High-resolution Structural and Thermodynamic Analysis of ... · High-resolution Structural and...

doi:10.1016/j.jmb.2006.11.080 J. Mol. Biol. (2007) 366, 1209–1221

High-resolution Structural and ThermodynamicAnalysis of Extreme Stabilization of HumanProcarboxypeptidase by Computational Protein Design

Gautam Dantas1, Colin Corrent1, Steve L. Reichow2

James J. Havranek1, Ziad M. Eletr4, Nancy G. Isern5, Brian Kuhlman4

Gabriele Varani1,2, Ethan A. Merritt1 and David Baker1,3⁎
1Department of Biochemistry,University of Washington,Seattle, WA 98195, USA2Department of Chemistry,University of Washington,Seattle, WA 98195, USA3Howard Hughes MedicalInstitute, University ofWashington, Seattle,WA 98195, USA4Department of Biochemistryand Biophysics, University ofNorth Carolina, Chapel Hill,NC 27599, USA5EMSL High Field MagneticResonance Facility, PNNL,Richland, WA 99352, USA
Present address: G. Dantas, DepaHarvard Medical School, 77 AvenueBoston, MA 02115, USA.Abbreviations used: HSQC, heter

single-quantum coherence; NOE, nueffect; NOESY,NOE spectroscopy; RMdeviation; RDF, radial distributionE-mail address of the correspondi

[email protected]

0022-2836/$ - see front matter © 2006 E

Recent efforts to design de novo or redesign the sequence and structure ofproteins using computational techniques have met with significant success.Most, if not all, of these computational methodologies attempt to modelatomic-level interactions, and hence high-resolution structural character-ization of the designed proteins is critical for evaluating the atomic-levelaccuracy of the underlying design force-fields. We previously used ourcomputational protein design protocol RosettaDesign to completelyredesign the sequence of the activation domain of human procarboxypepti-dase A2. With 68% of the wild-type sequence changed, the designedprotein, AYEdesign, is over 10 kcal/mol more stable than the wild-typeprotein. Here, we describe the high-resolution crystal structure and solutionNMR structure of AYEdesign, which show that the experimentallydetermined backbone and side-chains conformations are effectivelysuperimposable with the computational model at atomic resolution. Toisolate the origins of the remarkable stabilization, we have designed andcharacterized a new series of procarboxypeptidase mutants that gainsignificant thermodynamic stability with a minimal number of mutations;one mutant gains more than 5 kcal/mol of stability over the wild-typeprotein with only four amino acid changes. We explore the relationshipbetween force-field smoothing and conformational sampling by comparingthe experimentally determined free energies of the overall design and thesefocused subsets of mutations to those predicted using modified force-fields,and both fixed and flexible backbone sampling protocols.

© 2006 Elsevier Ltd. All rights reserved.

Keywords: Computational protein design; Rosetta; Thermodynamic stabi-lization; High-resolution protein structure; Procarboxypeptidase A2
*Corresponding author
Introduction

Natural proteins perform a startling diversity ofbiological functions, but comprise a minisculefraction of the theoretical sequence–structure space

rtment of Genetics,Louis Pasteur,

onuclearclear OverhauserSD, root-mean-squarefunction.ng author:

lsevier Ltd. All rights reserve

that polypeptides might occupy.1–4 The goal ofprotein design is to identify new free-energyminimain this sequence–structure landscape so as to expandthe functional repertoire of polypeptides beyond thatobserved in nature.5–9 The design of new proteinsshould allow for the creation of novel molecularmachines and therapeutics but requires an accuratedescription of the forces that govern protein struc-ture and folding.10,11 The last decade has witnessedtremendous advances in the development of in silicoprotein sequence and structure optimization algo-rithms. They have been applied successfully tocompletely redesign12 and thermodynamically sta-bilize natural protein folds,13 to create novel14 andthermodynamically-stabilized enzymes,15 to rede-sign protein–protein16 and protein–ligand17 interac-

d.

mailto:[email protected]

1210 High-resolution Structural Analysis of AYE Design

tions, and to create extremely stable novel proteinstructures.18,19 While structural validation in a fewcases has confirmed the high-resolution accuracy ofthe designs,12,15,16,18–20 the total repertoire of high-resolution structures of computationally designedproteins remains small. Structural characterizationof designed proteins is essential for validation of thedesign model and for evaluating the accuracy of theunderlying force-fields.In a large-scale evaluation of our computational

protein design methodology, we used RosettaDe-sign to completely redesign the sequence of ninesmall globular proteins.13 The redesign of theactivation domain of human procarboxypeptidaseA2, AYEdesign, was the most successful redesign; ithad a native-like secondary structure profile, wasrigid and well folded, was stabilized dramaticallyover its wild-type counterpart,13 and folded muchfaster and unfolded much slower than the wild-typeprotein.21 We have now determined high-resolutioncrystal and NMR structures of AYEdesign, toevaluate the atomic-level accuracy of the RosettaDe-sign protocol. We use the information gleaned fromthese structural studies to design and characterize anew series of AYE mutants that gain significantthermodynamic stability with a minimal number ofmutations. The analysis of these results providesinsight into the coupling between force-fieldsmoothing and the extent of conformational sam-pling in high-resolution protein modeling anddesign.

