ConTemplate Suggests Possible Alternative Conformations for a Query Protein of Known Structure

Narunsky, Aya; Nepomnyachiy, Sergey; Ashkenazy, Haim; Kolodny, Rachel; Ben‐Tal, Nir

doi:10.1016/j.str.2015.08.018

Cited by 13 publications

(12 citation statements)

References 56 publications

(61 reference statements)

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“…In this case, the scaffold chosen for our designs is also known to undergo conformational changes upon ligand binding; binding of the natural ligand stabilizes proteins of this family in the closed conformation, which we used in our design models (Dwyer et al, 2003;Narunsky et al, 2015). Although our zinc binding site is near the original ligand binding site, we did not explicitly model the open conformation of our scaffold; therefore, the binding site likely takes on multiple conformations, and some of these alternate conformations may also be able to coordinate zinc in unexpected ways.…”

Section: Resultsmentioning

confidence: 99%

Probing the minimal determinants of zinc binding with computational protein design

Guffy¹,

Der²,

Kuhlman³

2016

Protein Engineering, Design and Selection

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Structure-based protein design tests our understanding of the minimal determinants of protein structure and function. Previous studies have demonstrated that placing zinc binding amino acids (His, Glu, Asp or Cys) near each other in a folded protein in an arrangement predicted to be tetrahedral is often sufficient to achieve binding to zinc. However, few designs have been characterized with high-resolution structures. Here, we use X-ray crystallography, binding studies and mutation analysis to evaluate three alternative strategies for designing zinc binding sites with the molecular modeling program Rosetta. While several of the designs were observed to bind zinc, crystal structures of two designs reveal binding configurations that differ from the design model. In both cases, the modeling did not accurately capture the presence or absence of second-shell hydrogen bonds critical in determining binding-site structure. Efforts to more explicitly design second-shell hydrogen bonds were largely unsuccessful as evidenced by mutation analysis and low expression of proteins engineered with extensive primary and secondary networks. Our results suggest that improved methods for designing interaction networks will be needed for creating metal binding sites with high accuracy.

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Section: Resultsmentioning

confidence: 99%

Probing the minimal determinants of zinc binding with computational protein design

Guffy¹,

Der²,

Kuhlman³

2016

Protein Engineering, Design and Selection

View full text Add to dashboard Cite

show abstract

“…Reliable predictions of large‐scale conformational changes would be important not only for our general knowledge about a protein's conformational space, but also for many practical applications such as modeling for molecular replacement or for cryoEM or in docking studies. It would also enable the prediction of alternative conformations of a protein based on those on its homologs—an application that has been explored in the ConTemplate 23 and ModFlex 24 servers. Therefore, in this manuscript, we evaluate the conservation of large‐scale conformational changes directly using experimentally solved structures deposited in the Protein Data Bank (PDB) 25 …”

Section: Introductionmentioning

confidence: 99%

What the protein data bank tells us about the evolutionary conservation of protein conformational diversity

et al. 2022

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Proteins sample a multitude of different conformations by undergoing smalland large-scale conformational changes that are often intrinsic to their functions. Information about these changes is often captured in the Protein Data Bank by the apparently redundant deposition of independent structural solutions of identical proteins. Here, we mine these data to examine the conservation of large-scale conformational changes between homologous proteins. This is important for both practical reasons, such as predicting alternative conformations of a protein by comparative modeling, and conceptual reasons, such as understanding the extent of conservation of different features in evolution.To study this question, we introduce a novel approach to compare conformational changes between proteins by the comparison of their difference distance maps (DDMs). We found that proteins undergoing similar conformational changes have similar DDMs and that this similarity could be quantified by the correlation between the DDMs. By comparing the DDMs of homologous protein pairs, we found that large-scale conformational changes show a high level of conservation across a broad range of sequence identities. This shows that conformational space is usually conserved between homologs, even relatively distant ones.

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“…Extrinsic factors like molecular packing in the crystal lattice, pH, temperature, pressure and crystallization conditions are also known to affect the protein conformation. There are several studies that document the dynamic nature of proteins [11][12][13][14][15] contributed by one or more of these factors. The user friendly ConTemplate 12 webserver takes as input a protein structure (or model) and proposes possible alternative conformations for the protein.…”

Section: Introductionmentioning

confidence: 99%

“…There are several studies that document the dynamic nature of proteins [11][12][13][14][15] contributed by one or more of these factors. The user friendly ConTemplate 12 webserver takes as input a protein structure (or model) and proposes possible alternative conformations for the protein. The Protein Data Bank 16 Flexibility (PDBFlex) 13 , Conformational Diversity of the Native State (CoDNaS) 14 and Conformational Change Profile (CCProf) 15 and studies document the structural variations in proteins sharing >=95% sequence similarity.…”

Section: Introductionmentioning

confidence: 99%

Structural variations within proteins can be as large as variations observed across their homologues

et al. 2019

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Understanding the structural plasticity of proteins is key to understanding the intricacies of their functions and mechanistic basis. In the current study, we analyzed the available multiple crystal structures of the same protein for the structural differences. For this purpose we used an abstraction of protein structures referred as Protein Blocks (PBs) that was previously established. We also characterized the nature of the structural variations for a few proteins using molecular dynamics simulations. In both the cases, the structural variations were summarized in the form of substitution matrices of PBs. We show that certain conformational states are preferably replaced by other specific conformational states. Interestingly, these structural variations are highly similar to those previously observed across structures of homologous proteins (r 2 =0.923) or across the ensemble of conformations from NMR data (r 2 =0.919). Thus our study quantitatively shows that overall trends of structural changes in a given protein are nearly identical to the trends of structural differences that occur in the topologically equivalent positions in homologous proteins. Specific case studies are used to illustrate the nature of these structural variations.

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ConTemplate Suggests Possible Alternative Conformations for a Query Protein of Known Structure

Cited by 13 publications

References 56 publications

Probing the minimal determinants of zinc binding with computational protein design

Probing the minimal determinants of zinc binding with computational protein design

What the protein data bank tells us about the evolutionary conservation of protein conformational diversity

Structural variations within proteins can be as large as variations observed across their homologues

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