A genetic algorithm based design and experimental characterization

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A genetic algorithm based design and experimental characterization of a highly thermostable metalloprotein Esra Bozkurt, Marta A. S. Perez, Ruud Hovius, Nicholas J. Browning, and Ursula Rothlisberger J. Am. Chem. Soc., Just Accepted Manuscript • DOI: 10.1021/jacs.7b10660 • Publication Date (Web): 16 Jan 2018 Downloaded from http://pubs.acs.org on January 16, 2018

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Journal of the American Chemical Society

A genetic algorithm based design and experimental characterization of a highly thermostable metalloprotein Esra Bozkurt‡, Marta A. S. Perez‡, Ruud Hovius†, Nicholas J. Browning‡, and Ursula Rothlisberger‡* ‡Laboratory

of Computational Chemistry and Biochemistry, École Polytechnique Fédérale de Lausanne, EPFL, CH-1015 Lau-

sanne, Switzerland. †Laboratory

of Protein Engineering, École Polytechnique Fédérale de Lausanne, EPFL, CH-1015 Lausanne, Switzerland.

ABSTRACT: The development of thermostable and solvent-tolerant metalloproteins is a long-sought goal for many applications in synthetic biology and biotechnology. In this work, we were able to engineer a highly thermo- and organic solventstable metallo variant of the B1 domain of protein G (GB1) with a tetrahedral zinc-binding site reminiscent of the one of thermolysin. Promising candidates were designed computationally by applying a protocol based on classical and first-principles molecular dynamics simulations in combination with genetic algorithm (GA) optimization. The most promising of the computationally predicted mutants was expressed and structurally characterized and yielded a highly thermostable protein. The experimental results thus confirm the predictive power of the applied computational protein engineering approach for the de novo design of highly stable metalloproteins.

1 INTRODUCTION Metalloproteins1 possess distinct and unique properties and fulfil a wide scope of biological functions ranging from regulation to multiple catalytic activities2,3. For instance, iron-sulfur metalloproteins4,5 take part in photosynthesis and respiration in different organisms, while the copper active site in methane monooxygenase (MMO)6 can oxidase highly inert substrates such as methane and propylene. Among metalloproteins, zinc enzymes are especially noteworthy due to their unusual prowess in providing remarkable rate acceleration and structural stabilization. This broad versatility is in part due to the fact that the zinc coordination sphere can vary significantly in terms of coordination number and geometry as well as in the nature of coordinating ligands resulting in diverse chemical and biological functions7–12. As a result, the design of artificial zinc binding proteins has become an attractive target13–16 for both experimental and computational approaches. Nonetheless, the design of de novo proteins and in particular of metalloproteins is a highly nontrivial task17. One of the key questions is the choice of an appropriate structural starting template that can range from minimal synthetic models of the active site to full de novo engineered proteins18–20. Here we opted for an intermediary route by basing our design on a midsize protein domain.

Due to its exceptional thermo and mechano-stability, the B1 domain of Streptococcal protein G (GB1)21 is a particularly attractive option for such a purpose. GB1 is composed of 56 amino acids arranged in a single alpha helix and a fourstranded beta sheet. A number of highly thermostable mutants have been prepared with melting temperatures that even exceed that of the wild type by as much as 40 0C. In addition, for several of these mutants, crystal structures have been refined22–26 showing that the wild-type structure is highly conserved even upon the introduction of as much as seven mutations. Therefore, GB1 appears as a highly promising native scaffold for biomimetic protein engineering in general and metallo-functionalization in particular. Not surprisingly, since 1995, there have been numerous attempts to create structurally stable or even functional metal binding sites in GB1 that have so far met with only moderate success. Several groups have reported the design of zinc27,28, iron29 and copper30 binding sites, however in all cases, the mutations that have been introduced to allow for metal binding led to strongly (by more than 20oC) decreased TM values with respect to the wild-type. Here, we computationally designed a GB1 based metalloprotein using genetic algorithm optimization in combination with quantum mechanical based molecular dynamics simulations. This mutant features a tetrahedral solvent accessible zinc binding site in one of the loop regions with two histidines (23 and 50) and one glutamate residue (47) and

