Pietro Sormanni

The CamSol Method of Rational Design of Protein Mutants with Enhanced Solubility

Protein solubility is often an essential requirement in biotechnological and biomedical applications. Great advances in understanding the principles that determine this specific property of proteins have been made during the past decade, in particular concerning the physicochemical characteristics of their constituent amino acids. By exploiting these advances, we present the CamSol method for the rational design of protein variants with enhanced solubility. The method works by performing a rapid computational screening of tens of thousand of mutations to identify those with the greatest impact on the solubility of the target protein while maintaining its native state and biological activity. The application to a single-domain antibody that targets the Alzheimers Aβ peptide demonstrates that the method predicts with great accuracy solubility changes upon mutation, thus offering a cost-effective strategy to help the production of soluble proteins for academic and industrial purposes.

A natural product inhibits the initiation of α-synuclein aggregation and suppresses its toxicity

Significance Parkinson’s disease is characterized by the presence in brain tissues of aberrant aggregates primarily formed by the protein α-synuclein. It has been difficult, however, to identify compounds capable of preventing the formation of such deposits because of the complexity of the aggregation process of α-synuclein. By exploiting recently developed highly quantitative in vitro assays, we identify a compound, squalamine, that blocks α-synuclein aggregation, and characterize its mode of action. Our results show that squalamine, by competing with α-synuclein for binding lipid membranes, specifically inhibits the initiation of the aggregation process of α-synuclein and abolishes the toxicity of α-synuclein oligomers in neuronal cells and in an animal model of Parkinson’s disease. The self-assembly of α-synuclein is closely associated with Parkinson’s disease and related syndromes. We show that squalamine, a natural product with known anticancer and antiviral activity, dramatically affects α-synuclein aggregation in vitro and in vivo. We elucidate the mechanism of action of squalamine by investigating its interaction with lipid vesicles, which are known to stimulate nucleation, and find that this compound displaces α-synuclein from the surfaces of such vesicles, thereby blocking the first steps in its aggregation process. We also show that squalamine almost completely suppresses the toxicity of α-synuclein oligomers in human neuroblastoma cells by inhibiting their interactions with lipid membranes. We further examine the effects of squalamine in a Caenorhabditis elegans strain overexpressing α-synuclein, observing a dramatic reduction of α-synuclein aggregation and an almost complete elimination of muscle paralysis. These findings suggest that squalamine could be a means of therapeutic intervention in Parkinson’s disease and related conditions.

The s2D Method: Simultaneous Sequence-Based Prediction of the Statistical Populations of Ordered and Disordered Regions in Proteins

Extensive amounts of information about protein sequences are becoming available, as demonstrated by the over 79 million entries in the UniProt database. Yet, it is still challenging to obtain proteome-wide experimental information on the structural properties associated with these sequences. Fast computational predictors of secondary structure and of intrinsic disorder of proteins have been developed in order to bridge this gap. These two types of predictions, however, have remained largely separated, often preventing a clear characterization of the structure and dynamics of proteins. Here, we introduce a computational method to predict secondary-structure populations from amino acid sequences, which simultaneously characterizes structure and disorder in a unified statistical mechanics framework. To develop this method, called s2D, we exploited recent advances made in the analysis of NMR chemical shifts that provide quantitative information about the probability distributions of secondary-structure elements in disordered states. The results that we discuss show that the s2D method predicts secondary-structure populations with an average error of about 14%. A validation on three datasets of mostly disordered, mostly structured and partly structured proteins, respectively, shows that its performance is comparable to or better than that of existing predictors of intrinsic disorder and of secondary structure. These results indicate that it is possible to perform rapid and quantitative sequence-based characterizations of the structure and dynamics of proteins through the predictions of the statistical distributions of their ordered and disordered regions.

Rational design of antibodies targeting specific epitopes within intrinsically disordered proteins

Significance Although antibodies can normally be obtained against a wide variety of antigens, there are still hard targets, including weakly immunogenic epitopes, which are not readily amenable to existing production techniques. In addition, such techniques can be relatively time-consuming and costly, especially if the screening for a specific epitope is required. In this work we describe a rational design method that enables one to obtain antibodies targeting any specific epitope within a disordered protein or disordered region. We show that this method can be used to target three disordered proteins and peptides associated with neurodegenerative and systemic misfolding diseases. Antibodies are powerful tools in life sciences research, as well as in diagnostic and therapeutic applications, because of their ability to bind given molecules with high affinity and specificity. Using current methods, however, it is laborious and sometimes difficult to generate antibodies to target specific epitopes within a protein, in particular if these epitopes are not effective antigens. Here we present a method to rationally design antibodies to enable them to bind virtually any chosen disordered epitope in a protein. The procedure consists in the sequence-based design of one or more complementary peptides targeting a selected disordered epitope and the subsequent grafting of such peptides on an antibody scaffold. We illustrate the method by designing six single-domain antibodies to bind different epitopes within three disease-related intrinsically disordered proteins and peptides (α-synuclein, Aβ42, and IAPP). Our results show that all these designed antibodies bind their targets with good affinity and specificity. As an example of an application, we show that one of these antibodies inhibits the aggregation of α-synuclein at substoichiometric concentrations and that binding occurs at the selected epitope. Taken together, these results indicate that the design strategy that we propose makes it possible to obtain antibodies targeting given epitopes in disordered proteins or protein regions.

Targeting disordered proteins with small molecules using entropy.

