Interplay between partner and ligand facilitates the folding and binding of an intrinsically disordered protein.

Protein-protein interactions are at the heart of regulatory and signaling processes in the cell. In many interactions, one or both proteins are disordered before association. However, this disorder in the unbound state does not prevent many of these proteins folding to a well-defined, ordered structure in the bound state. Here we examine a typical system, where a small disordered protein (PUMA, p53 upregulated modulator of apoptosis) folds to an α-helix when bound to a groove on the surface of a folded protein (MCL-1, induced myeloid leukemia cell differentiation protein). We follow the association of these proteins using rapid-mixing stopped flow, and examine how the kinetic behavior is perturbed by denaturant and carefully chosen mutations. We demonstrate the utility of methods developed for the study of monomeric protein folding, including β-Tanford values, Leffler α, Φ-value analysis, and coarse-grained simulations, and propose a self-consistent mechanism for binding. Folding of the disordered protein before binding does not appear to be required and few, if any, specific interactions are required to commit to association. The majority of PUMA folding occurs after the transition state, in the presence of MCL-1. We also examine the role of the side chains of folded MCL-1 that make up the binding groove and find that many favor equilibrium binding but, surprisingly, inhibit the association process

Coupled folding-binding versus docking: A lattice model study

Using a simple hydrophobic/polar protein model, we perform a Monte Carlo study of the thermodynamics and kinetics of binding to a target structure for two closely related sequences, one of which has a unique folded state while the other is unstructured. We obtain significant differences in their binding behavior. The stable sequence has rigid docking as its preferred binding mode, while the unstructured chain tends to first attach to the target and then fold. The free-energy profiles associated with these two binding modes are compared.Comment: 17 pages, 7 figures (to appear in J. Chem. Phys.

Structural insights into the autoregulation and cooperativity of the human transcription factor Ets-2

Ets-2, like its closely related homologue Ets-1, is a member of the Ets family of DNA binding transcription factors. Both proteins are subject to multiple levels of regulation of their DNA binding and transactivation properties. One such regulatory mechanism is the presence of an autoinhibitory module, which in Ets-1 allosterically inhibits the DNA binding activity. This inhibition can be relieved by interaction with protein partners or cooperative binding to closely separated Ets binding sites in a palindromic arrangement. In this study we describe the 2.5 Å resolution crystal structure of a DNA complex of the Ets-2 Ets domain. The Ets domain crystallized with two distinct species in the asymmetric unit, which closely resemble the autoinhibited and DNA bound forms of Ets-1. This discovery prompted us to re-evaluate the current model for the autoinhibitory mechanism and the structural basis for cooperative DNA binding. In contrast to Ets-1, in which the autoinhibition is caused by a combination of allosteric and steric mechanisms, we were unable to find clear evidence for the allosteric mechanism in Ets-2. We also demonstrated two possibly distinct types of cooperative binding to substrates with Ets binding motifs separated by four and six base pairs and suggest possible molecular mechanisms for this behavior

Statistical mechanics models in protein association problems

Doctor of PhilosophyDepartment of PhysicsJeremy D. SchmitProtein-Protein interactions can lead to disordered states such as precipitates or gels, or to ordered states such as crystals or microtubules. In order to study the different natures of protein-protein interactions we have developed statistical mechanics models in order to interpret the varied behavior of different protein systems. The main point will be to develop theoretical models that infer the time a length scales that characterize the dynamics of the systems analyzed. This approach seek to facilitate a connection to simulations and experiments, where a high resolution analysis in length and time is possible, since the theories can provide insights about the relevant time and length scales, and also about issues that can appear when studying these systems. The first system studied is monoclonal antibodies in solution. Antibody solutions deviate from the dynamical and rheological response expected for globular proteins, especially as volume fraction is increased. Experimental evidence shows that antibodies can reversibly bind to each other via F[subscript]ab and F[subscript]c domains, and form larger structures (clusters) of several antibodies. Here we present a microscopic equilibrium model to account for the distribution of cluster sizes. Antibody clusters are modeled as polymers that can grow via reversible bonds either between two F[subscript]ab domains or between a F[subscript]ab and a F[subscript]c. We propose that the dynamical and rheological behavior is determined by molecular entanglements of the clusters. This entanglement does not occur at low concentrations where antibody-antibody binding contributes to the viscosity by increasing the effective size of the particles. The model explains the observed shear-thinning behavior of antibody solutions. The second system is protein condensates inside living cells. Biomolecule condensates appear throughout the cell serving a wide variety of functions, but it is not clear how functional properties show in the concentrated network inside the condensate droplets. Here we model disordered proteins as linear polymers formed by "stickers" evenly spaced by "spacers". The spacing between stickers gives rise to different network toplogies inside the condensate droplet, determining distinguishing properties such us density and client binding. The third system is protein-protein binding in a salt solutions. Biomolecular simulations are typically performed in an aqueous environment where the number of ions remains fixed for the duration of the simulation, generally with a number of salt pairs intended to match the macroscopic salt concentration. In contrast, real biomolecules experience local ion environments where the salt concentration is dynamic and may differ from bulk. We develop a statistical mechanics model to account for fluctuations of ions concentrations, and study how it affects the free energy of protein-protein binding

