Deep homology and design of proteasome chaperone proteins in Candidozyma auris

Domain: biology
Published: 2026-03-30
Editorial outcome: minor_revision

Abstract
A central tenet of biology is that protein structure mediates the sequence-function relationship. Recently, there has been excitement about the promise of advances in protein structure modeling to generate hypotheses about sequence-structure-function relationships. Here, we leverage structural similarity to identify rapidly evolving proteasome assembly chaperones and characterize their function in Candidozyma (Candida) auris. Despite extensive sequence divergence, we demonstrate conservation of function, corroborating that specific folds, and not sequences, are required for function. This theoretical premise suggests that protein structures with certain properties should be functionally interchangeable, even if they were not products of a common evolutionary history. To reduce this theory to practice, we performed structure-informed protein design, exploring sequence space that is not accessible via stepwise evolution, and mutated more than 40 residues in the Poc4 proteasome assembly chaperone to demonstrate that artificial proteins can rescue complex biological processes in the context of the whole cell. This sequence-structure-function relationship expands our ability to use structure to identify deep evolutionary relationships between proteins and generate hypotheses about gene function in non-model organisms. Overall, this helps to define and understand functional constraints on protein evolution, with important implications for both future protein design and retrospective function prediction.

Introduction
The causal relationship between sequence, structure, and function is central to our ability to assign function for newly discovered proteins and explore evolutionary variation based on inferred homology. While the importance of BLAST and other sequence similarity searches cannot be overstated, these approaches can fail to detect evolutionarily related proteins with high levels of sequence divergence1. However, since structure mediates the sequence-function relationship, signatures of shared evolutionary history are often better preserved at the level of structure than sequence2–4. These structurally-related but sequence distant proteins are often considered to be in the ‘twilight zone’1,4,5. Historically, homologous relationships of such proteins were difficult to identify at scale due to the challenges of protein structure determination, leading to their exclusion from functional genomic analyses. However, excluding proteins with low sequence identity can result in not just incomplete but systematically biased inferences about the composition and evolution of homologous systems. As an example, co-evolution analyses require an estimation of members of an orthogroup before calculating the evolutionary rate6. If rapidly evolving proteins are not included, the inferred identity and number of the coevolving units, and their respective rates of evolution, would be artefactually depressed.

Recent advances in computational protein structure prediction have enabled large-scale comparative structural analyses of proteins across broad swathes of evolution3,7–10. In turn, it has become possible to experimentally probe the constraints and flexibilities within which sequence-structure relationships evolve11–13. Studies of natural protein sequence variation show that multiple protein sequences—homologous or convergently evolved—often result in equivalent structures and thus similar function (Fig. 1A, points A to B). We can also examine functionally equivalent proteins to develop hypotheses about the structural requirements for function. In principle, such discoveries from testing such hypotheses should of de novo designed proteins that are imbued with the structural features needed to fulfill the biological requirements of the cell, even though they are disconnected from evolutionary history (Fig. 1A, points B to C)14.

Here, we explicitly test whether rapidly evolving protein-coding sequences predicted to encode similar structures result in similar functional phenotypes across evolutionary time. Such cases of structural conservation amidst sequence divergence are often viewed as cases of neutral evolution, where random sequence changes can accumulate between species because they do not result in the structural/functional changes that can then be selected for or against. As a representative case study, we examine components of proteasome assembly. Despite being involved in an essential, ubiquitously important process, we find that these assembly chaperone proteins vary considerably in their rate of evolution. In the non-model human fungal pathogen Candidozyma (Candida) auris, we identify and empirically validate a proteasome assembly chaperone that was previously undetectable by sequence because of its rapid evolution, but which retains structural signatures of homology. Disruptions of this protein in C. auris yield the same phenotype as disruption of its homologous counterparts in Saccharomyces cerevisiae, suggesting that the conservation in structure is sufficient to preserve function in proteasome assembly. Complementation of the C. auris mutant with the S. cerevisiae protein is sufficient to rescue growth, despite extensive sequence divergence. As this suggests that the folded structure of this protein may be sufficient to confer function, we use deep learning to design artificial proteasome chaperones to maintain the conserved structure and use these to rescue the C. auris mutant phenotype. This allows us to explore protein sequence space that was otherwise inaccessible due to epistatic constraints that would occur during stepwise evolution15,16. We then analyze the designed proteins to better characterize the structural determinants of function and the sequence determinants of structure. Our work demonstrates how modern computational methods, in combination with experimental characterization, can be used to explore the evolution of sequence-structure-function relationships and, from the insights gained, enable us to create functional molecules released from the constraints of evolutionary history.

