Fluorescence activated cell sorting for enzymatic activity

Directed evolution is a reliable method for protein engineering and as a tool for investigating structure/function relationships. A key for a successful directed evolution experiment is oftentimes the screen. Fluorescence activated cell sorting (FACS) is powerful high-throughput screening approach to isolate and identify mutants from large protein libraries. FACS has been successful in isolating proteins with improved or altered binding affinity. However, FACS screening for mutants with enhanced catalytic activity has been met with limited success. This review focuses on the FACS screening of protein libraries for enzymatic activity.     

Population dynamics simulations of functional model proteins

In order to probe the fundamental principles that govern protein evolution, we use a minimalist model of proteins to provide a mapping from genotype to phenotype. The model is based on physically realistic forces of protein folding and includes an explicit definition of protein function. Thus, we can find the fitness of a sequence from its ability to fold to a stable structure and perform a function. We study the fitness landscapes of these functional model proteins, that is, the set of all sequences mapped on to their corresponding fitnesses and connected to their one mutant neighbors. Through population dynamics simulations we directly study the influence of the nature of the fitness landscape on evolution. Populations are observed to move to a steady state, the distribution of which can often be predicted prior to the population dynamics simulations from the nature of the fitness landscape and a quantity analogous to a partition function. In this paper, we develop a scheme for predicting the steady-state population on a fitness landscape, based on the nature of the fitness landscape, thereby obviating the need for explicit population dynamics simulations and providing some insight into the impact on molecular evolution of the nature of fitness landscapes. Poor predictions are indicative of fitness landscapes that consist of a series of weakly connected sublandscapes.     

The potential and flux landscape theory of evolution

We established the potential and flux landscape theory for evolution. We found explicitly the conventional Wright's gradient adaptive landscape based on the mean fitness is inadequate to describe the general evolutionary dynamics. We show the intrinsic potential as being Lyapunov function(monotonically decreasing in time) does exist and can define the adaptive landscape for general evolution dynamics for studying global stability. The driving force determining the dynamics can be decomposed into gradient of potential landscape and curl probability flux. Non-zero flux causes detailed balance breaking and measures how far the evolution from equilibrium state. The gradient of intrinsic potential and curl flux are perpendicular to each other in zero fluctuation limit resembling electric and magnetic forces on electrons. We quantified intrinsic energy, entropy and free energy of evolution and constructed non-equilibrium thermodynamics. The intrinsic non-equilibrium free energy is a Lyapunov function. Both intrinsic potential and free energy can be used to quantify the global stability and robustness of evolution. We investigated an example of three allele evolutionary dynamics with frequency dependent selection (detailed balance broken). We uncovered the underlying single, triple, and limit cycle attractor landscapes. We found quantitative criterions for stability through landscape topography. We also quantified evolution pathways and found paths do not follow potential gradient and are irreversible due to non-zero flux. We generalized the original Fisher's fundamental theorem to the general (i.e., frequency dependent selection) regime of evolution by linking the adaptive rate with not only genetic variance related to the potential but also the flux. We show there is an optimum potential where curl flux resulting from biotic interactions of individuals within a species or between species can sustain an endless evolution even if the physical environment is unchanged. We offer a theoretical basis for explaining the corresponding Red Queen hypothesis proposed by Van Valen. Our work provides a theoretical foundation for evolutionary dynamics.     

Frustration Sculpts the Early Stages of Protein Folding

The funneled energy landscape theory implies that protein structures are minimally frustrated. Yet, because of the divergent demands between folding and function, regions of frustrated patterns are present at the active site of proteins. To understand the effects of such local frustration in dictating the energy landscape of proteins, here we compare the folding mechanisms of the two alternative spliced forms of a PDZ domain (PDZ2 and PDZ2as) that share a nearly identical sequence and structure, while displaying different frustration patterns. The analysis, based on the kinetic characterization of a large number of site‐directed mutants, reveals that although the late stages for folding are very robust and biased by native topology, the early stages are more malleable and dominated by local frustration. The results are briefly discussed in the context of the energy‐landscape theory.     

