Computational design of closely related proteinsthat adopt two well-defined but structurally
divergent folds
Kathy Y. Weia,b,c, Danai Moschidid, Matthew J. Bicka,b, Santrupti Nerlid,e, Andrew C. McShand,
Lauren P. Carterb, Po-Ssu Huangf, Daniel A. Fletcherc,g,h,i, Nikolaos G. Sgourakisd, Scott E. Boykena,b,1,2,and David Bakera,b,j,1
aDepartment of Biochemistry, University of Washington, Seattle, WA 98195; bInstitute for Protein Design, University of Washington, Seattle, WA 98195;
Department of Bioengineering, University of California, Berkeley, CA 94720; dDepartment of Chemistry and Biochemistry, University of California, Santa
Cruz, CA 95064; eDepartment of Computer Science, University of California, Santa Cruz, CA 95064; fDepartment of Bioengineering, Stanford University,
Stanford, CA 94305; gJoint UC Berkeley–UC San Francisco Graduate Group in Bioengineering, Berkeley, CA 94720; hDivision of Biological Systems andEngineering, Lawrence Berkeley National Laboratory, Berkeley, CA 94720; iChan Zuckerberg Biohub, San Francisco, CA 94158; and jHoward Hughes Medical
Institute, University of Washington, Seattle, WA 98195
c

The plasticity of naturally occurring protein structures, which canchange shape considerably in response to changes in environmental conditions, is critical to biological function. While computational methods have been used for de novo design of proteinsthat fold to a single state with a deep free-energy minimum[P.-S. Huang, S. E. Boyken, D. Baker, Nature 537, 320–327 (2016)],
and to reengineer natural proteins to alter their dynamics[J. A. Davey, A. M. Damry, N. K. Goto, R. A. Chica, Nat. Chem. Biol. 13,
1280–1285 (2017)] or fold [P. A. Alexander, Y. He, Y. Chen, J. Orban,
P. N. Bryan, Proc. Natl. Acad. Sci. U.S.A. 106, 21149–21154 (2009)],
the de novo design of closely related sequences which adopt welldefined but structurally divergent structures remains an outstanding challenge. We designed closely related sequences (over 94%
identity) that can adopt two very different homotrimeric helicalbundle conformations—one short (∼66 Å height) and the otherlong (∼100 Å height)—reminiscent of the conformational transitionof viral fusion proteins. Crystallographic and NMR spectroscopic
characterization shows that both the short- and long-state sequences
fold as designed. We sought to design bistable sequences for which
both states are accessible, and obtained a single designed protein
sequence that populates either the short state or the long state
depending on the measurement conditions. The design of sequences
which are poised to adopt two very different conformations sets thestage for creating large-scale conformational switches between structurally divergent forms.

|

protein engineering computational protein designchange calcium induced protein switch||

Downloaded by guest on March 18, 2020

T

SignificanceComputational protein design has focused primarily on thedesign of sequences which fold to single stable states, but inbiology many proteins adopt multiple states. We used de novo
protein design to generate very closely related proteins that
adopt two very different states—a short state and a long state,
like a viral fusion protein—and then created a single moleculethat can be found in both forms. Our proteins, poised between
forms, are a starting point for the design of triggered shapechanges.

| conformation

here are many examples of de novo designed amino acidsequences that fold to a single designed target structure (1,2), but designing new amino acid sequences capable of adopting
divergent structural conformations is challenging since the freeenergy difference between the two states must be small enoughthat a few amino acid changes can shift the global energy minimum from one state to the other, and both states must be stable
relative to the unfolded state. Redesign of natural protein backbones has yielded large conformational changes for systems,
such as the Zn antenna finger, Zinc-binding/Coiled coil (ZiCo),and designed peptide Sw2, that involve changes in oligomerization
state from a homotrimeric three-helix bundle to a monomericzinc-finger fold (3–5). The pH-induced oligomerization switch(pHios) de novo design also involves a change in oligomerization
state [pentamer to hexamer (6)]. In addition to changes in oligomerization state, sequence changes can introduce changes in helix
orientation; in variants of the Rop-homodimer, both parallel andantiparallel helical arrangements are populated (7–9). In cases
where there are not changes in oligomerization state or helix

www.pnas.org/cgi/doi/10.1073/pnas.1914808117

orientation, the two well-defined states are generally quite
similar, for example, the dynamic switching of DANCER proteins primarily involves a single tryptophan residue (10), andthe Rocker channel has two symmetrically related states thatare structurally identical (11). Finally, designed protein pH(12) and peptide- (13) dependent switches involve transitions
between a single well-defined state and less well-ordered states.
Overall, in most previous work, the differences in conformation
have either involved changes in oligomerization state or helix
orientation, been relatively small, or only one of the two states
is well defined. An exception is the engineering of sequenceswith 98% identity that switch folds between the naturally occurring GA and GB domains (14).

Author contributions: K.Y.W., P.-S.H., N.G.S., S.E.B., and D.B. designed research; K.Y.W.,
D.M., M.J.B., S.N., A.C.M., and L.P.C. performed research; K.Y.W., D.M., M.J.B., S.N.,
A.C.M., N.G.S., S.E.B., and D.B. analyzed data; and K.Y.W., D.M., P.-S.H., D.A.F., N.G.S.,
S.E.B., and D.B. wrote the paper.
The authors declare no competing interest.
This article is a PNAS Direct Submission.
This open access article is distributed under Creative Commons Attribution License 4.0(CC BY).
Data deposition: The data for X-ray structures have been deposited in the Research
Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) (https://www.
rcsb.org/) under the following PDB IDs: 6NX2 (AAA), 6NYI (XXA), 6NYE (XAX), 6NYK(XAX_GGDQ), 6NZ1 (XXA_GVDQ), 6NZ3 (XAA_GGHN), 6NXM (XAA_GVDQ), and 6NY8
(XAA_GVDQ with calcium). The data for NMR structures and their restraints have been
deposited in the RCSB PDB under PDB IDs 6O0I (XAA de novo) and 6O0C (XAA_GVDQ
mutant M4L de novo without calcium). NMR chemical shift assignments have been deposited in the Biological Magnetic Resonance Data Bank (BMRB) (http://www.bmrb.wisc.
edu/) under BMRB IDs 30574 (XAA de novo) and 30573 (XAA_GVDQ mutant M4L de novo
without calcium).
1

To whom correspondence may be addressed. Email: sboyken@lyell.com or dabaker@uw.
edu.

2

Present address: Lyell Immunopharma, Inc., Seattle, WA 98109.

This article contains supporting information online at https://www.pnas.org/lookup/suppl/
doi:10.1073/pnas.1914808117/-/DCSupplemental.