Results and Discussion

RosettaDesign was previously used to redesigncompletely the sequence of the activation domain ofhuman procarboxypeptidase A2.13 The 1.8 Å crystalstructure of the wild-type protein (1AYE)22 wasused as a template for the design simulation,allowing all amino acids except cysteine at all 70positions. The final sequence chosen for experimen-tal study, AYEdesign, differed from the wild-typeprotein by 68% over all residues and 33% over coreresidues. Far-UV circular dichroism (CD) spectros-copy, 1D 1H nuclear magnetic resonance (NMR)spectroscopy, and chemical and thermal denatur-ation experiments showed that AYEdesign adopteda well-folded, rigid structure, with a secondarystructure profile very similar to that of the wild-typeprotein. AYEdesign was found to be extremelystable; its folded structure is impervious to boilingand it is greater than 10 kcal/mol more stable thanthe wild-type protein (Table 2). It also folds ∼1000-fold faster and unfolds ∼20,000-fold slower than thewild-type protein.21 To extend the comparisonbetween AYEdesign and its wild-type parent toatomic resolution, we have now determined bothcrystal and solution NMR structures of AYEdesign.We produced and crystallized a selenomethionyl

(SeMet)-substituted variant of AYEdesign (AYE-des_VJQ), and solved the x-ray crystal structure ofAYEdes_VJQ to a resolution of 2.1 Å by direct

rebuilding into an unbiased multiple-wavelengthanomalous dispersion (MAD) electron density mapand residual difference Fourier maps. The finalRwork and Rfree were 0.20 and 0.27, respectively(Supplementary Data Table S1). The asymmetricunit of the crystal contains two independent proteinchains. The N-terminal 70 residues of each chainexhibit the expected procarboxypeptidase fold of theparent 1AYE design target. The Cα RMSD from thecomputational model is 1.68 Å and 1.28 Å for chainA and B, respectively, and this improves to 1.13 Åand 0.65 Å when 66 of the 70 residues are consideredfor chain A and B, respectively (Figure 2(a)).Two AYEdes_VJQ monomers associate to form a

dimer in the crystal. Dimerization is mediated, inpart, by the C termini of the two chains, which forman anti-parallel β-sheet consisting of residues 66–73from chain A and residues 64–70 from chain B(Figure 1(a)). However, the contribution of chain Ato the β-sheet includes three residues from thecleavable linker sequence that are not part of thedesigned sequence. Gel-filtration chromatographystudies (data not shown) of the AYEdes_VJQconstruct showed that the protein exists predomi-nantly as a dimer at 10–100 μM (where thermody-namic properties of the original AYEdesignconstruct were measured), as well as at crystallog-raphy concentrations (≥1 mM). Since the dimer inthe crystal structure was mediated at least partly byextra C-terminal residues not considered in theoriginal design, we prepared a new construct,AYEdes, with an N-terminal His6 tag followedonly by the 70 designed residues of AYEdesign.Consistent with our original biophysical character-ization, the AYEdes protein exists predominantlyas a monomer at concentrations of 10–100 μM asjudged by chromatography, but exhibits partialdimeric character at higher concentrations(≥1 mM) (data not shown). Analytical ultracentri-fugation suggests that AYEdes exists in a monomer–dimer equilibrium with an estimated Kd of ∼150 μM(Supplementary Data Figure S1). This weak associa-tion implies that protein dimerization plays aninsignificant role in the extreme thermodynamicstabilization of the designed monomer, and that thedimer dissociates well before the monomer unfolds.We confirmed this assumption by repeating CDequilibrium denaturation experiments at multipleconcentrations of AYEdes, where we observe thatthe melting curves and unfolding transitions for5 μM, 50 μM, and 100 μM protein are entirelycoincident. This result allowed us to fit the observedtwo-state unfolding of AYEdes as equilibriumdenaturation between folded monomers and un-folded monomers.To assess whether removal of the extra C-

terminal tag residues had any impact on theatomic-level structure of AYEdesign, we deter-mined the NMR solution structure of the AYEdesconstruct. The 1D 1H spectra and 2D 1H-15Nheteronuclear single-quantum coherence (HSQC)spectra of AYEdes exhibit the features of a well-folded protein (Figure 4), with well-dispersed NH

Figure 1. AYEdesign X-ray andNMR structures. (a) The AYE-design X-ray crystal structure(AYEdes_VJQ, chain A in lightblue, chain B in dark blue) andNMR solution structure (AYEdes,chain A in pink, chain B in red) aresuperimposed and shown as rib-bons. The protein forms a symmet-ric dimer that buries 740 Å ofsurface area of the back-face of theβ-sheet, with a gap volume index of2.37; these values are close to theaverage values observed for hetero-dimer interactions, but indicate aweaker interaction than is typicalfor homodimers or permanent pro-tein complexes.52 (b) The top 20NMRmodels from the final AYEdesstructure calculation are shown asCα backbones (different color foreach model). The ensemble pair-wise RMSD is 0.57(±0.18) Å overbackbone atoms and 1.09(±0.11) Åover heavy-atoms in residues 3–71in both subunits.

1211High-resolution Structural Analysis of AYE Design

resonances of uniform intensity.13 Protein back-bone and side-chain assignments were obtained bystandard procedures, as described in Materials andMethods. The uniform 1H-15N heteronuclear nuclearOverhauser effect (NOE) values (∼0.75) recorded forAYEdes indicate a conformationally rigid fold insolution reflecting the observed thermodynamicstability of this protein (Supplementary Data FigureS2). The T1/T2 ratios measured for AYEdes give acorrelation time of 10.64 ns, which is consistent withhomodimeric association under the conditions usedfor NMR.23 Notably, the HSQC spectrum contains asingle set of cross-peaks for each NH in the protein,indicating a fully symmetric association in solution.Structure determination was conducted in a two-step process; a partly-automated iterative stepdominated by NOE-derived distance constraintsfor generating models of a single subunit of AYEdes,followed by a second refinement step for buildingthe symmetric homodimer model using interfacialNOE constraints obtained from 3D 12C-edited-13C-filteredNOE spectroscopy (NOESY) data. In the finalcalculation, 100 structures (chains A and B) were

