Downloaded at UCSF LIBRARY on October 28, 2020 Aj Kortemme Tanja Ravetch V

UCSF UC San Francisco Previously Published Works

Title Engineered ACE2 receptor traps potently neutralize SARS-CoV-2.

Permalink https://escholarship.org/uc/item/5h1736nk

Authors Glasgow, Anum Glasgow, Jeff Limonta, Daniel et al.

Publication Date 2020-08-04

DOI 10.1101/2020.07.31.231746

Peer reviewed

eScholarship.org Powered by the California Digital Library University of California Downloaded at UCSF LIBRARY on October 28, 2020 aj Kortemme Tanja Ravetch V. Jeffrey Nix A. Matthew a Glasgow Anum neutralize SARS-CoV-2 potently traps receptor ACE2 Engineered h rmrcsiepoeno h ufc ftevrsbnsto www.pnas.org/cgi/doi/10.1073/pnas.2016093117 binds virus the of surface severe II the enzyme angiotensin-converting a on receptor membrane-bound protein of the of or spike (RBD) step (SARS-CoV-1) domain trimeric binding first the 1 receptor the the coronavirus infection, In prerequi- SARS-CoV-2 syndrome population. the respiratory infected without acute alternative, an rapid for a site offer proteins entry pandemic. developing which rapidly a infection, in and time spread precious costs viral these widespread on follow development based necessarily antibody is for and effort strategies pandemics, However, development (3–8). recent drug approaches and ongoing the past of in much effective recovered been of cells have B patients the sera from patient cloned convalescent antibodies from recombinant pan- and isolated Antibodies COVID-19 2). ongoing (1, the demic during infections (SARS-CoV-2) T display yeast SARS-CoV-2 patients. convalescent from antibodies faster neutralizing isolated for for need receptors the entry without known response therapeutic with viruses can for traps predesigned such Moreover, entry. be viral impair likely resis- other also viral would and that tance advantage SARS-CoV-2 key a the by offer with infections coronaviruses, traps ACE2-using fighting receptor to ACE2 the route Engineered in promising range. (IC50s) 100-ng/mL concentrations to neutralized inhibitory 10- SARS-CoV-2 half-maximal traps authentic with receptor virus and ACE2 stabilization optimal lentivirus increased most SARS-CoV-2–pseudotyped for the avidity, domain and (Fc) immunoglobulin fragment natu- human a the to crystallizable of fusion and addition domain 170-fold the collectrin RBD With ACE2 the ral ACE2. to wild-type bound than and tightly changes more con- acid variant amino highest-affinity seven The display. tained selec- surface and affinity yeast mutagenesis were using random variants tion by receptor 14-fold additional designed RBD an These the matured 12-fold. for affinity to improved up that pro- by computationally process flexible first design two-stage pro- a We backbone spike using tein cells. viral interface host ACE2–RBD the into the of designed entry tightly (RBD) prevent traps domain and receptor binding tein optimized receptor These stepwise the optimized, cells. bind a affinity of of infection describe SARS- block set CoV-2 potently we that a variants ACE2 generate Here, inactivated enzymatically to (ACE2). approach II engineering angiotensin- enzyme protein receptor syn- human converting viral the respiratory to the binding with acute protein begins spike infection severe (SARS-CoV-2) syndrome 2 and coronavirus respiratory 2020) drome (SARS-CoV-1) acute 31, July severe 1 review for for (received coronavirus 2020 mechanism 29, September essential approved and An WA, Seattle, Washington, of University Baker, David 94158 by CA Edited Francisco, San California, of University Pharmacology, Molecular and Cellular 10065; NY York, Canada; New 2H7, T6G AB Edmonton, Alberta, f of 94158; University Biology, CA Cell Francisco, San California, of University eateto eiie nvriyo aiona a rnic,C 94143; CA Francisco, San California, of University Medicine, of Department eateto iegneigadTeaetcSine,Uiest fClfri,SnFacso A94158; CA Francisco, San California, of University Sciences, Therapeutic and Bioengineering of Department rti niern prahst dniybnest viral to binders identify to approaches engineering Protein otetsvr ct eprtr ydoecrnvrs2 coronavirus therapeutics syndrome effective respiratory broadly acute for severe need treat urgent to an is here | | niia therapeutics antiviral eetrtrap receptor a,1 e a h n ae .Wells A. James and , eateto eia irbooyadImnlg,Uiest fAbra dotn BTG23 aaa and Canada; 2R3, T6G AB Edmonton, Alberta, of University Immunology, and Microbiology Medical of Department g ihlsJ Rettko J. Nicholas , efGlasgow Jeff , rnP Wiita P. Arun , | opttoa design computational b,1 e ei .Leung K. Kevin , b b,i,2 ailLimonta Daniel , c iK hn nttt fVrlg,Uiest fAbra dotn BTG21 Canada; 2E1, T6G AB Edmonton, Alberta, of University Virology, of Institute Shing Ka Li hsaaZha Shoshana , | e eateto aoaoyMdcn,Uiest fClfri,SnFacso A94143; CA Francisco, San California, of University Medicine, Laboratory of Department b c,d f ho .Lim A. Shion , ag Solomon Paige , ahlYamin Rachel , g aoaoyo oeua eeisadImnlg,RceelrUniversity, Rockefeller Immunology, and Genetics Molecular of Laboratory doi:10.1073/pnas.2016093117/-/DCSupplemental at online information supporting contains article This 2 1 under distributed a BY).y is (CC filed article access have open J.A.W. This Submission.y Direct and PNAS T.K., a is X.X.Z., article This I.L., work.y this J.G., to related A.G., patent provisional statement: research; supervised interest J.A.W. paper.y Competing the and T.K. wrote J.G., J.A.W. S.A.L. data; and A.G., and T.K., analyzed tools; J.G., S.A.L. S.Z., A.G., reagents/analytic and and N.J.R., N.J.R., new Y.Z., M.A.N., contributed Y.Z., I.L., P.S., K.K. I.L., D.L., P.S., and R.Y. D.L., research; J.G., and T.K., performed A.G., T.C.H., X.X.Z., research; K.K.L., A.P.W., designed J.V.R., O.S.R., J.A.W. D.L., J.G., A.G., contributions: Author wild-type of domain entry extracellular common soluble a the as Furthermore, ACE2 port. use as use- that well strains be as variant SARS-CoV-2 also emerging and other would SARS-CoV-1 traps pandemic binding both Receptor via for receptor. enter ful entry to virus ACE2 the the of ability to the receptor inhibit ACE2 also has an would to approach trap resistance This viral that (11). advantage entry potential facilitating the and bind- from ACE2 protein cellular spike ing viral the block that ACE2 domain the extracellular of variants viral soluble affinity-optimized traps”: block “receptor to domains formatted 10). other (9, entry or antibodies phage na as from binant such display, methods, efforts vitro yeast Ongoing in or RBD. use display the others by and on entry laboratory site anti- our viral binding by neutralizing ACE2 block Most the SARS-CoV-2 8). to and binding 4, SARS-CoV-1 (3, to cells bodies human enter to (ACE2) owo orsodnemyb drse.Eal [email protected] Email: addressed. be may correspondence whom work. To this to equally contributed J.G. and A.G. eetrtashv ag idn nefcsadbokthe block mutations. escape and impact viral potential ACE2 of interfaces the limiting binding diseases. interface, binding other receptor large respiratory entire from have proteins cause traps spike to receptor viral known bind also coronaviruses and spike- convales- patients from cent isolated viral as ACE2 antibodies infections high-affinity for optimized SARS-CoV-2 as effectively The authentic target neutralize cells. traps the into receptor entry (ACE2), angiotensin- SARS-CoV-2 II wild-type mediated on to enzyme domains based design, converting dimerization traps” computational to “receptor fusion use engineer and coronavirus We maturation, syndrome infections. affinity respiratory (SARS-CoV-2) acute therapeu- severe 2 building treat for approach to powerful tics and rapid engineering a protein offers pandemic, COVID-19 ongoing the During Significance sa lent taey epruddvlpeto ACE2 of development pursued we strategy, alternate an As b g i .Zhou X. Xin , ei Kao Kevin , b rn Lui Irene , b eateto hraetclChemistry, Pharmaceutical of Department b g rnS Rosenberg S. Oren , b agZhang Yang , o .Hobman C. Tom , ¨ v irre ognrt recom- generate to libraries ıve raieCmosAtiuinLcne4.0 License Attribution Commons Creative y . y https://www.pnas.org/lookup/suppl/ NSLts Articles Latest PNAS a , f c,d,h d i eatetof Department eatetof Department , , | f10 of 1

