High-resolution Structural and Thermodynamic Analysis of Extreme Stabilization of Human Procarboxypeptidase by Computational Protein Design

210

177

Here, we report the application of a computational approach that allows the rational design of enzymes with enhanced thermostability while retaining full enzymatic activity. The approach is based on the optimization of the energy of charge-charge interactions on the protein surface. We experimentally tested the validity of the approach on 2 human enzymes, acylphosphatase (AcPh) and Cdc42 GTPase, that differ in size (98 vs. 198-aa residues, respectively) and tertiary structure. We show that the designed proteins are significantly more stable than the corresponding WT proteins. The increase in stability is not accompanied by significant changes in structure, oligomerization state, or, most importantly, activity of the designed AcPh or Cdc42. This success of the design methodology suggests that it can be universally applied to other enzymes, on its own or in combination with the other strategies based on redesign of the interactions in the protein core.Until man duplicates a blade of grass, nature will laugh at his so-called scientific knowledge.Thomas Edison computational design ͉ protein engineering ͉ protein stability R ational engineering of proteins to enhance stability and yet retain their enzymatic activity is well motivated (1). One motivation is the practical significance of expanding the use of enzymes in many areas of the modern world, including protein therapeutics, enzymes for food industry, diagnostics, and other areas of industrial biotechnology. Another motivation is validation of the existing scientific knowledge. In this case, predictions made by the existing models for protein stability are subjected to thorough experiments, testing their applicability to protein design. In this paper, we present the results of rational design of enzymes with enhanced stability and unchanged enzymatic activity. This approach has 2 major differences from previously described successful protein design methods (2-5): (i) it concentrates only on the residues on the protein surface, and (ii) it optimizes just one type of interactions, namely, charge-charge interactions on the protein surface (6-15).One of the most important aspects of engineering proteins with enhanced stability, retaining the enzymatic activity, is often forgotten. However, for all of these design efforts to be practically useful, it is important that the engineered proteins retain their biological and enzymatic activity. This issue is particularly important when enhanced protein stability is achieved by redesigning the charge-charge interactions on the protein surface. Such redesign can lead to several potentially detrimental effects on the activity: (i) it can affect the electrostatic potential in the active center, thus reducing or even abolishing the activity; (ii) it can affect substrate/product binding and again reduce or abolish the enzymatic activity; or (iii) it can have effects on the kinetics of substrate binding and, thus, lower the activity via reduced rates of electrostatic steering (3,(16)(17)(18)(19)(20)(21)(22).To this end, it is imp...

Section: Resultsmentioning

confidence: 99%

Rational stabilization of enzymes by computational redesign of surface charge–charge interactions

Gribenko

Patel

Liu

et al. 2009

210

177

“…Computational and experimental approaches have been developed to identify stabilizing mutations. Computational methods generally rely on physicochemical models to estimate the thermodynamic impact of mutations (28,29). Stabilizing mutations can also be identified by analyzing evolutionary conservation or proteins from hyperthermophilic organisms (30,31).…”

Section: Discussionmentioning

confidence: 99%

A fundamental protein property, thermodynamic stability, revealed solely from large-scale measurements of protein function

Araya¹,

Fowler

Chen³

et al. 2012

243

264

The ability of a protein to carry out a given function results from fundamental physicochemical properties that include the protein's structure, mechanism of action, and thermodynamic stability. Traditional approaches to study these properties have typically required the direct measurement of the property of interest, oftentimes a laborious undertaking. Although protein properties can be probed by mutagenesis, this approach has been limited by its low throughput. Recent technological developments have enabled the rapid quantification of a protein's function, such as binding to a ligand, for numerous variants of that protein. Here, we measure the ability of 47,000 variants of a WW domain to bind to a peptide ligand and use these functional measurements to identify stabilizing mutations without directly assaying stability. Our approach is rooted in the well-established concept that protein function is closely related to stability. Protein function is generally reduced by destabilizing mutations, but this decrease can be rescued by stabilizing mutations. Based on this observation, we introduce partner potentiation, a metric that uses this rescue ability to identify stabilizing mutations, and identify 15 candidate stabilizing mutations in the WW domain. We tested six candidates by thermal denaturation and found two highly stabilizing mutations, one more stabilizing than any previously known mutation. Thus, physicochemical properties such as stability are latent within these large-scale protein functional data and can be revealed by systematic analysis. This approach should allow other protein properties to be discovered.deep mutational scanning | epistasis | high-throughput DNA sequencing