generated from the random-coil conformation. The20 lowest energy structures (Figure 1(b)) had anaverage Cyana24 target function of 2.75(±0.10) Å2

and an ensemble pair-wise root-mean-square devi-ation (RMSD) of 0.57(±0.18) Å over backbone atomsand 1.09(±0.11) Å over heavy-atoms in residues 3–71in both subunits (Supplementary Data Table S2).There was no distance constraint violated by morethan 0.2 Å, and no angle constraint violated by morethan 1.5°. When the ensemble was analysed withPROCHECKNMR,25 all dihedral angles were foundin the allowed regions of the Ramachandran plot(Supplementary Table S2). The Cα RMSD of thelowest energy AYEdes NMR model from the parent1AYE crystal structure is 1.51 Å over the 70 designedresidues, and improves to 1.05 Å when only the first66 of the 70 residues are considered (Figure 2(a)). Therelative rigid-body orientation of the two chains inthe NMR structure is virtually identical with theAYEdes_VJQ crystal structure (Figure 1(a)). Thesecombined structural results, together with gel-filtration analysis, suggest that at high concentra-tions, AYEdesign self-associates and buries the

Figure 2. Comparison of AYEdesign computational model and experimentally determined structures. (a) Both chainsof AYEdes_VJQ (light and dark blue) and AYEdes (pink and red) are superimposed on the AYEdesign computationalmodel (green), and are shown as Cα backbones in two orientations (related by a +90° rotation around the vertical axis inthe plane of the page). The Cα RMSD from the computational model is 1.68 Å, 1.28 Å, 1.51 Å, and 1.51 Å for chain A and Bof AYEdes_VJQ and AYEdes, respectively, and this improves to 1.13 Å, 0.65 Å, 1.05 Å and 1.05 Å, respectively, when 66 ofthe 70 residues are considered. (b) The two chains in AYEdes_VJQ (light and dark blue) differ notably from each other inthe conformation of the loop containing residues 25–27. The backbone of AYEdes_VJQ chain B in this region is effectivelysuperimposable with the AYEdesign computational model (green) as well as with the two chains of the AYEdes NMRstructure, but the backbone of AYEdes_VJQ chain A deviates at this point. Interestingly, this corresponds to one of twopoints at which an insertion or deletion distinguishes the sequence families of procarboxypeptidase A (the template in thisstudy) and procarboxypeptidase B; residues 25 and 26 are deleted from the procarboxypeptidase B sequence. TheAYEdes_VJQ chain A backbone in the present structure does not, however, adopt the conformation of procarboxy-peptidase B observed in PDB entry 1KWM (yellow), where the entire α-helix equivalent to residues 11–24 in the currentsequence is displaced to one side.


surface-exposed hydrophobic residues on the β-sheet surface, and the strand-swapping in the C-terminal tag residues (in AYEdes_VJQ) serves tostrengthen the dimeric interaction.The superimposed backbones of both the crystal

and NMR structures of AYEdesign and the parent

1AYE crystal structure (Figure 2(a)) demonstratethat RosettaDesign successfully generated a newamino acid sequence that is compatible with theAYEwt fold. This global design accuracy is likely adirect consequence of the highly accurate modelingof side-chain conformations; most side-chains in the

Figure 3. Atomic-level recovery of designed side-chain conformations in AYEdesign. The side-chains inthe protein core of the AYEdesign X-ray crystal structure(AYEdes_VJQ chain B, blue) and NMR solution structure(AYEdes chain B, red) are effectively superimposable onthe computational model (green). Selected side-chains areshown as sticks and the protein backbone of thecomputational model is shown as cartoon ribbons.


core of the AYEdesign NMR and crystal structuresare superimposable with those selected in theRosettaDesign computational model (Figure 3).Indeed 73% of all χ1 angles, 79% of χ2 angles(when χ1 is also correct), and 67% of χ3 angles(when χ1 and χ2 are also correct) were recoveredaccurately (AYEdes_VJQ_chainB compared to AYE-des_model; root-mean-square deviation (Supple-mentary Data Table S3). When only buriedresidues are considered, 77%, 100%, and 100% of

χ1, χ2 (when χ1 is also correct), and χ3 (when χ1and χ2 are also correct) angles, respectively, wererecovered accurately (Supplementary Data TableS3). A rotamer χ-angle is defined as recoveredaccurately if the angular difference from thecompared χ-angle is less than 40°. These statisticscompare favorably to mean rotamer recovery inside-chain repacking experiments of natural pro-teins using Rosetta (data not shown).The atomic-level similarity between the Rosetta-

Design computational model and the experimen-tally determined high-resolution structures ofAYEdesign suggests that specific computationallydesigned atomic-level interactions were directlyresponsible for the observed significant increase inthermodynamic stability. We successfully engi-neered over 10 kcal/mol of increased stabilityover the wild-type AYE protein, while changing48 out of 70 residues in the design process. How-ever, in the stabilization of biologically relevantproteins, the aim is often to gain the maximalamount of stability with the minimal number ofamino acid substitutions. Could we identify asmaller subset of the AYEdesign mutations thatwould still yield significant stabilization or were thelarge number of designed residues synergisticallycritical for the observed stabilization ? In addition tounderstanding the specific structural reasons behindthe AYEdesign stabilization, this reductionist ap-proach would provide a route to developing andparameterizing an automated computational meth-od for identifying small clusters of stabilizing aminoacid mutations.Using RosettaDesign and structural inspection of

the experimentally determined AYEdesign andAYEwt structures, we identified a set of residueslikely to contribute to increased stability. We focusedon designed residues that improve inter-residuepacking (increase in attractive interactions and/orremoval of repulsive interactions) and are likely toincrease the amount of hydrophobic surface areathat is buried upon folding; similar strategies have

