N-terminal acetylation (NTA) is an irreversible protein modification that predominantly occurs co-translationally on eukaryotic nascent chains emerging from the ribosome exit tunnel (Aksnes et al., 2019). This modification occurs on ~80% of human proteins (Aksnes et al., 2016) and impacts several protein functions including complex formation (Scott et al., 2011; Monda et al., 2013; Yang et al., 2013; Arnaudo et al., 2013; Gao et al., 2016), protein localization (Behnia et al., 2004; Setty et al., 2004; Dikiy and Eliezer, 2014; Miotto et al., 2015; Forte et al., 2011), and the N-end rule for protein degradation (Hwang et al., 2010; Shemorry et al., 2013; Park et al., 2015). NTA is catalyzed by a group of enzymes called N-terminal acetyltransferases (NATs), which belong to the Gcn5-related N-acetyltransferase (GNAT) family of enzymes. In humans, seven NATs have been identified to date: NatA, NatB, NatC, NatD, NatE, NatF, and NatH (Aksnes et al., 2019). NatA, NatB and NatC are responsible for the majority of NTA (Starheim et al., 2012). NatA and NatB are heterodimeric complexes, each with a distinctive catalytic subunit (NAA10 in NatA and NAA20 in NatB; Starheim et al., 2008) and a unique auxiliary subunit (NAA15 in NatA and NAA25 in NatB; Arnesen et al., 2005). NatC is a heterotrimeric complex that contains a catalytic subunit (NAA30) and two auxiliary subunits (NAA35 and NAA38; Starheim et al., 2009). Structural and biochemical studies of NatA reveal that the auxiliary subunit plays an important allosteric role in substrate binding specificity and catalysis (Liszczak et al., 2013) and also contributes to ribosome binding during translation (Magin et al., 2017; Knorr et al., 2019). NatA, NatB, and NatC exhibit distinguishable substrate specificity mainly toward the first two residues of the nascent chain N-termini. NatA accounts for 38% of the human N-terminal acetylome, acetylating small N-terminal residues after removal of the initial methionine residue (Arnesen et al., 2009), while NatB modifies N-termini with sequences of MD-, ME-, MN-, and MQ- (Van Damme et al., 2012; Van Damme et al., 2012). NatC/E/F have overlapping substrates, acting on N-terminal methionine when it is followed by several residues excluding D, E, N, and Q (Arnesen et al., 2009; Van Damme et al., 2016; Tercero et al., 1993; Evjenth et al., 2009; Van Damme et al., 2011; Støve et al., 2016; Liszczak et al., 2011). When another catalytic subunit (NAA50) binds to NatA, a dual enzyme complex NatE is formed (Gautschi et al., 2003; Deng et al., 2020), with catalytic crosstalk between NAA10 and NAA50 (Deng et al., 2020; Deng et al., 2019). We recently demonstrated that both NAA50, and a protein with intrinsic NatA inhibitory activity - Huntingtin-interacting protein K (HYPK; Gottlieb and Marmorstein, 2018; Weyer et al., 2017; Arnesen et al., 2010), can bind to NatA simultaneously to form a larger tetrameric complex (Deng et al., 2020). NatD and NatH are highly selective enzymes with restricted substrates, displaying activity toward H4/H2A and N-terminally processed actin, respectively (Goris et al., 2018; Drazic et al., 2018; Song et al., 2003). The unique localization of NatF to the Golgi membrane demonstrates NTA can occur post-translationally in some cases (Aksnes et al., 2015).

NatB is conserved from yeast to human in both complex composition and in its substrate specificity profile (Starheim et al., 2012). In Saccharomyces cerevisiae, the deletion of NatB subunits produces more severe phenotypes compared to the knockout of NatA or NatC subunits. Deletion of either NAA20 or NAA25 leads to similar phenotypes including slower growth rate, diminished mating, defects in actin cable formation, and aberrant mitochondrial and vacuolar inheritance (Polevoda et al., 2003). These observations suggest that the proper function of actin and tropomyosin requires NTA by the intact NatB complex (Polevoda et al., 2003). In humans, disruption of NatB (hNatB) by knockout leads to defects in proper actin cytoskeleton structure, cell cycle progression, and cell proliferation (Starheim et al., 2008; Ametzazurra et al., 2008; Ametzazurra et al., 2009; Neri et al., 2017). In addition, hNatB is upregulated in human hepatocellular carcinoma (Ametzazurra et al., 2008), where it has been suggested as a potential therapeutic target as silencing of this complex can block cell proliferation and tumor formation (Neri et al., 2017). hNatB-mediated NTA of α-synuclein (αSyn) has been shown to increase αSyn stability and lipid binding, and to reduce aggregation capacity (Dikiy and Eliezer, 2014; Watson and Lee, 2019; Mason et al., 2016; Maltsev et al., 2012; Trexler and Rhoades, 2012; Fernández and Lucas, 2018; Fauvet et al., 2012; Kang et al., 2012; Iyer et al., 2016). Since αSyn is a key protein in Parkinson's disease (PD; Halliday et al., 2011; Spillantini et al., 1998), hNatB might play an indirect role in PD pathogenesis in vivo as supported by a recent study (Vinueza-Gavilanes et al., 2020). It was also recently demonstrated that NTA of αSyn increases its propensity for lipid membrane binding without altering its structural properties of the bound state (Runfola et al., 2020).