PNAS Latest Articles | 1 of 8

BIOPHYSICS ANDCOMPUTATIONAL BIOLOGY

Edited by José N. Onuchic, Rice University, Houston, TX, and approved February 19, 2020 (received for review September 5, 2019)We sought to design sets of closely related de novo protein
sequences with two structurally divergent ground states having
the same oligomerization state. Inspired by class I viral fusion
proteins, such as influenza hemagglutinin (15–17), we chosehomotrimeric helical bundles as the fundamental architecture.
We decided on a design scheme with two divergent conformations containing a constant six-helix bundle “base” and a variable
portion with three inner helices and three “flipping” helices. In thecompact “short” state (∼66 Å height), the flipping helices fold back tointeract with the inner helices; in the extended “long” state(∼100 Å height), they extend to form interactions with eachother (Fig. 1A). Due to the difficulty of accurately computing
the relative stabilities of very different conformations, we first
designed related sequences which adopt one or the other of thetwo states. Then, guided by experiments, we identified structural features that affect the conformational preference between states and attempted to design single sequences which
adopt both states.
Results
We started from a variant of a previously Rosetta-designed sixhelix bundle [2L6HC3_13; Protein Data Bank (PDB) ID 5j0h](18) and introduced a cut in the outer helix to produce a disconnected segment to serve as the flipping helix. This flipping
helix was connected to the C terminus via either a turn to generate the short state or a contiguous helix to generate the longstate (Fig. 1D). To determine the appropriate hinge length,A

connectors of two to seven residues were designed using either
RosettaRemodel (19) or the insertion of short structured loops
as described previously (18). Rosetta design was used to sample side-chain rotamer conformations in the context of thedesigned backbone, and symmetric “fold-and-dock” calculations
were used to predict the three-dimensional (3D) structure basedon the designed amino acid sequence (see Materials andMethods, Computational Design). Designs were evaluated basedon how well the predicted structure matched the design model(SI Appendix, Fig. S1); for example, in the long state, we foundthat a helical hinge connector of five residues resulted in thelowest-energy solution with the best packing between helices (SIAppendix, Fig. S1B).
We selected sequences that were strongly predicted to foldinto one of the two states (SI Appendix, Fig. S1D), genes
encoding such designs were obtained, and the proteins were
purified and characterized. All initial designs were solubly
expressed and had circular dichroism (CD) spectra indicative of
well-folded, alpha-helical structures; three of four were trimericby size exclusion chromatography with multiangle light scattering (SEC-MALS) (SI Appendix, Fig. S2). However, by smallangle X-ray scattering (SAXS), it was difficult to determine
which state (short, long, or a combination) the proteins adopted (SI Appendix, Fig. S2).
To facilitate discrimination between the two states by SAXS,
we carried out a second round of design with 1) longer flipping helices (which resulted in a greater difference in lengthBm
C term
hinge

C

X
A
X: hydrophobic layer
XXX
XAX
XXA
XAA
AXX
AAX
AAA
AXA

interface Xt m
N termlong

base“short” state“long” state

Downloaded by guest on March 18, 2020

D

other
A: hydrogen bond layer

short

E

Fig. 1. Design and in silico characterization of proteins with two distinct, well-defined ground states. (A) Design concept for protein backbones with a“short” and a “long” state. The backbone consists of a stable base, mobile flipping helices (red), tunable interface, and a flexible hinge (yellow). (B) Tunableinterface between the inner helices and flipping helices. Each of three positions can be a hydrogen bond (green, “A”) or hydrophobic (black, “X”) layer. (C)Fraction of top 10 scored Rosetta folding predictions that resemble the short, long, or other structure for each permutation of possible interface configurations. (D) Initial design scheme. Starting with the previously characterized protein 2L3HC3_13 (PDB ID 5J0H) (cyan), a monomer is extracted, cut to produce aflipping helix, and reconnected with a hinge to produce the backbone of the short or long state. (E) Final design scheme. Previously characterized proteins
2L3HC3_13 (cyan) and 2L3HC3_23 (blue) are fused via their inner helices, outer helices are trimmed, and the hinge length is chosen such that the flipping
helices pack against each other in the long state.

2 of 8 | www.pnas.org/cgi/doi/10.1073/pnas.1914808117

Wei et al.

between the states and hence more differently predicted solutionscattering profiles) and 2) helical interfaces redesigned to favor
the short state (with the sequence optimized for the turn andpacking of the flipping helices on the inner helices) or the longstate (with the sequence optimized for packing between the
flipping helices across the symmetric interface). The previous
design round had enforced the same sequence at the interface
regions for all designs (SI Appendix, Fig. S3). The length of the

XXA

Aflipping helix was increased from 15 to 21 residues, and the hinge
length changed to three residues. The proteins in this second
round of designs expressed solubly, and three of the four werehelical by CD spectroscopy and ran as trimers by SEC-MALS (SIAppendix, Fig. S4). However, by SAXS all three appeared to bein the long state (SI Appendix, Fig. S4), suggesting that the
short state in this design scheme has higher free energy than thelong state.

XAX

B

AAA

F

XAX

C
L86
δ2

L79
δ2

I66
δ1

L79

15

L86

L86
18

13

13

XAA

D

bromine 2
XAA

E

20

L69

0.9

8
0.9
2
0.8
4
0.7
8
0.8
8
0.8
2

L79

H (ppm)

L69
M82

M82
25

I65

A64

NMR ensemble

2.0
0
1.9
5
1.5
6
1.5
1
0.9
3
0.8
8
0.8
2
0.7
7

L86

1

Downloaded by guest on March 18, 2020

network A

I65

20
22

bromine 1

M82 A64 L69 I65
ε
β
γ2 δ1

I66

I66

16

network A
XAA

L79

14

C (ppm)hinge
XAXside view

A64

network A

C (ppm)hingeside view

M82side view1

H (ppm)

RMSD
1.00 Å

Fig. 2. Modifying the number and position of hydrogen bond networks in the interface region changes the conformational state. (A) Crystal structure (gray)compared to model (cyan) of XXA (PDB ID 6NYI) shows the protein in the short state (rmsd = 1.37 Å). (B) Crystal structure (gray) compared to the Rosetta model(cyan) of XAX (PDB ID 6NYE) shows the protein in the short state (rmsd = 1.40 Å). (C) 3D CM-CMHM NOESY strip for XAX is consistent with the short conformationof the protein. (D) 3D CM-CMHM NOESY strip for XAA is consistent with the short conformation of the protein. (E) De novo NMR structure (PDB ID 6O0I) calculatedusing chemical shifts, long-range NOEs, and RDC data (beige) compared to the Rosetta model (cyan) shows the closed conformation (rmsd = 1.00 Å). (F) Crystal
structure (gray) compared to the model (cyan) of AAA (PDB ID 6NX2) shows the protein in the long state with ion (red spheres) coordination sites (rmsd = 1.40 Å).