Results
Structural homology in the absence of sequence homology predicts protein function
Structure-based similarity search is recognized to outperform sequence-based homology in retrospective benchmarks, and therefore structure-based homology search should enable better inferences of gene functions across large evolutionary distances where sequence-based methods fail17–21. These structure-based searches have been applied to specific classes of proteins but have not been fully explored at the genome scale, especially in C. auris. To examine this relationship, we compared the predictive power of Foldseek, a structure-based homology search algorithm, to BlastP, a sequence-based homology search algorithm, to detect orthologs for C. auris proteins amongst the proteins in the Swiss-Prot database (Fig. 1B, Supplementary Fig. 1A). As expected, we observed a high correlation between their respective bit-scores over the 5,008 genes that had predicted AlphaFold2 structures (Spearman Rank Correlation: 0.932, p-value < 0.0001). However, we identified 204 genes where structural homology may be able to predict function in the absence of sequence homology, as determined by significant Foldseek E-values and insignificant BlastP E-values. For example, the protein B9J08_002475 and its sequence orthologs are Metschnikowiaceae-lineage restricted (Fig. 1C) but have significant structural homology with the Aquarius family of RNA helicases that function in the U2 snRNP spliceosome (Supplementary Table 1) despite sharing less than 15% sequence identity. Similarly, B9J08_000767, which is a Candida-lineage restricted protein, has significant structural similarity to the Bem4 guanidine exchange factor (GEF) in S. cerevisiae but only 16.5% sequence identity (Fig. 1D, Supplementary Table 2). We are also able to leverage Foldseek against uncharacterized proteins present broadly throughout fungi, including B9J08_003970, which has structural similarity with mammalian long-chain fatty acid acyl-CoA synthetases 1, 5 and 6 (Fig. 1E, Supplementary Table 3).

During evolution, selection acts not just on single proteins but the entire functional unit of a protein complex6,22; therefore, we were particularly interested in the case of two proteins putatively involved in the highly coordinated and conserved process of proteasome assembly. We identified the uncharacterized protein B9J08_000884, with a similar structure to the Poc4 assembly chaperone protein, and B9J08_003917, which is annotated as a homolog of the Irc25 proteasome assembly chaperone (Supplementary Table 4)23–25. We will refer to these two proteins as Poc4 and Irc25, following nomenclature from S. cerevisiae. Proteins with structural similarity to Poc4 were widely present throughout Eukarya, and despite sequence identities below 20%, the overall topology of the protein domains is predicted to be conserved (Fig. 1F, Supplementary Fig. 1B). As the proteasome itself is highly conserved throughout Eukaryotes and has been implicated in human diseases such as neurodegeneration and cancer26, we decided to investigate the evolution and conservation of this assembly machinery further.

Sequence divergence in proteasome assembly chaperones
To better understand how distinct components of the proteosome might have evolved, we used amino acid and syntenic analysis to search for homologs of proteosome assembly components across fungi. The putative orthologs of Poc4 and Irc25 function as a heterodimer and mediate assembly of -subunits into the heptameric ring structure of the proteosome, interacting especially with the 5-subunit (Pup2), before dissociating during -subunit assembly (Fig. 2A)26. The Pba1-Add66 complex also contributes to -ring assembly around the Ump1 chaperone. We found that while the Pup2 proteasome subunit and the Ump1 assembly chaperone had detectable homologs throughout Saccharomycotina, the CTG clade lacked a clearly identifiable sequence that resembled the Poc4 proteins found in other yeast, and putative homologs of the other proteasome chaperones were at times only identifiable because of synteny (Fig. 2B). The similarity in structure between Irc25 and Poc4 and the human proteasome assembly chaperone protein PSMG3 also brings up the possibility that Poc4 and Irc25 are highly diverged paralogs.