Compared to the comprehensive structural and biochemical characterization of NatA (Liszczak et al., 2013; Magin et al., 2017; Knorr et al., 2019; Deng et al., 2019; Gottlieb and Marmorstein, 2018; Weyer et al., 2017), the study of NatB has been limited, particularly in humans. Recently, the crystal structure of Candida albicans (Ca) NatB bound to a bisubstrate CoA-peptide conjugate was determined, providing important insights into substrate specificity and NTA by caNatB (Hong et al., 2017). However, hNAA20 and hNAA25 share only ~40% and~20% sequence identity with the Candida albicans homolog (Hong et al., 2017), respectively. Moreover, nearly all biological studies of NatB have been conducted in Saccharomyces cerevisiae (Lee et al., 2014; Caesar et al., 2006; Singer and Shaw, 2003), Arabidopsis (Ferrández-Ayela et al., 2013; Huber et al., 2020), mouse (Ohyama et al., 2012), and human (Starheim et al., 2008; Ametzazurra et al., 2008; Ametzazurra et al., 2009; Neri et al., 2017) as model organisms. As a result, the mode of human NatB-mediated catalysis and αSyn-specific NatB recognition remains unresolved. In this study, we report the 3.5 Å resolution cryo-electron microscopy (cryo-EM) structure of the ~130 KDa hNatB bound to a bisubstrate CoA-αSyn conjugate together with a structure-guided analysis of mutational effects on catalytic activity. This analysis reveals functionally important structural differences between hNaB and related NAT enzymes, as well as insights into the molecular mechanisms that define αSyn and related substrates that are recognized for hNatB-mediated N-terminal acetylation.

Since the identification of hNatB more than a decade ago, many studies have shown that it N-terminally acetylates important proteins such as actin, tropomyosin, CDK2, and α-Syn, and its function has connections to diseases such as hepatocellular carcinoma and Parkinson's disease (Starheim et al., 2008; Polevoda et al., 2003; Ametzazurra et al., 2008; Neri et al., 2017; Halliday et al., 2011; Spillantini et al., 1998). Despite its clear biological importance, hNatB-mediated NTA by hNatB remained poorly understood. Here we developed a CoA-αSyn conjugate hNatB inhibitor, determined the cryo-EM structure of CoA-αSyn inhibitor-bound hNatB, and carried out associated structure-guided mutagenesis and activity assays. This has led to the identification of functionally important differences with human NatA and C. albicans NatB. These studies have also provided evidence for important hNatB-specific elements responsible for αSyn recognition and N-terminal acetylation, providing direct implications for NatB recognition of other canonical substrate proteins.

Consistent with previous studies, we have demonstrated that hNatB acetylates a cognate ‘MD’ N-terminus and is unable to N-terminally acetylate non-cognate N-termini that are substrates for other NATs such as NatA, NatC, and NatE. We demonstrated for the first time that hNatB can acetylate an α-Syn peptide in vitro, directly linking hNatB to NTA of α-Syn. We have also demonstrated that αSyn peptides lacking the Met1 or both the Met1 and Asp2, do not serve as hNatB substrates, confirming the strict substrate specificity of hNatB. This is consistent with our structural model showing significant interactions between hNatB-NAA20 and both the first and second N-terminal residues of an αSyn peptide, with important but less extensive interactions with the third and fourth residues. This hierarchy of interactions likely explains how NatB enzymes can accommodate cognate substrates that diverge at positions three and four.