BIOPHYSICS AND COMPUTATIONAL BIOLOGY (WT) human recombinant ACE2 (APN01) was found to be safe in healthy volunteers (12) and in a small cohort of patients with acute respiratory distress syndrome (13) by virtue of ACE2’s intrinsic angiotensin-converting activity, which is not required for viral entry. APN01 is currently in phase 2 clinical trials in Europe for treatment of SARS-CoV-2 (14) (NCT04335136). However, we and others have shown that WT ACE2 binds the SARS-CoV- 2 spike RBD with only modest affinity (KD ∼ 15 nM) (15–17). ACE2 is therefore a good candidate for affinity optimization, especially because potent blocking antibodies to the spike protein can be isolated with binding affinity (KD ) values in the mid- to low-picomolar range (3, 4, 6, 8, 9, 18–20). Here, we improve the binding affinity of ACE2 for the monomeric spike RBD by 170-fold using a hybrid computational and experimental protein engineering approach. We demon- strate that after fusion to a human immunoglobulin (IgG) crystallizable fragment (Fc) domain and the natural collectrin domain of ACE2, our most effective ACE2-Fc variant has a half-maximal inhibitory concentration (IC50) of 28 ng/mL in pseudotyped SARS-CoV-2 neutralization assays and comparable neutralization in authentic SARS-CoV-2 infection assays, reducing viral replication to almost undetectable levels. ACE2 receptor traps are promising therapeutic candidates, especially given the potential for viral escape mutations to impact antibody efficacy (5, 21) and low neutralizing antibody levels in a subset of recovered patients (6). Fig. 1. ACE2 receptor trap strategy. Two computational design strategies were used to predict mutations to ACE2(614) (light blue shape) that enhance Results its affinity for the SARS-CoV-2 spike RBD: 1) saturation mutagenesis at com- We reengineered the soluble extracellular domain of ACE2 putational alanine scanning hot spots, followed by local ACE2 redesign [residues 18 to 614, ACE2(614)] to bind the RBD of (blue star mutations) and 2) combining mutations from computational saturation mutagenesis and experimental DMS data (green star mutations). the SARS-CoV-2 spike protein using a combined computa- Designed ACE2 variants were mutagenized and screened for binding to the tional/experimental protein engineering strategy (Fig. 1). First, RBD, and additional mutations that improved the binding affinity were iso- we computationally redesigned ACE2(614) using the Rosetta lated (red star mutations). Engineered ACE2(614) variants were fused to the macromolecular modeling suite, introducing sets of mutations ACE2 collectrin domain (residues 615 to 740, yellow ovals) and expressed as that improved the KD of an ACE2(614)-Fc fusion protein for Fc fusions (purple shapes) with an additional mutation to inactivate ACE2 the SARS-CoV-2 spike RBD from 3- to 11-fold over the WT peptidase activity (white star mutations). KD,app values represent appar- ACE2(614)-Fc protein in biolayer interferometry (BLI) bind- ent binding affinities measured between yeast surface-displayed ACE2(614) ing assays. Then, we affinity matured the improved ACE2(614) variants and the monomeric RBD. IC50 values represent those measured designs in a pooled yeast display format. Additional mutations for the four most potent neutralizing variants in SARS-CoV-2 pseudotyped virus assays. discovered through yeast display conferred a further 14-fold improvement in the apparent binding affinity (KD,app ) for the RBD over the computationally designed parent ACE2(614), as To determine whether point mutations at these positions could measured on the surface of yeast. The final ACE2 variants have improve the ACE2–RBD binding affinity, we performed com- KD,app close to 100 pM for the monomeric spike RBD. putational saturation mutagenesis at these positions (excluding High-resolution ACE2–RBD structures (22, 23) show a large, mutations to cysteine to avoid potential disulfide bond forma- flat binding interface primarily comprising the N-terminal helices tion) and recalculated the interface energy for each model (SI of ACE2 (residues 18 to 90), with secondary interaction sites Appendix, Table S2). While we found no amino acid substitu- spanning residues 324 to 361 (Fig. 2A). To computationally tions at positions 42 and 353 that were predicted to be stabilizing, redesign ACE2(614) for increased binding affinity with the RBD, several substitutions at position 34 were predicted to improve we first determined which amino acid side chains are most cru- the interaction energy between ACE2 and the RBD (Fig. 2B). cial to the ACE2–RBD interaction (“hot spots”) by performing Histidine 34 was mutated to a valine in the lowest-energy model a computational alanine scan on the binding interface using an because we anticipated favorable hydrophobic interactions with established method in Rosetta (26, 27). Then, we systematically leucine 455 in the RBD. In the highest-energy model, histidine redesigned a subset of hot spot residues and their local environ- 34 was mutated to an overly bulky isoleucine. ment to generate models for interfaces and selected the lowest We reasoned that both H34V and H34I, as the “best” and (best)-scoring ACE2 designs for testing (Fig. 2 A–C). “worst” point mutants, were predicted to substantially affect the Computational alanine scanning suggested that the binding interface energy in the context of their chemical environment affinity of the ACE2–RBD interaction depends most crucially on and that additional local mutations might improve binding affin- six amino acid side chains (H34, Y41, Q42, Y83, K353, and D355) ity in both models to yield different viable solutions. We applied on ACE2 as assessed by values of the predicted change in binding the Rosetta “Coupled Moves” flexible backbone design proto- energy upon mutation to alanine [DDG(complex)] greater than col (28) to redesign the local environment of V34 and I34 in 1 Rosetta Energy Unit (REU) (Fig. 2A and SI Appendix, Table each model (Fig. 2C). ACE2 side chains within 4 A˚ of residue 34 S1). To determine which of these hot spots to target for computa- were allowed to mutate, while other ACE2 and RBD side chains tional design, we evaluated each hot spot residue by two metrics: within 8 A˚ of ACE2 residue 34 could change rotamer and/or the per-residue energy and the contribution of the residue to the backbone conformations (“repacking”) (Materials and Methods). interface energy (Materials and Methods). Higher energies indi- This approach did not identify additional favorable mutations cate lower stability. Hot spot residues H34, Q42, and K353 were to H34V ACE2 in any of the models, but there were one to targeted for further design. four additional mutations in the H34I ACE2 models. The lowest

2 of 10 | www.pnas.org/cgi/doi/10.1073/pnas.2016093117 Glasgow et al. Downloaded at UCSF LIBRARY on October 28, 2020 Downloaded at UCSF LIBRARY on October 28, 2020 lso tal. et Glasgow respec- ACE2(614)-Fc, WT the 2 than lower (Fig. times measured 11 tively and were 3 RBD and be the to ACE2(614)-Fc for H34V ACE2(614)-Fc designed K31F/H34I/E35Q computationally 29), BLI-measured of The (11, Methods ). values studies and previous (Materials in cells for shown Expi293 fusion in as domain spike, Fc to expressed RBD IgG affinity transiently human improved spike We C-terminal for proteins. a with purified fusions ACE2(614) using Fc assays as BLI variants in ACE2 designed tionally 5,ad42t 9)i h oe s h Tsrcuewere structure WT Appendix, S1 (SI the comparable Fig. were to vs. solutions 452 design model both 418, for the energies to in 416 1 494) than residues less to RBD 492 and and 39 to 456, to corresponding 29 (atoms residues positions ACE2 repackable of rmsds and the mutable interfaces, the redesigned in lowest-energy methylene both the For with F31 Q35. bond interaction interface, hydrophobic the hydrogen of favorable a side a against a ACE2 made packed the made I34 On ACE2 L455. Q35 RBD and repositioned ACE2 Q493, RBD solution, repositioned 2C a this addi- (Fig. with In two E35Q S1). had and Fig. ACE2 K31F H34I mutations: on tional based protein energy-designed activity peptidase ACE2 inactivate to mutations histidine two in as table well The as replicate. ACE2, biological in V34 separate (D to shown and/or a added magenta. conformations was is in (24) rotameric “rep” shown DMS change Each mutations, from additional (25). to mutation amino two allowed knockout change in glycan were to resulted N90Q that permitted H34I the residues were CVD118, around that RBD Design ( yellow. residues and models. in ACE2 ACE2 trap shown magenta). orange; receptor are E in in residues) ACE2 shown shown (“repackable” diverse H34 positions and light generate residue atom in labeled to (WT shown backbone are ACE2 design are residues) I34 further 614 and (“mutable” for to ( ACE2 identity selected 91 mutagenesis. V34 residues were acid saturation and around H34I computational blue, performed and in for was H34V shown selected design H34. are backbone were to 90 spheres, to mutations magenta 18 stabilizing as Residues several RBD. shown predicted spike K353, the and binding Q42, to H34, strongly blue. contribute that spheres) as (shown residues 2. Fig. nvtoBImaueet hwta eindAE(1)F idn fnte oteRDaeipoe -t 1fl vrW C264-c ogenerate To ACE2(614)-Fc. WT over 11-fold to 2- improved are RBD the to affinities binding ACE2(614)-Fc designed that show measurements BLI vitro In ) et ecaatrzdtebnigafiiiso h computa- the of affinities binding the characterized we Next, ). opttoa lnn cnigietfidAE o spot hot ACE2 identified scanning alanine Computational (A) RBD. spike the to affinity binding improved for ACE2 of design Computational E. ,adtettlsme rdce arieinterface pairwise predicted summed total the and A, ˚ D and .W lotse idn fteRBD the of binding tested also We E). and IAppendix, SI D it h K the lists K D D ausfrtedsge C2vrat,wt roso h t o irto curves titration for fits the of errors with variants, ACE2 designed the for values n itdnsi oiin 7 n 7 oehrcodnt a coordinate together 378 and 374 positions (24), Zn site in glycosylation histidines N90 the and recent at mutations A for with activity. enrichment variants at reported peptidase ACE2 interface study native (DMS) the protein’s scanning to mutational the adjacent deep as is well that as glycan N90, a removing of the impact determine to ACE2(614)-Fc H34V/N90Q/H374N/H378N to (30). casamino with EBY100 3A) supplemented on medium (Fig. induced galactose synthetic first level in was simple cells ACE2(614) display a WT to surface for of fusions expression GFP and The as enhanced induction C-terminal cloned of and was readout Aga2p, ACE2(614), tag, WT Myc to a vari- addition these of in random- Each ants, K31F/H34I/E35Q. a and avid- H34V, for H34V/N90Q, mutations: avoid chose N90Q, following templates the We to with starting library, maturation. yeast-displayed domain as ized affinity surface variants Fc mutagenized dominate for ACE2(614) the might a four fusions without that expressed Aga2p effects cells, ity as yeast we in variants RBD, display ACE2(614) spike of the library for proteins ACE2(614)-Fc WT over affinity 2 improved (Fig. 10-fold showed ACE2(614)- H34V/N90Q/H374N/H378N Fc assay, BLI the In (11). ofrhripoetebnigafiiyo h designed the of affinity binding the improve further To 2+ i.S2) Fig. Appendix, (SI activity enzymatic for necessary ion D and E). opttoa auainmutagenesis saturation Computational B) NSLts Articles Latest PNAS C Flexible ) | f10 of 3 and