Figure 4. 1H-15N HSQC spec-trum of AYEdes. The HSQC spec-trum of ∼1 mM 15N-AYEdes in50 mM potassium phosphate (pH7.0), 100 mM KCl, recorded at298 K and 750 MHz. Peaks arelabeled with the one-letter aminoacid code and sequence number,unlabeled peaks in the upper rightcorner of the spectrum correspondto side-chain NH2 from Gln andAsn residues.


been employed to stabilize proteins by computa-tional protein design.15,26 In order to generalize ourconclusions about protein stabilization, we catego-rized mutations in terms of their potential contribu-tion to inter-helical packing, inter-strand packing,and helix–strand packing. We used RosettaDesign toscore different combinations of these mutations inthe context of the wild-type protein crystal structure(1AYE). In the design calculations, sets of one tothree residues were allowed a binary choice betweentheir AYEwt and AYEdesign sequence identities. Allother amino acids were restricted to their wild-typesequence identities, but were allowed to repack.For experimental testing, we chose the five lowest-

energy two-point and three-point mutants accordingto the version of RosettaDesign used to select theoriginal AYEdesign sequence (Rosetta_SmallRadii).Two additional four-point and five-point mutantsthat are combinations of structurally-independentmutational clusters from the top-scoring mutantswere also selected for experimental characteriza-tion to assess additivity in stabilization. Designedmutants N16F_A52W and A52W_V53F are pre-dicted to improve inter-helical packing, E5V_H42Vand E5V_H42V_R44L are predicted to improveinter-strand packing, I14V_T40P is predicted toalleviate a helix–strand inter-atomic clash, F30W ispredicted to improve helix–strand packing, andE5V_H42V_R44L_F30W and E5V_H42V_R44L_A52W_V53F test combinations of the other mutants.The middle column in Figure 5 shows the Rosetta-Design models of the mutants (yellow) in the contextof their AYEwt structural amino acid neighbors(colored CPK). The corresponding views of theAYEwt and AYEdes_VJQ crystal structures areshown in the left and right columns, respectively.Site-directed mutagenesis of the AYEwt gene was

used to generate the designed mutants describedabove. Like AYEwt andAYEdes, themutant proteinswere over-expressed in Escherichia coli, and purifiedto ≥95% homogeneity using Ni-affinity chromatog-raphy. All mutants were expressed at high levels andwere soluble. The far-UV CD scans of all the mutantsare identical with AYEwt and AYEdes (Figure 6(a)),suggesting that the mutations did not affect proteinsecondary structure significantly. Protein stabilitywas assessed by following the guanidine hydrochlo-ride (GuHCl)-induced change of the CD signal. Thefree energies of unfolding were estimated from theexcellent fits of the chemical denaturation data(Figure 6(b)) to a two-state model.All seven designed mutants were found to be

more stable than AYEwt (Table 2). A52W_V53F andI14V_T40P were modestly stabilizing with freeenergy improvements over wild-type of 0.7 and0.8 kcal/mol, respectively. The two other two-pointmutants, N16F_A52W and E5V_H42V, showedincreased stabilization with free energy improve-ments over wild-type of 1.5 and 2.2 kcal/mol,respectively. The three-point mutant E5V_H42V_R44L and the five-point combination mutantE5V_H42V_R44L_A52W_V53F showed dramaticfree-energy improvements of 3.0 kcal/mol and 4.1

kcal/mol, respectively. The most dramatic stabili-zation was observed with the four-point mutantE5V_H42V_R44L_F30W, which resulted in a free-energy improvement of 5.2 kcal/mol. In contrast,the original AYEdesign achieved 10.3 kcal/mol ofstabilization, but 48 residues were changed in thedesign process.These results show that the force-field used to

successfully design the extremely stable AYEdesignsequence13 is successful also in selecting multiplesmaller subsets of mutants that still confer signifi-cant increases in stability into AYEwt. However, theRosetta force-field has been through significantchanges since the original redesign experiment,and we were interested in evaluating whetherattempts at improving conformational samplingand force-field smoothing have resulted in designprotocols that retain their successful predictivepower.To redesign the sequence of even a small protein,

the size of the sequence–structure space to besearched is enormous.1–4 A variety of approxima-tions have been employed to render this problemcomputationally tractable. The most common is tohold the co-ordinates of protein backbone atomsfixed, and to select residues that stabilize thisconformation; this is often referred to as the “inversefolding problem”.27 Furthermore, side-chain tor-sional degrees of freedom are typically restricted to adiscrete set of commonly observed values(rotamers).28 The limited conformational samplingafforded by these approximations is coarse relativeto the spatial variation of the Lennard-Jonespotentials used to evaluate the packing of potentialprotein structure. This sparse sampling of atomisticpotentials by design algorithms can lead to severeunder-packing of protein cores. It is commonpractice to address this difficulty by reducing theatomic radii used to evaluate packing,12 and in ouroriginal redesign experiment13 we scaled down theatomic radii in our model to 95% of CHARMM19values; we call this force-field Rosetta_SmallRadii(Table 1).In parallel with our large-scale natural protein

redesign experiment,13 we were also applyingRosettaDesign to create a novel protein fold, aprotein sequence and structure not previouslyobserved in nature. Because it was unlikely thatany arbitrarily chosen protein backbone would bedesignable, it was essential that the design proce-dure in this case included a search of backboneconformational space in addition to sequence space.Accordingly, we incorporated the backbone optimi-zation component of the high-resolution structurepredictionmodule of Rosetta intoRosetta_SmallRadii,such that iterations between sequence and back-bone optimization could proceed under the guid-ance of the same energy function. This protocolwas initially used to select five novel-topology orTop sequences for experimental characterization.While all five Top proteins were quite stable andappeared to have the correct α/β secondarystructure profiles, they appeared to have somewhat