Wei et al.

PNAS Latest Articles | 3 of 8

BIOPHYSICS ANDCOMPUTATIONAL BIOLOGY

hingeOur third round of designs aimed to generate short and longstates with more equal stability. We used a larger portion of
2L6HC3_13 as the base to provide more stability, and fused it witha second Rosetta-designed six-helix bundle (2L6HC3_23) (18) byaligning the matching superhelical parameters of the inner threehelices (Fig. 1E). Compared with the second-generation designs,
in the short state the flipping helix was positioned closer to theinner helices and the termini of the hinge region were closer together, allowing closer packing in the short state (SI Appendix, Fig.
S5). Four designs with different fusion sites, placement of hydrogen bond networks, and loop flexibilities were tested; all expressedsolubly and were helical by CD, but the two larger designs were
not trimeric by SEC-MALS (SI Appendix, Fig. S6). One design was
confirmed to be in the long state by crystallography, again indicating that the short state had higher energy than the long state(Fig. 2F).
Tuning the Short-/Long-State Difference with Hydrogen Bond Networks.

To tune the relative stability of the short and long states, we introduced modular hydrogen bond networks buried in the shortstate, but partially exposed in the long state. The interface strength
between the inner and flipping helices is expected to depend on
both the number and position of the hydrogen bond networks[replacing hydrophobic packing with more polar networks resultsin weaker interfaces (18), and solvent exposed locations are more
likely to be disrupted by competing water interactions]. This
strategy had the added advantage of creating more soluble proteinsbecause residues necessarily exposed in the long state—when the
flipping helix extends, parts of the inner helices it previouslyApacked against are solvent exposed—are not entirely hydrophobic(as they would be if the stabilizing interactions were entirely
nonpolar, as in most design calculations). The interaction energy
between the flipping helix and the inner helices in the short state
was tuned by combining hydrogen bond layers (“A”) or hydrophobic layers (“X”) in different orders in each of three possible
positions (18) (Fig. 1B). Designs were given three-letter names
corresponding to the layers in order, starting at the hinge proximal
position. Structure prediction calculations (Rosetta symmetricfold-and-dock) suggested that some layer combinations (such as
XAX) would be more favorable for the short state than others(such as AAA) and that the short and long backbones states would
be among the lowest-energy states of these systems (Fig. 1C).
We constructed all eight possible permutations of two different layers in three positions, dubbed SERPNTs (in silico
engineered rearrangeable protein topologies). We set the threehinge residues to glycine to reduce favorable contributions to thelong-state free energy from the helical form of the hinge. Alleight constructs expressed well, and by SEC most samples weremonodisperse or had a small aggregation peak, with only AXA
forming a large soluble aggregate (SI Appendix, Fig. S7C). SECMALS measurements indicated that, in solution, XAX, XAA,
and AAA were trimeric as expected; CD wavelength and temperature measurements for XAX, XAA, and AAA showed that thedesigns were helical and highly temperature stable (SI Appendix,
Fig. S7 D and E).
The number and position of the hydrogen bond networks
appears to determine the state which is populated—designs with
one network folding into the short state, with two networks, intoBbackupkey

XXA_GVDQ vs XXA

XAA_GGHN
hinge

network A

network A
Downloaded by guest on March 18, 2020

side view

E

hinge

D

side view

network A

XAX_GGDQ vs XAX
hinge

C

side viewFig. 3. Tuning the hinge region can change the protein state. (A) Positions of key hinge residue G75 and backup hinge residue T76 have the potential toform an ion coordination site in the long state, shown here, but not in the short state. (B) Examples of natural sites include calcium-coordinating residues ofhuman cytomegalovirus glycoprotein B (PDB ID 5CXF; blue) and nickel-coordinating residues of methylmalonyl CoA decarboxylase (PDB ID 1EF8; yellow). (C)Crystal structure of hinge modification XAX_GGDQ (orange; PDB ID 6NYK), like its parent XAX (green), is in the short state. (D) Crystal structure of hinge
modification XXA_GVDQ (orange; PDB ID 6NZ1), like its parent XXA (green), is in the short state. (E) Crystal structure of hinge modification XAA_GGHN (PDB
ID 6NZ3), unlike parent XAA, is in the long state.

4 of 8 | www.pnas.org/cgi/doi/10.1073/pnas.1914808117

Wei et al.

Tuning the Short-/Long-State Free-Energy Difference in the Hinge
Region. To develop amino acid sequences for which the freeenergies of the short and long states would be still closer together, we next tuned the hinge region, which transitioned fromloop to helix in the conformational change (Fig. 2 A, B, and E vs.
Fig. 2F). In the long state but not in the short state, the “key”

B

XAA
30mM CaXAA_GVDQ
30mM CaC
M82 I66 A71
ε δ1 βA71

0 0mM Ca

0mM Ca0 q*Rg 7 0 q*Rg 7

I66

16

M82

18
A71

M82

M82

14

20
22

1.9
4
1.8
6
0.9
2
0.8
6
1.5
8
1.5
0

24

Downloaded by guest on March 18, 2020

NMR

crystal1

H (ppm)Fig. 4. Bistable design XAA_GVDQ is in the short state by NMR and in the long state by crystallography. (A) Summary of crystallographic and NMR characterization of XAA_GVDQ with and without calcium: (Left) Rosetta models based on RDC and chemical shift data show the protein to be in the short state
without calcium (PDB ID 6O0C); (Right) crystal structure shows the protein to be in the long state with calcium (blue) and chloride (green; PDB ID 6NY8). (B)Normalized Kratky plots from SAXS experiments for control protein XAA (linker GGGT) and sample protein XAA_GVDQ measured with up to 30-mM calcium.
(C) 3D CM-CMHM NOESY strips of XAA_GVDQ indicate the protein as in the short state. (D) Crystallographic results at the hinge and hydrogen bond networks
with calcium shown as a blue sphere (Left); crystal packing from two different views with the flipping helix highlighted in red (Middle and Right).

Wei et al.