BIOPHYSICS AND COMPUTATIONAL BIOLOGY 3.1) and 200 pM (for sort 3.2) equilibrium sorts. The sequences of 21 clones from an 8-h off-rate sort 4 did not show clonal con- vergence but were enriched in favorable mutations in agreement with published DMS data (24). A very stringent fifth sort, in which surface-displayed ACE2 was allowed to dissociate from RBD for 12 h at room temperature and only 0.2% of the cell population was collected, still did not result in sequence con- vergence but showed enrichment of one clone derived from the computationally designed K31F/H34I/E35Q ACE2(614) variant. The enriched ACE2(614) variant had the following seven mutations: Q18R, K31F, N33D, H34S, E35Q, W69R, and Q76R. Interestingly, a majority of sequences from sorts 4 and 5 were derived from the K31F/H34I/E35Q ACE2(614) parent, but many of these had mutations at I34 to serine or alanine (SI Appendix, Fig. S5). This observation suggested that while I34 led to an alternate design variant, the isoleucine was not always the ideal amino acid at this position. A small number of additional mutations appeared in variants originating from different parents, including F40L/S, N49D/S, M62T/I/V, and Q101R, while others appeared only in the K31F/H34I/E35Q background, such as L79P/F and L91P. Following sorts 3 through 5, 18 to 24 individual yeast clones were picked from each sort for further characterization. After growth and induction, we analyzed each population for high- affinity mutants by staining with decreasing concentrations of the Affinity maturation by yeast surface display of pooled error-prone Fig. 3. RBD monomer. The best mutants from each sort were sequenced PCR libraries on designed ACE2 variants and DMS-guided design. (A) Monomeric ACE2(614) variants were expressed as Aga2p-GFP fusions on the (mutations are listed in SI Appendix, Table S3), and their KD,app surface of yeast cells. Binding of ACE2(614) to the spike RBD was quanti- values for the monomeric spike RBD were measured by on- fied by incubation of the cells in a solution of biotinylated RBD, followed yeast titrations (Fig. 3D and SI Appendix, Table S3). The best- by staining the cells with streptavidin Alexa Fluor 647, washing the cells, characterized mutants from sorts 3.1, 3.2, 4, and 5 had affinities and measuring fluorescent populations by flow cytometry. (B) Stringency of 0.52, 0.45, 0.19, and 0.12 nM, respectively [between 39- and was increased in each round of yeast display to enrich the cell popula- 170-fold higher affinity than WT ACE2(614)]. Although each tion for ACE2(614) variants that bound the RBD tightly. Equilibrium sorts sort contained a variety of mutants, the highest-affinity clones with decreasing RBD concentrations were used for sorts 1 to 3, and off- contained N33D and H34S mutations and were derived from rate sorts with increasing dissociation times and decreasing gate size were the K31F/H34I/E35Q ACE2(614) variant. The low likelihood of used for the last two sorts. (C) Representative cell populations by flow cytometry for yeast expressing a tight binding ACE2(614) variant from sort multiple base mutations in a single codon in error-prone PCR 4 compared with yeast expressing the computationally designed parent, mutagenesis likely favored the I34S mutation from this back- K31F/H34I/E35Q ACE2(614), incubated with 0.1 nM RBD monomer. The addi- ground; interestingly, ACE2 receptors from pangolin species that tional mutations in the sort 4 variant shift the cell population higher on are hypothesized to be SARS-CoV-2 reservoirs also include a the y axis due to tighter RBD binding. (D) On-yeast titration curves for cells serine at position 34 (32, 33). ACE2 N33 does not directly con- expressing ACE2(614) variants chosen from sorts 3 (Y313), 4 (Y353), and 5 tact the RBD in the crystal structure, but the enrichment of (Y373) that bind the RBD most tightly, compared with WT ACE2(614) (Y208) the N33D mutation in our affinity maturation was consistent and K31F/H34I/E35Q ACE2(614) (Y293). (E) On-yeast titration curves for cells with the enrichment of this point mutant in the DMS study (24). expressing the ACE2(614) variants generated by DMS-guided design, com- As an orthogonal approach to generate affinity-enhanced pared with WT ACE2(614) (Y208). Titration curves in D and E are fit to ACE2 variants, we leveraged the results from the DMS exper- biological duplicates, shown as points. Variant names, mutations, and KD,app values are in SI Appendix, Table S3. MFI, median fluorescence intensity. iment by Procko (24) to perform an additional round of DMS-guided computational design. Our original computational design strategy (Fig. 2 A–C) targeted alanine scan hot spots, as acids (SGCAA) media at 20 ◦C and 30 ◦C, and we confirmed described. The DMS experiment of Procko (24) identified ben- binding using biotinylated spike RBD-Fc and streptavidin Alexa eficial ACE2 point mutations in the ACE2–RBD interface at Fluor 647 (SI Appendix, Fig. S3 A and B). Binding of the RBD nonhot-spot positions, which could improve binding affinity by was well correlated with GFP expression, precluding the need direct interactions with the RBD, as well as outside the bind- for Myc-tag (expression) staining (SI Appendix, Fig. S3 A and B). ing interface, which might serve a stabilizing role. These two Sixteen sublibraries of ACE2 residues 18 to 103 were made classes of mutations would not have been predicted by our com- by homologous recombination into ACE2(614) using the four putational design strategy. Thus, we performed another round input templates, each mutagenized at four different rates using of computational saturation mutagenesis at nonhot-spot ACE2 deoxyribonucleotide triphosphate (dNTP) analogues (31). After positions in the ACE2–RBD interface (A25, T27, K31), as well transformation into EBY100 cells for a total library size of 2.7 × as the noninterface residue W69, to predict additional mutations. 107 members, sequencing of 24 presort clones showed an even We generated a set of DMS-guided, computationally designed distribution of mutations across residues 18 to 103 with repre- ACE2 variants with three to four mutations each that included sentation from all four input sequences (SI Appendix, Fig. S3 C at least two mutations outside the interface chosen directly from and D). We carried out sorts of increasing stringency using dif- the DMS dataset, combined with one to two mutations from ferent concentrations of RBD monomer as outlined in Fig. 3B the computational saturation mutagenesis at nonhot-spot posi- and SI Appendix, Fig. S4 and analyzed individual clones along the tions that were also enriched in DMS (SI Appendix, Fig. S6 and way. Sort 3 was performed with multiple binding stringencies and Table S3). These designed proteins were displayed on the surface expression temperatures. For example, sorts of ACE2 induced at of yeast as ACE2(614)-Aga2p fusions. We measured the KD,app 30 ◦C did not show increased expression in subsequent rounds, of the DMS-guided ACE2(614) variants for the monomeric but high-affinity clones were observed from both 500 pM (for sort RBD to be between 0.4 and 1 nM by on-yeast titrations, which