Figure 5. Recapitulation of RosettaDesign stabilization with minimal mutations in AYE. RosettaDesign models of top-scoring AYE mutants (side-chains, yellow) in the context of their AYEwt structural amino acid neighbors (side-chains,CPK) with the AYEwt protein backbone represented in ribbons (olive) are shown in the central column. Thecorresponding views of the AYEwt (mutated side-chains, cyan) and AYEdes_VJQ chain B(mutated side-chains, green)crystal structures are shown in the left and right columns, respectively. The mutations are labeled above thecorresponding illustration in the central column.


molten cores. Speculating that this was the result ofover-packing the protein interior, we increased theatomic radii to values consistent with high-resolu-tion crystal structures. With this modification, wewere able to successfully design the Top7 protein;we found it to be folded and extremely stable(ΔG°=13.2 kcal/mol), and the X-ray crystal struc-ture of Top7 showed it to be virtually identical withthe design model (Cα RMSD=1.17Å) at atomic-resolution.19 We recently showed that de novostructure prediction of small protein domains wasalso improved by the use of this version of the

Rosetta force-field,29 producing models of hereto-fore unprecedented accuracy (RMSD <1.5 Å). Con-sequently, the force-field used for these successes,termed Rosetta_HardRep (Table 1), became thedefault for both protein design and high-resolutionstructure prediction in Rosetta. It is important tonote that both of the applications for which thisforce-field proved superior incorporate some typeof backbone conformational freedom.To compare the relative predictive ability of the

old and new Rosetta force-fields in the context of afixed protein backbone design simulation, we

Figure 6. Biophysical character-ization of AYE stabilization recapi-tulationmutants. (a) The far-UVCDspectra of 25 μM AYEwt, sevendesignedAYEmutants, andAYEdesin 25mMTris (pH8.0), 50mMNaCl,at 25 °C. (b) The CD signal at 220 nmas a function of GuHCl concentra-tion for all the above proteins at aconcentration 5 μM in 25 mMHCl(pH 8.0), 50 mM NaCl at 25 °C.


repeated the AYE mutant design simulationsusing Rosetta_SmallRadii and Rosetta_HardRep.The predicted free energies of these mutantsrelative to the wild-type protein are summarizedin Table 2. The Rosetta_SmallRadii force-field wasable to successfully predict the stabilizing effect ofa majority of the designed mutants. In starkcontrast, the Rosetta_HardRep force-field incorrectlypredicted all but two of the mutants to be de-stabilizing. This supports the idea that tight packing,when described with coarse conformational sam-pling but evaluated with a standard molecularmechanics potential, can yield spurious atom–atomclashes.We have attempted to reconcile the sampling

Table 1. Summary of RosettaDesign force-field variants

Force-field variantRelativeradii size

Repulsivetreatment

Backboneflexibility

HardRep – r12 NoSmallRadii < HardRep r12 NoDampRep > HardRep Damped r12 NoFlexBB = HardRep r12 Yes

See Materials and Methods for details.

and the evaluation by altering each separately. In theformer case, we have developed a damped variant ofthe Lennard-Jones potential, and in the latter wehave expanded the conformational sampling byintroducing limited backbone flexibility.It has been shown that rotamer libraries must be

supplemented with a large number of extra dihe-dral–space conformers to sample adequately astandard Lennard-Jones potential when the back-bone is held fixed.30 We have taken an alternativeapproach by selecting a computationally tractablerotamer library (and thus a fixed sampling densityin side-chain dihedral space), and adapting ourpacking potential to that level of sampling. Thisadaptation is necessary to avoid the spurious clashesthat result from a mismatch in resolution betweensampling and evaluation. Previously, the primaryadaptation considered to reduce clashes is areduction in atomic radii.12,13 This has the dangerof also shifting the maxima in atom–atom radialdistribution functions (RDFs), resulting in system-atic deviations from native structures. We haveobserved such shifts in large-scale repacking tests(data not shown). To overcome these problems, wedeveloped a new force-field, Rosetta_DampRep

Table 2. Observed and computed ΔΔG values (kcal/mol) for AYE mutants


(Table 1), in which the Lennard-Jones potential wasmodified such that the atom–atom RDFs of struc-tures repacked under the potential match thoseresulting from replacing each side-chain in thenative structure with the rotamer in a given librarythat has the lowest heavy-atom coordinate RMSDfrom the native side-chain. Thus, we attempted tomatch not the native structure, but the bestapproximation to the native at a fixed resolution.Atomic radii were varied empirically to ensure thatmaxima in the RDFs of repacked and approximatedstructures were in agreement (Supplementary DataFigure S3). Atomic radii were either held fixed(typically for polar atoms) or scaled by a factor of1.07 (typically for non-polar atoms). It is interestingthat, in contrast to common practice, we found thatsome radii should be increased and none decreasedto adapt best to the fixed backbone approximation.Although the scaling term was determined empir-ically, we speculate that expanded radii may correctfor either “overcompression” due to the small butfinite attractive component of the Lennard-Jonespotential at longer ranges or the omission of thermaleffects in the repacking calculations. Finally, weempirically selected a “switch point” on the repul-sive side of the Lennard-Jones curve at which thepotential changes to a linear functional form, with aslope taken from the tangent at the switch point. Asingle value (given as a fraction of the distance to thepotential minimum) was determined for all atomtypes, and was selected to match the RDFs betweenrepacked and approximated native structures atdistances less than the maximum. Although theRosetta_DampRep potential was constructed tomatch RDFs, we have observed that it also yieldsimproved performance in side-chain repackingapplications (Supplementary Data Table S4). Werepeated the AYE mutants design simulations usingRosetta_DampRep, and observed that, similar toRosetta_SmallRadii, this new force-field successfullypredicted the stabilizing effect of a majority of themutants (Table 2). We were thus able to observegood design predictions in a fixed-backbone contextusing two different methods for damping thecomputational evaluation of atomic-overlap in