PNAS Latest Articles | 5 of 8

BIOPHYSICS ANDCOMPUTATIONAL BIOLOGY

bones are compatible with modular replacement of hydrogenbonding layers between the helices and with mutations in thehinge region, we carried out more detailed structural characterization to determine if any of the designs could adopt bothconformations. Crystal structures were determined for all potential
bistable candidates (XAX_GGDQ, XXA_GVDQ, XAA_GGHN,
and XAA_GVDQ), and we chose to focus on XAA_GVDQ becauseof the presence of a bound calcium. Detailed NMR and crystallographic characterizations of design XAA_GVDQ, described

13

D

1.5

A Bistable Designed Sequence That Adopts Both Short and Long
States. Having found that both the short- and long-state back-C (ppm)- Ca2+ + Ca2+

I(q)/I(0)*(q*Rg)2A

hinge residue (G75) and the “backup” hinge residue (T76) havethe potential to form an ion coordination site (Fig. 3A). Similar
natural sites include the calcium coordination site in humancytomegalovirus glycoprotein B (PDB ID 5CXF) (20) and thenickel coordination site in methylmalonyl CoA decarboxylase(PDB ID 1EF8) (21) (Fig. 3B), among others (SI Appendix, Figs.
S11–S13) (22). We sought to design calcium- or nickel-bindingsites in the long state by introducing aspartic acid or histidine at
the key hinge residue position. We also designed for structural
ambiguity in the turn—with the result that the secondary structure prediction for residue 75 is mixed helical and coil, but withlow confidence (SI Appendix, Fig. S14).
Crystal structures showed that designs XAX_GGDQ (PDB ID
6NYK) and XXA_GVDQ (PDB ID 6NZ1), which introduced apotential calcium coordination site, adopted the short state liketheir respective parent designs without the hinge residue modifications (i.e., XAX and XXA) (Fig. 3 C and D). In contrast, thecrystal structure of XAA_GGHN (PDB ID 6NZ3), which introduced a potential nickel coordination site (occupied by awater molecule in the structure), was in the extended state, unlike the parent XAA design, with rmsd 1.44 Å to the extended
model (Fig. 3E). Together, these results show that the hinge
region is amenable to mutation without causing the protein to
misfold into undesigned conformations.

I66

a more dynamic short state, and with three networks, into thelong state (see details in SI Appendix). Crystal structures of designs XXA (PDB ID 6NYI) and XAX (PDB ID 6NYE) matched
the modeled short state (Fig. 2 A and B). For both, most of thedeviation, as expected, was in the flexible hinge: the crystal
structures showed that each monomer adopted a different loop.
The hydrogen-bond network residues were closer to the computational model in XAX than in XXA, likely because they wereburied in the former and solvent exposed in the latter. By NMR,
the average solution structure adopted by XAX was locked in thecompact state, as shown by the presence of multiple NOEs froma 3D CM-CMHM nuclear Overhauser enhancement spectroscopy(NOESY) spectrum (Fig. 2C). Analysis of an MAI(LV)proS methyllabeled XAA sample also suggested a short state, with the flipping
helix shifted up (toward the hinge) compared with the design model(Fig. 2 D and E and SI Appendix, Fig. S8). The flipping helix of
XAA appears to have a more flexible interface (relative to XAX),
as evidenced by increased linewidths in both the amide transverse
relaxation optimized spectroscopy (TROSY) and methyl heteronuclear multiple quantum coherence (HMQC) spectra (SI Appendix, Fig. S9, Left). The crystal structure of design AAA (PDB
ID 6NX2) was in the long state with some deviation from thepredicted model because the asparagines of two of the hydrogenbond networks coordinated bromide ions and shifted the helicalregister (ions and waters were not explicitly accounted for duringmodeling) (Fig. 2F and SI Appendix, Fig. S10). These results
suggest the potential for a single sequence that can interconvert
between the two designed states since a change in three residues,
corresponding to the location of a hydrogen bond network, canswitch the observed state (i.e., XAA vs. AAA).

Downloaded by guest on March 18, 2020in the following paragraphs, suggest that this sequence may indeed populate both short and long states.
To characterize the structure in solution, we prepared a selective MAI(LV)proS methyl-labeled XAA_GVDQ sample (SIAppendix, Fig. S9, Right). In the absence of calcium, the 3D CMCMHM NOESY and residual dipolar couplings (RDCs) wereconsistent with the short state. We solved the NMR structureusing the chemical shifts, long-range NOEs (both methyl to methyl
and amide to methyl), and RDCs, and found it to be very close to
the short-state design model with an rmsd of 1.19 Å (Fig. 4 A and
C and SI Appendix, Fig. S15 and Table S6; PDB ID 6O0C).
We next sought to determine the structure of the design in thepresence of calcium. Comparison of RDCs, the two-dimensional(2D) 1H-15N amide TROSY spectrum, and 2D 1H-13C methyl
HMQC recorded using XAA_GVDQ samples with and without
calcium (SI Appendix, Fig. S15) showed that the average solution
structure in the presence of calcium remains in the short stateand exhibits a range of nonspecific chemical shift perturbations
at solvent-exposed residues. Overlays of one-dimensional (1D)
methyl proton spectra showed a significant loss of signal in a
calcium-concentration–dependent manner due to the formationof a nonobservable state, likely a higher-order oligomer or aggregate (SI Appendix, Fig. S15). SAXS analysis of XAA_GVDQ
and the control sequence with no aspartate, XAA (linker
GGGT), showed calcium-dependent changes in the normalized
Kratky plot, indicating an increase in size (Fig. 4B and SI Appendix, Table S4).
Because calcium-induced oligomerization or aggregation complicated NMR structure determination of the calcium-boundstate, despite efforts to optimize pH, temperature, concentration, calcium, and buffer components, we turned to X-ray crystallography and sought to determine crystal structures in both theabsence and presence of calcium. After extensive screening, wewere able to solve a structure in the absence of calcium (SI Appendix, Fig. S17, PDB ID 6NXM) in which the flipping helices
interacted with the inner helices in the same manner as they wouldin the designed short state, but did so in a domain-swappedmanner with a symmetry mate to form a hexamer. This was consistent with the observation of the short state by NMR in theabsence of calcium; the domain swapping almost certainly arose
due to crystallization conditions.
We next sought to solve the structure of the design in thepresence of calcium. We succeeded in solving the structure in 50mM calcium acetate by molecular replacement to 2.3-Å resolution (SI Appendix, Table S3). The protein was in the designed
long state with a metal ion coordinated by the aspartates in thehinge region (PDB ID 6NY8; Fig. 4 A and D). The ion was most
likely calcium given the coordination and crystallography conditions, which consisted of 0.05-M calcium acetate, 0.1-M sodium
acetate pH 4.5, 40% (wt/vol), and 1,2-propanediol at 18 °C.
It is plausible that a calcium-bound long state similar to thatobserved in the calcium-bound crystal structure was transiently
populated in solution in the presence of calcium, along with theshort apo-state. This state may have been more prone to aggregation, as suggested by the calcium-dependent signal loss in
the NMR experiment, which was carried out at high protein
concentrations. Alternatively, it is possible that the long state in
the crystal structure was not populated in solution conditions andwas instead driven by crystallization conditions and forces rather
than ion coordination, but these crystal-specific interactions
would likely have been quite small as the flipping helix maderelatively few crystal-lattice interactions (Fig. 4D).
Discussion
We designed a set of de novo proteins in which small changes(three mutations) in the interface or hinge region cause theproteins to fold into two distinct and structurally divergent
conformations. In contrast to most previous work, the6 of 8 | www.pnas.org/cgi/doi/10.1073/pnas.1914808117