Amyloid Polymorphism in the Protein Folding and Aggregation Energy Landscape

Protein folding involves a large number of steps and conformations in which the folding protein samples different thermodynamic states characterized by local minima. Kinetically trapped on‐ or off‐pathway intermediates are metastable folding intermediates towards the lowest absolute energy minima, which have been postulated to be the natively folded state where intramolecular interactions dominate, and the amyloid state where intermolecular interactions dominate. However, this view largely neglects the rich polymorphism found within amyloid species. We review the protein folding energy landscape in view of recent findings identifying specific transition routes among different amyloid polymorphs. Observed transitions such as twisted ribbon→crystal or helical ribbon→nanotube, and forbidden transitions such helical ribbon?crystal, are discussed and positioned within the protein folding and aggregation energy landscape. Finally, amyloid crystals are identified as the ground state of the protein folding and aggregation energy landscape.     

Manipulating the stereoselectivity of limonene epoxide hydrolase by directed evolution based on iterative saturation mutagenesis

Limonene epoxide hydrolase from Rhodococcus erythropolis DCL 14 (LEH) is known to be an exceptional epoxide hydrolase (EH) because it has an unusual secondary structure and catalyzes the hydrolysis of epoxides by a rare one-step mechanism in contrast to the usual two-step sequence. From a synthetic organic viewpoint it is unfortunate that LEH shows acceptable stereoselectivity essentially only in the hydrolysis of the natural substrate limonene epoxide, which means that this EH cannot be exploited as a catalyst in asymmetric transformations of other substrates. In the present study, directed evolution using iterative saturation mutagenesis (ISM) has been tested as a means to engineer LEH mutants showing broad substrate scope with high stereoselectivity. By grouping individual residues aligning the binding pocket correctly into randomization sites and performing saturation mutagenesis iteratively using a reduced amino acid alphabet, mutants were obtained which catalyze the desymmetrization of cyclopentene-oxide with stereoselective formation of either the (R,R)- or the (S,S)-diol on an optional basis. The mutants prove to be excellent catalysts for the desymmetrization of other meso-epoxides and for the hydrolytic kinetic resolution of racemic substrates, without performing new mutagenesis experiments. Since less than 5000 tranformants had to be screened for achieving these results, this study contributes to the generalization of ISM as a fast and reliable method for protein engineering. In order to explain some of the stereoselective consequences of the observed mutations, a simple model based on molecular dynamics simulations has been proposed.     

Focusing mutations into the P. fluorescens esterase binding site increases enantioselectivity more effectively than distant mutations

Rational design of enzymes with improved properties, such as enantioselectivity, usually focuses mutations within the substrate binding site. On the other hand, directed evolution of enzymes usually targets the entire protein and discovers beneficial mutations far from the substrate binding site. In this paper, we propose an explanation for this discrepancy and show that a combined approach--random mutagenesis within the substrate binding site--is better. To increase the enantioselectivity (E) of a Pseudomonas fluorescens esterase (PFE) toward methyl 3-bromo-2-methylpropionate, we focused mutagenesis into the substrate binding site at Trp28, Val121, Phe198, and Val225. Five of the catalytically active mutants (13%) showed better enantioselectivity than wild-type PFE. The increases in enantioselectivity were higher (up to 5-fold, reaching E = 61) than with mutants identified by random mutagenesis of the entire enzyme.     

Visualizing Soluble Protein Mutants by Using Monomeric Red Fluorescent Protein as a Reporter for Directed Evolution

Directed evolution-based protein engineering usually generates large library contained insoluble mutants because of structural disturbance by mutation. To reduce the workload and costs, it is crucial to identify and eliminate those insoluble variants prior to dedicated analysis. Here, we demonstrate a method to visualize soluble protein mutants by using monomeric red fluorescent protein (mRFP) as a fusion tag. A plasmid was devised to express nicotinic acid mononucleotide adenylyltransferase (NadD) fused with a GGGS-linked mRFP tag at the C-terminus. The plasmid was subjected to site saturation mutagenesis within the nadD gene, used to transform Escherichia coli DH10B competent cells, leading to colonies with different red intensities. It was found that the fluorescence intensity of the cell culture correlated positively with the content of NadD-mRFP mutant in the supernatant. Mutation at position 132 led to a library of which most colonies lost the red phenotype, indicating that the position had a key role for proper protein folding. Similarly, mRFP enabled identification of soluble mutants of other enzymes including 1-deoxy-D-xylulose-5-phosphate reductoisomerase and phosphite dehydrogenase. These data suggested that mRFP can serve as a fusion reporter for visualizing soluble protein mutants to facilitate more efficient library screening in directed evolution.     