Rosetta; either scaling down atomic radii or explic-itly damping the repulsive component of theLennard-Jones potential.As an alternate approach to using potentials with

damped repulsive terms, we tested whether theRosetta_HardRep potential could be used to success-fully predict the stability of the AYE mutants if theprotein backbone and side-chains were allowed torelax following mutation. The flexible backboneprotocol, Rosetta_FlexBB (Table 1), begins withgradient-based minimization of the backbone andside-chain torsion angles in the wild-type structure.Mutations are modeled onto the relaxed wild-typestructure and repacked along with neighboringresidues to identify low-energy rotamers. Followingrepacking, the backbone and side-chain torsionangles are minimized once more. The energies ofthe relaxed wild-type and mutated structures arecompared to calculate the change in protein stability.In general, the protein structure does not varydramatically with this protocol, backbone devia-tions are typically less than 0.4 Å RMSD. Indepen-dent simulations do not produce identical structuresand energies; therefore, 100 simulations wereperformed for each mutation and the lowest energyresult was used for comparison. We observed that,similar to the fixed-backbone Rosetta_SmallRadii andRosetta_DampRep force-fields, Rosetta_FlexBB wasable to successfully predict the stabilizing effect ofa majority of the AYE mutations (Table 2).Despite the overall success of these predictions, the

design search space was restricted in this test, sincethe programwas given only a binary choice betweenthe original AYEwt and AYEdesign sequences. For atrue evaluation of design prediction, all amino acidsshould be allowed at the design positions. Accord-ingly, the protocol with the best ΔΔG° prediction forAYEdes, Rosetta_DampRep, was used to redesign themutated residues in the seven mutants describedabove, allowing all 20 amino acids to be chosen atthose positions. Table 3 shows that RosettaDesignpredominantly designs either the same or similaramino acids as those picked in the binary choiceexperiment; E5V, I14T, F30W, T40P,H42V, andA52Ware identical, and N16W and V53Y are similar types

Table 3. Rosetta_DampRep design predictions for AYE stabiliza-tion recapitulation clusters


of mutations (N16F and V52F in AYEdesign). OnlyR44K does not match the AYEdesign trend.It is instructive to compare the results of our work

with other studies of this protein, since others haveused AYEwt as a subject for rational stabilizationattempts. Villegas et al.31 mutated surface-exposedresidues on the two helices to improve predictedhelical propensity, and reported that two four-pointmutants (one set per helix) stabilized the protein by1.1 kcal/mol and 1.5 kcal/mol. A combined eight-point mutant stabilized the protein by 2.8 kcal/mol.Table 2 shows that RosettaDesign was also able tosuccessfully predict the stabilizing effects of two outof three of these mutants.

Conclusion

By solving the crystal and NMR structures ofAYEdesign, we have demonstrated the high-resolu-tion accuracy of our computational protein designmethodology, RosettaDesign. A comparison of theexperimentally determined structures and our com-putational model showed that the extreme thermo-dynamic stabilization of AYEdes was a directconsequence of atomically accurate modeling ofboth backbone and side-chain conformations. Weused the information gleaned from these structuralstudies to identify small clusters of residues that canindependently provide significant thermodynamicstabilization, and showed that RosettaDesign cansuccessfully predict the stabilizing effect of thesemutations. Finally, we compared different force-fields and approaches to computing the free-energychange associated with these stabilizing mutations,and found that good recapitulation with fixed back-bone models and coarse sampling around side-chainrotamers requires either reduced radii or dampedrepulsion terms, while the current, more accurateRosetta force-field yields good predictions whenused with explicit modeling of backbone flexibility.

Materials and Methods

Protein expression and purification

The computationally designed amino acid sequence ofAYEdesign has been reported.13 Two different expressionconstructs that contain the AYEdesign sequence wereprepared.The first construct (used for crystallography) was a

fusion construct in a pET3a-based vector consisting of anN-terminal His6 tag, the 70 residues of the AYEdesignsequence, a 15-residue linker containing a TEV protease

cleavage site, and the C-terminal 62 residues of structuralgenomics target sequence Lmaj000047 (geneDB identifierLmjF25.2320). This construct was prepared to leveragethe excellent stability and solubility of AYEdesign topotentially improve the solubility of unrelated proteinsthat are tagged to it. Cleavage of the expressed fusionprotein by TEV protease should yield one chain(AYEdes_VJQ) with the N-terminal His6 tag, the AYEde-sign sequence, and nine C-terminal linker residues fromthe TEV cleavage site, and another chain with six N-terminal linker residues from the TEV cleavage site and thestructural genomics target protein. The fusion protein wasexpressed in E. coli BL21 (DE3) in the presence of seleno-methionine as described,32 and purified using a Ni-NTAcolumn (Qiagen). The column was washed with His-tagged TEV protease with the intent of releasing only thetarget Lmaj000047 fragment. However, for unknownreasons, both cleavage fragments were released from thecolumn and inadvertently carried forward into crystalliza-tion trials. In any case, the AYEdes_VJQ fragment crystal-lizedpreferentially and its structurewasdetermined de novousing multiple-wavelength anomalous diffraction (MAD).The second construct (used for NMR spectroscopy and

thermodynamic measurements) was in a pet29b-basedvector consisting of an N-terminal His6 tag followed bythe 70 residues of the AYEdesign sequence. This construct(AYEdes), was expressed in E. coli BL21 (DE3) in LB or M9minimal medium supplemented with appropriately iso-tope-labeled NH4Cl and glucose, as needed, and purifiedby Ni-affinity chromatography followed by gel-filtrationchromatography. Purified samples contained no impuritythat was detectable by SDS-PAGE.The wild-type AYE construct (AYEwt) in a pet29b-based

vector was used essentially as described,21 except the C-terminal His6 tag was moved to the N terminus by PCRsubcloning, to match the AYEdes construct. All mutantswere generated in the context of this construct using theQuick Change Site-Directed mutagenesis kit (Stratagene).

