Triple‐Helix‐Stabilizing Effects in Collagen Model Peptides Containing PPII‐Helix‐Preorganized Diproline Modules

Maassen, Andreas; Gebauer, Jan; Abraham, Elena Theres; Grimm, Isabelle; Neudörfl, Jörg‐Martin; Kühne, Ronald; Neundorf, Ines; Baumann, Ulrich; Schmalz, Hans‐Günther

doi:10.1002/ange.201914101

Cited by 7 publications

(5 citation statements)

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“…Studies of CMPs revealed that all natural amino acids destabilize the triple helix when replacing Pro in the GlyProHyp triplet 14 , while hydroxylation of Pro at the Y position stabilizes the structure 3 . Throughout the 1990s 12 and more recenlty 15,16 , a substantial portion of CMP studies have focused on uncovering and exploiting the stabilizing effects of the post-translational modification of Pro on the triple helix by leveraging synthetic Pro derivatives 3,[15][16][17][18][19] .…”

Section: Introductionmentioning

confidence: 99%

Peptoid Residues Make Diverse, Hyperstable Collagen Triple-Helices

et al. 2021

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The triple-helical structure of collagen, responsible for collagen's remarkable biological and mechanical properties, has inspired both basic and applied research in synthetic peptide mimetics for decades. Since non-proline amino acids weaken the triple helix, the cyclic structure of proline has been considered necessary, and functional collagen mimetic peptides (CMPs) with diverse sidechains have been difficult to produce. Here we show that N-substituted glycines (N-glys), also known as peptoid residues, exhibit a general triple-helical propensity similar to or greater than proline, allowing synthesis of thermally stable triple-helical CMPs with unprecedented sidechain diversity. We found that the N-glys stabilize the triple helix by sterically promoting the preorganization of individual CMP chains into the polyproline-II helix conformation. Our findings were supported by the crystal structures of two atomic-resolution N-gly-containing CMPs, as well as experimental and computational studies spanning more than 30 N-gly-containing peptides. We demonstrated that N-gly sidechains with diverse exotic moieties including a 'click'-able alkyne and a photo-sensitive sidechain can be incorporated into stable triple helices, enabling functional applications such spatio-temporal control of cell adhesion and migration on a gelatin matrix. The folding principles discovered in this study open up opportunities for a new generation of collagen mimetic therapeutics and materials with extraordinary properties. design principles uncovered in this study drastically expand the library of residues with high triple-helical propensity, which has immense implications for a new generation of collagenmimetic therapeutics and materials. Results and DiscussionTriple-helical stability of CMPs with N-glys. To investigate the triple-helical folding propensity of peptoids residues, we inserted a series of N-gly guests into the central X position of a conventional CMP host peptide with the sequence: Ac-(GlyProHyp)3-Gly-X-Hyp-(GlyProHyp)3-NH2 (designated as X-CMP, Fig. 1b, and supplementary Materials and Methods) 34 . We measured the X-CMPs' triple-helical stability via thermal unfolding experiments monitored under circular dichroism (CD, Fig. 1c, Supplementary Section 3 and Table S1), first in a group of N-glys with sidechains selected from the canonical amino acids (Fig. 1d). It is known that Pro is the most stabilizing amino acid at position X, and substitution from Pro to another canonical amino acid clearly reduces Tm by 4-17 °C (Fig. 1d, column AA) 14 . Surprisingly, we found that many of the N-glys with canonical sidechains were at least as stable as Pro, and almost all N-gly residues were more stable than their amino acid counterparts (Fig. 1d, exception: Nval), with the biggest Tm difference seen between Nphe-and Phe-CMP (Fig. 1c). These results demonstrate that, in the X position of the CMP, shifting the sidechain from the Cα carbon to the nitrogen (i.e., transforming a canonical amino acid to its peptoid analogue) may improve triple-he...