Isolation of a Dosage Dependent Lethal Mutation in Ubiquitin Gene of Saccharomyces Cerevisiae

Summary: Ubiquitin is a small protein with a highly conserved sequence, playing a pivotal role in ubiquitin proteasome system (UPS). Considering the central role UPS has in cellular homeostasis, several drugs have been developed to target UPS to remove cells responsible for cancer and other neurodegenerative diseases. As an alternative to the above approach, in the present study we have isolated dose dependent lethal form of ubiquitin gene by in vitro evolution. In vitro evolution is a powerful tool for developing proteins with novel and desirable properties. The ubiquitin gene of Saccharomyces cerevisiae was subjected to in vitro evolution and lethal mutations were selected. The ubiquitin of S. cerevisiae differs only by three residues from human ubiquitin. The mutants were selected by expressing the protein in temperature sensitive ubi4 deletion mutants of ubiquitin. Most of the mutations in ubiquitin gene failed to complement UBI4 phenotype under heat shock. Only one of the mutants caused cell lysis, even at permissive temperature. Interestingly, expression of the same protein in wild type S. cerevisiae cells left them unaffected, establishing the mutant protein as a competitive inhibitor for UPS. Sequencing of the mutant gene showed four completely novel amino acid substitutions. They are namely, Ser20 to Phe, Ala46 to Ser, Leu50 to Pro and Ile61 to Thr. Construction of the mutant ubiquitin gene and characterization of the mutant phenotype along with the nature and location of the mutations are presented.     

Predicting Fixation Tendencies of the H3N2 Influenza Virus by Free Energy Calculation

Influenza virus evolves to escape from immune system antibodies that bind to it. We used free energy calculations with Einstein crystals as reference states to calculate the difference of antibody binding free energy (ΔΔG) induced by amino acid substitution at each position in epitope B of the H3N2 influenza hemagglutinin, the key target for antibody. A substitution with positive ΔΔG value decreases the antibody binding constant. On average an uncharged to charged amino acid substitution generates the highest ΔΔG values. Also on average, substitutions between small amino acids generate ΔΔG values near to zero. The 21 sites in epitope B have varying expected free energy differences for a random substitution. Historical amino acid substitutions in epitope B for the A/Aichi/2/1968 strain of influenza A show that most fixed and temporarily circulating substitutions generate positive ΔΔG values. We propose that the observed pattern of H3N2 virus evolution is affected by the free energy landscape, the mapping from the free energy landscape to virus fitness landscape, and random genetic drift of the virus. Monte Carlo simulations of virus evolution are presented to support this view.     

Cellular automata and its applications in protein bioinformatics

With the explosion of protein sequences generated in the postgenomic era, it is highly desirable to develop high-throughput tools for rapidly and reliably identifying various attributes of uncharacterized proteins based on their sequence information alone. The knowledge thus obtained can help us timely utilize these newly found protein sequences for both basic research and drug discovery. Many bioinformatics tools have been developed by means of machine learning methods. This review is focused on the applications of a new kind of science (cellular automata) in protein bioinformatics. A cellular automaton (CA) is an open, flexible and discrete dynamic model that holds enormous potentials in modeling complex systems, in spite of the simplicity of the model itself. Researchers, scientists and practitioners from different fields have utilized cellular automata for visualizing protein sequences, investigating their evolution processes, and predicting their various attributes. Owing to its impressive power, intuitiveness and relative simplicity, the CA approach has great potential for use as a tool for bioinformatics.     

Expanding the substrate scope of enzymes: combining mutations obtained by CASTing

In a previous paper, the combinatorial active-site saturation test (CAST) was introduced as an effective strategy for the directed evolution of enzymes toward broader substrate acceptance. CASTing comprises the systematic design and screening of focused libraries around the complete binding pocket, but it is only the first step of an evolutionary process because only the initial libraries of mutants are considered. In the present study, a simple method is presented for further optimization of initial hits by combining the mutational changes obtained from two different libraries. Combined lipase mutants were screened for hydrolytic activity against six notoriously difficult substrates (bulky carboxylic acid esters) and improved mutants showing significantly higher activity were identified. The enantioselectivity of the mutants in the hydrolytic kinetic resolution of two substrates was also studied, with the best mutant-substrate combination resulting in a selectivity factor of E=49. Finally, the catalytic profile of the evolved mutants in the hydrolysis of simple nonbranched carboxylic acid esters, ranging from acetate to palmitate, was studied for theoretical reasons.     