“…A count of all buried, unsatisfied hydrogen bonds was obtained using a SASA probe of 1.4 Å. Hydrogen bonds were defined with a strict geometric criteria (23). To generate a library of fully redesigned models, all structures were then subjected to sequence optimization and rotamer repacking on a fixed backbone using RosettaDesign with both a standard and dampened Lennard-Jones potential (9). The resulting structures were analyzed for packing quality and buried, unsatisfied hydrogen bond count.…”

Section: Methodsmentioning

confidence: 99%

“…Comparison to the mutant crystal structure yielded ΔΔE (difference in the respective energy function upon mutation, Table S3). We determined the rate of true positive prediction for reversion to the native (known to be favorable) with both our protocol and the current RosettaDesign protocol (9) (Fig. 1C).…”

Section: Fully Redesigned Proteins Exhibit Poorly Packed Hydrophobic mentioning

confidence: 99%

See 1 more Smart Citation

Automated selection of stabilizing mutations in designed and natural proteins

Borgo

Havranek

2012

Self Cite

124

The ability to engineer novel protein folds, conformations, and enzymatic activities offers enormous potential for the development of new protein therapeutics and biocatalysts. However, many de novo and redesigned proteins exhibit poor hydrophobic packing in their predicted structures, leading to instability or insolubility. The general utility of rational, structure-based design would greatly benefit from an improved ability to generate well-packed conformations. Here we present an automated protocol within the RosettaDesign framework that can identify and improve poorly packed protein cores by selecting a series of stabilizing point mutations. We apply our method to previously characterized designed proteins that exhibited a decrease in stability after a full computational redesign. We further demonstrate the ability of our method to improve the thermostability of a well-behaved native protein. In each instance, biophysical characterization reveals that we were able to stabilize the original proteins against chemical and thermal denaturation. We believe our method will be a valuable tool for both improving upon designed proteins and conferring increased stability upon native proteins.W ell-packed hydrophobic cores are a hallmark of protein structure (1, 2). Consistent with the central role the hydrophobic effect plays in protein stability, defects in core packing are associated with decreased stability (3) and loss of conformational specificity (4, 5). Analytical tools for the assessment of core packing are useful for identifying errors in experimentally determined structures and for rationalizing and predicting the effects of mutations on protein stability. Not surprisingly, the assembly of well-packed cores has been a central goal for computational protein design since its inception (6).Despite this central focus, models generated by computational protein design algorithms often exhibit poor hydrophobic packing. This is due to both the simplified structural representation and the scoring methods used by standard design protocols. Structurally, the protein backbone is treated as rigid, and different side-chain orientations are sampled at each position. These side chains are limited to a discrete set of commonly observed conformations known as rotamers. This combination implies a limited ability to fill arbitrary volumes compactly. The coarseness of this representation is exacerbated by the scoring functions, which generally include some form of the Lennard-Jones atomatom interaction term taken from molecular mechanics. There is a severe and well-known mismatch between the distances over which this term can vary strongly and the resolution afforded by a rotameric representation of side chains. Xiang and Honig addressed this problem by increasing the number of allowable rotamers until the scoring function could be satisfactorily sampled (7). More commonly, the scoring function is modified to accommodate the rotameric representation. This can be accomplished by reducing the atomic radii to mitigate clashes or by...