Here we have presented hNatB-αSyn interactions that can be used to rationalize the substrate specificity of hNatB: N-terminal sequences containing ‘MD-', ‘ME-', ‘MN-', and ‘MQ-'. αSyn-Met1 sits in a hydrophobic pocket that comfortably accommodates a methionine residue, whereas shorter sidechains or longer polar or charged sidechains would fit poorly (Figure 5B–C). The nature of this binding pocket is similar to the described hNAA50 recognition of Met1 (Liszczak et al., 2011; Figure 5B–C). Although both of hNAA50 and hNAA20 can N-terminally acetylate peptides with Met at the first position, no overlapping activity has been observed. This can be rationalized based on the chemical properties of the second residue in the cognate peptide. We find that the αSyn-Asp2 sidechain forms hydrogen bonds with the hNAA20 sidechains His73 and Thr75. These polar residues in the peptide binding site of hNAA20 would likely serve as poor acceptors of the largely hydrophobic residues targeted by hNAA50. The hNatB substrate client profile featuring D-, E-, N-, or Q-residues in position two is consistent with the mechanisms of substrate recognition observed in the binding pocket for αSyn-Asp2. The aliphatic regions of each of these sidechains (D, E, N, Q) would all benefit from the extensive hNatB van der Waals interactions surrounding the aliphatic region for αSyn-Asp2 (Tyr27, His73, Thr75, Phe111, and Tyr138). This second residue would also form a hydrogen bond interaction with His73 and Thr75, which may accommodate the carboxyl sidechains of both the shorter D- and N- and longer E- and Q- sidechains. Notably, His73 and Thr75 are strictly conserved from yeast to man (Figure 5 and Figure 2—figure supplement 3). In contrast, shorter polar or nonpolar sidechains would less efficiently fill the pocket for residue two, while larger polar or charged sidechains would likely result in steric clashes. In agreement with this, we have demonstrated that H73A mutation has a severe impact on hNatB catalysis (Table 1).

The hNatB/CoA-αSyn structure has implications for the mode of hNatB catalysis. While previous studies have suggested that hNAA50-Tyr31 plays an important role in catalysis, mutation of the corresponding hNaa20 residue, Tyr27, had minimal effects on hNatB kinetic parameters. Strikingly, our mutational analysis has identified the functional importance of hNatB-NAA20 residues His73, Asn116, and Tyr123, although Tyr123 is the only residue that is in position to play a catalytic role (Figure 5A). Specifically, Tyr123 is in position to play a catalytic role, potentially as a general base and/or acid, through a bridging water molecule (although a water molecule is not visible at the current resolution). Interestingly, hNAA50 contains a tyrosine residue at the same position (hNAA50-Tyr124), although the mechanistic significance of this tyrosine residue has not yet been described (Liszczak et al., 2011). It would be of interest to determine if hNAA50-Tyr124 also plays an important catalytic role, similar to the corresponding hNAA20-Tyr123 of hNatB.

The biological importance of hNatB and its connection to various disease processes highlights it as an important target for probe and inhibitor development. Indeed, a recent study highlights hNatB as a therapeutic target for αSyn toxicity (Vinueza-Gavilanes et al., 2020). Our development of a CoA-αSyn conjugate bisubstrate with an IC₅₀ of ~1.6 µM represents a step in this direction, although the structural information provided here could further aid to the rational development of more drug-like hNatB inhibitors with possible therapeutic applications.

Cryo-EM data submissions to the Protein Data Bank (PDB code 6VP9), Electron Microscopy Data Bank (EMD code 21307) and Electron Microscopy Public Image Archive (EMPIAR-10477).

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Acceptance summary:

This work reports a high resolution cryoEM structure of human NatB, whose N-terminal acetylation activity has been linked to both Parkinson's disease and hepatocellular carcinoma. Compared with other NAT complexes, little is known about hNatB. These studies reveal functional features of hNatB, key determinants for α-synuclein N-terminal acetylation, and important residues for substrate-specific recognition and acetylation. These results have implications for the development of drug-like hNatB inhibitors with possible therapeutic applications.

Decision letter after peer review:

Thank you for submitting your article "Molecular Basis for N-terminal Α-Synuclein Acetylation by Human NatB" for consideration by eLife. Your article has been reviewed by two peer reviewers, and the evaluation has been overseen by a Reviewing Editor and Huda Zoghbi as the Senior Editor. The following individual involved in review of your submission has agreed to reveal their identity: Sjors HW Scheres (Reviewer #1).

We would like to draw your attention to changes in our revision policy that we have made in response to COVID-19 (https://elifesciences.org/articles/57162). Specifically, we are asking editors to accept without delay manuscripts, like yours, that they judge can stand as eLife papers without additional data, even if they feel that they would make the manuscript stronger. Thus the revisions requested below only address clarity and presentation.

