How protein stability and new functions trade off

Optimizing protein stability in vivo

Identifying mutations that stabilize proteins is challenging because most substitutions are destabilizing. In addition to being of immense practical utility, the ability to evolve protein stability in vivo may indicate how evolution has formed today's protein sequences. Here we describe a genetic selection that directly links the in vivo stability of proteins to antibiotic resistance. It allows the identification of stabilizing mutations within proteins. The large majority of mutants selected for improved antibiotic resistance are stabilized both thermodynamically and kinetically, indicating that similar principles govern stability in vivo and in vitro. The approach requires no prior structural or functional knowledge and allows selection for stability without a need to maintain function. Mutations that enhance thermodynamic stability of the protein Im7 map overwhelmingly to surface residues involved in binding to colicin E7, showing how the evolutionary pressures that drive Im7-E7 complex formation have compromised the stability of the isolated Im7 protein.

Exploring protein fitness landscapes by directed evolution

Directed evolution circumvents our profound ignorance of how a protein's sequence encodes its function by using iterative rounds of random mutation and artificial selection to discover new and useful proteins. Proteins can be tuned to adapt to new functions or environments by simple adaptive walks involving small numbers of mutations. Directed evolution studies have shown how rapidly some proteins can evolve under strong selection pressures and, because the entire 'fossil record' of evolutionary intermediates is available for detailed study, they have provided new insight into the relationship between sequence and function. Directed evolution has also shown how mutations that are functionally neutral can set the stage for further adaptation.

Mimicking the evolution of a thermally stable monomeric four-helix bundle by fusion of four identical single-helix peptides

Internal symmetry is a common feature of the tertiary structures of proteins and protein domains. Probably, because the genes of homo-oligomeric proteins duplicated and fused, their evolutionary descendants are proteins with internal symmetry. To identify any advantages that cause monomeric proteins with internal symmetry to be selected evolutionarily, we characterized some of the physical properties of a recombinant protein with a sequence consisting of two tandemly fused copies of the Escherichia coli Lac repressor C-terminal alpha-helix. This polypeptide exists in solution mainly as dimer that likely maintains a four-helix bundle motif. Thermal unfolding experiments demonstrate that the protein is considerably more stable at elevated temperatures than is a homotetramer consisting of four non-covalently associated copies of a 21-residue polypeptide similar in sequence to that of the Lac repressor C-terminal alpha-helix. A tandem duplication of our helix-loop-helix polypeptide yields an even more thermally stable protein. Our results exemplify the concept that fusion of non-covalently assembled polypeptide chains leads to enhanced protein stability. Herein, we discuss how our work relates to the evolutionary selective-advantages realized when symmetrical homo-oligomers evolve into monomers. Moreover, our thermally stable single-chain four-helix bundle protein may provide a robust scaffold for development of new biomaterials.

A survey of proteins encoded by non-synonymous single nucleotide polymorphisms reveals a significant fraction with altered stability and activity

On average, each human gene has approximately four SNPs (single nucleotide polymorphisms) in the coding region, half of which are nsSNPs (non-synonymous SNPs) or missense SNPs. Current attention is focused on those that are known to perturb function and are strongly linked to disease. However, the vast majority of SNPs have not been investigated for the possibility of causing disease. We set out to assess the fraction of nsSNPs that encode proteins that have altered stability and activity, for this class of variants would be candidates to perturb cellular function. We tested the thermostability and, where possible, the catalytic activity for the most common variant (wild-type) and minor variants (total of 46 SNPs) for 16 human enzymes for which the three-dimensional structures were known. There were significant differences in the stability of almost half of the variants (48%) compared with their wild-type counterparts. The catalytic efficiency of approx. 14 variants was significantly altered, including several variants of human PKM2 (pyruvate kinase muscle 2). Two PKM2 variants, S437Y and E28K, also exhibited changes in their allosteric regulation compared with the wild-type enzyme. The high proportion of nsSNPs that affect protein stability and function, albeit subtly, underscores the need for experimental analysis of the diverse human proteome.