The variable presence of different proteosome components suggested that the folding chaperones and core components may have different evolutionary rates from each other. To compare the extent of divergence among core proteins and folding chaperones, we used the putatively orthologous sequences from BlastP and inferred the maximum likelihood phylogeny describing the evolutionary history of each gene using the best-fit model of sequence evolution, as determined by Akaike information criterion (Supplementary Table 5, Supplementary Figs. 2A-C). The proteins investigated displayed vastly different rates of divergence, with the assembly chaperones showing rapid evolution. As expected, the evolutionary distance between Pup2 orthologs is much smaller than the difference between chaperone orthologs (Figs. 2C, E). The lack of mating and gene flow in the CTG clade can allow for rapid drift. However, this is not the only cause of rapid evolution of the chaperones as the higher rate of evolution among the chaperone proteins is not unique to any species lineage but is true across all taxa (Figs. 2D, E, Supplementary Fig. 3). Importantly, we also observe that Poc4 appears to be evolving faster than its co-chaperone Irc25 within the CTG clade (Figs. 2D,E, Supplementary Fig. 3D). One possible reason for this discrepancy in chaperone evolution rate is expression levels, as higher expression is generally associated with lower evolutionary rate27. Previously published RNAseq data show that Poc4 expression is much lower than other core particle assembly chaperones (Supplementary Fig. 4)28, but the translation rate is not known. To examine the possibility that POC4 is in a specifically mutagenic locus, we examined the sequence divergence of genes near POC4. We failed to observe high rates of sequence divergence among genes near the POC4 locus, suggesting that this divergence is not due to its presence in a mutational hotspot (Supplementary Fig. 5).

C. auris POC4 encodes a bona fide proteasome assembly chaperone
While we observed structural similarity to known Poc4 proteasome assembly chaperones, the extreme sequence divergence suggested that its role in proteasome assembly might not be preserved. Furthermore, while previous studies have identified structural conservation in the absence of sequence identity across large evolutionary distances, many of these predictions lack direct experimental evidence regarding the conservation of protein function. Proteins with highly conserved folds often display significant differences in catalytic activity and substrate specificity29,30. Therefore, to test whether C. auris Poc4 retained canonical interactions with the proteasome, we performed co-immunoprecipitation assays with an ALFA-tagged variant of Poc4 and the -subunits of the 20S core particle. We found this physical interaction was preserved (Fig. 3A and Supplementary Figs. 6A-B), suggesting that the capacity to act as an assembly chaperone had persisted in Poc4 even as its amino acid sequence changed beyond recognition.

Next, we directly characterized whether this physical interaction was involved in the same cellular functions. Disruption of proteasome function through genetic perturbations (e.g., deletion of Pre9 subunit) or pharmacological inhibition (e.g., MG-132 treatment) increased the level of ubiquitinated proteins within a cell (Fig. 3B). We reasoned that disruption of Poc4 should also produce these phenotypes. Consistent with our model, we observed increased total ubiquitinated proteins in Poc4 and Irc25 deletion strains relative to the wild-type AR0382 strain (Fig. 3B). MG-132 treatment had limited effects on fungal growth at permissive temperatures but significantly reduced growth at high temperatures across three fungal species (Fig. 3C), demonstrating a conserved connection between proteasome inhibition and thermotolerance across organisms. Similar results were observed with a 2nd proteasome inhibitor, Bortezomib, but not general antifungal drugs (Supplementary Figs. 7A-B). Furthermore, C. auris cells lacking Poc4 or Irc25 are hypersensitive to MG-132 even at permissive temperatures (Supplementary Fig. 7C). Consistent with the pharmacological data, loss of either IRC25 or POC4 resulted in a temperature sensitive phenotype, where both mutants are unable to grow at 42°C, but growth is restored upon complementation (Fig. 3D). Additionally, the ∆irc25 and ∆poc4 individual deletion strains phenocopy each other, but deletion of both genes does not alter the phenotype beyond a single deletion, suggesting non-redundant functions for these proteins (Fig. 3E). We also do not see differences in protein expression of either Poc4 or Irc25 upon deletion of the reciprocal co-chaperone, unlike murine PAC3 and PAC4 expressed in HEK293T cells23 (Supplementary Fig. 8). By contrast, deletion of the gene encoding Pre9, a proteasome subunit, results in temperature sensitive phenotype even at 37°C (Supplementary Figs. 9A-B). Taken together, these experimental data demonstrate that, despite losing detectability as a sequence homolog C. auris Poc4 has retained a conserved evolutionary role in proteasome function.