The two reviewers were positive about your submission, and we will be willing to accept it for publication subject to satisfactory responses to their comments below. N-terminal acetylation of α-synuclein is an area of interest. It is, for example, known to increase the affinity of α-synuclein for lipid membranes; in this context, the recent paper by Runfola et al. should be discussed.

Reviewer #1:

This paper describes a cryo-EM structure of human NatB in complex with a CoA-peptide with the N-terminal sequence of human α-synuclein, as well as complementing binding/activity assays with mutants that were designed based on the structure. The cryo-EM structure was done to good standards and the paper is very well written. I am therefore enthusiastic about publication in eLife and have only a few relatively minor comments:

"We therefore incorporated this sequence into a peptide substrate named "MDVF" for an in vitro acetyltransferase assay (see Materials and methods for the full sequence)." I thought this was a 4-residue peptide, but later found out it was longer. Why not just put the entire sequence here in the main text for improved clarity?

"among where the predicted first and second α-helices were built as poly-alanine due to a lack of resolvable side-chain density (Figure 4—figure supplement 1)." I had hoped to see some of the bad density for these helices in a supplemental figure. Actually, inspection of the map reveals that density is weak up to residue 146. This points to disorder or structural flexibility in this region, which should be explicitly mentioned in the main text. Did the authors try to perform focussed classification with signal subtraction (possibly keeping the orientations fixed) to select a subset of the 1M particles that would be better ordered in this region? Might be worth a try, as it may also provide insights in the nature of the flexibility in this region.

It would be good to have a figure of the cryo-EM density of the entire complex in a panel in one of the main figures. Currently, there are only a few panels with local zoomed-in views f the reconstructed cryo-EM density.

FSC curves between the refined PDB model and the cryo-EM are missing. Also, to show that the map was not overfitted, FSC_work and FSC_free curves (where one refines a perturbed model against one half-map and then calculates FSCs of that model against both half-maps) should be included.

The ResMap doesn't look right: I strongly doubt the local resolution in the N-terminal part of hNAA25 is 4.5A: it looks a lot worse. Perhaps it's just a matter of choosing the colour scale, or perhaps the authors could try RELION's own implementation of local resolution estimation.

"We demonstrated for the first time that hNatB can acetylate an α-Syn

peptide in vitro, directly linking hNatB to Parkinson disease." That is too strong: the structure does not provide a direct link to PD.

Cryo-EM processing: why was Bayesian polishing not performed? Also, with ~1M particles left, it could be that more classification after the polishing could further improve the map.

Cryo-EM processing: How was map post-processing (map sharpening) performed?

Reference Kimanius et al., 2016: better use the RELION-3 reference by Zivanov et al., 2018.

Reviewer #2:

Deng et al. present the structure and functional analysis of the human NatB protein, bound to CoA with an αSyn fragment. I only comment on the methodological aspects of the manuscript.

The method description in the main text is rather short. A Titan Krios with K3 was used, and Table 2 lists parameters. However, these are not sufficient to verify the quality of the work. For example, which software was used for data collection (EPU or SerialEM or other)? How many frames were used per video? What mode of the K3 was used (CDC or Counting)? The magnification is specified as 105kx, but with the 5micrometer pixel size of the K3 that would correspond to a pixel size on the sample of 0.476A at the sample level. However, the Table 2 lists a pixel size of 0.83A per pixel. Is that physical pixel or super-resolution pixel? In any case, the magnification value is probably wrong, and may be a historically originated software bug in the used Titan Krios? Or is that magnification valid for the Flu-screen in the Titan, which has nothing to do with the K3?

How many KDa is the molecular weight of the determined structure?

In addition to the model in the PDB, the raw data should be deposited in the EMPIAR and the reconstructed map should be deposited in the EMDB.

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

Thank you for resubmitting your work entitled "Molecular Basis for N-terminal Α-Synuclein Acetylation by Human NatB" for further consideration by eLife. Your revised article has been evaluated by Huda Zoghbi (Senior Editor) and a Reviewing Editor after consultation with the reviewers.

The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance, as outlined below:

Please confirm that in Figure 2—figure supplement 1, panel D, the model used for the 2 half-map curves was actually refined in one of the two half-maps, and then used for FSC against both half-maps. They should also indicate which of the two half-maps it was refined in. Currently, it reads (which indeed seems to be the case) that these are not the requested FSC_work and FSC_test curves, but that instead they have just used the model from the refinement against the final map to calculate a FSC curve against the two half-maps. That is not informative. The key is refinement in one half-map (which may be overfitted, but this would then show up in a lower FSC curve with the other half-map). This needs to be resolved.

