Protein Folding and Structure Prediction from the Ground Up II: AAWSEM for α/β Proteins

Chen, Mingchen; Lin, Xin; Lu, Wei; Onuchic, José N.; Wolynes, Peter G.

doi:10.1021/acs.jpcb.6b09347

Cited by 23 publications

(40 citation statements)

References 46 publications

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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)(23)(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.…”

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confidence: 99%

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

Chen

Wolynes

2017

Proc. Natl. Acad. Sci. U.S.A.

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104

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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...

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confidence: 99%

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

Chen

Wolynes

2017

Proc. Natl. Acad. Sci. U.S.A.

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104

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“…The predictions of T251, 256b, and 2z15 are topologically correct, although there are some deviations in the secondary structure relative to the experimental structure. Adding evolutionary information to AWSEM yields a much better prediction for T251 than AWSEM or AAWSEM . The structure for T0766 is largely correct except for the fact that one of the α‐helices is not fully formed and one of the β‐strands is not fully formed.…”

Section: Resultsmentioning

confidence: 96%

“…Coarse‐grained models of proteins can overcome the computational expense of using more detailed atomistic models . Our group has developed a series of coarse‐grained protein force fields that have been shown to accurately predict protein structures from single sequences alone, without exploiting structural knowledge about homologues . The optimization of the coarse‐grained force field takes advantage of insights from energy landscape theory to learn both the form of the energy function as well as the corresponding parameters in the coarse‐grained force field.…”

Section: Introductionmentioning

confidence: 99%

Protein structure prediction: making AWSEM AWSEM‐ER by adding evolutionary restraints

2017

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Protein sequences have evolved to fold into functional structures, resulting in families of diverse protein sequences that all share the same overall fold. One can harness protein family sequence data to infer likely contacts between pairs of residues. In the current study, we combine this kind of inference from coevolutionary information with a coarse-grained protein force field ordinarily used with single sequence input, the Associative memory, Water mediated, Structure and Energy Model (AWSEM), to achieve improved structure prediction. The resulting Associative memory, Water mediated, Structure and Energy Model with Evolutionary Restraints (AWSEM-ER) yields a significant improvement in the quality of protein structure prediction over the single sequence prediction from AWSEM when a sufficiently large number of homologous sequences are available. Free energy landscape analysis shows that the addition of the evolutionary term shifts the free energy minimum to more native-like structures, which explains the improvement in the quality of structures when performing predictions using simulated annealing. Simulations using AWSEM without coevolutionary information have proved useful in elucidating not only protein folding behavior, but also mechanisms of protein function. The success of AWSEM-ER in de novo structure prediction suggests that the enhanced model opens the door to functional studies of proteins even when no experimentally solved structures are available.

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“…Recently, we developed a multi-scale atomistic AWSEM model (AAWSEM) [23], which harnesses the power of all-atom explicit-solvent simulations to directly generate atomistic structures for use as associative memory terms of an AWSEM simulation. AAWSEM has been shown to be able to reliably fold both α-exclusive proteins [23] and α/β proteins [24]. In particular, AAWSEM is especially useful for investigating dynamics of disordered proteins such as PAGE4 because the lack of known structure limits the utility of the AWSEM model.…”

Section: Introductionmentioning

confidence: 99%

PAGE4 and Conformational Switching: Insights from Molecular Dynamics Simulations and Implications for Prostate Cancer

Lin

Roy

Jolly

et al. 2018

Preprint

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Prostate-Associated Gene 4 (PAGE4) is a disordered protein implicated in the progression of prostate cancer. PAGE4 can be phosphorylated at two residue sites by Homeodomain-Interacting Protein Kinase 1 (HIPK1) to facilitate its binding to the Activator Protein-1 (AP-1) transcription factor. Contrarily, a further hyperphosphorylation of PAGE4 by CDC-Like Kinase 2 (CLK2) reduces its binding affinity to AP-1, thus affecting androgen receptor (AR) activity levels downstream. Both Small-angle X-ray scattering (SAXS) and Single molecule fluorescence resonance energy transfer (smFRET) experiments show an expansion of PAGE4 upon hyperphosphorylation and a more significant increase in size in its N-terminal half than that in its C terminus.To understand the underlying mechanism behind this structural transition, we performed a set 1 . 14, 2018; of constant temperature molecular dynamics simulations (MDS) with Atomistic AWSEM -a multi-scale model combining detailed atomistic and coarse-grained simulation approaches. By simulating PAGE4 in its wildtype and phosphorylated forms, our simulations reveal that electrostatic interaction drives a transient formation of a N-terminal loop, which causes the change of size in different forms of PAGE4. Phosphorylation also changes the preference of secondary structure formation in different forms of PAGE4, which signifies transition between states that have different degrees of disorder. Finally, we construct a mechanism-based mathematical model capturing the interactions of different forms of PAGE4 with the AP-1 and AR, a key therapeutic target in prostate cancer. Our model predicts intracellular oscillatory dynamics of HIPK1-PAGE4, CLK2-PAGE4 and AR activity, indicating phenotypic heterogeneity in an isogenic cell population. Thus, conformational switching among different forms of PAGE4 may potentially affect the efficiency of therapeutic targeting of AR. CC-BY-NC-ND 4.0 International licenseIt is made available under a (which was not peer-reviewed) is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. The copyright holder for this preprint . http://dx.doi.org/10.1101/264010 doi: bioRxiv preprint first posted online Feb.

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Protein Folding and Structure Prediction from the Ground Up II: AAWSEM for α/β Proteins

Cited by 23 publications

References 46 publications

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

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

Protein structure prediction: making AWSEM AWSEM‐ER by adding evolutionary restraints

PAGE4 and Conformational Switching: Insights from Molecular Dynamics Simulations and Implications for Prostate Cancer

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