Confinement Effects on the Kinetics and Thermodynamics of Protein Dimerization

In the cell, protein complexes form relying on specific interactions between their monomers. Excluded volume effects due to molecular crowding would lead to correlations between molecules even without specific interactions. What is the interplay of these effects in the crowded cellular environment? We study dimerization of a model homodimer both when the mondimers are free or tethered to each other. We consider a structured environment: Two monomers first diffuse into a cavity of size $L$ and then fold and bind within the cavity. The folding and binding are simulated using molecular dynamics based on a simplified topology based model. The {\it confinement} in the cell is described by an effective molecular concentration $C \sim L^{-3}$. A two-state coupled folding and binding behavior is found. We show the maximal rate of dimerization occurred at an effective molecular concentration $C^{op}\simeq 1m$M which is a relevant cellular concentration. In contrast, for tethered chains the rate keeps at a plateau when $CC^{op}$. For both the free and tethered cases, the simulated variation of the rate of dimerization and thermodynamic stability with effective molecular concentration agrees well with experimental observations. In addition, a theoretical argument for the effects of confinement on dimerization is also made

Splice variants of DOMINO control Drosophila circadian behavior and pacemaker neuron maintenance.

Circadian clocks control daily rhythms in behavior and physiology. In Drosophila, the small ventral lateral neurons (sLNvs) expressing PIGMENT DISPERSING FACTOR (PDF) are the master pacemaker neurons generating locomotor rhythms. Despite the importance of sLNvs and PDF in circadian behavior, little is known about factors that control sLNvs maintenance and PDF accumulation. Here, we identify the Drosophila SWI2/SNF2 protein DOMINO (DOM) as a key regulator of circadian behavior. Depletion of DOM in circadian neurons eliminates morning anticipatory activity under light dark cycle and impairs behavioral rhythmicity in constant darkness. Interestingly, the two major splice variants of DOM, DOM-A and DOM-B have distinct circadian functions. DOM-A depletion mainly leads to arrhythmic behavior, while DOM-B knockdown lengthens circadian period without affecting the circadian rhythmicity. Both DOM-A and DOM-B bind to the promoter regions of key pacemaker genes period and timeless, and regulate their protein expression. However, we identify that only DOM-A is required for the maintenance of sLNvs and transcription of pdf. Lastly, constitutive activation of PDF-receptor signaling rescued the arrhythmia and period lengthening of DOM downregulation. Taken together, our findings reveal that two splice variants of DOM play distinct roles in circadian rhythms through regulating abundance of pacemaker proteins and sLNvs maintenance

MAP7 regulates axon morphogenesis by recruiting kinesin-1 to microtubules and modulating organelle transport.

Neuronal cell morphogenesis depends on proper regulation of microtubule-based transport, but the underlying mechanisms are not well understood. Here, we report our study of MAP7, a unique microtubule-associated protein that interacts with both microtubules and the motor protein kinesin-1. Structure-function analysis in rat embryonic sensory neurons shows that the kinesin-1 interacting domain in MAP7 is required for axon and branch growth but not for branch formation. Also, two unique microtubule binding sites are found in MAP7 that have distinct dissociation kinetics and are both required for branch formation. Furthermore, MAP7 recruits kinesin-1 dynamically to microtubules, leading to alterations in organelle transport behaviors, particularly pause/speed switching. As MAP7 is localized to branch sites, our results suggest a novel mechanism mediated by the dual interactions of MAP7 with microtubules and kinesin-1 in the precise control of microtubule-based transport during axon morphogenesis