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2 a flexible 4th coordination site. In addition to the mutations that accommodate the metal ion, six thermostabilizing mutations (Y3F/E15V/T16I/T18I/T25E/V29F) were used to fortify the core. This computationally designed metallo-variant was subsequently expressed in E. coli and isolated in high yield. Circular dichroism (CD) spectroscopy, analytical ultracentrifugation (AUC) and X-ray crystallography were used to characterize the design. The computationally optimized and functionalized mutant shows indeed a high stability even in the apo form (with a T M of the apoprotein of 73.6 ± 0.7 0C in 2.5 M guanidium hydrochloride buffer that is 36oC higher than the one of the wild type). This combined experimental and computational study constitute a successful example of the de novo engineering and structural characterization of a metallo miniprotein. The resulting highly thermostable zinc binding variant of GB1 opens the way for further functionalization of this mini-protein for applications in catalysis, biosensor design and metal-mediated nanostructure design. 2 RESULTS AND DISCUSSION 2.1. Creating an artificial metal binding site via genetic algorithm (GA) optimization Genetic algorithms (GA) can be successfully applied to a wide variety of high-dimensional optimization problems31. We have previously demonstrated that our in-house developed genetic algorithm toolbox EVOLVE can be utilized to optimize training sets of small organic molecules for machine learning32 or to maximize the catalytic activity of biomimetic scaffolds.33 Here, EVOLVE has been applied to wild-type GB1 to engineer an optimal metal binding site. Wild-type GB1 is free of cysteine and histidine residues, which may act as potential metal chelating ligands. Therefore, in a first step, we used the GA to explore the best locations for histidines as the amino acid with the highest propensity for zinc coordination. 11 boundary residues (12, 16, 18, 23, 25, 29, 33, 37, 43, 45 and 50) were varied during this search whereas core residues were excluded since the introduction of metal-binding amino acids in the core might lead to significant perturbation of the protein structure and furthermore, solvent accessibility is limited in the core hampering the coordination of a water molecule as putative zinc ligand that might ultimately serve as catalytically activatable species. For each of the 11 boundary positions, 24 side chain rotamers were considered: 8 with a hydrogen on the delta nitrogen, (HID), 8 with hydrogen on epsilon nitrogen (HIE) and 8 with hydrogens on both nitrogens, i.e. a positively charged histidine (HIP).

Figure 1. Two different views of the GA optimized histidinerich mutant with the highest fitness. The highest fitness value reached was -29.6 kcal/mol with respect to the wild type sequence. The energetically preferred rotomers of the

histidine residues are shown in licorice representation (blue). The space explored by the GA is the product of the number of possible rotamers at each variable position and therefore is composed of 2411 possible rotamer sequences. Due to the stochastic nature of the GA, we performed 3 independent GA runs with a population size of 100 propagated for 200 generations resulting in a total pool of 60’000 individuals that were evolutionary optimized with respect to a fitness function assessing protein stability (see Supporting Information for more details). The GA optimization suggests that histidines can be accommodated at several GB1 boundary positions yielding mutants that are predicted to be even more stable than the wild-type. Figure 1 shows the fittest solution of histidines on boundary residues of the GB1 protein in a front view (left) and rotated by 180o (right). It turns out that the histidines at locations 23, 45 and 50 are close enough to each other and strategically well oriented to form a potential metal binding site. This triple mutant 23H/45H/50H with a putative zinc coordination center is predicted to be 2.6 kcal/mol more stable than the wild-type protein (Table 1). In a second round of GA sequence optimizations, all amino acids were included as potential mutants. These runs showed that position 45 showed a strong propensity for hydrophobic residues in agreement with two experimental studies that have shown that mutation of position 45 to Trp34 and Phe35 leads to a stabilization of the protein. For this reason, for the location of a highly thermostable metal binding site, we kept histidines in positions 23 and 50 while we choose to find an alternative to position 45 in order to keep this position free for possible thermostabilizing mutations. In a next step, we kept residue 45 in the wild-type form and explored position 47 for possible zinc coordinating ligands. In this case, the GA optimization converges to a solution with 23H/47E/50H, a mutant that is predicted to be 5.7 kcal/mol more stable than the wild type sequence (Table1). In this way, we thus identified the metal binding site involving His23, His50, Glu47 and a flexible fourth ligand (e.g. a water molecule from the solvent) that is predicted to be even more stable than the previously optimized triple His site. Encouragingly, it is common to find tetrahedral zinc binding sites in loop regions of αβ class proteins, especially in DNA-binding small domains36–40. Finally, we use the GA to optimize side chain rotamer composition of the mutations 3F/15V/16I/18I/25E/29F41,42 that fortify the GB1 core together with the previously determined putative metal binding site 23H/47E/50H. The final designed GB1 mutant 3F/15V/16I/18I/23H/25E/29F/47E/50H (termed 6B123H/47E/50H) is predicted to be stabilized by 17.4 kcal/mol (Table 1) with an estimated increase in melting temperature of ca. 13 oC with respect to the wild type. Based

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3 on these computational results, 6B123H/47E/50H was selected for experimental characterization.