4 of 10 | www.pnas.org/cgi/doi/10.1073/pnas.2016093117 Glasgow et al. Downloaded at UCSF LIBRARY on October 28, 2020 Downloaded at UCSF LIBRARY on October 28, 2020 lso tal. et Glasgow off Appendix, (SI reduced RBD greatly the had with S8 also interactions Fig. monovalent yeast for in rates maturation affinity due 4B BLI (Fig. and by rates measured off S8 accurately decreased Fig. be massively to the tight to too the were with spike interactions FL binding ACE2(740)-Fc designed tationally eerbs otemto fmaueet(L s bind- efficacy. vs. neutralization (BLI with measurement correlated well of and method yeast) the on ing to robust were thermal the in maintains RBD it ACE2. but spike WT S10 ), the of Fig. stability to , Appendix binding (SI H345L assay impact (39). BLI not a an S9 ) does in and activity and assay peptidase S2 activity detectable is have Figs. not and does , Appendix binding mutation ACE2(740)-Fc substrate (SI inactivation for destabilizing important the not is which include the instead, adapted to H345L we scaffold Therefore, were S9 ). ACE2(740)-Fc Fig. mutations , Appendix inactivation (SI spectroscopy, enzymatic destabilizing (CD) ACE2-Fc H374N/H378N dichroism the the circular of but by temperature measured as melting constructs variants Fc-fused apparent our the in domain Incorpo- improved collectrin cycle. ACE2 catalytic the absence the of ration the representing in structures is methods multiple mutations computational of site using active predict of to therapeutic difficult destabilization factor ACE2-based relative optimal important The an an scaffold. engineering also in is consider ablated stability to H378N, protein and However, H374N binding. mutations, inactivation the inal for 2 affinity (Fig. binding the RBD affecting off-target avoid without to effects ACE2 site. vasodilation of active activity enzyme peptidase the the outside inactivated binds clin- We RBD in The safe 13). be (12, to trials shown ical was and vasodilator, a angiotensin(1–7), 38). (37, translate not protein did soluble yeast well-folded from on to mutations expression stabilizing variant indicat- ACE2 of fusions, display, reports yeast Fc numerous as despite expressed that ing poorly were campaign display spike FL the for in domain decrease collectrin dramatic the 4B a without (Fig. and or RBD with spike ACE2-Fc the monovalent saw for the indeed Fc in we decrease the RBD, with 3.7-fold spike RBD Compared a the spike BLI. with using to interaction ACE2- spike) ACE2(614)-Fc [ACE2(740)-Fc] (FL of domain spike binding full-length collectrin tested and through the We interaction would with effects. ACE2–spike RBDs Fc avidity the spike and of two bind stabilization strength additional independently the the ACE2 can the increase and of trimer inclusion domain the spike that collectrin hypothesized the We the 36). in (35, Furthermore, repositioning ACE2 RBDs spike. by to three effective binding perhaps more the improved (29), be for monomers infection to ACE2 shown col- viral the recently blocking containing also ACE2 in were (SI WT of domain domains fusions lectrin peptidase Fc S7). between (34). Fig. contacts helix Appendix, C-terminal transmembrane con- and domain its intercollectrin tacts additional to reveals extracellular also ACE2 structure the The of connecting a domain domain as collectrin ACE2 peptidase the shows 4A). with structure (Fig. microscopy dimer, spike for cryo-electron affinity recent binding the A protein’s of the 740) inclusion improve to 615 whether could (residues Fc tested domain collectrin different we ACE2 C-terminal in BLI, natural Using variants formats. ACE2 fusion affinity-matured and designed, F40D. and lowest H34A, T27Y, the A25V, with mutations: following design 3E computational (Fig. guided ACE2(614) WT than higher and 51-fold and 21- between is efudta h idn fnt mrvmnst ACE2 to improvements affinity binding the that found We to II angiotensin converts ACE2 of domain soluble The computationally WT, of binding characterized next We IAppendix SI .AE(4)F ainsfo M-udddesign DMS-guided from variants ACE2(740)-Fc A–E). F and and D i.S8 Fig. Appendix, SI .Tehgetafiiymtnsfo u yeast our from mutants highest-affinity The G). and .TeAE(1)vratfo DMS- from variant ACE2(614) The S3). Table , E and 1) u orig- Our (11). S2) Fig. Appendix, SI .Bt Tadcompu- and WT Both A–E). K D fW ACE2(740)- WT of and K D IAppendix, SI ,app a the had K Zn D 2+ of fteAE ainstruhipoe fnt,saiiy and stability, affinity, improved through variants ACE2 the potency neutralization of the increased dramatically domain Fc IgG 0.1 S13). of Fig. range Appendix, the (SI in were 1 values IC50 to directly results: more similar affinity- entry yielded the viral and of differ- on effect molecules a the ACE2(740)-Fc and measure enhanced and h) laboratory reproducibility 26 different ensure a than in to conducted rather were strain h SARS-CoV-2 with (16 ent experiments times incubation neutralization ). S12 shorter Fig. SARS-CoV-2 Appendix, concen- (SI live the ACE2 assay at Additional neutralization the the cells in of uninfected used None in trations cytotoxicity 40). from induced (6, isolated respectively variants antibodies patients ng/mL, reported COVID-19 recently 73 convalescent with potency, and comparable neutralization 89 is most approximately the 4F of (Fig. displayed IC50s 313 with and 310 5 at ants viral efficacy 0.05 neutralization diminished had at only considerably starting ACE2(740)-Fc concentrations 50 each at to 313 levels 0.005 and RNA from 310, vari- concentrations 293, affinity-matured at Variants yeast tested were and 313 310, ant design variant DMS-guided designed computationally 293, 208), 4F (Fig. (variant SARS-CoV-2 ACE2(740)-Fc fide affinity bona the using in and assay neutralization neutralization efficient design, demonstrating yeast DMS-guided in maturation design, originating computational variants from ACE2(740)-Fc with potency, neutralization 0.5 than less was ACE2(614)-Fc CVD118, affinity-enhanced variant, intermediate 50 this 4E, IgG for (Fig. anti-GFP IC50 tested The concentration an improved highest over the N90Q 50,000-fold at control, than and more H34V com- by of neutralization mutations inclusion predicted 370-fold additional the by and putationally pseudotyped of level neutralization ACE2(614), fusion the improved monomeric biosafety that ACE2(614) over from a to determined results in domain We Fc the cells assays. reflected neutralization VeroE6 viral closely infect facility to 3 used was CoV-2 treating for 17). trials (16, S4) clinical Table 4D in (Fig. currently infections improve is SARS-CoV-2 that significantly unmodified APN01 domain The molecule 4 Fc ACE2(740). (Fig. the unmodified ACE2(740) to over fusion neutralization collectrin the and compu- of from addition domain, ACE2 maturation, misfolded affinity to and mutations otherwise design the tational or that revealed unstable data ization is variant 4D molecule’s low (Fig. the and this because campaign display sibly despite yeast the in SARS-CoV-2, enrichment neutralize [T27A/K31F/N33D/ 353 effectively not variant does ACE2(740)-Fc] ACE2 H34S/E35Q/N61D/K68R/L79P/H345L respectively, 313, affinity-enhanced and 28 the improve- 293, 4D; and 311, Fig. significant 310, 36, in (variants to 55, efficacy paths 58, in of ments multiple values demonstrating neu- IC50 display ng/mL, surface with yeast SARS-CoV-2 using tralized molecules maturation affinity ACE2(740)-Fc and DMS-guided design, design, different computational embry- from cells, derived human mutations with (HEK) ACE2-expressing kidney in onic assay neutralization viral n uhni ASCV2(i.4 lentivirus (Fig. and pseudotyped SARS-CoV-2 purified, against were authentic neutralization format, and display viral ACE2(740)-Fc yeast for H345L assayed compu- and the from design, in expressed variants DMS-guided infec- ACE2 design, SARS-CoV-2 neutralizing tational affinity-improved in several efficacy tions, their evaluate To h nlso fteAE olcrndmi n h human the and domain collectrin ACE2 the of inclusion The diino h C2cleti oanfrhrimproved further domain collectrin ACE2 the of Addition SARS- fide bona which in assays neutralization viral from Data /Lfrvrat23adlwrfrvrat 1 n 313 and 310 variants for lower and 293 variant for µg/mL and and .W locnre that confirmed also We S4). Table Appendix, SI .Ti etaiainpotency neutralization This S4). Table Appendix, SI .Tkntgte,teneutral- the together, Taken S11). Fig. Appendix, SI C and ain 0e ssmlrt the to similar is 208e) variant D, and µg/mL. C–F i.S1and S11 Fig. Appendix, SI NSLts Articles Latest PNAS .I h pseudotyped the In ). /L hl WT while µg/mL, /L Vari- µg/mL. K D ,app µg/mL). | µg/mL. .WT ). pos- , f10 of 5

BIOPHYSICS AND COMPUTATIONAL BIOLOGY A

C D

Fig. 4. Increased stability, affinity, and avidity effects result in tighter binding between ACE2(740)-Fc and FL spike and potent viral neutralization. (A) Plasmid constructs for expression of ACE2(614) and ACE2(740) (Left) and spike in the monomeric RBD and full-length forms (Right). Avi tag, target sequence for intracellular biotinylation by BirA; hIgG1-Fc, human immunoglobulin 1 Fc domain; interleukin-2 (IL2) SS, IL2 signal sequence (cleaved); native SS, native spike signal sequence; thrombin site, thrombin cleavage site; T4 trimer, T4 bacteriophage fibritin trimerization motif; tobacco etch virus (TEV)-linker, TEV protease cleavage sequence and glycine-serine linker; 8X- or 6XHis tag, polyhistidine tag. (B) BLI measurements show decreased KD for ACE2(740)-Fc compared with ACE2(614)-Fc for the interaction with the spike RBD. Binding between ACE2-Fc and the FL spike protein results in a KD less than 100 pM due to very low off rates. Solid lines show response curves for twofold dilution titration spanning 0.37 to 50 nM RBD. Dotted lines show calculated fits. (C) Table of all ACE2 variants with scaffolds and mutations tested in pseudotyped and authentic SARS-CoV-2 viral neutralization assays, listed with their origin. (D) Fc fusion, inclusion of the collectrin domain, and affinity-enhancing mutations improve neutralization of ACE2 constructs against pseudotyped SARS-CoV-2 virus, except for misfolded variant 353. Error bars represent SDs over all technical replicates from two to four biological replicates. Biological replicates were separate experiments using different preparations of the ACE2 variant and pseudovirus, each with two or four technical replicates. Statistical significance with P < 0.01 was determined using a homoscedastic two-tailed t test. Authentic SARS-CoV-2 viral neutralization experiments with ACE2 variants in VeroE6 cells showed that (E) Fc fusion (CVD013) and addition of computationally predicted mutations (CVD118) enhance neutralization by greater than 50,000-fold over a control anti-GFP IgG antibody sample and that (F) inclusion of the collectrin domain, computationally predicted mutations (CVD293), DMS-guided mutations (CVD310), and mutations from affinity maturation in yeast (CVD313) enhance neutralization potency over a control anti-GFP IgG antibody sample to IC50 values of 73 to 136 ng/mL. E and F show results from different experiments in biological duplicate. Error bars represent the SEM.