differences in conformation of our designs are relatively large,
they do not rely on changes in oligomerization state, and bothstates are well defined. Most notably, the protein XAA_GVDQ
adopts the designed short state by NMR in the absence of calcium, and the designed long state by crystallography in thepresence of calcium. The extensive tuning needed to find conditions in which our designed proteins adopt two states, and thechallenge posed by the aggregation tendency of one of the states,
highlights the remarkable properties of natural two-state proteins (such as viral fusion proteins) that convert between two
well-behaved but very different conformations.
Given that changes in three residues in the hinge region canchange the conformation of the design (hinge GGHN is long;
GGGT is short), future work on these residues may yield designs
that populate soluble short and long states in equilibrium and areswitchable in solution conditions. Our designed systems, poisedas they are between two different states, are excellent starting
points for design of triggered conformational changes—only
small binding free energies will be required to switch conformational states; a particularly interesting possibility is synthetic
environmentally sensitive membrane fusion proteins analogous
to those of the viral proteins that inspired the design scheme.
Materials and Methods
Computational Design. To connect the backbone after the outer helix cut was
introduced (Fig. 1 and SI Appendix, Fig. S1), RosettaRemodel was used toinsert helical fragments for the long state; a blueprint file was used to
specify the length (2–7) and secondary structure (i.e., H) of the insert (19).
For the short state, a database lookup method was used to insert small,structured loops (helix-turn-helix motifs) as described previously (18, 23).
Amino acid sequence and side-chain rotamer conformations of the flipping helices, hinge connectors, and surrounding regions were optimized
using RosettaDesign (24) calculations carried out as described previously(18). Early designs also utilized Rosetta Multistate (25) to identify amino acidsequences that resulted in favorable side-chain packing in both short andlong states (SI Appendix, Fig. S1 C and D). Hydrogen bond networks were
designed and evaluated using the HBNet (18) method in Rosetta (26). Hydrogen bond network residues were constrained during design using
AtomPair constraints on the donors and acceptors of the hydrogen bonds as
described previously (18).
Amino acid sequences of the short, structured loops were chosen based on
how closely the torsion angle preference of a given sequence [ABEGO torsion
bin, where “A” indicates the alpha region of the Ramachandran plot; “B,”the beta region; “E” and “G,” the positive phi region for beta strands andhelices respectively; and “O,” the cis peptide conformation (27)] matched
the torsion angles of the inserted loop backbone (28); sequences that have ahigh propensity to adopt the structure of the designed helix-turn-helix
backbone should favor the short state, whereas sequences that deviate
from ideal torsional preferences or contain flexible residues, such as glycine,
should allow for the flipping helix to deviate from the short state.
To redesign hydrogen bond layers to hydrophobic layers and minimize
surface-exposed hydrophobics, and to reinforce packing around new loop
sequences, designable positions were designated in a resfile and side chainswere sampled without backbone movement using PackRotamersMover in
RosettaScripts (29). Backbone movement was disallowed to minimize disruption of the hydrogen bond network.
To predict whether a given designed sequence would prefer the shortbackbone, extended long backbone, or a mix of both, symmetric fold-anddock calculations were performed (30); results were evaluated by symmetric rms distance to measure how closely the structures predicted to be thelowest-energy matched each of the short and long designed backbones (Fig. 1C
and SI Appendix, Fig. S1D). Designs and fold-and-dock outputs were also manually inspected to identify surface-exposed hydrophobic residues, which could
lead to aggregation problems once the proteins were purified. Energy calculations used the then default Rosetta score function talaris2013 (31) for fold-anddock calculation and the then experimental ref2015 (32) for design calculations.
Note that all calculations were done using symmetry flags or the symmetricversions of protocols to specify the three-fold rotational symmetry (C3) of themolecules.
Online RosettaCommons documentation links are as follows: RosettaRemodel,
https://www.rosettacommons.org/docs/latest/application_documentation/
design/rosettaremodel; Multistate Design, https://www.rosettacommons.org/

Wei et al.

Synthetic Gene Construction. Synthetic genes were ordered from Genscript
Inc. and delivered in pET28b+ Escherichia coli expression vectors, inserted at
the NdeI and XhoI sites. Genes were encoded in frame with the N-terminal
hexahistidine tag and thrombin cleavage site. A stop codon was added at
the C terminus just before XhoI.
Bacterial Protein Expression and Purification. Plasmids were transformed into
chemically competent E. coli BL21 Star (DE3) (Invitrogen) or Rosetta (DE3)pLysS (QB3 MacroLabs). Starter cultures were grown in lysogeny broth (LB)
media with 50-μg/mL kanamycin overnight with shaking at 37 °C. Five milliliters of starter culture was used to inoculate 500-mL 2xTY with 50- to
100-μg/mL kanamycin at 37 °C until optical density (OD) 600 = 0.6. Cultures werecooled to 18 °C and induced with 0.1-mM isopropyl β- d-1-thiogalactopyranoside(IPTG) at OD 600 = 0.8 and grown overnight. Cells were harvested bycentrifugation at 3,500 rcf for 15 min at 4 °C and resuspended in lysis buffer(25-mM Tris pH 8.0, 300-mM NaCl, 20-mM imidazole), then lysed by sonication. Lysates were cleared by centrifugation at 14,500 rcf for at least
45 min at 4 °C. Supernatant was applied to 0.5- to 1-mL Ni-NTA resin (Qiagen)in gravity columns preequilibrated in lysis buffer. The column was washedthrice with 10 column volumes (CVs) of wash buffer (25-mM Tris pH 8.0,300-mM NaCl, 20-mM imidazole). Protein was eluted with 25-mM Tris pH
8.0, 300-mM NaCl, 250-mM imidazole, and 0.5-mM tris(2-carboxyethyl)
phosphine (TCEP). Proteins were buffer exchanged using Akta Pure FPLC(GE Healthcare) and a HiPrep 26/10 desalting column (GE Healthcare) into
25-mM Tris pH 8.0, 300-mM NaCl. The hexahistidine tag was removed bythrombin cleavage by incubating with 1:5,000 thrombin (EMD, Millipore)overnight at room temperature. Proteins were further purified by gel filtration using FPLC and a Superdex 75 10/300 GL size exclusion column (GEHealthcare).
CD Measurements. CD wavelength scans (260 to 195 nm) and temperaturemelts (25 to 95 °C) were measured using an AVIV model 410 CD spectrometer. Temperature melts monitored absorption signal at 222 nm and werecarried out at a heating rate of 4 °C/min. Protein samples were prepared at
0.25 mg/mL in PBS in a 1-mm cuvette.