Evolution of stability in a cold-active enzyme elicits specificity relaxation and highlights substrate-related effects on temperature adaptation

Molecular aspects of thermal adaptation of proteins were studied by following the co-evolution of temperature dependence, conformational stability, and substrate specificity in a cold-active lipase modified via directed evolution. We found that the evolution of kinetic stability was accompanied by a relaxation in substrate specificity. Moreover, temperature dependence and selectivity turned out to be mutually dependent. While the wild-type protein was strictly specific for short-chain triglycerides (C4) in the temperature range 10-50 degrees C and displayed highest activity in the cold, its stabilized variant was able to accept C8 and C12 molecules and its selectivity was temperature dependent. We could not detect any improvement in the overall structural robustness of the mutant when the structure was challenged by temperature or chemical denaturants. There is, however, strong evidence for local stabilization effects in the active-site region provided by two independent approaches. Differential scanning fluorimetry revealed that the exposure of hydrophobic patches (as the active site is) precedes denaturation, and molecular dynamics simulations confirmed that stability was obtained by restriction of the mobility of the lid, a flexible structure that regulates the access to the enzyme active site and influences its stability. This reduction of lid movements is suggested to be accompanied by a concomitant increase in the mobility of other protein regions, thus accounting for the observed broadening of substrate specificity.

Following evolutionary paths to protein-protein interactions with high affinity and selectivity

How do intricate multi-residue features such as protein-protein interfaces evolve? To address this question, we evolved a new colicin-immunity binding interaction. We started with Im9, which inhibits its cognate DNase ColE9 at 10(-14) M affinity, and evolved it toward ColE7, which it inhibits promiscuously (Kd > 10(-8) M). Iterative rounds of random mutagenesis and selection toward higher affinity for ColE7, and selectivity (against ColE9 inhibition), led to an approximately 10(5)-fold increase in affinity and a 10(8)-fold increase in selectivity. Analysis of intermediates along the evolved variants revealed that changes in the binding configuration of the Im protein uncovered a latent set of interactions, thus providing the key to the rapid divergence of new Im7 variants. Overall, protein-protein interfaces seem to share the evolvability features of enzymes, that is, the exploitation of promiscuous interactions and alternative binding configurations via 'generalist' intermediates, and the key role of compensatory stabilizing mutations in facilitating the divergence of new functions.

Activation of anthranilate phosphoribosyltransferase from Sulfolobus solfataricus by removal of magnesium inhibition and acceleration of product release

Anthranilate phosphoribosyltransferase from the hyperthermophilic archaeon Sulfolobus solfataricus (ssAnPRT) is encoded by the sstrpD gene and catalyzes the reaction of anthranilate (AA) with a complex of Mg(2+) and 5'-phosphoribosyl-alpha1-pyrophosphate (Mg.PRPP) to N-(5'-phosphoribosyl)-anthranilate (PRA) and pyrophosphate (PP(i)) within tryptophan biosynthesis. The ssAnPRT enzyme is highly thermostable (half-life at 85 degrees C = 35 min) but only marginally active at ambient temperatures (turnover number at 37 degrees C = 0.33 s(-1)). To understand the reason for the poor catalytic proficiency of ssAnPRT, we have isolated from an sstrpD library the activated ssAnPRT-D83G + F149S double mutant by metabolic complementation of an auxotrophic Escherichia coli strain. Whereas the activity of purified wild-type ssAnPRT is strongly reduced in the presence of high concentrations of Mg(2+) ions, this inhibition is no longer observed in the double mutant and the ssAnPRT-D83G single mutant. The comparison of the crystal structures of activated and wild-type ssAnPRT shows that the D83G mutation alters the binding mode of the substrate Mg.PRPP. Analysis of PRPP and Mg(2+)-dependent enzymatic activity indicates that this leads to a decreased affinity for a second Mg(2+) ion and thus reduces the concentration of enzymes with the inhibitory Mg(2).PRPP complex bound to the active site. Moreover, the turnover number of the double mutant ssAnPRT-D83G + F149S is elevated 40-fold compared to the wild-type enzyme, which can be attributed to an accelerated release of the product PRA. This effect appears to be mainly caused by an increased conformational flexibility induced by the F149S mutation, a hypothesis which is supported by the reduced thermal stability of the ssAnPRT-F149S single mutant.