6 of 10 | www.pnas.org/cgi/doi/10.1073/pnas.2016093117 Glasgow et al. Downloaded at UCSF LIBRARY on October 28, 2020 Downloaded at UCSF LIBRARY on October 28, 2020 i.5. Fig. E35Q) H34I, nanomolar K31F, with 293, H34S, (variant bound N33D, parent com- K31F, its designed and with H345L) putationally mutation 313, inactivation (variant enzymatic RBDs affin- and yeast from E35Q, spike trap in receptor NL63 maturation a and ACE2(740)-Fc, ity WT SARS-CoV-1 Indeed, 5). the (Fig. bind ACE2(740)-Fc expressed WT could robustly whether variants most tested coronavirus our We human and 41). and ACE2(740)-Fc SARS-CoV-1 (25, by coronaviruses caused (HCoV)-NL63 mechanisms, those entry as cell such ACE2-dependent with infections ratory of variants. use affinity-enhanced the the neutralization effects, of the to potency these central to is of scaffold due result ACE2(740)-Fc RBD H345L trimeric combined the monomeric a full-length the As the with effects. the that than avidity observed stronger with is also ACE2-Fc protein We spike (34). dimeric alone of Fc may interaction the domain would with than collectrin achieved together closer the be molecules ACE2 but the position dimerization, to serve ACE2 in results and 4 (Fig. avidity lso tal. et Glasgow K (A–C (B, ACE2(740)-Fc, G–I D–F D C2bsdteaetc ol eue otetohrrespi- other treat to used be could therapeutics ACE2-based ausa niae.Dte ie hwcluae t.Teeteeyso f aeosre in observed rate off slow extremely The fits. calculated show lines Dotted indicated. as values ,wihi ls opeiu bevtosfrteN6 RBD– NL63 the for observations previous to close is which ), ,teSR-o- B (D–F RBD SARS-CoV-1 the ), n eso nanomolar of tens and ) Tadegnee C270-cbn h ASCV1RDadteHo-L3RD ersnaieBImaueet o (A, for measurements BLI Representative RBD. HCoV-NL63 the and RBD SARS-CoV-1 the bind ACE2(740)-Fc engineered and WT and E, .TeF fusion Fc The S7). and S2 Figs. Appendix, SI H 3FH4/3QAE(4)F,ad(C, and ACE2(740)-Fc, K31F/H34I/E35Q ) K D ,adteHo-L3RD(G–I RBD HCoV-NL63 the and ), oteSR-o- B Fg 5 (Fig. RBD SARS-CoV-1 the to K D oteN6 B Fg 5 (Fig. RBD NL63 the to tcnetain f035t 0 MRD ihtehgetRDcnetaintse and tested concentration RBD highest the with RBD, nM 100 to 0.375 of concentrations at ) and F, I 3FN3/3SE5/35 C270-citrcin ihteSR-o- RBD SARS-CoV-2 the with interactions ACE2(740)-Fc K31F/N33D/H34S/E35Q/H345L ) osbeuigbt opttoa einadslcinmethods selection is and it design show computational we both Here, using (48). possible treatment have of HIV some for although examples trials 47), clinical (46, Administration-approved entered biologics antiviral Drug as traps and receptor Food There half-lives. no long afford are and avidity human- achieve to to fused Fc form engineered dimeric by in improved proteins sufficiently these often presenting is simply Affinity thera- 43–45). at tumor (31, produced scale and factor, peutic cytokines growth other and endothelial alpha, factor vascular necrosis binding biother- for as extensively apeutics used been have traps receptor Engineered Discussion (42). protein membrane CD26) IV as pepdidase known dipeptidyl also the (DPP4; with interactions through but ACE2 ideEs eprtr ydoe(ES B pt 5 nM the 150 to to S15 S14). up appreciably Fig. RBD Appendix, Fig. bind (MERS) (SI not Appendix, syndrome did respiratory (SI East variants Middle (2) ACE2 the identity struc- contrast, sequence similar In low have 73% RBDs its and while SARS-CoV-2 to tures RBD, and due SARS-CoV-2 SARS-CoV-1 likely the the is to ACE2-Fc the similarity for with structure/sequence affinity interaction binding weaker RBD The NL63 (41). interaction ACE2 WT C rcue K precluded ;MR-o atce ne el o via not cells enter particles MERS-CoV ); D determination. NSLts Articles Latest PNAS and D, | WT G) f10 of 7

