Protein fabrication automation

Cox, J. Colin; Lape, Janel; Sayed, Mahmood A.; Hellinga, Homme W.

doi:10.1110/ps.062591607

Cited by 51 publications

(50 citation statements)

References 66 publications

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“…The wild-type proteins and cysteine variants were produced by cell-free in vitro transcription and translation (TnT) using an E. coli extract from Bl21 Star (DE3) (Invitrogen; C6010-03) (34) programmed with a synthetic linear DNA fragment that was constructed using automated, PCR-mediated gene assembly (35). The synthetic gene sequences (see SI Fabricated Synthetic Gene Sequences (ORFs)) comprise a 5′ T7-promoter, a 5′ ribosome binding site, and a 3′ T7-terminator flanking an open reading frame whose DNA sequence was optimized for protein expression using a computational algorithm that manipulates mRNA structure (Allert, Cox, and Hellinga, in preparation).…”

Section: Cell-free Expression and Purification Of Proteins Encoded Bymentioning

confidence: 99%

Picomole-scale characterization of protein stability and function by quantitative cysteine reactivity

Isom

Vardy

Oas

et al. 2010

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

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The Gibbs free energy difference between native and unfolded states ("stability") is one of the fundamental characteristics of a protein. By exploiting the thermodynamic linkage between ligand binding and stability, interactions of a protein with small molecules, nucleic acids, or other proteins can be detected and quantified. Determination of protein stability can therefore provide a universal monitor of biochemical function. Yet, the use of stability measurements as a functional probe is underutilized, because such experiments traditionally require large amounts of protein and special instrumentation. Here we present the quantitative cysteine reactivity (QCR) technique to determine protein stabilities rapidly and accurately using only picomole quantities of material and readily accessible laboratory equipment. We demonstrate that QCRderived stabilities can be used to measure ligand binding over a wide range of ligand concentrations and affinities. We anticipate that this technique will have broad applications in high-throughput protein engineering experiments and functional genomics. Macromolecular stability is therefore one of the most fundamental thermodynamic measures in biochemistry by quantitatively reporting on structure-function relationships to provide a universal monitor for biochemical function.There are two distinct approaches for determining protein stability (4). The first measures the free energy of protein (un)folding under equilibrium conditions by assessing the fraction of the native state using spectroscopy, hydrodynamic observations, functional assays, or calorimetry. The second exploits the relationship between protein dynamics and stability by monitoring the differential reactivity of internal chemical groups in native and unfolded states. This second approach measures conformational free energies, which under appropriate conditions corresponds to global protein stability. Amide proton exchange is used most commonly to monitor such differential reactivity (5-9), but its widespread use to assess biological function typically is limited by the need for specialized instrumentation and relatively large amounts of protein. Recently, cysteine reactivity (10-14) and proteolysis (15) have emerged as alternative means to determine rates of protein (un)folding and estimate protein stabilities. Here we present a method, quantitative cysteine reactivity (QCR), in which protein stability is determined by monitoring the reactivity of cysteine residues buried in the hydrophobic core of proteins. This approach has the advantage over more traditional methods for measuring protein stability in that it requires only picomoles (nanograms) of protein, uses simple instrumentation accessible to any lab, can be reasonably high throughput, and can provide site-specific thermodynamic information. QCR can be used to determine apparent protein stabilities rapidly and accurately, construct Gibbs-Helmholtz stability profiles, measure ligand binding over a large range of ligand concentrations and affinities, and infer e...

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Section: Cell-free Expression and Purification Of Proteins Encoded Bymentioning

confidence: 99%

Picomole-scale characterization of protein stability and function by quantitative cysteine reactivity

Isom

Vardy

Oas

et al. 2010

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

Self Cite

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“…A second round library that fixes consensus residues from the first rounds of experimental screening, but includes previously excluded amino acids, may be one strategy to more completely sample amino acids observed during simulations. Another approach would be to use gene synthesis techniques to exactly include every low-scoring sequence observed computationally (33). For example, in this case all 323 top-scoring sequences might be synthesized in a highly parallel format and each sequence might be assayed individually.…”