Crystallographic structure determination

Crystals of AYEdes_VJQ grew from sitting dropscontaining 1 μl of protein solution (6.9 mg/ml protein in20 mM Hepes (pH 7.5), 0.5 M NaCl, 2 mM β-mercap-toethanol, 5% (v/v) glycerol), 1 μl of crystallization buffer(20% (w/v) PEG 1000, 40 mM CaCl2, 100 mM sodiumacetate), and 1 μl of crystallization buffer containingmicrocrystalline seeds from earlier crystallization trials.Diffraction data at three wavelengths were collected

from a single crystal on beamline 8.2.1 at the AdvancedLight Source (ALS). Data were integrated and scaled usingthe HKL2000 package.33 Essentially the entire backbone ofthe two monomers in the crystal asymmetric unit wasauto-traced by the program RESOLVE,34 on the basis ofinitial phases derived from four Se sites identifiedautomatically by SHELXD.35 Automated assignment andfitting of protein side-chains failed utterly, since at thatpoint the sequence was still mistakenly expected to matchthat of Lmaj000047. Manual inspection of the experimen-tally phased electron density maps easily assignedidentities for residues making up the eight-residuesequence MVEWFLEM spanning the two SeMet sites ineach chain. This characteristic sequence fragment revealedthe true identity of the structure to be the AYEdes designsequence plus the nine linker residues proximal to the TEVcleavage site (AYEdes_VJQ). The remaining side-chainswere placed using the real-space fit and refine mode ofXfit.36 Only the first three residues from the linkersequence in each chain were well-ordered; hence, the


final crystallographic model contains 73 residues perchain. The structure was refined at 2.1 Å resolution usingthe program REFMAC5,37 yielding standard residualsRwork and Rfree of 0.20 and 0.27, respectively (Supplemen-tary Data Table S1). The stereochemistry and fit to densityof the final model were validated using MolProbity38 andCoot.39 Of 142 (ϕ,ψ) dihedral angle pairs, 139 are infavored regions of backbone conformational space, whilethe remaining three residues are in allowed regions.

NMR structure determination

Freshly purified samples of AYEdes were concentratedto ∼1 mM by centrifugation and were prepared for NMRstudies in 8% (v/v) 2H2O or ∼100% 2H 2O containing50 mM potassium phosphate (pH 7.0) and 100 mM KCl.NMR experiments were recorded at 298 K on a BrukerDRX 500 and DMX 750 MHz as well as on a Bruker500 MHz equipped with cryo-probe (at NMRFAM) andVarian 600 MHz spectrometers (at PNNL). Combinationsof standard triple-resonance experiments (HNCO, HNCA,HN(CO)CACB, HNCACB, and HCCH-TOCSY)40 wereused to obtain nearly complete assignments for 72residues. Heteronuclear 13C and 15N-edited 3D andhomonuclear 2D NOESY experiments collected withmixing times of 100 ms were used to obtain structuralrestraints. Intra-molecular restraints were obtained from13C-filtered chirp-NOESY data collected at PNNL with amixing time of 100ms on the 600MHzVarian spectrometerequipped with a cryo-probe. Spectra were processed usingNMRPipe,41 and analyzed with Sparky†. 1H,15N-Hetero-nuclear NOE, T1 and T2 relaxation experiments were allcollected on the Bruker DRX 500 MHz spectrometer andanalyzed using ModelFree.42 NOE assignments andstructure calculations for the AYEdes monomeric subunitwere performed initially using combined automated andmanual methods in CYANA.24 Assigned inter-molecularNOE restraints were duplicated for chains A and B of theAYEdes symmetric homodimer and intra-molecular NOErestraints were derived from 13C-filtered chirp-NOESYdata. Torsion angle restraintswere included forϕ/ψ anglesaccording to TALOS predictions,43 and hydrogen bondingconstraintswere derived fromamide 2H2Oprotectiondata.Structure calculations for AYEdes were completed withCYANA v2.1 and visualized using MOLMOL.44 Analysiswith PROCHECK found 100% of the residues for AYEdesin allowed regions of the Ramachandran plot.45 Structuralstatistics from 20/100 lowest energy structures (chains Aand B) are provided (Supplementary Data Table S2).

Size-exclusion (gel-filtration) chromatography

Size-exclusion chromatography was carried out usingan analytical Superdex-75 column (Amersham Pharmacia)with the Pharmacia FPLC system (GP-250 gradientprogrammer, P-500 Pump). Protein samples at concentra-tions used for NMR (600 μM–1.2 mM) or CD (5–100 μM)were equilibrated in 25 mM Tris– HCl (pH 8.0), 20 mMEDTA, 50 mMNaCl at 25 °C, and run on the Superdex-750column at a flow-rate of 1 ml/min.