BIOPHYSICS AND COMPUTATIONAL BIOLOGY to dramatically improve the binding for dimeric ACE2 for the from convalescent patients or selection by in vitro methods (10). SARS-CoV-2 spike RBD to the range of high-affinity antibodies. Thus, it represents a rapid and orthogonal approach to gener- We used several computational design methods in Rosetta ating therapeutic candidates for treating future viral pandemics, to predict mutations that could enhance the affinity of ACE2 without any prerequisite for an infected human population. Engi- for the SARS-CoV-2 RBD, with one innovation: following com- neered receptor traps can be stockpiled as potentially useful drug putational saturation mutagenesis, we proceeded to the local candidates for multiple viruses that use the same port of entry redesign step with the lowest-energy point mutant (H34V) as as we show for HCoV-NL63 and pandemic viruses SARS-CoV-1 well as the highest-energy point mutant (H34I). Our hypothesis and SARS-CoV-2 and decrease the likelihood of viral resistance, was that mutating and optimizing the positions of surround- although the impact of mutations on the immunogenicity of the ing residues would allow us to identify alternative low-energy molecule is unknown and would need to be monitored in human solutions for the ACE2–RBD interaction, which proved to be subjects. Our study on ACE2 provides a systematic road map to the case. We experimentally validated that the variant designed redesigning an entry receptor as a therapeutic, and we believe from H34I ACE2 improved binding affinity, pseudotyped viral the same strategy could be applied to other entry receptors such neutralization, and authentic viral neutralization in two inde- as DPP4 for treating MERS and aminopeptidase N (ANPEP) pendent laboratories compared with other computationally pre- for treating upper respiratory tract infections by HCoV- dicted mutations, despite the fact that no single mutation in 229E (42, 51). this design conferred a fitness advantage in DMS (Figs. 2 and 4 and SI Appendix, Table S1) (24). In our strategy, we did not Materials and Methods include a sublibrary based on the purely WT sequence, instead Structural modeling and computational protein design are in SI Appendix, opting for N90Q, which both removes the variable of heteroge- Supplemental computational methods: Command lines and input files (com- nous glycosylation in yeast and enhances affinity. Strikingly, the mand lines and input files for each section). We used the 2019.38 release computationally designed H34I-containing variant outcompeted of Rosetta 3.12 (Git SHA1 hash number: 2019.38.post.dev+231.master. the N90Q ACE2 mutant and was the parent of the most effec- 04d3e581085 04d3e581085629b0f0c46f1e1aef9e61978e0eeb). tive ACE2 molecules to emerge from affinity maturation (SI Appendix, Fig. S5 and Table S3). It is highly unlikely that the Preparation of ACE2–Spike Structure for Modeling. To model ACE2–spike interactions, we used the 2.50-A˚ resolution X-ray structure of the spike RBD K31F, H34I, and E35Q mutations would have arisen using a complexed with the soluble extracellular domain of ACE2 as determined purely experimental evolution strategy due to mutational bias in by Wang et al. (23) (Protein Data Bank [PDB] ID code 6LZG). This struc- error-prone PCR. While yeast display affinity maturation can be ture was downloaded from the PDB, relaxed with coordinate constraints done in the span of several weeks, developing the computational on backbone and side chain heavy atoms, and minimized in Rosetta with- design pipeline and testing the resulting designed ACE2 variants out constraints using default options using the beta nov16 score function only took 1 week. This demonstrates the potential benefits of (command lines are in SI Appendix, Supplemental computational methods: developing computational design methods that include steps to Command lines and input files). diversify solutions. Engineered ACE2 receptor traps present key advantages in Identification of ACE2 Residues That Contribute to Binding in the ACE2–Spike treating SARS-CoV-2 infections. Several groups have isolated Interface and Are Chosen for Design. To determine which residues contribute most strongly to the ACE2–spike interaction, we used the Robetta Com- antibodies from convalescent patients, confirmed their neutral- putational Interface Alanine Scanning Server (26, 27) (publicly available at ization potencies, characterized their affinities to the RBD, and http://robetta.bakerlab.org/alascansubmit.jsp) to perform a computational in some cases, determined their structures. A subset of the neu- alanine scan on the relaxed and minimized input structure of the complex. tralizing antibodies blocks ACE2, while the remainder binds The alanine scan identified 18 ACE2 residues in the interface, 6 of which had spike epitopes outside the ACE2 binding interface (3, 4, 6–10, DDG(complex) values greater than one. These hot spots represent amino 18–20, 40). By contrast, ACE2 receptor traps directly compete acid side chains that are predicted to significantly destabilize the interface with the essential viral entry mechanism. Recent reports indicate when mutated to alanine. SI Appendix, Table S1 shows the full results of that RBD binding antibodies are also susceptible to diminished computational alanine scanning. affinity at lower pH, which could lead to lower viral neutraliza- We used two metrics to determine which hot spots could most likely be tion and potentially, reinfection (36). Finally, viral escape muta- mutated to improve the ACE2–spike binding affinity: 1) the total per-residue energy as evaluated by the Rosetta score function to be the sum of all one- tions can render antibody therapeutics ineffective, but escape body and half the sum of all two-body energies for that residue and 2) the mutations that reduce the efficacy of an ACE2 receptor trap total contribution of the residue to the interface energy, which is the sum of binding are also likely to reduce viral invasion. Many of the pairwise residue energies over all residue pairs (R1, R2) where R1 belongs to affinity-enhancing mutations that we described are in the recep- ACE2 and R2 belongs to the spike RBD. We classified hot-spot residues that tor binding site, and so, it is conceivable that they could be had total residue energies in the top 30% of all residues in ACE2 as well as selectively targeted by a mutant virus; however, we show that total cross-interface interaction energies greater than 0.5 REU as residues even the NL63 RBD can still bind our ACE2 variants despite its in the ACE2–spike interface to be targeted for design. These residues were significant sequence and structure divergence from the SARS- H34, Q42, and K353. CoV-2 RBD. Receptor traps based on WT ACE2 (11, 49), antibody fusions (50), or affinity-enhanced mutants (29), which Computational Saturation Mutagenesis at Targeted ACE2 Interface Residue Positions. We systematically computationally mutated H34, Q42, and include naturally occurring mutations that were also found in our K353 in ACE2 to every other amino acid except cysteine, allowing all residues engineering efforts (33), have also been reported to neutralize with side chain heavy atoms in ACE2 or spike within 6 A˚ of the mutated pseudovirus and spike-based cell fusion. Our work harnesses the position to repack (change rotameric conformation); minimized the entire power of protein engineering approaches to build on these lines complex; and recalculated all of the pairwise interaction energies across the of research by engineering orders of magnitude higher affinity ACE2–spike interface and various interface metrics. These interface met- and demonstrating potent neutralization of authentic SARS- rics were the solvent-accessible surface area buried at the interface; the CoV-2 virus. We also anticipate that engineered ACE2 receptor change in energy when ACE2 and spike RBD are separated vs. when they are traps could synergize in a mixture with neutralizing antibodies complexed; the energy of separated chains per unit interface area; the number of buried and unsatisfied hydrogen bonds at the interface; a packing that bind the RBD outside the ACE2 binding site to treat viral statistic score for the interface; the binding energy of the interface calcu- infections (20). lated with cross-interface energy terms; a binding energy calculated using The systematic two-pronged affinity optimization approach for Rosetta’s centroid mode and score 3 score function; the number of residues engineering ACE2 receptor traps was achieved by a small team at the interface; the average energy of each residue at the interface; the in several months, which is comparable with antibody isolation energy of each side of the interface; the average per-residue energy for each

