Frustration in the energy landscapes of multidomain protein misfolding

2016

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Aplysia cytoplasmic polyadenylation element binding (CPEB) protein, a translational regulator that recruits mRNAs and facilitates translation, has been shown to be a key component in the formation of long-term memory. Experimental data show that CPEB exists in at least a low-molecular weight coiled-coil oligomeric form and an amyloid fiber form involving the Q-rich domain (CPEB-Q). Using a coarse-grained energy landscape model, we predict the structures of the low-molecular weight oligomeric form and the dynamics of their transitions to the β-form. Up to the decamer, the oligomeric structures are predicted to be coiled coils. Free energy profiles confirm that the coiled coil is the most stable form for dimers and trimers. The structural transition from α to β is shown to be concentration dependent, with the transition barrier decreasing with increased concentration. We observe that a mechanical pulling force can facilitate the α-helix to β-sheet (α-to-β) transition by lowering the free energy barrier between the two forms. Interactome analysis of the CPEB protein suggests that its interactions with the cytoskeleton could provide the necessary mechanical force. We propose that, by exerting mechanical forces on CPEB oligomers, an active cytoskeleton can facilitate fiber formation. This mechanical catalysis makes possible a positive feedback loop that would help localize the formation of CPEB fibers to active synapse areas and mark those synapses for forming a long-term memory after the prion form is established. The functional role of the CPEB helical oligomers in this mechanism carries with it implications for targeting such species in neurodegenerative diseases.long-term memory | mechanical prion | protein aggregation | Q-rich protein I t is widely believed that learning involves the modification in number, strength, and structure of specific localized synaptic connections. Although short-term memory formation occurs without protein synthesis, establishing long-term memory (LTM) involves protein synthesis localized at the synapse area, thus requiring a stable translational regulatory system that activates mRNA and protein synthesis in the synapse (1-3). It has long been recognized that the relatively short half-life of most proteins in eukaryotic cells (4) poses questions about the long timescales over which memories can be retained. It has been suggested that forming a very stable prion could provide a mechanism for achieving memory longevity (5, 6). An excellent candidate species has emerged from the works of Kandel and coworkers (1-3) and Lindquist and coworker (6) on cytoplasmic polyadenylation element binding (CPEB). It has been established, in Aplysia, that Aplysia cytoplasmic polyadenylation element binding (ApCPEB) activates mRNA and mediates synaptic protein synthesis for at least 72 h and that it does so by taking on a functional prion-like form (3, 7). Forming the prion is, thus, a key element in LTM formation and maintenance.Prions were first proposed as protein-only infectious particles causing Creu...

Section: Significancementioning

confidence: 99%

Energy landscapes of a mechanical prion and their implications for the molecular mechanism of long-term memory

Chen

Zheng

2016

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“…To overcome these problems, we use coarse-grained simulations of the aggregation of HTT exon 1-encoded fragments that use the AWSEM force field. While being efficient to simulate, the AWSEM force field can predict the structures of protein monomers (22-24) and predict details of assembly into oligomers (9,(25)(26)(27)(28). We have already used the model to explore the detailed mechanisms of aggregation of pure polyQ peptides (9) and the peptide implicated in Alzheimer's disease (28), Aβ40.…”

mentioning

confidence: 99%

Aggregation landscapes of Huntingtin exon 1 protein fragments and the critical repeat length for the onset of Huntington’s disease