The human proteome includes many disordered proteins. Although these proteins are closely linked with a range of human diseases, no clinically approved drug targets them in their monomeric forms. This situation arises, at least in part, from the current lack of understanding of the mechanisms by which small molecules bind proteins that do not fold into well-defined conformations. To explore possible solutions to this problem, we discuss quite generally how an overall decrease in the free energy associated with intermolecular binding can originate from different combinations of enthalpic and entropic contributions. We then consider more specifically a mechanism of binding by which small molecules can affect the conformational space of a disordered protein by creating an entropic expansion in which more conformations of the protein become populated.

A protein homeostasis signature in healthy brains recapitulates tissue vulnerability to Alzheimer’s disease

A tissue vulnerability map based on Aβ and tau homeostasis in healthy brains predicts the staging of Alzheimer’s disease. In Alzheimer’s disease, aggregates of Aβ and tau in amyloid plaques and neurofibrillary tangles spread progressively across brain tissues following a characteristic pattern, implying a tissue-specific vulnerability to the disease. We report a transcriptional analysis of healthy brains and identify an expression signature that predicts—at ages well before the typical onset—the tissue-specific progression of the disease. We obtain this result by finding a quantitative correlation between the histopathological staging of the disease and the expression patterns of the proteins that coaggregate in amyloid plaques and neurofibrillary tangles, together with those of the protein homeostasis components that regulate Aβ and tau. Because this expression signature is evident in healthy brains, our analysis provides an explanatory link between a tissue-specific environmental risk of protein aggregation and a corresponding vulnerability to Alzheimer’s disease.

Understanding the frustration arising from the competition between function, misfolding, and aggregation in a globular protein

Significance The amino acid sequence of a protein encodes a wide range of different properties, including function, folding, and avoidance of aggregation. The resulting requirements on the sequence may be in conflict with each other, thus creating the possibility of misfolding and dysfunction. To investigate possible mechanisms whereby such unwanted outcomes can be prevented, we study the folding process of frataxin, a protein whose aberrant folding is associated with Friedreich’s ataxia. Our results indicate that the regions prone to misfolding are highly protected against aggregation along the folding pathway of this protein. Folding and function may impose different requirements on the amino acid sequences of proteins, thus potentially giving rise to conflict. Such a conflict, or frustration, can result in the formation of partially misfolded intermediates that can compromise folding and promote aggregation. We investigate this phenomenon by studying frataxin, a protein whose normal function is to facilitate the formation of iron–sulfur clusters but whose mutations are associated with Friedreich’s ataxia. To characterize the folding pathway of this protein we carry out a Φ-value analysis and use the resulting structural information to determine the structure of the folding transition state, which we then validate by a second round of rationally designed mutagenesis. The analysis of the transition-state structure reveals that the regions involved in the folding process are highly aggregation-prone. By contrast, the regions that are functionally important are partially misfolded in the transition state but highly resistant to aggregation. Taken together, these results indicate that in frataxin the competition between folding and function creates the possibility of misfolding, and that to prevent aggregation the amino acid sequence of this protein is optimized to be highly resistant to aggregation in the regions involved in misfolding.

Simultaneous quantification of protein order and disorder

Nuclear magnetic resonance spectroscopy is transforming our views of proteins by revealing how their structures and dynamics are closely intertwined to underlie their functions and interactions. Compelling representations of proteins as statistical ensembles are uncovering the presence and biological relevance of conformationally heterogeneous states, thus gradually making it possible to go beyond the dichotomy between order and disorder through more quantitative descriptions that span the continuum between them.

Selective targeting of primary and secondary nucleation pathways in Aβ42 aggregation using a rational antibody scanning method

A rational approach enables the almost complete suppression of nucleation events in Aβ42 aggregation using designed antibodies. Antibodies targeting Aβ42 are under intense scrutiny because of their therapeutic potential for Alzheimer’s disease. To enable systematic searches, we present an “antibody scanning” strategy for the generation of a panel of antibodies against Aβ42. Each antibody in the panel is rationally designed to target a specific linear epitope, with the selected epitopes scanning the Aβ42 sequence. By screening in vitro the panel to identify the specific microscopic steps in the Aβ42 aggregation process influenced by each antibody, we identify two antibodies that target specifically the primary and the secondary nucleation steps, which are key for the production of Aβ42 oligomers. These two antibodies act, respectively, to delay the onset of aggregation and to block the proliferation of aggregates, and correspondingly reduce the toxicity in a Caenorhabditis elegans model overexpressing Aβ42. These results illustrate how the antibody scanning method described here can be used to readily obtain very small antibody libraries with extensive coverage of the sequences of target proteins.

Rational design of mutations that change the aggregation rate of a protein while maintaining its native structure and stability

A wide range of human diseases is associated with mutations that, destabilizing proteins native state, promote their aggregation. However, the mechanisms leading from folded to aggregated states are still incompletely understood. To investigate these mechanisms, we used a combination of NMR spectroscopy and molecular dynamics simulations to compare the native state dynamics of Beta-2 microglobulin (β2m), whose aggregation is associated with dialysis-related amyloidosis, and its aggregation-resistant mutant W60G. Our results indicate that W60G low aggregation propensity can be explained, beyond its higher stability, by an increased average protection of the aggregation-prone residues at its surface. To validate these findings, we designed β2m variants that alter the aggregation-prone exposed surface of wild-type and W60G β2m modifying their aggregation propensity. These results allowed us to pinpoint the role of dynamics in β2m aggregation and to provide a new strategy to tune protein aggregation by modulating the exposure of aggregation-prone residues.