8 of 10 | www.pnas.org/cgi/doi/10.1073/pnas.2016093117 Glasgow et al. Downloaded at UCSF LIBRARY on October 28, 2020 Downloaded at UCSF LIBRARY on October 28, 2020 lso tal. et Glasgow (53). Weil and Singh of version methods. modified a using yeast Library. Yeast of Analysis (52). al. et Benatuil of method Transformations. Yeast emission). nm excitation/405 nm (320 monitored 100 ZnCl and nM) 0.3 to 2-(N (diluted 50 variants activity; ACE2 peptidase of ACE2 Sci- quantify to Life used was Assay. ences) Enzo (Mca-APK-DNP; Activity yl)acetyl-Ala-Pro-Lys(2,4-dinitrophenyl)-OH Proteolytic ACE2 irreversible was Melting points. ACE2. these WT between for an denatured and was tem- protein 0% melting the apparent as the baseline and T 100%, before-melt as perature, baseline the after-melt of the of average average 25 an at using measured from normalized were temperature the nm increasing 280 by to measured were in nm diluted 25 225 were at variants curves ACE2 ing ACE2 purified cuvettes. using quartz spectrometer 1-mm 300 Denaturation. J-710 in Jasco Thermal a solutions with on variant collected Spectroscopy were CD data by CD Stability of Determination R kinetics had data binding BLI Noncooperative to fits equation. All Hill assumed. were the affinity steady-state using the determined and was 10.0 values, the response version by maximum normalized software were group were equi- equilibrium) steady-state HT theoretical (R data data Analysis The response Raw fitting. signal Data global binding s. librium Octet with 900 association analysis in kinetic s; wells, curves curve-fitting 180 baseline using binding buffer, in 1:1 PBS-T dissociation to antigen, in s; with fit tips tips 600 rinsing load and analyte, s; by period; 60 bind- with baseline PBS-T, association The in establish period. tips an s; rinse dissociation during 180 follows: a buffer as during was same well protocol washing the ing from the in to ranging spike returned concentrations nM then at as 100 solutions used to spike be 7.4; 0 the pH to PBS-T, to 7.4, in exposed washed pH were separately (PBS-T), tips streptavidin Tween-20 bovine Antigen-bound 0.05% 0.2% antigen. with the and (PBS) saline (BSA) and buffered albumin phosphate system in serum RED96 nM 10 Octet to and variants an diluted ACE2 were using Biotinylated sequences ForteBio). temperature (Pall gene tips room biosensor ACE2 present streptavidin-coated at microplate. out is the carried spike were in in and listed solution are interaction, in mutations biotin–streptavidin analyte the a transparent BLI. as optically by an Using to tip tethered Spike is biosensor variant to ACE2 biotinylated Affinity the ments, Binding of Determination from The energies scored. interaction was pairwise structure used. whole was cross-interface was final trials The summed interface 20 the 493. the redesigned and and of the 455, minimized, lowest for to and 453 solution to repacked 417, lowest-energy 494 again residues 37 and the RBD 493, and in and ACE2 492, for 36, complex 38 allowed 456, amino were 34, to 455, atoms change 30 33, backbone 453, of residues to 452, 32, positions the 418, 38 29, in 417, Changes and residues repack. 416, residues 35, ACE2 RBD allowing 31, A to and while 30, angles. applied identities was residues torsion (28) acid chain ACE2 Moves) side neighboring (Coupled and algorithm allow backbone design isoleucine. interface backbone or the flexible valine to either applied to was H34 6 mutagenesis. mutated within saturation first computational Residues we the simulations, from these H34 In favorable to energetically experi- least mutations for and most constructs point Mutations. the select incorporated H34I to that models or testing of mental H34V sets additional Incorporating two Residues generated We Interface ACE2 of Redesign with comparison for used was value. interface trials WT five the the pair- cross-interface from summed energies the interaction of lowest wise the and the protocol, five energy complex; this modeled interface using was the times mutation the point in Each and residue bonds. bonds; hydrogen a cross-interface hydrogen from of cross-interface energy of average number the total interface; the of side ◦ mrhln)taeufncai MS ufr al n 10 and NaCl, M 1 buffer, (MES) acid -morpholino)ethanesulfonic 2 B,p .,t ocnrtosrnigfo o3 to 2 from ranging concentrations to 7.4, pH PBS, µL o80 to C eemxdi 6wl lt.Fursec nraeoe iewas time over increase Fluorescence plate. 96-well a in mixed were m,app ◦ sn aeo 1 of rate a using C a eemndt etetmeauea hc 0 of 50% which at temperature the be to determined was , fteitraewr eakd n minimization and repacked, were interface the of A ˚ lcrcmeetEY0 eepeae ythe by prepared were EBY100 Electrocompetent fnt measurements Affinity . S1 Appendix Appendix, SI oaayesqecs lsiswr sltdfrom isolated were plasmids sequences, analyze To IAppendix SI ◦ n 80 and C yrlsso (7-methoxycoumarin-4- of Hydrolysis ◦ e iue Dsetafo 200 from spectra CD minute. per C 2 gons ffit) of (goodness a ulmethods. full has ◦ c-P-N n5 mM 50 in Mca-APK-DNP µM .Mligcredt were data curve Melting C. IAppendix SI aho solutions of each µL norBIexperi- BLI our In > 0.90. .Melt- µM. a full has µM sas iu tc a iue o3t 5 to 3 to diluted neutralization was For stock (Promega). virus System determined Assay assays, was Luciferase infection Bright-Glo viral Cellular the h. indicating using 60 reporter 10,000 for virus at luciferase stock D10 seeded of of series was expression with dilution filtration HEK-ACE2 twofold and replaced with batch, infected harvest virus and was before cells each h solution titer 48 To for transfection supernatants. propagated of the was a HEK- virus h, the with into and 24 plasmids pseudovirus media, transfecting After spike by cells. (Dulbecco’s prepared Briefly, 293T was media [FBS]). gene serum D10 reporter heat- University, luciferase 10% bovine in + Stanford solution fetal cultured Kim, penicillin/streptomycin inactivated 1% Peter were + of medium cells Eagle laboratory modified HEK-ACE2 the from CA. plas- Pseudovirus gift Stanford, (54). a described were previously as mids conducted were Assay. assays virus Neutralization Virus Pseudotyped SARS-CoV-2 mna ehd,spotn als n uprigfiue r vial in available are figures Appendix supporting SI and tables, supporting methods, imental Information. Supporting reagent. the GloMax adding a after with min 10 recorded (Promega) was by GM3510 luminescence mixed Model which Explorer were after Samples plates, the instructions. shaking manufacturer’s the 100 following mixing in strate) after (ATP) assayed 100 triphosphate with were adenosine media lysates of Cells quantitation cells. for cultured used was (Promega) Assay. Cytotoxicity the h. and 24 SARS-CoV- of resources), was instead h assay (BEI 16 the 2019-nCoV/USA-WA1/2020 was in duration isolate infection used clinical strain clinical virus the 2 California, note, of University Of the Francisco. at San (15) described previously as performed assays 3. S13 Level Fig. Biosafety Appendix, at SI Assays Neutralization SARS-CoV-2 Additional and forward following PCR: The for CAATGGTTTAACAGGCACAGG-3 control. used were internal AGGAGTATG-3 pairs the primer as reverse human using transcript method 94 2(−∆∆CT) RNA of the cycles using 45 calculated were Detec- conditions PCR 55 cycling Real-Time s, Touch 30 The Green CFX96 (Bio-Rad). SYBR the System PerfeCTa in tion with BioSciences) 1 performed (Quanta man- to was SuperMix the 0.5 qRT-PCR to according using protocol. (Promega) ufacturer’s Transcriptase transcribed manufacturer’s Reverse reverse the ImProm-II and was following RNA RNA (Macherey-Nagel) Total kit protocol. RNA NucleoSpin the Assay. qRT-PCR SARS-CoV-2 uninfected qPCR. from by supernatant quantitation culture viral the for with collection VeroE6. incubated 37 lysates at were cell incubated cells by were Mock followed cells h and 24 well, for cells each added, was to proteins added the with were medium culture h Complete 1 PBS. for with proteins twice the with 0.1 of 37 (MOI) at infection of multiplicity 37 the and at at (Gibco) infected h FBS (SARS-CoV-2/CANADA/VIDO 3% 1 with SARS-CoV-2 for supplemented and media preincubated of proteins fresh in antibody) mixed isolate were (anti-GFP 01/2020) clinical control or Canadian blocking the 3, level 3. biosafety Level 1.2 At at plate Biosafety 96-well a at in plated Assay Neutralization replicates SARS-CoV-2 biological four preparations). variant to ACE2 two different and from (repeated stocks time) replicates virus values same technical different (using average eight the IC50 to at control. four run blocker using experiments no calculated the were of SDs value and average luminescent Assay the the Luciferase to normalizing Bright-Glo signal by the determined 37 was using at Neutralization measured h (Promega). was 60 signal for luciferase out lular carried 37 was at Infection h 1 for incubated 80 was solution blocker and 3× of 3× at at prepared 40 seeded were in cells well HEK-ACE2 per on cells performed 10,000 were assays neutralization dovirus ftevrsadbokriouu eetaserdt E-C2cells. HEK-ACE2 to transferred were inoculum blocker and virus the of µL ◦ n %CO 5% and C lce n 50 and blocker ◦ o 0s n 68 and s, 60 for C . 0 frcntttdClTtrGoRaet(ufrpu sub- plus (buffer Reagent CellTiter-Glo reconstituted of µL n 5 and 2 et h i a eoe,adteclswr washed were cells the and removed, was mix the Next, . h elie-l uiecn elVaiiyAssay Viability Cell Luminescent CellTiter-Glo The ocnrto nD0mda n9-elfra,50 format, 96-well In media. D10 in concentration eegnrtdfo ieSR-o- neutralization SARS-CoV-2 live from generated were 0 fvrswr ie nec el n h virus the and well, each in mixed were virus of µL -GCATTTGCGGTGGACGAT-3 ealdcmuainlmtos diinlexper- additional methods, computational Detailed fD0 odtrieI5,bokrds series dose blocker IC50, determine To D10. of µL ◦ o N nlss oa N a xrce using extracted was RNA total analysis, RNA For ◦ o 0s eeepeso fl hne was change) (fold expression Gene s. 20 for C .Teclswr ahdoc ihPSand PBS with once washed were cells The C. × 0 10 n 5 and 4 el e eladicbtdovernight. incubated and well per cells 0 -CTCAAGTGTCTGTGGATCACG-3 × ◦ ,a hc on h intracel- the point which at C, β 10 atn5 -actin NSLts Articles Latest PNAS 5 uiecneuis Pseu- units. luminescence ◦ 0 .Atrpreincubation, After C. ASCV2sie5 spike SARS-CoV-2 , suoye reporter Pseudotyped 0 -TGGATCAGCAAGC- eo6clswere cells VeroE6 β atnmessenger -actin ◦ fcomplete of µL n %CO 5% and C ftotal of µg eut in Results | ◦ f10 of 9 for C 0 (2). µL 0 2 -

BIOPHYSICS AND COMPUTATIONAL BIOLOGY Data Availability. All study data are included in the article and SI Appendix. Laboratory for Cell Analysis, which is supported by National Cancer Insti- tute Cancer Center Support Grant P30CA082103. A.G. was supported by ACKNOWLEDGMENTS. We thank Jamie Byrnes, Susanna Elledge, mem- NIH Grant 1K99GM135529. I.L. and N.J.R. were supported by NSF Graduate bers of the laboratory of T.K., and the entire COVID-19 team in the Research Fellowships. Research in the laboratory of J.V.R. was supported by laboratory of J.A.W. for helpful discussions and support. We acknowl- Rockefeller University and NIH Grant U19AI111825. A.P.W. was supported by edge the Chan Zuckerberg Biohub scientists, particularly John Pak, for NIH Grant DP2 OD022552. S.A.L. is a Merck Fellow of the Helen Hay Whitney plasmids to express SARS-CoV-1 and HCoV-NL63 RBDs; Dr. Peter Kim Foundation. X.X.Z. was supported by a Merck Fellowship from Damon Run- at Stanford University for the plasmids for pseudotyped lentivirus; and yon Cancer Research Foundation Grant DRG-2297-17. Research in the labo- the laboratory of Florian Krammer for plasmids to express the full- ratory of T.C.H. was supported by the Canadian Institutes of Health Research length SARS-CoV-2 spike protein. We also valued helpful discussions with and the Li Ka Shing Institute of Virology. T.K. was supported by funding from Dr. Diane Barber at the University of California, San Francisco (UCSF); the Chan Zuckerberg Biohub Investigator Program and a COVID-19 grant Dr. Sam Lai at the University of North Carolina; and Drs. Ho Cho, from the UCSF Program for Breakthrough Biomedical Research (PBBR). Hari Hariharan, and Henry Chan at Bristol Myers Squibb. We thank J.A.W. is supported by National Cancer Institute Grant R35 GM122451-01 Darryl Falzarano of the Vaccine and Infectious Disease Organization– and Fast Grants from Emergent Ventures 2154, grants from Chan Zuckerberg International Vaccine Center, University of Saskatchewan for providing the Biohub and UCSF PBBR, and funding from Harrington Discovery Institute SARS-CoV-2 strain for this work. Cell sorting was performed at the UCSF Grant GA33116.