Analytical ultra-centrifugation

Sedimentation equilibrium studies on AYEdes wereconducted in a Beckman XL-A analytical ultracentrifuge

† http://www.cgl.ucsf.edu/home/sparky/

using six-channel 12 mm Epon charcoal-filled center-pieces. All scans were conducted at 20 °C using anabsorbance wavelength of 280 nm at rotor speeds of25,000 rpm, 35,000 rpm, and 45,000 rpm. AYEdesconcentrations were determined from a scan at 3000 rpmto be 13 μM, 33 μM, and 50 μM. Data were collected in25 mM Tris–HCl (pH 8.0), 50 mM NaCl with and without20 mM EDTA. The effect of EDTA on the associative stateof AYEdes was negligible. Equilibration for 8 h wasdeemed sufficient by identical absorbance scans collectedafter 6 h and 8 h at each speed.The UltraScan software package was used for data

analysis as well as deriving solvent density and partialspecific volume parameters‡. The weight-averaged mo-lecular mass, MW, was determined for individual equilib-rium scans by fitting to a single ideal species model usingnon-linear least-squares analysis. Residuals to the fit wererandom, and the fitted values for the baseline offset agreedwell with values determined using the meniscus-depletionmethod. Next, global fits were performed for each proteinconcentration across the three speeds to determine MW ateach concentration. Amonomer–dimer equilibriummodelwas used to determine the dissociation constant. Confi-dence limits were determined by Monte Carlo analysiswith UltraScan.

Circular dichroism (CD)

CD data were collected on an Aviv 62A DS spectrom-eter. Far-UV CD wavelength scans (260–195 nm) at 25 °Cwere collected in a 1 mm path-length cuvette. Guanidi-nium hydrochloride (GuHCl)-induced protein denatur-ation was followed by the change in ellipticity at 220 nm ina 1 cm path-length cuvette, using a Microlab titrator(Hamilton) for denaturant mixing. Temperature wasmaintained at 25 °C with a Peltier device. All CD datawere converted to mean residue ellipticity. To obtain avalue for ΔGU

H2O, the denaturation curves were fit by non-linear least-squares analysis using a linear extrapolationmodel.46

Computational procedure

Our method for computational protein design, Rosetta-Design, has been described in detail.13,19 In brief,RosettaDesign contains two main components; an energyfunction that ranks the relative fitness of amino sequencesfor a given protein structure and a Monte Carlooptimization procedure for rapidly searching sequencespace. The energy function is a linear combination of a 6-12 Lennard-Jones potential, the Lazaridis–Karplus implicitsolvation model,47 an empirical hydrogen bondingpotential,48 backbone-dependent rotamer probabilities,49amino acid probabilities for particular regions of ϕ/ψspace, and a simple electrostatics pseudo-energy derivedfrom the distance distributions of polar residues in thePDB.50 In addition, each amino acid has a unique referenceenergy that provides an implicit treatment of the unfoldedstate and enforces a native-like sequence composition.Weights for the various energy terms were determined asdescribed.51 Briefly, all rotamers from a backbone-depen-dent library are placed at each position in a set of proteins.Each energy component is calculated for each rotamerwith the remainder of the protein held fixed. The energyterms form the coefficients of a matrix; an optimal vector

‡ www.ultrscan.uthscsa.edu

http://www.ultrscan.uthscsa.edu

http://www.cgl.ucsf.edu/home/sparky/


of weights is obtained such that the energy gap betweennative and non-native rotamers is maximized. Theseweights are then used to redesign fully the training setof proteins. The weights are again optimized, now usingthe redesigned proteins, rather than the native proteins, asthe context in which the energy matrix is determined. Theprocedure is iterated through ∼5 cycles of weightoptimization and full redesign before the weights con-verge. This process compensates for the fact that theweight determination step makes a linearizing approxi-mation to the full design problem when it calculatesrotamer energies in an otherwise unchanged background.Four variants of the general RosettaDesign force-field

were employed in this study (Table 1). In the version ofRosettaDesign used to select the original AYEdesignsequence (Rosetta_SmallRadii),13 the atomic radii werescaled by 0.95 relative to standard CHARMM 19 radii.The damped repulsive variant of RosettaDesign (Rosetta_DampRep) differs from standard RosettaDesign in itstreatment of the Lennard-Jones potential in the repulsiveregion (where atom–atom energies are greater than zero).At distances less than a specified fraction of the energyminimum, the potential takes on a linear form, with itsslope selected to match that of the Lennard-Jones potentialat that distance. Additionally, atomic radii are scaled by aconstant factor; a factor of 1.07 was found empirically toimprove agreement between the atom–atom distancedistribution maxima observed in native crystal structuresand the same structures when side-chain positions wererepacked using RosettaDesign. Both Rosetta_SmallRadiiand Rosetta_DampRep keep the co-ordinates of the proteinbackbone fixed during the design simulation. In a thirdvariant of RosettaDesign, the protein backbone wasallowed to relax following a mutation. This protocol(Rosetta_FlexBB) begins with relaxing the wild-typestructure with gradient-based minimization of side-chainand backbone torsion angles using an energy function thathas full-size radii and a standard representation of theLennard-Jones potential. This relaxed structure is used tocalculate the energy of the wild-type sequence and is usedas the template for making mutations. The energy of themutant structure is determined by repacking the residuessurrounding the site of mutation followed by gradient-based minimization of backbone and side-chain torsionangles. As a control for the above RosettaDesign variants,a fourth protocol (Rosetta_HardRep) uses the Rosetta_FlexBB force-field with standard atomic radii and Len-nard-Jones potential, while keeping the protein backbonefixed during design simulations.

PDB accession codes

X-ray coordinates and structure factors have beendeposited with the PDB as accession code 1vjq. NMRCoordinates and experimental constraint files have beendeposited with the PDB as accession code 2gjf.

Acknowledgements

We thank the facilities at NMRFAM (Madison, WI,supported by NIH) and PNNL (Richland, WA,supported by DOE) for access to NMR instrumen-tation. This work was supported, in part, by NIHgrants to G.V., B.K. and D.B.

Supplementary Data

Supplementary data associated with this articlecan be found, in the online version, at doi:10.1 016/j.jmb.20 06.11.080

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Edited by M. Guss

(Received 29 July 2006; received in revised form 23 November 2006; accepted 28 November 2006)
Available online 2 December 2006

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