Structural predictions for curli amyloid fibril subunits CsgA and CsgB

DeBenedictis, Elizabeth P.; Ma, Dan; Keten, Sinan

doi:10.1039/c7ra08030a

Cited by 38 publications

(47 citation statements)

References 99 publications

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“…Our model results in a β-solenoid structure, Fig. 8c DeBenedictis et al in 2017 presented and discussed ab initio models for the Curlin repeats family members CsgA and CsgB [38], their best models is in agreement with our model (a direct comparison is difficult as the coordinates is not available of their model). The model is furthermore confirmed by the partial structure of the repeat units of CsgA published by Perov et al [39] where they crystallize in parallel β-sheets with individual units situated perpendicular to the fibril axis (corresponding PDB IDs are 6G8C, 6G8D, 6G8E).…”

Section: Curlin Repeats Familysupporting

confidence: 80%

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Accurate contact-based modelling of repeat proteins predicts the structure of Curlin and SPW repeats

Bassot

Elofsson

2019

Preprint

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Repeat proteins are an abundant class in eukaryotic proteomes. They are involved in many eukaryotic specific functions, including signalling. For many of these families, the structure is not known. Recently, it has been shown that the structure of many protein families can be predicted by using contact predictions from direct coupling analysis and deep learning.However, their unique sequence features present in repeat proteins is a challenge for contact predictions DCA-methods. Here, we show that using the deep learning-based PconsC4 is more effective for predicting both intra and interunit contacts among a comprehensive set of repeat proteins. In a benchmark dataset of 819 repeat proteins about one third can be correctly modelled and among 51 PFAM families lacking a protein structure, we produce models of five families with estimated high accuracy.Structure Prediction of Repeats proteomes. Their primary sequence present repetition in the amino acid sequences that origin structures with repeated folds/domains. Although the repeated units are easy to be recognized in primary sequence, often structure information are missing. Here we used contact prediction for predicting the structure of repeats protein directly from their primary sequences. We benchmark our method on a dataset comprehensive of all the known repeated structures. We evaluate the contact predictions and the obtained models set for different classes of proteins and different lengths of the target, and we benchmark the quality assessment of the models on repeats proteins. Finally, we applied the methods on the repeat PFAM families missing of resolved structures, five of them modelled with high accuracy.A classification of repeat proteins was proposed by Kajava [12,13] based on the length of the repeat units and the tertiary structure of the repeat units. According to Kajava's classification, there are five classes of repeat proteins. However, in this study, we ignore class I and II because there are no available structures for class I, and class II structures are folded in a coiled-coil structure easy to be predicted. Moreover, the extreme amino acid 2 4

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Section: Curlin Repeats Familysupporting

confidence: 80%

“…subclasses as classified in repeatsDB 2.0 [14] Class III is dominated by solenoid structures (Figure1 III.1, III.2 III.3) [13], and there is a wide range in the numbers of units (from 4 to 38). Also, the length of the individual unit is widely variable, e.g.…”

Section: Figure1 Repeats Proteins Classification Representation Ofmentioning

confidence: 99%

Accurate contact-based modelling of repeat proteins predicts the structure of Curlin and SPW repeats

Bassot

Elofsson

2019

Preprint

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“…To progress beyond AFM-based mechanical testing and determine binding behavior at an atomistic resolution, in silico free energy calculations are necessary. Recently, we have presented atomistic models for individual CsgA and CsgB subunits, 30 which can be used as a foundation for investigations of fibrils using both all-atom 31 and coarse-grained molecular dynamics (MD) simulations. 32 From this work by DeBenedictis et al, the RobB-5 CsgB structure and the CsgA-map model based upon it will be utilized in this paper.…”

Section: Althoughmentioning

confidence: 99%

“…The CsgA and CsgB subunit structures used were predicted in our previous work. 30 Subunits were initially placed in proximity to each other such that their beta-strands are perpendicular to the fiber axis and subjected to implicit solvent simulations to allow docking to occur. Briefly, two subunit structures were positioned such that strands R1 and R5 were aligned, strands R1' and R5' were aligned, and internally conserved polar residues (Ser, Gln, and Asn) maintained alignment across the interface.…”

Section: Dimer Structuresmentioning

confidence: 99%

Dimerization energetics of curli fiber subunits CsgA and CsgB

2019

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Curli fibers are functional amyloids that exhibit strong adhesion and robust self-assembly as biofilm structural components; however, the binding energetics and mechanical properties of wild-type curli are not well understood. To address this, we present dimer structures made up of the major and minor curli subunits (CsgA and CsgB), perform free energy calculations to obtain absolute binding energies, and estimate the Young's modulus and persistence length of curli fibers. Equilibrium molecular dynamics simulations are used to evaluate nonbonded interactions. Binding energies are most favorable for CsgB-CsgA, while CsgA-CsgA dimers have a higher binding energy than CsgB-CsgB despite possessing less favorable nonbonded interaction energies. Decomposing each potential of mean force of separation indicated that solvent effects positively impact CsgA-CsgA binding but not CsgB-CsgB and CsgB-CsgA. Charged residues and conserved polar residues were also notable contributors to attractive nonbonded interactions, underlining their importance in dimer assembly. Our findings elucidate sequence effects on binding energy contributions and establish theoretical limits for the elasticity, persistence length, and strength of curli fibers.npj Computational Materials (2019) 5:27 ; https://doi.

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“…The structures of CsgA subunits derived from molecular modeling approaches have been employed to study curli mechanics and adhesion. 28,29 The adhesion of single CsgA monomers to a surface has revealed the importance of flexibility and side chain chemistry, as well as correlated motion within the curli core. 30 Coarse-grained (CG) simulations of nanofibers using steered molecular dynamics have shown the importance of bending rigidity in resisting desorption.…”

Section: Introductionmentioning

confidence: 99%

Adhesive behavior and detachment mechanisms of bacterial amyloid nanofibers

Wang

Keten

2019

npj Comput Mater

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Amyloid nanofibers, such as curli nanofibers, have proven capable of adhering strongly to abiotic surfaces. However, the adhesive performance of individual nanofibers and the dependence of this performance on physical properties remain to be characterized. We carried out coarse-grained molecular dynamics simulations to determine the detachment mechanisms of single amyloid fibers from surfaces. Taking a generic model inspired from the curli nanofiber subunit CsgA, we discover that the amyloid nanofibers can undergo three different peeling processes when pulled at a constant rate normal to the surface. Computational phase diagrams built from parametric studies indicate that strong nanofibers with high cohesive energy detach by peeling smoothly away from the substrate while weak fibers break prematurely. At intermediate ratios, hinge formation occurs and the work of peeling the nanofiber is twice the adhesive energy due to the additional energy required to bend the nanofiber during desorption. Varying the geometry of amyloid subunits revealed that the work of peeling decreases for thicker nanofibers, suggesting that the tape-like monomeric structure of amyloids may facilitate better adhesive performance. Our results demonstrate how the dimensions and adhesive and cohesive properties of the amyloid nanofibers can be optimized to resist mechanical peeling.npj Computational Materials (2019) 5:29 ; https://doi.

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Structural predictions for curli amyloid fibril subunits CsgA and CsgB

Abstract: CsgA are the building blocks of curli fibrils.

Cited by 38 publications

References 99 publications

Accurate contact-based modelling of repeat proteins predicts the structure of Curlin and SPW repeats

Accurate contact-based modelling of repeat proteins predicts the structure of Curlin and SPW repeats

Dimerization energetics of curli fiber subunits CsgA and CsgB

Adhesive behavior and detachment mechanisms of bacterial amyloid nanofibers

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