Polycation-π Interactions Are a Driving Force for Molecular Recognition by an Intrinsically Disordered Oncoprotein Family

Molecular recognition by intrinsically disordered proteins (IDPs) commonly involves specific localized contacts and target-induced disorder to order transitions. However, some IDPs remain disordered in the bound state, a phenomenon coined "fuzziness", often characterized by IDP polyvalency, sequence-insensitivity and a dynamic ensemble of disordered bound-state conformations. Besides the above general features, specific biophysical models for fuzzy interactions are mostly lacking. The transcriptional activation domain of the Ewing's Sarcoma oncoprotein family (EAD) is an IDP that exhibits many features of fuzziness, with multiple EAD aromatic side chains driving molecular recognition. Considering the prevalent role of cation-π interactions at various protein-protein interfaces, we hypothesized that EAD-target binding involves polycation- π contacts between a disordered EAD and basic residues on the target. Herein we evaluated the polycation-π hypothesis via functional and theoretical interrogation of EAD variants. The experimental effects of a range of EAD sequence variations, including aromatic number, aromatic density and charge perturbations, all support the cation-π model. Moreover, the activity trends observed are well captured by a coarse-grained EAD chain model and a corresponding analytical model based on interaction between EAD aromatics and surface cations of a generic globular target. EAD-target binding, in the context of pathological Ewing's Sarcoma oncoproteins, is thus seen to be driven by a balance between EAD conformational entropy and favorable EAD-target cation-π contacts. Such a highly versatile mode of molecular recognition offers a general conceptual framework for promiscuous target recognition by polyvalent IDPs. © 2013 Song et al

Methods for protein complex prediction and their contributions towards understanding the organization, function and dynamics of complexes

Complexes of physically interacting proteins constitute fundamental functional units responsible for driving biological processes within cells. A faithful reconstruction of the entire set of complexes is therefore essential to understand the functional organization of cells. In this review, we discuss the key contributions of computational methods developed till date (approximately between 2003 and 2015) for identifying complexes from the network of interacting proteins (PPI network). We evaluate in depth the performance of these methods on PPI datasets from yeast, and highlight challenges faced by these methods, in particular detection of sparse and small or sub- complexes and discerning of overlapping complexes. We describe methods for integrating diverse information including expression profiles and 3D structures of proteins with PPI networks to understand the dynamics of complex formation, for instance, of time-based assembly of complex subunits and formation of fuzzy complexes from intrinsically disordered proteins. Finally, we discuss methods for identifying dysfunctional complexes in human diseases, an application that is proving invaluable to understand disease mechanisms and to discover novel therapeutic targets. We hope this review aptly commemorates a decade of research on computational prediction of complexes and constitutes a valuable reference for further advancements in this exciting area.Comment: 1 Tabl

The Extraction of Community Structures from Publication Networks to Support Ethnographic Observations of Field Differences in Scientific Communication

The scientific community of researchers in a research specialty is an important unit of analysis for understanding the field specific shaping of scientific communication practices. These scientific communities are, however, a challenging unit of analysis to capture and compare because they overlap, have fuzzy boundaries, and evolve over time. We describe a network analytic approach that reveals the complexities of these communities through examination of their publication networks in combination with insights from ethnographic field studies. We suggest that the structures revealed indicate overlapping sub- communities within a research specialty and we provide evidence that they differ in disciplinary orientation and research practices. By mapping the community structures of scientific fields we aim to increase confidence about the domain of validity of ethnographic observations as well as of collaborative patterns extracted from publication networks thereby enabling the systematic study of field differences. The network analytic methods presented include methods to optimize the delineation of a bibliographic data set in order to adequately represent a research specialty, and methods to extract community structures from this data. We demonstrate the application of these methods in a case study of two research specialties in the physical and chemical sciences.Comment: Accepted for publication in JASIS