Downloaded by guest on March 18, 2020

SAXS Measurements. Proteins were purified by gel filtration using Akta Pure
FPLC and the Superdex 75 10/300 GL into SAXS buffer (20-mM Tris pH 8.0, 150mM NaCl, and 2% glycerol). Fractions containing trimers were collected andconcentrated using Spin-X UF 500 10 molecular weight cut-off (MWCO) spincolumns (Corning), and the flow-through from the spin columns was used as
buffer blanks. Samples were prepared at concentrations of 3- to 8-mg/mL.
SAXS measurements were made at the SIBYLS 12.3.1 beamline at the Advanced Light Source (ALS). The light path was generated by a superbend
magnet to provide a 1,012-photon/s flux (1-Å wavelength) and detected on a
Pilatus3 2M pixel array detector. Each sample was collected multiple times
with the same exposure length, generally every 0.3 s for a total of 10 s,
resulting in 30 frames per sample.
Each dataset plotted was a separately experimentally measured sample
and initially processed in ScÅtter (https://bl1231.als.lbl.gov/scatter/). The
normalized Kratky plots were structurally interpreted by evaluating the location of the peak relative to a reference sample. SAXS profiles were also
analyzed using the FoXS Server (https://modbase.compbio.ucsf.edu/foxs/)(33, 34). For the best analysis consistency, we examined the fit of the data toeach of the two states separately (rather than as an ensemble of both statesusing the FoXS server by providing both models or using the MultiFoXS
protocol) and made the simplifying assumption that the better fit represented the dominant state in solution.
Protein Crystallography, X-Ray Data Collection, and Structure Determination.
Proteins were purified by gel filtration using Akta Pure FPLC and theWei et al.

Superdex 75 10/300 GL into 20-mM Tris pH 8.0, 150-mM NaCl and concentrated to 3 to 10 mg/mL. Most commonly, 8-mg/mL samples were screenedusing a Mosquito (TTP Labtech) with JCSG I-IV (Qiagen), Index (Hampton
Research), and Morpheus (Molecular Dimensions) screens. Sitting drops of 1:1
mixture of 150- to 200-nL protein and 150- to 200-nL reservoir solution wereincubated at 4 °C or 18 °C. Crystallization conditions are provided in SI Appendix, Table S2. The X-ray datasets were collected at the Berkeley Center
for Structural Biology beamlines 8.2.1 and 8.3.1 of the ALS at the Lawrence
Berkeley National Laboratory (LBNL). Datasets were indexed and scaled using HKL2000 (35) or XDS (36). Structures were determined by molecularreplacement with the program PHASER (37) within the Phenix suite (38)using the Rosetta design models as the initial search model. The molecularreplacement results were used to build the design structures and initiate
crystallographic refinement and model rebuilding. Structure refinement
was performed using the phenix.refine program (38, 39). Manual rebuilding using the COOT (Crystallographic Object-Oriented Toolkit) software program (40) and the addition of water molecules allowed constructionof the final models. Summaries of statistics are provided in SI Appendix,
Table S3.
NMR Spectroscopy and Structure Determination. All experiments wererecorded at 37 °C on an 800-MHz Bruker Avance III spectrometer equippedwith a triple resonance inverse (TCI) cryoprobe. NMR samples contained
20-mM sodium phosphate pH 6.2, 100-mM NaCl, 0.01% NaN3, and 1-U proteaseinhibitor mixture (Roche) in 95% H2O/5% D2O. For backbone and methyl
assignments, labeled samples were prepared using well-established protocols (41, 42). Briefly, backbone assignments were performed on uniformly
13 15
C/ N, perdeuterated protein samples using transverse relaxation
optimized spectroscopy (TROSY)-based 3D experiments, HNCO, HNCA andHN(CA)CB. Side-chain methyl assignments were performed starting from the
backbone assignments and using unambiguous nuclear Overhauser effect(NOE) connectivities observed in 3D CM-CMHM, 3D CM-NHN, and 3D HNHαCMHM band-Selective Optimized-Flip-Angle Short-Transient (SOFAST) nuclear Overhauser enhancement spectroscopy (NOESY) experiments, recorded
on a U-[15N, 12C, 2H] MAI(LV)proS (Met 13Ce, Ala 13Cβ, Ile 13Cδ1, Leu
12Cδ1/13Cδ2, Val 12Cγ1/13Cγ2) or AI(LV)proS selective methyl-labeled sample.
The calcium titrations for XAA_GVDQ were performed in 20-mM Tris·HCl pH
7.2, 100-mM NaCl, and 0-, 0.5-, 1-, 2-, 5-, 10-, 15-, 20-, 25-, 30-, and 50-mM
CaCl2 buffer conditions.
Backbone amide 1DNH RDCs were obtained using 2D 1H-15N transverse
relaxation-optimized spectroscopy (ARTSY) (43). For the XAA_GVDQ sample,
the alignment media were 10-mg/mL Pf1 phage (ASLA Biotech) for experiments performed without calcium and 15-mg/mL Pf1 phage for experiments
performed in the presence of 5-mM CaCl2. The 2H quadrupolar splittings
were 8.7 Hz and 9.3 Hz in the absence and presence of CaCl2, respectively.
For the XAA sample, the alignment media were 10-mg/mL Pf1 phage andthe 2H quadrupolar splitting was equal to 6.2 Hz. All NMR data were processed with NMRPipe (44) and analyzed using NMRFAM-SPARKY (45). The
chemical shift deviations (CSDs) of 13C methyls (p.p.m.) were calculated using
the equation ΔδCH3 = [1/2(ΔδH2 + ΔδC2/4)]1/2. The CSDs of 15N amides (p.p.m.)were calculated using the equation ΔδNH = [1/2(ΔδH2 + ΔδN2/25)]1/2.
Structure modeling from our NMR data was performed using Rosetta’s
fold-and-dock protocol (30, 46–48). Two sets of calculations were performed
using different input data: 1) backbone chemical shifts and RDCs (to model
the structure of XAA_GVDQ in the presence and absence of calcium [Fig. 4 A,
Bottom]) and 2) backbone chemical shifts, long-range NOEs, and RDCs (tocalculate the de novo NMR structures for XAA [Fig. 2E] and XAA_GVDQ [Fig.
4D]) (49). In the second set of calculations, we used a uniform upper distancebound of 10 Å for all 92 NOE restraints for XAA and for all 139 NOE restraints for XAA_GVDQ (SI Appendix, Table S5). The 10 lowest-energy
structures from each calculation showing good agreement with the RDCs
and chemical shifts and a minimum number of NOE violations were deposited in the PDB under accession codes 6O0I for XAA (BMRB ID 30574) and
6O0C for XAA_GVDQ mutant M4L (BMRB ID 30573).
Data Availability. The data for X-ray structures have been deposited in the
Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB
PDB) (https://www.rcsb.org/) under the following PDB IDs: 6NX2 (AAA), 6NYI
(XXA), 6NYE (XAX), 6NYK (XAX_GGDQ), 6NZ1 (XXA_GVDQ), 6NZ3 (XAA_GGHN),
6NXM (XAA_GVDQ), and 6NY8 (XAA_GVDQ with calcium). The data for
NMR structures have been deposited in the RCSB PDB under PDB IDs 6O0I
(XAA de novo) and 6O0C (XAA_GVDQ mutant M4L de novo without calcium), and in the Biological Magnetic Resonance Data Bank (BMRB) (http://
www.bmrb.wisc.edu/) under BMRB IDs 30574 (XAA de novo) and 30573