Section: Discussionmentioning

confidence: 99%

Engineering a protein–protein interface using a computationally designed library

Guntas

Purbeck

Kuhlman

2010

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

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Computational algorithms for protein design can sample large regions of sequence space, but suffer from undersampling of conformational space and energy function inaccuracies. Experimental screening of combinatorial protein libraries avoids the need for accurate energy functions, but has limited access to vast amounts of sequence space. Here, we test if these two traditionally alternative, but potentially complementary approaches can be combined to design a variant of the ubiquitin-ligase E6AP that will bind to a nonnatural partner, the NEDD8-conjugating enzyme Ubc12. Three E6AP libraries were constructed: (i) a naive library in which all 20 amino acids were allowed at every position on the target-binding surface of E6AP (13 positions), (ii) a semidirected library that varied the same residue positions as in the naive library but disallowed mutations computationally predicted to destabilize E6AP, and (iii) a directed library that used docking and sequence optimization simulations to identify mutations predicted to be favorable for binding Ubc12. Both of the directed libraries showed >30-fold enrichment over the naive library after the first round of screening with a split-dihydrofolate reductase complementation assay and produced multiple tight binders (K d < 100 nM) after four rounds of selection. Four rounds of selection with the naive library failed to produce any binders with K d 's lower than 50 μM. These results indicate that protein design simulations can be used to create directed libraries that are enriched in tight binders and that in some cases it is sufficient to computationally screen for well-folded sequences without explicit binding calculations.computational protein design | protein engineering | Rosetta C omputational design and selection from combinatorial libraries are alternative approaches for protein engineering. In computational design, high-resolution models of protein structure are used to predict amino acid sequences that will stabilize target protein structures or complexes. Computational design has been used to stabilize protein structures and interfaces, redesign protein-binding specificities, and in a few cases build protein structures from scratch (1-4). Despite these successes, many problems in protein engineering remain very difficult for computational design: These include the design of protein-protein interactions and the creation of enzymes that compare favorably with naturally occurring enzymes (5-9). In silico ranking of designed interfaces is challenging because large free energies of desolvation have to be correctly balanced by hydrogen bonding and van der Waals interactions that are sensitive to small changes in atomic positions. As a result, there are often significant errors in calculated energies for protein-binding events. One advantage of screening or selecting from large-scale combinatorial libraries is that it does not rely on the accuracy of an energy functioneach sequence is experimentally tested for the desired functionality. Protein selection techniques such as...

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“…Synthetic genes can be used to express target proteins of interest in a host cell, making it possible to produce protein fragments of a size manageable for structural analysis, to understand how variations in protein sequence affects binding properties of the protein, and to design novel proteins [1]. Use of a designed synthetic gene which codes for the target protein, rather than a naturally occurring gene, can also enhance the gene's expression level in the host, for example by matching the codon bias with that of the host in which the gene is expressed or by removing introns from the gene [2].…”

Section: Introductionmentioning

confidence: 99%

“…There are already many algorithms and software packages available for oligo design [1], [2], [4]- [10]. These methods vary in the types of design criteria they support, and in the underlying design optimization techniques (as well as in other aspects not considered further here, such as the user interface).…”

Section: Introductionmentioning

confidence: 99%

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On the Design of Oligos for Gene Synthesis

Thachuk

Condon

2007

2007 IEEE 7th International Symposium on BioInformatics and BioEngineering

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Abstract-Methods for reliable synthesis of long genes offer great promise for protein synthesis via expression of synthetic genes, with applications to improved analysis of protein structure and function, as well as engineering of novel proteins. Current technologies for gene synthesis use computational methods for design of short oligos, which can then be reliably synthesized and assembled into the desired target gene. For collision-oblivious oligo design -when mishybridizations between oligos are ignored -we give a simple and efficient dynamic programming algorithm. We conjecture that the collision-aware oligo design problem is N P-hard and provide evidence that mishybridizations between oligos occur infrequently in the designs from the collisionoblivious algorithm. We extend our dynamic programing algorithm to achieve collision-aware oligo design, when the target gene can be partitioned into independently-assembled short segments. We evaluate our methods on a large biological gene set.

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Protein fabrication automation

Cited by 51 publications

References 66 publications

Picomole-scale characterization of protein stability and function by quantitative cysteine reactivity

Picomole-scale characterization of protein stability and function by quantitative cysteine reactivity

Engineering a protein–protein interface using a computationally designed library

On the Design of Oligos for Gene Synthesis

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