Computational Redesign of Thioredoxin Is Hypersensitive toward Minor Conformational Changes in the Backbone Template

Johansson, Kristoffer E.; Johansen, Nicolai Tidemand; Christensen, Steffan Wittrup; Horowitz, Scott; Bardwell, James C.A.; Olsen, Johan G.; Willemoës, Martin; Lindorff‐Larsen, Kresten; Ferkinghoff‐Borg, Jesper; Hamelryck, Thomas; Winther, Jakob R.

doi:10.1016/j.jmb.2016.09.013

Cited by 22 publications

(48 citation statements)

References 66 publications

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“…As we have seen previously (11), the designed sequences are highly dependent on the choice of template (Figure 1 and Figure S1) even though these are very similar in terms of structure. The 120 designed sequences for a given template and protocol have an average of 39±3% and 40±3% pairwise identity for P1 and P2 respectively (Table S2).…”

Section: Computational Designmentioning

confidence: 52%

“…The computational redesign of the Thioredoxin fold was based on eight backbone templates taken from the protein data bank (PDB). Seven of the templates were the same as in our previous study, however, the poorest performing template, 1dby, was replaced by the X-ray structure of a design from the same study, 5j7d (11). The latter was based on the best performing template, 1fb0, and could be considered a "second-generation" redesign of 1fb0.…”

Section: Computational Designmentioning

confidence: 99%

“…As a test case, we redesign, using recently developed methods, the Thioredoxin fold. This allows for a direct comparison with our previous work (11), primarily to address the issue of template selection in the design process. Thioredoxin (Trx) is a small protein (∼110 residues), but still large enough to pose a significant challenge in design and larger than most de novo designs (4,6).…”

Section: Introductionmentioning

confidence: 99%

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Computational and experimental assessment of backbone templates for computational protein design

Johansson

O'Shea

et al. 2021

Preprint

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Computational protein design has taken big strides over the recent years, however, the tools available are still not at a state where a sequence can be designed to fold into a given protein structure at will and with high probability. We have here applied a recent release of Rosetta Design to redesign a set of structurally very similar proteins belonging to the Thioredoxin fold. We determined design success using a combination of a genetic screening tool to assay folding/stability in E. coli and selecting the best hits from this for further biochemical characterization. We have previously used this set of template proteins for redesign and found that success was highly dependent on template structure, a trait which was also found in this study. Nevertheless, state of the art design software is now able to predict the best template, most likely due to the introduction of the cart_bonded energy term. The template that led to the greatest fraction of successful designs was the same (a Thioredoxin from spinach) as that identified in our previous study. Our previously described redesign of Thioredoxin, which also used the spinach protein as template, however also performed well. In the present study, both these templates yielded proteins with compact folded structures, and enforces the conclusion that any design project must carefully consider different design templates. Fortunately, selecting designs using the cart_bonded energy term appears to correctly identify such templates.

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Section: Computational Designmentioning

confidence: 52%

Section: Computational Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Computational and experimental assessment of backbone templates for computational protein design

Johansson

O'Shea

et al. 2021

Preprint

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“…This iterative approach is known as flexible‐backbone sequence design and is particularly suited for de novo design, where the input backbone structure is generated from scratch and likely requires further refinement guided by side chain placement—coupling the optimization of protein backbone and side chains is more likely to lead to well‐packed protein structures. Fixed‐backbone design, in contrast, leads to sequences that are too dependent on the starting backbone structure and therefore not every backbone template is suitable for design . The FastDesign method is one of the most powerful flexible‐sequence design protocols used in Rosetta .…”

Section: Methods For De Novo Design Of Protein Structuresmentioning

confidence: 99%

Essentials of de novo protein design: Methods and applications

Marcos

Silva

2018

WIREs Comput Mol Sci

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The field of de novo protein design has undergone a rapid transformation in the last decade and now enables the accurate design of protein structures with exceptional stability and in a large variety of folds not necessarily restricted to those seen in nature. Before the existence of de novo protein design, traditional strategies to engineer proteins relied exclusively on modifying existing proteins already with a similar to desired function or, at least, a suitable geometry and enough stability to tolerate mutations needed for incorporating the desired functions. De novo computational protein design, instead, allows to completely overcome this limitation by permitting the access to a virtually infinite number of protein shapes that can be suitable candidates to engineer function. Recently, we have seen the first examples of such functionalization in the form of de novo proteins custom designed to bind specific targets or small molecules with novel medical and biotechnological applications. Despite this progress, the incursion on this nascent field can be difficult due to the plethora of approaches available and their constant evolution. Here, we review the most relevant computational methods for de novo protein design with the aim of compiling a comprehensive guide for researchers embarking on this field. We illustrate most of the concepts in the view of Rosetta, which is the most extensively developed software for de novo protein design, but we highlight relevant work with other protein modeling softwares. Finally, we give an overall view of the current challenges and future opportunities in the field. This article is categorized under: Computer and Information Science > Computer Algorithms and Programming Structure and Mechanism > Computational Biochemistry and Biophysics Software > Molecular Modeling Structure and Mechanism > Molecular Structures

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“…Therefore, it can be considered to be at least partly knowledge-based. Several other successes were obtained 18,19 with updated versions of the Rosetta energy function, 16 including a recent large-scale study where 15000 miniproteins (40-43 amino acids) were redesigned. 20 6% of the 15000 designs were shown 3 to be successful; i.e., the designed miniproteins folded into the correct 3D conformation.…”

Section: Introductionmentioning

confidence: 99%

A physics-based energy function allows the computational redesign of a PDZ domain

Opuu

Sun

Hou

et al. 2019

Preprint

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A powerful approach to understand protein structure and evolution is to perform computer simulations that mimic aspects of evolution. In particular, structure-based computational protein design (CPD) can address the inverse folding problem, exploring a large space of amino acid sequences and selecting ones predicted to adopt a given fold. Previously, CPD has been used to entirely redesign several proteins: all or most of the protein sequence was allowed to mutate freely; among sampled sequences, those with low computed folding energy were selected, and a few percent of them did indeed adopt the correct fold. Those studies used an energy function that was partly or largely knowledge-based, with several empirical terms. Here, we show that a PDZ domain can be entirely redesigned using a "physics-based" energy function that combines standard molecular mechanics and a recent, continuum electrostatic solvent model. Many thousands of sequences were generated by Monte Carlo simulation. Among the lowest-energy sequences, three were chosen for experimental testing. All three could be overexpressed and had native-like circular dichroism and 1D-NMR spectra. Two exhibited an increase in their thermal denaturation curves when a peptide ligand was present, indicating binding and suggesting correctly folded proteins. Evidently, the physical principles that govern molecular mechanics and continuum electrostatics are sufficient to perform whole-protein redesign. This is encouraging, since these methods provide physical insights, can be systematically improved, and are transferable to other biopolymers and ligands of medical or technological interest.2

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Computational Redesign of Thioredoxin Is Hypersensitive toward Minor Conformational Changes in the Backbone Template

Cited by 22 publications

References 66 publications

Computational and experimental assessment of backbone templates for computational protein design

Computational and experimental assessment of backbone templates for computational protein design

Essentials of de novo protein design: Methods and applications

A physics-based energy function allows the computational redesign of a PDZ domain

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