1. J. H. Beigel et al., Remdesivir for the treatment of Covid-19: Preliminary report. N. 30. S. Lim, J. E. Glasgow, M. Filsinger Interrante, E. M. Storm, J. R. Cochran, Dual dis- Engl. J. Med. 383, 994 (2020). play of proteins on the yeast cell surface simplifies quantification of binding 2. P. Zhou et al., A pneumonia outbreak associated with a new coronavirus of probable interactions and enzymatic bioconjugation reactions. Biotechnol. J. 12, 1600696 bat origin. Nature 579, 270–273 (2020). (2017). 3. R. Shi et al., A human neutralizing antibody targets the receptor-binding site of SARS- 31. M. S. Kariolis et al., An engineered Axl ‘decoy receptor’ effectively silences the Gas6- CoV-2. Nature 584, 120–124 (2020). Axl signaling axis. Nat. Chem. Biol. 10, 977–983 (2014). 4. Y. Wu et al., A noncompeting pair of human neutralizing antibodies block COVID-19 32. Z. Liu et al., Composition and divergence of coronavirus spike proteins and host ACE2 virus binding to its receptor ACE2. Science 368, 1274–1278 (2020). receptors predict potential intermediate hosts of SARS-CoV-2. J. Med. Virol. 9, 595– 5. A. Baum et al., Antibody cocktail to SARS-CoV-2 spike protein prevents rapid 601 (2020). mutational escape seen with individual antibodies. Science 369, 1014–1018 (2020). 33. H. Mou et al., Mutations from bat ACE2 orthologs markedly enhance ACE2-Fc neu- 6. D. F. Robbiani et al., Convergent antibody responses to SARS-CoV-2 in convalescent tralization of SARS-CoV-2. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7337384/ individuals. Nature 584, 437–442 (2020). (30 June 2020). 7. C. O. Barnes et al., Structures of human antibodies bound to SARS-CoV-2 spike reveal 34. R. Yan et al., Structural basis for the recognition of SARS-CoV2 by full-length human common epitopes and recurrent features of antibodies. Cell 182, 828–842.e16 (2020). ACE2. Science 367, 1444–1448 (2020). 8. W. Li et al., Rapid selection of a human monoclonal antibody that potently neu- 35. D. Wrapp et al., Cryo-EM structure of the 2019-nCoV spike in the prefusion tralizes SARS-CoV-2 in two animal models. https://www.biorxiv.org/content/10.1101/ conformation. Science 367, 1260–1263 (2020). 2020.05.13.093088v2 (2 June 2020). 36. T. Zhou et al., Cryo-EM structures delineate a pH-dependent switch that medi- 9. J. Huo, A. Le Bas, R. R. Ruza, H. M. E. Duyvesteyn, Neutralizing nanobodies bind SARS- ates endosomal positioning of SARS-CoV-2 spike receptor-binding domains. http:// CoV-2 spike RBD and block interaction with ACE2. Nat. Struct. Mol. Biol. 27, 846–854 biorxiv.org/lookup/doi/10.1101/2020.07.04.187989 (31 July 2020). (2020). 37. S. Park et al., Limitations of yeast surface display in engineering proteins of high 10. S. Miersch et al.. Synthetic antibodies neutralize SARS-CoV-2 infection of mammalian thermostability. Protein Eng. Des. Sel. 19, 211–217 (2006). cells. https://doi.org/10.1101/2020.06.05.137349 (10 June 2020). 38. M. C. Julian et al., Co-evolution of affinity and stability of grafted 11. C. Lei et al., Neutralization of SARS-CoV-2 spike pseudotyped virus by recombinant amyloid-motif domain antibodies. Protein Eng. Des. Sel. 28, 339–350 ACE2-Ig. Nat. Commun. 11, 2070 (2020). (2015). 12. M. Haschke et al., Pharmacokinetics and pharmacodynamics of recombinant human 39. J. L. Guy, R. M. Jackson, H. A. Jensen, N. M. Hooper, A. J. Turner, Identification of crit- angiotensin-converting enzyme 2 in healthy human subjects. Clin. Pharmacokinet. 52, ical active-site residues in angiotensin-converting enzyme-2 (ACE2) by site-directed 783–792 (2013). mutagenesis. FEBS J. 272, 3512–3520 (2005). 13. A. Khan et al., A pilot clinical trial of recombinant human angiotensin-converting 40. P. J. M. Brouwer et al., Potent neutralizing antibodies from COVID-19 patients define enzyme 2 in acute respiratory distress syndrome. Crit. Care 21, 234 (2017). multiple targets of vulnerability. Science 369, 643–650 (2020). 14. V. Monteil et al., Inhibition of SARS-CoV-2 infections in engineered human tissues 41. K. Wu, W. Li, G. Peng, F. Li, Crystal structure of NL63 respiratory coronavirus receptor- using clinical-grade soluble human ACE2. Cell 181, 905–913.e7 (2020). binding domain complexed with its human receptor. Proc. Natl. Acad. Sci. U.S.A. 106, 15. I. Lui et al., Trimeric SARS-CoV-2 spike interacts with dimeric ACE2 with limited intra- 19970–19974 (2009). spike avidity. https://doi.org/10.1101/2020.05.21.109157 (21 May 2020). 42. N. Wang et al., Structure of MERS-CoV spike receptor-binding domain complexed 16. A. C. Walls et al., Structure, function, and antigenicity of the SARS-CoV-2 spike with human receptor DPP4. Cell Res. 23, 986–993 (2013). glycoprotein. Cell 181, 281–292.e6 (2020). 43. C. Huang, Receptor-Fc fusion therapeutics, traps, and MIMETIBODY technology. Curr. 17. J. Lan et al., Structure of the SARS-CoV-2 spike receptor-binding domain bound to the Opin. Biotechnol. 20, 692–699 (2009). ACE2 receptor. Nature 581, 215–220 (2020). 44. L. T. Dang et al., Receptor subtype discrimination using extensive shape complemen- 18. D. Pinto et al., Cross-neutralization of SARS-CoV-2 by a human monoclonal SARS-CoV tary designed interfaces. Nat. Struct. Mol. Biol. 26, 407–414 (2019). antibody. Nature 583, 290–295 (2020). 45. J. Hou et al., Design of a superior cytokine antagonist for topical ophthalmic use. 19. Y. Meng et al., A highly conserved cryptic epitope in the receptor binding domains of Proc. Natl. Acad. Sci. U.S.A. 110, 3913–3918 (2013). SARS-CoV-2 and SARS-CoV. Science 368, 630–633 (2020). 46. J. B. B. Ridgway, L. G. Presta, P. Carter., ‘Knobs-into-holes’ engineering of antibody 20. X. Chi et al., A neutralizing human antibody binds to the N-terminal domain of the CH3 domains for heavy chain heterodimerization. Protein Eng. Des. Sel. 9, 617–621 Spike protein of SARS-CoV-2. Science 369, 650–655 (2020). (1996). 21. J. Sui et al., Effects of human anti-spike protein receptor binding domain antibodies 47. E.-M. Strauch et al., Computational design of trimeric influenza-neutralizing pro- on severe acute respiratory syndrome coronavirus neutralization escape and fitness. teins targeting the hemagglutinin receptor binding site. Nat. Biotechnol. 35, 667–671 J. Virol. 88, 13769–13780 (2014). (2017). 22. J. Shang et al., Structural basis of receptor recognition by SARS-CoV-2. Nature 581, 48. W. T. Shearer et al., Recombinant CD4-IgG2 in human immunodeficiency virus 221–224 (2020). type 1–infected children: Phase 1/2 study. J. Infect. Dis. 182, 1774–1779 23. Q. Wang et al., Structural and functional basis of SARS-CoV-2 entry by using human (2000). ACE2. Cell 181, 894–904.e9 (2020). 49. J. B. Case et al., Neutralizing antibody and soluble ACE2 inhibition of a replication- 24. E. Procko, The sequence of human ACE2 is suboptimal for binding the S spike pro- competent VSV-SARS-CoV-2 and a clinical isolate of SARS-CoV-2. Cell Host Microbe tein of SARS coronavirus 2. http://biorxiv.org/lookup/doi/10.1101/2020.03.16.994236 28, 475–485.e5 (2020). (11 May 2020). 50. X. Miao et al., A novel biparatopic antibody-ACE2 fusion that blocks SARS-CoV- 25. F. Li, W. Li, M. Farzan, C. S. Harrison, Structure of SARS coronavirus spike receptor- 2 infection: Implications for therapy. https://doi.org/10.1101/2020.06.14.147868 (15 binding domain complexed with receptor. Science 309, 1864–1868 (2005). June 2020). 26. T. Kortemme, D. Baker, A simple physical model for binding energy hot spots in 51. C. L. Yeager et al., Human aminopeptidase N is a receptor for human coronavirus protein–protein complexes. Proc. Natl. Acad. Sci. U.S.A. 99, 14116–14121 (2002). 229E. Nature 357, 420–422 (1992). 27. T. Kortemme, D. E. Kim, D. Baker. Computational alanine scanning of protein-protein 52. L. Benatuil, J. M. Perez, J. Belk, C.-M. Hsieh, An improved yeast transformation interfaces. Sci. STKE 2004, pl2 (2004). method for the generation of very large human antibody libraries. Protein Eng. Des. 28. N. Ollikainen, M. R. de Jong, T. Kortemme, Coupling protein side-chain and backbone Sel. 23, 155–159 (2010). flexibility improves the re-design of protein-ligand specificity. PLoS Comput. Biol. 11, 53. M. V. Singh, P. A. Weil, A method for plasmid purification directly from yeast. Anal. e1004335 (2015). Biochem. 307, 13–17 (2002). 29. Y. Li et al., Potential host range of multiple SARS-like coronaviruses and an 54. K. H. D. Crawford et al., Protocol and reagents for pseudotyping lentiviral par- improved ACE2-Fc variant that is potent against both SARS-CoV-2 and SARS-CoV-1. ticles with SARS-CoV-2 spike protein for neutralization assays. Viruses 12, 513 http://biorxiv.org/lookup/doi/10.1101/2020.04.10.032342 (11 April 2020). (2020).

10 of 10 | www.pnas.org/cgi/doi/10.1073/pnas.2016093117 Glasgow et al. Downloaded at UCSF LIBRARY on October 28, 2020