PNAS Latest Articles | 7 of 8

BIOPHYSICS ANDCOMPUTATIONAL BIOLOGY

docs/latest/application_documentation/design/mpi-msd; HBNet, https://www.rosettacommons.org/docs/latest/scripting_documentation/RosettaScripts/
Movers/movers_pages/HBNetMover; Constraint File, https://www.rosettacommons.
org/docs/latest/rosetta_basics/file_types/constraint-file; Resfile, https://www.rosettacommons.org/docs/latest/rosetta_basics/file_types/resfiles;
PackRotamersMover, https://www.rosettacommons.org/docs/latest/scripting_documentation/RosettaScripts/Movers/movers_pages/PackRotamersMover;
RosettaScripts, https://www.rosettacommons.org/docs/latest/scripting_documentation/RosettaScripts/RosettaScripts; Fold and dock, https://www.rosettacommons.org/docs/latest/application_documentation/structure_
prediction/fold-and-dock; Score Functions, https://www.rosettacommons.
org/docs/latest/rosetta_basics/scoring/score-types; Symmetry, https://www.
rosettacommons.org/demos/latest/tutorials/Symmetry/Symmetry.

ACKNOWLEDGMENTS. We thank X. Ren, J. Hurley, G. Meigs, P. Adams,
B. Sankaran, and A. Kang for help with X-ray crystallography. We thankK. Burnettt, G. Hura, and J. Tanamachi for help with SAXS. We thank
C. Nixon and S. Marqusee for help with CD. We thank B. Belardi, M. Vahey,
S. Son, S. Ovchinnikov, and the rest of the Fletcher and Baker laboratories fordiscussion. We thank the University of Wisconsin for the Hyak supercomputer and Rosetta@Home volunteers (https://boinc.bakerlab.org) for computing resources. Funding: SAXS data collection was conducted at the ALS,
a national user facility operated by Lawrence Berkeley National Laboratory
on behalf of the Department of Energy (DOE), Office of Basic Energy Sciences, through the Integrated Diffraction Analysis Technologies (IDAT) program, supported by the DOE Office of Biological and Environmental
Research. Additional support comes from the National Institutes of Healthproject ALS-ENABLE (P30 GM124169) and a High-End Instrumentation grant(S10OD018483). Crystallography data collection was conducted at Beamlines
8.3.1 and 8.21 at the ALS, which is operated by the University of California
Office of the President, Multicampus Research Programs and Initiatives (MR15-328599), the National Institutes of Health (R01 GM124149 and P30
GM124169), Plexxikon Inc., and the Integrated Diffraction Analysis Technologies program of the DOE Office of Biological and Environmental Research.
The Advanced Light Source (Berkeley, CA) is a national user facility operated
by the Lawrence Berkeley National Laboratory on behalf of the DOE undercontract number DE-AC02-05CH11231, Office of Basic Energy Sciences. All
NMR data were recorded at the 800-MHz NMR spectrometer at University ofCalifornia, Santa Cruz (UCSC), funded by the Office of the Director, NIH,
under High-End Instrumentation (HIE) Grant S10OD018455. We acknowledge additional support from the NIH through Grants R35GM125034(NIGMS) and R01AI143997(NIAID), and through Career Development Award
AI2573-01(NIAID), which funded the Baker computational cluster at UCSC.
D.A.F. acknowledges the Chan Zuckerberg Biohub for support.

1. P.-S. Huang, S. E. Boyken, D. Baker, The coming of age of de novo protein design.
Nature 537, 320–327 (2016).
2. P. Lu et al., Accurate computational design of multipass transmembrane proteins.
Science 359, 1042–1046 (2018).
3. Y. Hori, Y. Sugiura, Effects of Zn(II) binding and apoprotein structural stability on theconformation change of designed antennafinger proteins. Biochemistry 43, 3068–
3074 (2004).
4. E. Cerasoli, B. K. Sharpe, D. N. Woolfson, ZiCo: A peptide designed to switch folded
state upon binding zinc. J. Am. Chem. Soc. 127, 15008–15009 (2005).
5. X. I. Ambroggio, B. Kuhlman, Computational design of a single amino acid sequencethat can switch between two distinct protein folds. J. Am. Chem. Soc. 128, 1154–1161(2006).
6. R. Lizatovic et al., A de novo designed coiled-coil peptide with a reversible pH-induced
oligomerization switch. Structure 24, 946–955 (2016).
7. Y. Gambin et al., Direct single-molecule observation of a protein living in two opposed native structures. Proc. Natl. Acad. Sci. U.S.A. 106, 10153–10158 (2009).
8. A. Schug, P. C. Whitford, Y. Levy, J. N. Onuchic, Mutations as trapdoors to twocompeting native conformations of the Rop-dimer. Proc. Natl. Acad. Sci. U.S.A. 104,
17674–17679 (2007).
9. M. Munson et al., What makes a protein a protein? Hydrophobic core designs thatspecify stability and structural properties. Protein Sci. 5, 1584–1593 (1996).
10. J. A. Davey, A. M. Damry, N. K. Goto, R. A. Chica, Rational design of proteins thatexchange on functional timescales. Nat. Chem. Biol. 13, 1280–1285 (2017).
11. N. H. Joh, G. Grigoryan, Y. Wu, W. F. DeGrado, Design of self-assembling transmembrane helical bundles to elucidate principles required for membrane protein
folding and ion transport. Philos. Trans. R. Soc. Lond. B Biol. Sci. 372, 20160214 (2017).
12. S. E. Boyken et al., De novo design of tunable, pH-driven conformational changes.
Science 364, 658–664 (2019).
13. R. A. Langan et al., De novo design of bioactive protein switches. Nature 572, 205–210(2019).
14. P. A. Alexander, Y. He, Y. Chen, J. Orban, P. N. Bryan, A minimal sequence code forswitching protein structure and function. Proc. Natl. Acad. Sci. U.S.A. 106, 21149–
21154 (2009).
15. B. Podbilewicz, Virus and cell fusion mechanisms. Annu. Rev. Cell Dev. Biol. 30, 111–
139 (2014).
16. T. Ivanovic, J. L. Choi, S. P. Whelan, A. M. van Oijen, S. C. Harrison, Influenza-virus
membrane fusion by cooperative fold-back of stochastically induced hemagglutininintermediates. eLife 2, e00333 (2013).
17. J. J. Skehel, D. C. Wiley, Receptor binding and membrane fusion in virus entry: The
influenza hemagglutinin. Annu. Rev. Biochem. 69, 531–569 (2000).
18. S. E. Boyken et al., De novo design of protein homo-oligomers with modularhydrogen-bond network-mediated specificity. Science 352, 680–687 (2016).
19. P.-S. Huang et al., RosettaRemodel: A generalized framework for flexible backbone
protein design. PLoS One 6, e24109 (2011).
20. H. G. Burke, E. E. Heldwein, Crystal structure of the extracellular domain of glycoprotein B from Human Cytomegalovirus. Protein Data Bank. https://www.rcsb.org/
structure/5cxf. Accessed 28 July 2015.
21. M. M. Benning, T. Haller, J. A. Gerlt, H. M. Holden, Crystal structure of methylmalonylcoa decarboxylase. Protein Data Bank. https://www.rcsb.org/structure/1ef8. Accessed
28 July 2015.
22. V. Putignano, A. Rosato, L. Banci, C. Andreini, MetalPDB in 2018: A database of metalsites in biological macromolecular structures. Nucleic Acids Res. 46, D459–D464 (2018).
23. Z. Chen et al., Self-assembling 2D arrays with de novo protein building blocks. J. Am.
Chem. Soc. 141, 8891–8895 (2019).
24. B. Kuhlman, D. Baker, Native protein sequences are close to optimal for their structures. Proc. Natl. Acad. Sci. U.S.A. 97, 10383–10388 (2000).