The two reviewers were positive about your submission, and we will be willing to accept it for publication subject to satisfactory responses to their comments below. N-terminal acetylation of α-synuclein is an area of interest. It is, for example, known to increase the affinity of α-synuclein for lipid membranes; in this context, the recent paper by Runfola et al. should be discussed.

In the Introduction, a sentence is added to summarize the results from the recent manuscript by Runfola et al., which demonstrates the importance of N-terminal acetylation on the lipid membrane binding properties of a-synuclein.

Reviewer #1:

This paper describes a cryo-EM structure of human NatB in complex with a CoA-peptide with the N-terminal sequence of human α-synuclein, as well as complementing binding/activity assays with mutants that were designed based on the structure. The cryo-EM structure was done to good standards and the paper is very well written. I am therefore enthusiastic about publication in eLife and have only a few relatively minor comments:

"We therefore incorporated this sequence into a peptide substrate named "MDVF" for an in vitro acetyltransferase assay (see Materials and methods for the full sequence)." I thought this was a 4-residue peptide, but later found out it was longer. Why not just put the entire sequence here in the main text for improved clarity?

Full sequences for the peptide substrates used in the study are now indicated in the main text.

"among where the predicted first and second α-helices were built as poly-alanine due to a lack of resolvable side-chain density (Figure 4—figure supplement 1)." I had hoped to see some of the bad density for these helices in a supplemental figure. Actually, inspection of the map reveals that density is weak up to residue 146. This points to disorder or structural flexibility in this region, which should be explicitly mentioned in the main text. Did the authors try to perform focussed classification with signal subtraction (possibly keeping the orientations fixed) to select a subset of the 1M particles that would be better ordered in this region? Might be worth a try, as it may also provide insights in the nature of the flexibility in this region.

We added a sentence in the main text stating “The N terminal region (residue 1-164) displays relatively weak EM density compared to other regions, suggesting that it is relatively flexible (Figure 2—figure supplement 2).”

While we agree that further focused classification might improve the local resolution of the N-terminal region, we have chosen not to do this since this region does not appear to mediate biologically important interactions in our structure and would therefore not alter the main conclusions of our study. Nonetheless, the raw cryo-EM data have been deposited in the EMPIAR database so other researchers can access and analyze this dataset further if an interest arises.

It would be good to have a figure of the cryo-EM density of the entire complex in a panel in one of the main figures. Currently, there are only a few panels with local zoomed-in views f the reconstructed cryo-EM density.

We now show the fit of the complex into the cryo-EM density in Figure 2—figure supplement 2, panel D. This figure also illustrates the relatively poor density of the N-terminal region of hNatB.

FSC curves between the refined PDB model and the cryo-EM are missing. Also, to show that the map was not overfitted, FSC_work and FSC_free curves (where one refines a perturbed model against one half-map and then calculates FSCs of that model against both half-maps) should be included.

We have now calculated the FSC curves with the refined PDB model against each half map and the summed map, and show these curves in Figure 2—figure supplement 1 panel D.

The ResMap doesn't look right: I strongly doubt the local resolution in the N-terminal part of hNAA25 is 4.5A: it looks a lot worse. Perhaps it's just a matter of choosing the colour scale, or perhaps the authors could try RELION's own implementation of local resolution estimation.

We thank the review for pointing this out. The previous local resolution map likely did not seem correct because most of the regions of NAA25, except for the N-terminal region (1-164), has a resolution beyond 4.5 Å. We have re-run a ResMap in Relion with different color scale and have illustrated a new local resolution map in Figure 2—figure supplement 1, panel B.

"We demonstrated for the first time that hNatB can acetylate an α-Syn

peptide in vitro, directly linking hNatB to Parkinson disease." That is too strong: the structure does not provide a direct link to PD.

We have softened this statement to “directly linking hNatB to NTA of α-Syn”

Cryo-EM processing: why was Bayesian polishing not performed? Also, with ~1M particles left, it could be that more classification after the polishing could further improve the map.

We attempted particle polishing on this dataset, but this surprisingly resulted in artifactual density in the resulting map. We believe that this was due to some small defects in the K3 camera during data collection, which corrupted the particle polishing process. We therefore were unable to exploit particle polishing to improve the resolution of our structure. Instead, two rounds of CTF refinement were performed to achieve the current resolution for model building. This is described in the Materials and methods section of the manuscript.