S. cerevisiae Poc4 can function in C. auris, despite considerable sequence divergence
The C. auris Poc4 role in proteasome function, despite its highly divergent sequence, suggests considerable flexibility in sequence-structure relationships within which evolution can operate while preserving essential functions. Recent advances in prediction of multi-subunit protein complexes have made it possible to assess whether the physical interactions are preserved. We used AlphaFold3 to fold the proteasome core particle during the end of the alpha ring assembly, with the Pba1-Add66 and Irc25-Poc4 chaperone complexes on opposite faces of the proteasome, as this is thought to be the final step before Irc25-Poc4 dissociates, and thus this state represents the maximum point of potential protein-protein interactions for the chaperone complex. Starting with the S. cerevisiae complex as a baseline, we observed high predicted structural quality and similarity with the subset of the larger proteasome complex experimentally characterized by cryo-electron microscopy31–33 (Supplementary Fig. 10, ipTM = 0.78, RMSD = 1.159 to 9D0T) and the Irc25-Poc4-Pup2 complex (RMSD = 0.646 to PDB: 2Z5C). This helped build confidence that the computationally predicted structure recapitulates native structures, and thus the quality of the prediction for the C. auris sequences. Using the same parameters, we folded the C. auris proteasome complex and also observed high predicted structural quality and structural similarity with the S. cerevisiae proteasome complex (Fig. 4A, Supplementary Fig. 11A, ipTM = 0.81). Furthermore, we observe high structural similarity between our predictions of the C. auris Irc25-Poc4-Pup2 complex and experimental structures from S. cerevisiae and H. sapiens, giving us confidence in our ability to model these higher order interactions (Supplementary Fig. 12).

Although we observe discrepancies between the AF3 and experimental structures regarding loops and disordered regions, none of these regions are in the Pup2-Poc4-Irc25 subcomplex. Comparing the S. cerevisiae and C. auris complexes, we observe a conserved position of Poc4 around the pore of the proteasome with Pba1-Add66 on the opposite face. Notably, in addition to the conserved hydrogen bonds between the Irc25 and Poc4 protein along the dimerization interface, we observe interactions between helix-2 of Poc4 and helix-2 of Pup2, with polar interactions at the N-termini, hydrophobic packing along each helix, and the C-termini hydrophobically pack against each other, with the polar interactions at the N-termini of each helix, (defined by the C-alpha atom of 83 of Pup2, and the C-alpha of 63 of Poc4) being 18.1 Å for S. cerevisiae and 19.3 Å for C. auris, suggesting that Poc4-proteasome interactions are crucial for chaperone activity (Fig. 4B, Supplementary Fig. 13).