Figure 2. GA optimization of the rotamer composition of the metal binding site. Mutant with metal center 1 (23H/45H/50H) in red, with metal binding center 2 (23H/47E/50H) in blue, and final mutant 3F/15V/16I/18I/23H/25E/29F/47E/50H in green. Fitness values are reported as a function of the number of generations during GA optimization for 3 independent runs using different frames as starting points (See computational details). Table 1 Results of GA based sequence optimization. Calculated fitness values for metallo-GB1 variants (in kcal/mol) with and without entropy corrections and predicted changes in TM (oC) with respect to the wild-type. Mutations 23H/45H/50H 23H/47E/50H 3F/15V/16L/18L/23H/25E/29F/47E/50H

Fitness (kcal/mol) -2.6 -5.7 -17.4

Fitness with entropy (kcal/mol) -2.5 -4.9 -16.1

∆Tm (oC) -2.0 -3.9 -12.9

2.2. Dynamics and structure of the designed metallogb1 mutant in solution We first assessed the finite temperature behaviour of the designed mutant in solution by classical molecular dynamics at 300 K. These simulations showed that even the apoprotein is structurally very stable in a fold close to the wildtype over the entire MD run of 500 ns consistent with the results obtained with the GA optimization. This is also confirmed in the CD measurements of the metalfree form of the designed mutant in different buffers and solvents (Figure 3). In all cases, the CD spectrum remains similar in shape and magnitude to the one of wild-type GB1, indicating that the native structure is kept and the fold is stable over a wide pH range. It should also be noted that there is almost no change in the shape of the CD spectrum even in the presence of high salt concentrations and the designed mutant is even able to tolerate organic solvents. In fact, the CD spectra acquired at 50oC are essentially the same in trifluoroethanol, methanol and acetonitrile (see Supplementary Information).

The measurement of the temperature-dependent CD data (Supporting Information) fully corroborates the high stability of the computationally designed mutant yielding a melting temperature of the apo form that is significantly higher (73.6 ± 0.7 oC) than the one of wild-type GB1 (38.0 ± 1.3oC) in 2.5 M guanidium chloride (pH 7.0). Furthermore, thermal denaturation is fully reversible. We also performed thermal unfolding experiments at two different protein concentrations to gain first indications about the possible oligomerization state in solution. Previously, Schmidt et al.43 discussed the stability of several GB1 variants at varying concentrations and pointed out that dimeric forms showed concentration dependent TM values. We observed that the thermal unfolding transition of the designed mutant does not depend on concentration over the range of 2 µM to 10 µM protein. Thermal unfolding transitions are provided in the Supplementary Information.

Figure 3. Stability of apo metallo-GB1. a, CD spectra of the computationally designed apo protein (at 10 µM protein concentration) at various pH values. b, CD spectra of the apo protein in TFE (trifluoroethanol), acetonitrile and methanol at 20oC. c, A representative frame of 6B123H/47E/50H from allatom MD simulations aligned with the quadruple mutant (16I/18I/25E/29F) of GB1 (PDB code: 2ONQ44). Cα atoms of mutated residues are shown as coloured spheres. Subsequently, we also examined the zinc bound protein by means of QM/MM molecular dynamics simulations. These QM/MM simulations further confirm that monomeric Zn6B123H/47E/50H in aqueous solution retains the tetrahedral geometry over the entire length of the simulation of ~40 ps with a water molecule as 4th ligand. The close resemblance of this zinc binding site to the active site of thermolysin 45 suggests that the designed mutant might possess proteolytic activity. However, we were not able to detect any peptidase activity neither with BSA (bovine serum albumin)46 or a synthetic fluorogenic substrate, 2-aminobenzoyl-AlaGly-Leu-Ala-nitrobenzylamide (Abz-AGLA-Nba) at different pH values. To shed more light on the behavior of the mutant in solution, analytical ultracentrifugation (AUC) was used to determine the oligomerization state with and without zinc ions. Some proteins can be monomeric even at high concentrations (>1mM), although they are identified as dimers in the crystal47. AUC is applied widely as an efficient method to understand the self-assembly properties of biomacromolecules even at low (10 µM protein/metal) concentrations.



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4 Sedimentation velocity experiments (Figure 4) indicated that in the absence of Zn2+ only the monomeric form exists. However, at 50 µM protein and 200 µM Zn2+ concentrations, dimeric species form in solution.