Molecular networks and system-level properties

Molecular systems biology aims to describe the functions of complex biological processes through recursive integration of molecular analysis, modeling, simulation and theory. It focuses on networks that originate from interconnection of genes, proteins and metabolites whose dynamic interactions generate, as an emergent property of the system, the corresponding function. Although evolutionary optimized, intracellular biochemical parameters, such as the expression level of gene products or the affinity between two or more proteins, must have a permissible range that gives robustness against perturbations to the system. Using the yeast G(1)-to-S transition network as an example we show that sophisticated relations exist among network structure, emergent property and robustness. Different emergent properties are generated from the same network by changing the strength of its interactions, not only by altering expression level, but also through mono and multi-site phosphorylation/dephosphorylation. Besides, multi-site protein phosphorylation modules, widespread in cell cycle, may ensure robust and coherent timing of cell cycle transitions as it happens for the onset of DNA replication. In conclusion, the modulation of biological function/emergent property by modifying interaction strength provides an efficient, highly tunable device to regulate biological processes. Furthermore, the principles outlined herein may provide new insight to network analysis in drug discovery.

Chaperonin overexpression promotes genetic variation and enzyme evolution

Most protein mutations, and mutations that alter protein functions in particular, undermine stability and are therefore deleterious. Chaperones, or heat-shock proteins, are often implicated in buffering mutations, and could thus facilitate the acquisition of neutral genetic diversity and the rate of adaptation. We examined the ability of the Escherichia coli GroEL/GroES chaperonins to buffer destabilizing and adaptive mutations. Here we show that mutational drifts performed in vitro with four different enzymes indicated that GroEL/GroES overexpression doubled the number of accumulating mutations, and promoted the folding of enzyme variants carrying mutations in the protein core and/or mutations with higher destabilizing effects (destabilization energies of >3.5 kcal mol(-)(1), on average, versus approximately 1 kcal mol(-)(1) in the absence of GroEL/GroES). The divergence of modified enzymatic specificity occurred much faster under GroEL/GroES overexpression, in terms of the number of adapted variants (>or=2-fold) and their improved specificity and activity (>or=10-fold). These results indicate that protein stability is a major constraint in protein evolution, and buffering mechanisms such as chaperonins are key in alleviating this constraint.

Protein dynamism and evolvability

The traditional view that proteins possess absolute functional specificity and a single, fixed structure conflicts with their marked ability to adapt and evolve new functions and structures. We consider an alternative, "avant-garde view" in which proteins are conformationally dynamic and exhibit functional promiscuity. We surmise that these properties are the foundation stones of protein evolvability; they facilitate the divergence of new functions within existing folds and the evolution of entirely new folds. Packing modes of proteins also affect their evolvability, and poorly packed, disordered, and conformationally diverse proteins may exhibit high evolvability. This dynamic view of protein structure, function, and evolvability is extrapolated to describe hypothetical scenarios for the evolution of the early proteins and future research directions in the area of protein dynamism and evolution.

Effects of ploidy and recombination on evolution of robustness in a model of the segment polarity network

Many genetic networks are astonishingly robust to quantitative variation, allowing these networks to continue functioning in the face of mutation and environmental perturbation. However, the evolution of such robustness remains poorly understood for real genetic networks. Here we explore whether and how ploidy and recombination affect the evolution of robustness in a detailed computational model of the segment polarity network. We introduce a novel computational method that predicts the quantitative values of biochemical parameters from bit sequences representing genotype, allowing our model to bridge genotype to phenotype. Using this, we simulate 2,000 generations of evolution in a population of individuals under stabilizing and truncation selection, selecting for individuals that could sharpen the initial pattern of engrailed and wingless expression. Robustness was measured by simulating a mutation in the network and measuring the effect on the engrailed and wingless patterns; higher robustness corresponded to insensitivity of this pattern to perturbation. We compared robustness in diploid and haploid populations, with either asexual or sexual reproduction. In all cases, robustness increased, and the greatest increase was in diploid sexual populations; diploidy and sex synergized to evolve greater robustness than either acting alone. Diploidy conferred increased robustness by allowing most deleterious mutations to be rescued by a working allele. Sex (recombination) conferred a robustness advantage through "survival of the compatible": those alleles that can work with a wide variety of genetically diverse partners persist, and this selects for robust alleles.

A framework for evolutionary systems biology

BACKGROUND

Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects.

RESULTS

Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions in silico. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism.

CONCLUSION

EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.

