of same, the lifespan of flies expressing the used the aggregation rates of the mutants expression in E. coli.31 Furthermore, wild-type Ab peptide was observed to of the protein AcP43 to parametrize an natively unfolded proteins tend to have be about 45 days, while the lifespan of equation that has the same form as the more charged and fewer hydrophobic the flies expressing the E22G variant was one used for prediction of aggregation amino acids32 in order to increase their reduced to about 10 days.21 We also propensities. In the new predictions, we solubility in the absence of the protection found that flies expressing the F20E mu- assumed that regions characterized by against aggregation provided by a folded tant lived 25% longer than flies expres- either positive or negative propensities structure,19 but despite these features sing the wild-type Ab peptide, and that are important to predict the proto- their expression levels are in some cases the F20E mutant does not form in vivo fibrillar propensity. We made this lower than those of globular proteins,33 deposits, even when its transcription le- hypothesis because regions associated with thus indicating the key role played by the vels are three times higher than those of negative propensities are usually charged or native structure in maintaining the solu- the wild-type Ab peptide. High correla- have a high propensity for being unstruc- bility of polypeptide chains.19 tion was also found between predicted tured, which may play a key role at the aggregation propensities and locomotor early stages of the oligomerization pro- deficits. Some deviations from this trend cess.44–46 In the approach that we have Protein concentrations and were, however, observed. The I31E mu- described, the chemical properties that we neurotoxicity of Ab peptide tation on the E22G background use for predicting the aggregation rates into aggregates in Drosophila (I31E/E22G) exhibited neuronal effects that fibrillar or protofibrillar assemblies are si- melanogaster did not match the predicted aggregation milar. As we, however, determined the propensity. Intriguingly, the I31E/E22G parameters through separate fitting proce- The possibility of using protein chemis- peptide was found to aggregate in vitro at dures in which the aggregation rates into try to make quantitative predictions a rate that matches the predictions but its specific types of assemblies were measured, about cellular processes is further illu- deposits were not accompanied by cav- the relative weights of the chemical proper- strated here by reviewing a study in ities in brain tissue. Moreover, even ties are different, thus resulting in specific which the aggregation propensities of a when the transcription levels of the predictions for each type of assembly series of mutational variants of the Ab I31E/E22G peptide are twice as much process.20 peptide were related to the lifespan of as the levels of the E22G peptide, the The predicted protofibrillar propensi- transgenic Drosophila melanogaster.21 In protein was not observed to be toxic. ties showed a correlation of 83% with that study the aggregation propensities Importantly, the case of the F20E and the fly longevity, revealing a stronger

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