Figure 4. Oligomerization state of metallo-GB1 in solution. (a) Normalized sedimentation coefficient distribution of the 50 µM GB1 mutant in the absence and presence of 200 µM Zn2+. (b) Representative QM/MM snapshot of the metal binding site in the monomeric protein. 2.3. Crystal structure analysis of the designed mutant bound to Zn2+ The structure of the designed Zn-6B123H/47E/50H mutant was determined via X-ray crystallography. We were able to refine the crystal structure of this metallo-form of GB1 to 1.1 Å. The crystal structure revealed a head-to-tail dimer architecture in which each monomer contains 56 residues and the overall topology of the wild-type fold is kept. In the crystal, the designed binding site 23H/47E/50H is indeed occupied by a zinc ion in a tetrahedral coordination geometry in which the fourth position is however occupied by the C-terminus of the glutamate residue (56E) from the second monomer instead of a solvent molecule. Head-to-tail interaction between the two monomers is thus is mediated by two aromatic (23H and 50H) and two charged residues (47E and 56E). Lys10 from monomer 1 interacts with the backbone and the side chain oxygen of the zinc chelating residue Glu47. In addition, a second zinc binding site at the proteinprotein interface is also formed by Asp22 and Glu42 in the high resolution crystal structure (PDB ID: 5OFS). This also provides an oxygen atom of Glu42 a proper position to interact with His23 through N-H…O hydrogen bonding, presumably providing further structural stabilization (Figure 5). The resulting primary zinc-coordination sphere of metal binding site M1, except for the presence of 56E from the other monomer, is very similar to the ones found in thermolysin45 and carboxypeptidase A48 (Figure 5). Despite having ten mutations, the structure is highly similar to the wildtype protein with a root mean square (RMS) deviation of 1.2 Å (1PGA49) and 1.1 Å (1PGB) when backbone atoms (Cα positions) are aligned. Based on the crystal structure, it seems likely that the mode of dimerization in solution (observed at 50 µM protein and

200 µM Zn2+) corresponds to a head-to-tail association, instead of head-to-head or side-by-side arrangement. Previous studies have shown that some GB1 variants form headto-head dimers when both positions 16 and 37 are mutated

Figure 5. 1.1 Å X-ray structure of the metallo-GB1 mutant (PDB ID: 5OFS). (a) Two views of the head-to-tail arrangement with the two metal ions. (b) Close-up view of the two zinc binding sites. Some characteristic h-bond interactions are shown as dashed black lines. to leucine25. On the other hand, no oligomerization was observed for a GB1-IIEF variant with Ile16, Ile18, Glu25 and Phe29 mutations.22 We also addressed this point by using CheckMyMetal server (http://csgid.org/csgid/metal_sites/)50, which analyses metal binding sites and ranks other possible metal ions according to their probability. The server suggested a glutamate residue as the fourth ligand and this is consistent with the head-to-tail organization observed in the crystal structure. Clearly, at higher concentrations, the zinc bound protein arranges into the crystallographically identified form. Similar metal ion induced dimerization phenomena occur in a variety of proteins including engineered cytochrome cb56251, maltose binding protein52, an ATPase family protein53 and Staphylococcal enterotoxin54. Finally, we also investigated the head-to-tail dimer structure computationally. The resulting QM/MM structure in aqueous solution is consistent with the X-ray structure and the tetrahedral coordination geometry is retained all throughout the QM/MM run of 25 ps. The novel head-to-tail association of Zn6B123H/47E/50H is also interesting per se in view of the design of specific supramolecular assemblies. Therefore, our computational design protocol and its experimental validation suggest that small protein domains could serve as generic building blocks for an à-la-carte creation of metalloproteins and metal-mediated protein-protein interactions. 3 CONCLUSIONS The design of highly stable metalloproteins is a long-standing goal to create a variety of versatile biomolecules. Here, we have demonstrated that a computational design strategy


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5 based on genetic algorithm optimization and classical and QM/MM molecular dynamics simulations can aid the experimental incorporation of new metal binding sites into native protein scaffolds. With a combined computational/experimental approach, it was possible to create a highly thermostable metallo form of GB1 containing a tetrahedral zinc binding site as confirmed by temperature-dependent CD measurements and X-ray crystallography. The remarkably high melting temperature, solvent tolerance and its capability in metal mediated dimerization also make this mutant an attractive starting point for the generation of specific superstructures based on protein self-assembly. With the crystal structure of Zn-6B123H/47E/50H now in hand, further engineering of the metal binding site with natural and unnatural amino acids may allow for a further functionalization and the introduction of specific catalytic activities. ASSOCIATED CONTENT All experimental and computational details are given in the Supporting Information. This material is available free of charge via the Internet at http://pubs.acs.org.

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AUTHOR INFORMATION Corresponding Author * [email protected]

Funding Sources

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UR gratefully acknowledges financial support from the Swiss National Science Foundation Grant No. 200020-146645 and the NCCR MARVEL.

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ACKNOWLEDGMENT

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The authors thank the National Computing Center CSCS and EPFL SCITAS for providing computing time. We are grateful to Kai Johnsson for hosting the experimental work in his laboratory. We also thank Christian Heinis for providing the CD spectropolarimeter. The authors thank Harm-Anton Klok and Ahmet Bekdemir for the analytical ultracentrifugation experiments. We thank Florence Pojer for X-ray data collection. Finally, we thank Laure Menin for running the mass spectrometry.

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