Chen

2017

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Huntington's disease (HD) is a neurodegenerative disease caused by an abnormal expansion in the polyglutamine (polyQ) track of the Huntingtin (HTT) protein. The severity of the disease depends on the polyQ repeat length, arising only in patients with proteins having 36 repeats or more. Previous studies have shown that the aggregation of N-terminal fragments (encoded by HTT exon 1) underlies the disease pathology in mouse models and that the HTT exon 1 gene product can self-assemble into amyloid structures. Here, we provide detailed structural mechanisms for aggregation of several protein fragments encoded by HTT exon 1 by using the associative memory, water-mediated, structure and energy model (AWSEM) to construct their free energy landscapes. We find that the addition of the N-terminal 17-residue sequence (NT 17 ) facilitates polyQ aggregation by encouraging the formation of prefibrillar oligomers, whereas adding the C-terminal polyproline sequence (P 10 ) inhibits aggregation. The combination of both terminal additions in HTT exon 1 fragment leads to a complex aggregation mechanism with a basic core that resembles that found for the aggregation of pure polyQ repeats using AWSEM. At the extrapolated physiological concentration, although the grand canonical free energy profiles are uphill for HTT exon 1 fragments having 20 or 30 glutamines, the aggregation landscape for fragments with 40 repeats has become downhill. This computational prediction agrees with the critical length found for the onset of HD and suggests potential therapies based on blocking early binding events involving the terminal additions to the polyQ repeats.Huntington's disease | aggregation | solubility | aggregation free energy landscape | critical length H untingtin (HTT) is a huge protein (3,100 amino acid residues) that has been implicated in a variety of physiological functions (1, 2). Having an expanded polyglutamine (polyQ) region of 36 or more glutamine residues in the N terminus of HTT leads to Huntington's disease as witnessed by the deposition of large intracellular protein aggregates or inclusion bodies, which are comprised primarily of N-terminal fragments coded by the exon 1 sequence of the mutant HTT (2-5). These N-terminal fragments, each composed of an N-terminal 17-residue sequence (NT17), a polyQ sequence that has expanded in length, and a proline-rich region afterward, originate from proteolysis of HTT (2, 3). The aggregation of the HTT exon 1 product is, therefore, believed to cause Huntington's disease. Clinical studies have shown an inverse correlation between polyQ length and age of disease onset (5). By implicating polymer physics in the disease process, this regularity has intrigued biophysicists for decades.Expanded polyQ sequences, more generally, are associated with nine known neurodegenerative diseases (4). Biophysical chemists have, therefore, focused on first understanding the aggregation of pure polyQ peptides. The rate of aggregation of polyQ peptides is length-dependent, and primary nucleation is rate-limiti...

“…Coarse-grained Hamiltonians that optimize δE/ΔE for a training set of proteins yield energy landscapes with transferable parameters have been shown to successfully predict structures of monomers with quite different sequences and also to predict dimer interfaces of globular proteins de novo (12,19,20). AWSEM's transferable tertiary interactions also equip the model to investigate problems such as the complex energy landscapes of designed proteins and multidomain protein misfolding as well as the mechanism of the initiation of aggregation (21)(22)(23).…”

Section: Ingredients Of Awsem-membranementioning

confidence: 99%

Predictive energy landscapes for folding α-helical transmembrane proteins

Kim

Schafer

2014

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We explore the hypothesis that the folding landscapes of membrane proteins are funneled once the proteins' topology within the membrane is established. We extend a protein folding model, the associative memory, water-mediated, structure, and energy model (AWSEM) by adding an implicit membrane potential and reoptimizing the force field to account for the differing nature of the interactions that stabilize proteins within lipid membranes, yielding a model that we call AWSEM-membrane. Once the protein topology is set in the membrane, hydrophobic attractions play a lesser role in finding the native structure, whereas polar-polar attractions are more important than for globular proteins. We examine both the quality of predictions made with AWSEM-membrane when accurate knowledge of the topology and secondary structure is available and the quality of predictions made without such knowledge, instead using bioinformatically inferred topology and secondary structure based on sequence alone. When no major errors are made by the bioinformatic methods used to assign the topology of the transmembrane helices, these two types of structure predictions yield roughly equivalent quality structures. Although the predictive energy landscape is transferable and not structure based, within the correct topological sector we find the landscape is indeed very funneled: Thermodynamic landscape analysis indicates that both the total potential energy and the contact energy decrease as native contacts are formed. Nevertheless the near symmetry of different helical packings with respect to native contact formation can result in multiple packings with nearly equal thermodynamic occupancy, especially at temperatures just below collapse.energy landscape theory | molecular dynamics T he folding of globular proteins has come to be well understood starting from Anfinsen's thermodynamic hypothesis (1), by means of statistical energy landscape theory (2-5) and its principle of minimal frustration. Evolution selects the sequences of most globular proteins so that folding is, by and large, thermodynamically controlled and the landscape is dominated by the interactions between residues that are close together in the folded state, i.e., the native contacts. In vivo folding of α-helical transmembrane proteins differs from the usually autonomous folding of globular proteins in that, during translation, another actor, the translocon, generally assists the nascent chain in either translocating across or integrating peptides into the lipid membrane. Topology, by which we mean the "specification of the number of transmembrane helices and their in and/or out orientations across the membrane" (ref. 6, p. 909), in vivo is thus initially established cotranslationally with few exceptions. Large barriers between alternate topologies once the protein is folded, along with the involvement of the translocon catalyst, suggest a role for kinetic control in folding of α-helical transmembrane proteins. In light of these differences, what aspects of energy landscape theory,...