Mapping the cytochrome C folding landscape

The solution to the riddle of how a protein folds is encoded in the conformational energy landscape for the constituent polypeptide. Employing fluorescence energy transfer kinetics, we have mapped the S.cerevisiae iso-1 cytochrome c landscape by monitoring the distance between a C-terminal fluorophore and the heme during folding. Within 1 ms after denaturant dilution to native conditions, unfolded protein molecules have evolved into two distinct and rapidly equilibrating populations: a collection of collapsed structures with an average fluorophore-heme distance (r) of 27 A and a roughly equal population of extended polypeptides with r > 50 A. Molecules with the native fold appear on a time scale regulated by heme ligation events ( approximately 300 ms, pH 7). The experimentally derived landscape for folding has a narrow central funnel with a flat upper rim on which collapsed and extended polypeptides interchange rapidly in a search for the native structure.     

Photo‐Driven Hydrogen Evolution by an Artificial Hydrogenase Utilizing the Biotin‐Streptavidin Technology

Photocatalytic hydrogen evolution by an artificial hydrogenase based on the biotin‐streptavidin technology is reported. A biotinylated cobalt pentapyridyl‐based hydrogen evolution catalyst (HEC) was incorporated into different mutants of streptavidin. Catalysis with [Ru(bpy)₃]Cl₂ as a photosensitizer (PS) and ascorbate as sacrificial electron donor (SED) at different pH values highlighted the impact of close lying amino acids that may act as a proton relay under the reaction conditions (Asp, Arg, Lys). In the presence of a close‐lying lysine residue, both, the rates were improved, and the reaction was initiated much faster. The X‐ray crystal structure of the artificial hydrogenase reveals a distance of 8.8 Å between the closest lying Co‐moieties. We thus suggest that the hydrogen evolution mechanism proceeds via a single Co centre. Our findings highlight that streptavidin is a versatile host protein for the assembly of artificial hydrogenases and their activity can be fine‐tuned via mutagenesis.     

Spectral tuning of photoactive yellow protein

We report a theoretical study on the optical properties of a small, water-soluble photosensory receptor, photoactive yellow protein (PYP). A hierarchical ab initio molecular orbital calculation accurately evaluated the optical absorption maximum of the wild-type, as well as the lambda(max) values of 12 mutants. Electronic excitation of the chromophore directly affects the electronic state of nearby atoms in the protein environment. This effect is explicitly considered in the present study. Furthermore, the spectral tuning mechanism of PYP was investigated at the atomic level. The static disorder of a protein molecule is intimately related to the complex nature of its energy landscape. By using molecular dynamics simulation and quantum mechanical structure optimization, we obtained multiple minimum energy conformations of PYP. The statistical distribution of electronic excitation energies of these minima was compared with the hole-burning experiment (Masciangioli, T. [2000] Photochem. Photobiol. 72, 639), a direct observation of the distribution of excitation energies.     

Preferential attachment during the evolution of a potential energy landscape

It has previously been shown that the network of connected minima on a potential energy landscape is scale-free, and that this reflects a power-law distribution for the areas of the basins of attraction surrounding the minima. Here, the aim is to understand more about the physical origins of these puzzling properties by examining how the potential energy landscape of a 13-atom cluster evolves with the range of the potential. In particular, on decreasing the range of the potential the number of stationary points increases and thus the landscape becomes rougher and the network gets larger. Thus, the evolution of the potential energy landscape can be followed from one with just a single minimum to a complex landscape with many minima and a scale-free pattern of connections. It is found that during this growth process, new edges in the network of connected minima preferentially attach to more highly connected minima, thus leading to the scale-free character. Furthermore, minima that appear when the range of the potential is shorter and the network is larger have smaller basins of attraction. As there are many of these smaller basins because the network grows exponentially, the observed growth process thus also gives rise to a power-law distribution for the hyperareas of the basins.     