25. A. Leaver-Fay, R. Jacak, P. B. Stranges, B. Kuhlman, A generic program for multistate
protein design. PLoS One 6, e20937 (2011).
26. A. Leaver-Fay et al., ROSETTA3: An object-oriented software suite for the simulationand design of macromolecules. Methods Enzymol. 487, 545–574 (2011).
27. Y.-R. Lin et al., Control over overall shape and size in de novo designed proteins. Proc.
Natl. Acad. Sci. U.S.A. 112, E5478–E5485 (2015).
28. E. Marcos et al., Principles for designing proteins with cavities formed by curved β
sheets. Science 355, 201–206 (2017).
29. S. J. Fleishman et al., RosettaScripts: A scripting language interface to the Rosetta
macromolecular modeling suite. PLoS One 6, e20161 (2011).
30. R. Das et al., Simultaneous prediction of protein folding and docking at high resolution. Proc. Natl. Acad. Sci. U.S.A. 106, 18978–18983 (2009).
31. M. J. O’Meara et al., Combined covalent-electrostatic model of hydrogen bonding
improves structure prediction with Rosetta. J. Chem. Theory Comput. 11, 609–622(2015).
32. H. Park et al., Simultaneous optimization of biomolecular energy functions on features from small molecules and macromolecules. J. Chem. Theory Comput. 12, 6201–
6212 (2016).
33. D. Schneidman-Duhovny, M. Hammel, J. A. Tainer, A. Sali, Accurate SAXS profile
computation and its assessment by contrast variation experiments. Biophys. J. 105,
962–974 (2013).
34. D. Schneidman-Duhovny, M. Hammel, J. A. Tainer, A. Sali, FoXS, FoXSDock andMultiFoXS: Single-state and multi-state structural modeling of proteins and theircomplexes based on SAXS profiles. Nucleic Acids Res. 44, W424–W429 (2016).
35. Z. Otwinowski, W. Minor, Processing of X-ray diffraction data collected in oscillation
mode. Methods Enzymol. 276, 307–326 (1997).
36. W. Kabsch, XDS. Acta Crystallogr. D Biol. Crystallogr. 66, 125–132 (2010).
37. A. J. McCoy et al., Phaser crystallographic software. J. Appl. Crystallogr. 40, 658–674(2007).
38. P. D. Adams et al., PHENIX: A comprehensive Python-based system for macromolecular structure solution. Acta Crystallogr. D Biol. Crystallogr. 66, 213–221 (2010).
39. P. V. Afonine et al., Joint X-ray and neutron refinement with phenix.refine. Acta
Crystallogr. D Biol. Crystallogr. 66, 1153–1163 (2010).
40. P. Emsley, K. Cowtan, Coot: Model-building tools for molecular graphics. Acta Crystallogr. D Biol. Crystallogr. 60, 2126–2132 (2004).
41. V. Tugarinov, L. E. Kay, Ile, Leu, and Val methyl assignments of the 723-residue malate
synthase G using a new labeling strategy and novel NMR methods. J. Am. Chem. Soc.
125, 13868–13878 (2003).
42. V. Tugarinov, V. Kanelis, L. E. Kay, Isotope labeling strategies for the study of highmolecular-weight proteins by solution NMR spectroscopy. Nat. Protoc. 1, 749–754 (2006).
43. N. C. Fitzkee, A. Bax, Facile measurement of 1H-15N residual dipolar couplings inlarger perdeuterated proteins. J. Biomol. NMR 48, 65–70 (2010).
44. F. Delaglio et al., NMRPipe: A multidimensional spectral processing system based on
UNIX pipes. J. Biomol. NMR 6, 277–293 (1995).
45. W. Lee, M. Tonelli, J. L. Markley, NMRFAM-SPARKY: Enhanced software for biomolecular NMR spectroscopy. Bioinformatics 31, 1325–1327 (2015).
46. N. G. Sgourakis et al., Determination of the structures of symmetric protein oligomers
from NMR chemical shifts and residual dipolar couplings. J. Am. Chem. Soc. 133, 6288–
6298 (2011).
47. F. DiMaio, A. Leaver-Fay, P. Bradley, D. Baker, I. André, Modeling symmetric macromolecular structures in Rosetta3. PLoS One 6, e20450 (2011).
48. M. D. Tyka et al., Alternate states of proteins revealed by detailed energy landscapemapping. J. Mol. Biol. 405, 607–618 (2011).
49. S. Nerli, A. C. McShan, N. G. Sgourakis, Chemical shift-based methods in NMR structure determination. Prog. Nucl. Magn. Reson. Spectrosc. 106–107, 1–25 (2018).

Downloaded by guest on March 18, 2020

(XAA_GVDQ mutant M4L de novo without calcium). All other data are
included in the manuscript and SI Appendix.

8 of 8 | www.pnas.org/cgi/doi/10.1073/pnas.1914808117

Wei et al.