Molecular mechanisms of folding of intrinsically disordered proteins

In this thesis, we studied the interaction between the intrinsically disordered domain of the nucleoprotein (N) of Measles virus (MeV), NTAIL, and its partner XD, the X domain of the MeV phosphoprotein (P). It had been previously shown that the α-MoRE (residues 489-506) of NTAIL undergoes an α-helical folding after binding to XD (induced fit mechanism) while regions flanking the α-MoRE remain disordered (fuzzy) in the complex. The fuzzy appendage preceding the α-MoRE was shown to decrease the binding affinities towards XD and the rate of folding of the α-MoRE. In this thesis, by producing NTAIL variants (single-site variants, truncation variants, artificial variants) and performing kinetic experiments of the interaction with XD, we studied the folding after binding mechanism of NTAIL at the single residue level, and investigated the mechanisms through which the fuzzy region hampers the binding affinity and the folding rate of the α-MoRE. We concluded that the central part of the helix is responsible for the initial interactions driving the binding with XD. Moreover, we found that the fuzzy region causes a decrease in the folding rate of the α-MoRE through a combination of entropic and enthalpic effects. We also studied the interaction between NTAIL and a variant of XD, I504A, that populates only the native state. These studies showed that both the binding and the folding steps of the NTAIL-XD interaction are highly dependent on the shape of XD, suggesting that this IDP folds by heterogeneous nucleation via a mechanism induced by the shape of the partner (templated folding)

Opening-up the objective function: choice behavior and economic and non-economic variables—core and marginal altruism

A revised model of the preference function is presented incorporating utility maximizing acts of material self-sacrifice. This model incorporates neoclassical and behavioral arguments, allowing for the stylized fact that economic agents are motivated by both material and non-material incentives. Given such a preference function, choice behavior is modeled as a function of relative opportunity costs (price) and real income. Preferences are determined by a variety of variables inclusive of social capital and education. There is therefore a core preference based upon non-economic variables and a ‘marginal' component which is a function of conventional economic variables. The relative importance of these two components in determinating choice behavior is an empirical question. Building upon conventional tools, a demand curve for moral acts is derived and underlying income and substitution effects discussed. Empirical evidence from the tipping literature is used to illustrate the model.

A nanny model for intrinsically disordered proteins

Proteins without a well-defined tertiary structure are intrinsically unstable and are prone to degradation by the 20S proteasome. In my thesis, I investigate the protection mechanisms of intrinsically disordered (ID) protein regions via protein interactions using the AP-1 complex as a model system. AP-1 is composed of c-Fos and c-Jun proteins, out of which c-Fos has a shorter half-life than c-Jun. Interactions by c-Jun were shown to prolong the lifetime of c-Fos, leading to the proposal of the nanny model. This mechanism, where weak protein interactions protect unstructured regions without an induced folding, however, has never been probed directly. Here I investigate the nature of the interactions of c-Fos with c-Jun and how changes in disordered regions contribute to changes in half-life. I use mutational analysis to provide insight into changes in degradation rate as a function of the binding affinity in the bound form with c-Jun. I designed five mutants at the structured regions of c-Fos affecting specific contact sites (L165V, L172V) or charge separation (E175D, E189D, K190R) with c-Jun of which both modulate c-Fos turnover, proportionally to their impact on binding affinity. Interestingly, removal of the disordered region in the complex beyond the structured domain is observed to decrease c-Fos half-life indicating their role in the stability of the complex. The finding suggests that the protein turnover by the 20S proteasome can be fine-tuned by both structured and unstructured regions between c-Fos and c-Jun, consistent with the proposed 'nanny' model. These results highlight a novel aspect of disordered regions present in the bound form (fuzziness) in regulating protein half-life via fine-tuning the association rates between the two proteins. First, it demonstrates that the protection of disordered regions from degradation could be achieved without inducing a stable structure as confirmed by ECD spectroscopy. Binding to a partner generates a fuzzy complex, where fuzzy regions in protein complexes can serve as a nonspecific transient anchor. Second, the protection of disordered regions can be achieved with many binding configurations in the bound state without decreasing the conformational entropy. Thus, the protective role of fuzzy interactions from the 20S proteasome could also provide a possible explanation for how low-complexity sequence motifs involved in higher-order protein structures might serve as selective inhibitors of proteolysis.d