Conformational substates modulate hydride transfer in dihydrofolate reductase

In earlier studies of the hydride-transfer reaction catalyzed by dihydrofolate reductase (DHFR) we identified features of the protein correlated with variations in the reaction barrier. We extend the scope of those studies by carrying out potential of mean force (PMF) simulations to determine the hydride-transfer barrier in the wild-type protein as well as the G121V and G121S mutants. While our prior studies focused on the reactant state, our current work addresses the full reaction pathway and directly probes the reactive event. The free energy barriers and structural ensembles resulting from these PMF calculations exhibit the same trends reported in our previous work. Fluctuations present in these simulations also exhibit trends associated with differences in the hydride-transfer barrier height. Moreover, vibrational modes anticipated to promote hydride transfer exhibit larger amplitudes in simulations that generate lowered barriers. The results of our study indicate that discrete basins (substates) on a potential energy landscape of the enzyme give rise to distinct hydride-transfer barriers. We suggest that the long-range effects of mutations at position 121 within DHFR are mediated by differentially preorganized protein environments in the context of distinct substate distributions, with concomitant changes to the dynamic properties of the enzyme.     

Relationship between the organization of the PS II super complex and the functions of the photosynthetic apparatus

The chlorophyll fluorescence and the photosynthetic oxygen evolution (flash-induced oxygen yield patterns and oxygen bursts under continuous irradiation) were investigated in the thylakoid membranes with different stoichiometry and organization of the chlorophyll-protein complexes. Data show that the alteration in the organization of the photosystem II (PS II) super complex, i.e. the amount and the organization of the light-harvesting chlorophyll a/b protein complex (LHCII), which strongly modifies the electric properties of the membranes, influences both the energy redistribution between the two photosystems and the oxygen production reaction. The decrease of surface electric parameters (charge density and dipole moments), associated with increased degree of LHCII oligomerization, correlates with the strong reduction of the energy transfer from PS II to PSI. In the studied pea thylakoid membranes (wild types Borec, Auralia and their mutants Coeruleovireus 2/16, Costata2/133, Chlorotica XV/1422) with enhanced degree of oligomerization of LHCII was observed: (i) an increase of the S(0) populations of PS II in darkness; (ii) an increase of the misses; (iii) an alteration of the decay kinetics of the oxygen bursts under continuous irradiation. There is a strict correlation between the degree of LHCII oligomerization in the investigated pea mutants and the ratio of functionally active PS II alpha to PS II beta centers, while in thylakoid membranes without oligomeric structure of LHCII (Chlorina f2 barley mutant) the PS II alpha centers are not registered.     

Incorporating specificity into optimization: evaluation of SPA using CSAR 2014 and CASF 2013 benchmarks

Scoring functions of protein–ligand interactions are widely used in computationally docking software and structure-based drug discovery. Accurate prediction of the binding energy between the protein and the ligand is the main task of the scoring function. The accuracy of a scoring function is normally evaluated by testing it on the benchmarks of protein–ligand complexes. In this work, we report the evaluation analysis of an improved version of scoring function SPecificity and Affinity (SPA). By testing on two independent benchmarks Community Structure-Activity Resource (CSAR) 2014 and Comparative Assessment of Scoring Functions (CASF) 2013, the assessment shows that SPA is relatively more accurate than other compared scoring functions in predicting the interactions between the protein and the ligand. We conclude that the inclusion of the specificity in the optimization can effectively suppress the competitive state on the funnel-like binding energy landscape, and make SPA more accurate in identifying the “native” conformation and scoring the binding decoys. The evaluation of SPA highlights the importance of binding specificity in improving the accuracy of the scoring functions.     

TargetATPsite: A template‐free method for ATP‐binding sites prediction with residue evolution image sparse representation and classifier ensemble

Understanding the interactions between proteins and ligands is critical for protein function annotations and drug discovery. We report a new sequence‐based template‐free predictor (TargetATPsite) to identify the Adenosine‐5′‐triphosphate (ATP) binding sites with machine‐learning approaches. Two steps are implemented in TargetATPsite: binding residues and pockets predictions, respectively. To predict the binding residues, a novel image sparse representation technique is proposed to encode residue evolution information treated as the input features. An ensemble classifier constructed based on support vector machines (SVM) from multiple random under‐samplings is used as the prediction model, which is effective for dealing with imbalance phenomenon between the positive and negative training samples. Compared with the existing ATP‐specific sequence‐based predictors, TargetATPsite is featured by the second step of possessing the capability of further identifying the binding pockets from the predicted binding residues through a spatial clustering algorithm. Experimental results on three benchmark datasets demonstrate the efficacy of TargetATPsite. © 2013 Wiley Periodicals, Inc.