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Section: Introductionmentioning

confidence: 99%

Peptoid Residues Make Diverse, Hyperstable Collagen Triple-Helices

et al. 2021

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“…Only when the proline residue is in the C γ -exo ring pucker can an n→π * interaction stabilize the trans isomer of the peptide bond. The C γ -exo ring pucker preorganizes the main chain torsion angles and enhances triple-helix stability (19). Hence, prolyl 4-hydroxylation is essential for the stability of triple-helical collagen due to its a stereoelectronic effect.…”

Section: Stereoelectronic Effects Of Proline Hydroxylation On Yaamentioning

confidence: 99%

Quality Control of Procollagen in Cells

Ito

Nagata

2021

Annu. Rev. Biochem.

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Collagen is the most abundant protein in mammals. A unique feature of collagen is its triple-helical structure formed by the Gly-Xaa-Yaa repeats. Three single chains of procollagen make a trimer, and the triple-helical structure is then folded in the endoplasmic reticulum (ER). This unique structure is essential for collagen's functions in vivo, including imparting bone strength, allowing signal transduction, and forming basement membranes. The triple-helical structure of procollagen is stabilized by posttranslational modifications and intermolecular interactions, but collagen is labile even at normal body temperature. Heat shock protein 47 (Hsp47) is a collagen-specific molecular chaperone residing in the ER that plays a pivotal role in collagen biosynthesis and quality control of procollagen in the ER. Mutations that affect the triple-helical structure or result in loss of Hsp47 activity cause the destabilization of procollagen, which is then degraded by autophagy. In this review, we present the current state of the field regarding quality control of procollagen. Expected final online publication date for the Annual Review of Biochemistry, Volume 90 is June 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

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“…The PPII helix consists of almost 3~8 amino acid residues, and it occupies only about 2% in the protein. The PPII helix has special biological characteristics and plays a crucial role in biochemical fields such as signal transduction, cell movement, and immune response [2,3]. There are many interactions between the PPII helix and proteins or nucleic acids, such as SH3, WW, EVH1, GYF, UEV, and inhibitor proteins, which interact with the PPII helix [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

BERT-PPII: The Polyproline Type II Helix Structure Prediction Model Based on BERT and Multichannel CNN

Feng

Wang

et al. 2022

BioMed Research International

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Predicting the polyproline type II (PPII) helix structure is crucial important in many research areas, such as the protein folding mechanisms, the drug targets, and the protein functions. However, many existing PPII helix prediction algorithms encode the protein sequence information in a single way, which causes the insufficient learning of protein sequence feature information. To improve the protein sequence encoding performance, this paper proposes a BERT-based PPII helix structure prediction algorithm (BERT-PPII), which learns the protein sequence information based on the BERT model. The BERT model’s CLS vector can fairly fuse sample’s each amino acid residue information. Thus, we utilize the CLS vector as the global feature to represent the sample’s global contextual information. As the interactions among the protein chains’ local amino acid residues have an important influence on the formation of PPII helix, we utilize the CNN to extract local amino acid residues’ features which can further enhance the information expression of protein sequence samples. In this paper, we fuse the CLS vectors with CNN local features to improve the performance of predicting PPII structure. Compared to the state-of-the-art PPIIPRED method, the experimental results on the unbalanced dataset show that the proposed method improves the accuracy value by 1% on the strict dataset and 2% on the less strict dataset. Correspondingly, the results on the balanced dataset show that the AUCs of the proposed method are 0.826 on the strict dataset and 0.785 on less strict datasets, respectively. For the independent test set, the proposed method has the AUC value of 0.827 on the strict dataset and 0.783 on the less strict dataset. The above experimental results have proved that the proposed BERT-PPII method can achieve a superior performance of predicting the PPII helix.

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Triple‐Helix‐Stabilizing Effects in Collagen Model Peptides Containing PPII‐Helix‐Preorganized Diproline Modules

Cited by 7 publications

References 50 publications

Peptoid Residues Make Diverse, Hyperstable Collagen Triple-Helices

Peptoid Residues Make Diverse, Hyperstable Collagen Triple-Helices

Quality Control of Procollagen in Cells

BERT-PPII: The Polyproline Type II Helix Structure Prediction Model Based on BERT and Multichannel CNN

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