Cryo-EM processing: How was map post-processing (map sharpening) performed?

This is now explained in the Materials and methods section as follows: After refinement, a mask was created in Relion with an initial binarization threshold of 0.005, covering the protein complex and extending the binary map and soft-edge by 12 pixels. The map was sharpened with the created mask by estimating B-factor automatically in Relion.

Reference Kimanius et al., 2016: better use the RELION-3 reference by Zivanov et al., 2018.

This reference (Zivanov et al., 2018) is now added.

Reviewer #2:

Deng et al. present the structure and functional analysis of the human NatB protein, bound to CoA with an αSyn fragment. I only comment on the methodological aspects of the manuscript.

The method description in the main text is rather short. A Titan Krios with K3 was used, and Table 2 lists parameters. However, these are not sufficient to verify the quality of the work. For example, which software was used for data collection (EPU or SerialEM or other)? How many frames were used per video? What mode of the K3 was used (CDC or Counting)? The magnification is specified as 105kx, but with the 5micrometer pixel size of the K3 that would correspond to a pixel size on the sample of 0.476A at the sample level. However, the Table 2 lists a pixel size of 0.83A per pixel. Is that physical pixel or super-resolution pixel? In any case, the magnification value is probably wrong, and may be a historically originated software bug in the used Titan Krios? Or is that magnification valid for the Flu-screen in the Titan, which has nothing to do with the K3?

We have now added more detail of how the data were collected in the Materials and methods section. With regard to the pixel size, we now indicate that while we used the super resolution mode with a pixel size of 0.415 Å /pixel, we binned the data twofold to 0.83 Å /pixel when motion correction was performed and all further data processing was based on the motion-corrected images with 0.83 Å /pixel.

How many KDa is the molecular weight of the determined structure?

We now indicate in the Introduction section that hNatB is ~130 KDa.

In addition to the model in the PDB, the raw data should be deposited in the EMPIAR and the reconstructed map should be deposited in the EMDB.

We have now deposited the raw data (Raw videos, picked-particle star file and others) into EMPIAR with access ID of EMPIAR-10477. This information is now added in Table 2. The model and map will be released when the manuscript is published, with access ID of PDB 6VP9, or EMD-21307.

[Editors' note: further revisions were suggested prior to acceptance, as described below.]

Please confirm that in Figure 2—figure supplement 1, panel D, the model used for the 2 half-map curves was actually refined in one of the two half-maps, and then used for FSC against both half-maps. They should also indicate which of the two half-maps it was refined in. Currently, it reads (which indeed seems to be the case) that these are not the requested FSC_work and FSC_test curves, but that instead they have just used the model from the refinement against the final map to calculate a FSC curve against the two half-maps. That is not informative. The key is refinement in one half-map (which may be overfitted, but this would then show up in a lower FSC curve with the other half-map). This needs to be resolved.

We thank the reviewer for pointing out this mistake. We have now refined the model in one of the independent half maps (in the new figure, we actually refined the model in half map 2), and then used the newly refined model to calculate the FSC curves against both independent half maps. The figure is now replaced with a new one, and the figure legend is updated to indicate which half map was used to refine in, to distinguish FSC_work and FSC_test.

Author details

1. Sunbin Deng

   1. Department of Chemistry, University of Pennsylvania, Philadelphia, United States
   2. Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing - original draft

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-7798-4317

2. Buyan Pan

   Department of Chemistry, University of Pennsylvania, Philadelphia, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

3. Leah Gottlieb

   1. Department of Chemistry, University of Pennsylvania, Philadelphia, United States
   2. Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States

   Contribution

   Conceptualization, Data curation, Investigation, Methodology, Writing - review and editing

   Competing interests

   No competing interests declared

4. E James Petersson

   1. Department of Chemistry, University of Pennsylvania, Philadelphia, United States
   2. Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States

   Contribution

   Conceptualization, Data curation, Supervision, Funding acquisition, Project administration, Writing - review and editing

   Competing interests

   No competing interests declared

5. Ronen Marmorstein

   1. Department of Chemistry, University of Pennsylvania, Philadelphia, United States
   2. Abramson Family Cancer Research Institute, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States
   3. Department of Biochemistry and Biophysics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, United States

   Contribution

   Conceptualization, Resources, Formal analysis, Supervision, Funding acquisition, Project administration, Writing - review and editing

   For correspondence

   marmor@upenn.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-4373-4752

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