Enzyme (re)design: lessons from natural evolution and computation

The (re)design of enzymes to catalyze 'new' reactions is a topic of considerable practical and intellectual interest. Directed evolution (random mutagenesis followed by screening/selection) has been used widely to identify novel biocatalysts. However, 'rational' approaches using either natural divergent evolution or computational predictions based on chemical principles have been less successful. This review summarizes recent progress in evolution-based and computation-based (re)design.

TransCent: computational enzyme design by transferring active sites and considering constraints relevant for catalysis

Background

Computational enzyme design is far from being applicable for the general case. Due to computational complexity and limited knowledge of the structure-function interplay, heuristic methods have to be used.

Results

We have developed TransCent, a computational enzyme design method supporting the transfer of active sites from one enzyme to an alternative scaffold. In an optimization process, it balances requirements originating from four constraints. These are 1) protein stability, 2) ligand binding, 3) pK_a values of active site residues, and 4) structural features of the active site. Each constraint is handled by an individual software module. Modules processing the first three constraints are based on state-of-the-art concepts, i.e. RosettaDesign, DrugScore, and PROPKA. To account for the fourth constraint, knowledge-based potentials are utilized. The contribution of modules to the performance of TransCent was evaluated by means of a recapitulation test. The redesign of oxidoreductase cytochrome P450 was analyzed in detail. As a first application, we present and discuss models for the transfer of active sites in enzymes sharing the frequently encountered triosephosphate isomerase fold.

Conclusion

A recapitulation test on native enzymes showed that TransCent proposes active sites that resemble the native enzyme more than those generated by RosettaDesign alone. Additional tests demonstrated that each module contributes to the overall performance in a statistically significant manner.

Relative tolerance of an enzymatic molten globule and its thermostable counterpart to point mutation

Enzyme structures reflect the complex interplay between the free energy of unfolding (DeltaG) and catalytic efficiency. Consequently, the effects of point mutations on structure, stability, and function are difficult to predict. It has been proposed that the mutational robustness of homologous enzymes correlates with a higher initial DeltaG. To examine this issue, we compared the tolerance of a natural thermostable chorismate mutase and an engineered molten globular variant to targeted mutation. These mutases possess similar sequence, structure, and catalytic efficiency but dramatically different DeltaG values. We find that analogous point mutations can have widely divergent effects on catalytic activity in these scaffolds. In a set of five rationally designed single-amino acid changes, the thermostable scaffold suffers activity losses ranging from 50-fold smaller, for an aspartate-to-glycine substitution at the active site, to 2-fold greater, for a phenylalanine-to-tryptophan substitution in the hydrophobic core, versus that of the molten globular scaffold. However, biophysical characterization indicates that the variations in catalytic efficiency are not caused by losses of either secondary structural integrity or thermodynamic stability. Rather, the activity differences between variant pairs are very much context-dependent and likely stem from subtle changes in the fine structure of the active site. Thus, in many cases, it may be more productive to focus on changes in local conformation than on global stability when attempting to understand and predict how enzymes respond to point mutations.

Intense neutral drifts yield robust and evolvable consensus proteins

What changes occur when a natural protein that had been under low mutation rates is subjected to a neutral drift at high mutational loads, thus generating genetically diverse (polymorphic) gene ensembles that all maintain the protein's original function and structure? To address this question we subjected large populations of TEM-1 beta-lactamase to a prolonged neutral drift, applying high mutation rates and purifying selection to maintain TEM-1's existing penicillinase activity. Purging of deleterious mutations and enrichment of beneficial ones maintained the sequence of these ensembles closer to TEM-1's family consensus and inferred ancestor. In particular, back-to-consensus/ancestor mutations that increase TEM-1's kinetic and thermodynamic stability were enriched. These acted as global suppressors and enabled the tolerance of a broad range of deleterious mutations, thus further increasing the genetic diversity of the drifting populations. The probability of a new function emerging (cefotaxime degradation) was also substantially increased in these ensembles owing to the presence of many gene variants carrying the global suppressors. Our findings indicate the unique features of large, polymorphic neutral ensembles generated under high mutational loads and prompt the speculation that the progenitors of today's proteins may have evolved under high mutational loads. The results also suggest that predictable back-to-consensus/ancestor changes can be used in the laboratory to generate highly diverse and evolvable gene libraries.