Given these structural similarities despite only sharing only 20% sequence identity, we next sought to characterize whether the Poc4 homologs were functionally interchangeable between species. To understand the potential mechanism of rescue, we predicted the fold of the C. auris proteasome complex as above but replaced the endogenous Poc4 with S. cerevisiae Poc4 using AlphaFold3 (Fig. 4D, Supplementary Fig. 7E). Despite considerable sequence divergence, S. cerevisiae Poc4 is still predicted to interact with C. auris Irc25 and the Pup2 subunit with pDockQ2 scores of 0.42 and 0.25, respectively. The pDockQ2 score summarizes the predicted alignment error from AlphaFold3 over the interface residues within 15 Å between proteins, with scores above 0.2 corresponding to ‘Acceptable’ docking as defined by Critical Assessment of Predicted Interactions (CAPRI) community34,35. This suggested that although specific interaction residues were disrupted, the overall interaction interface is maintained. So, we tested if a CTG-optimized Poc4 allele from S. cerevisiae would complement the temperature-sensitive growth defects of the C. auris deletion strain (Fig. 4C). We expressed ScPoc4 under a constitutive promoter in the C. auris ∆poc4 background and observed full restoration of thermotolerance, suggesting that proteasome assembly activity is being rescued. Complementation of ∆poc4 with a promoter-matched C. auris Poc4 also restores growth at 42 °C, but growth was not enhanced over that of the respective wildtype. Of note, we were unable to complement with the S. cerevisiae Poc4 allele under control of the endogenous C. auris Poc4 promoter because this strain failed to express (Supplementary Fig. 14). We then immunoprecipitated the Poc4 and found that in C. auris, S. cerevisiae Poc4 physically interacts with the proteasome -subunits and Irc25 (Fig. 4E, Supplementary Figs. 4C-D), albeit to a lesser degree. Thus, we show a deeply conserved role of Poc4 across fungi that has persisted despite erosion of sequence signatures of homology.

Prospective testing of designed chaperone proteins
Our results suggest that certain structural features are sufficient for Poc4 proteasome assembly functions, but the generality of this inference is limited by the fact that Poc4 variants from the two species have a shared evolutionary history and have been shaped by natural selection. Meaning, despite the sequence divergence, the Poc4 protein in S. cerevisiae has also been selected for function as an assembly chaperone, and this selection bias could explain the functional rescue independent from the structural determinants of function. We hypothesized that prospectively testing the function of protein sequences outside of the evolutionarily accessible sequence space would allow us to understand the structural requirements for Poc4 activity. Towards this goal, we tested whether artificially designed sequences conditional on the structure of the native C. auris Poc4 expressed in C. auris would be sufficient to rescue the mutant phenotype (Fig. 5A), as these would not share the evolutionary bias of other naturally occurring Poc4 sequences. Given the higher conservation of the 29 residues at the Poc4 and Irc25 dimerization interface, we first predicted the Poc4 and Irc25 dimer using AlphaFold3 and then designed the remaining 82 positions of Poc4 considering any residue type except cysteine. To do this, we used Frame2Seq, a state-of-the-art masked language model for sequence design36, which only considers the predicted backbone geometry of Poc4, and the predicted interaction with Irc25. We wanted to achieve a level of sequence diversity comparable to natural variation, so we used the default temperature parameter of 1.0. We generated 5,000 designs, refolded each using AlphaFold2 and observed that for the 82 variable residues, recovery of the native Poc4 sequence ranged between 50-70 percent identity and 98.9% had an average pLDDT score > 90, suggesting the scaffold is designable by Frame2Seq (Supplementary Fig. 15A). While this level of divergence is less than the 20% sequence conservation for S. cerevisiae to C. auris, to sample these sequences through unbiased deep mutational scanning would require testing > 25^19 = 3.6e25 sequences.

To assess how the design sequences relate to naturally occurring Poc4 sequences, we leveraged embedding sequences into the continuous space learned by the ESM2 protein language model. In addition to the native C. auris, Poc4 and Irc25 sequences, and the re-designed Poc4, we also embedded the orthologous sequences identified through Foldseek and the POC3_POC4 pfam family (PF10448) and used UMAP to project the embedded representations to 2-dimensions. We observed clustering among the Poc4 homologs and among the Irc25 homologs. However, the designed structures appeared to be a distinct cluster (Supplementary Fig. 15B), which gave us confidence that our designs were distinct from natural Poc4 chaperones.

From these, we sampled 70 sequences for closer inspection, choosing 9 designs for experimental testing, with 61 to 64% sequence identity to C. auris Poc4 but without homology by BlastP to other proteins (Fig. 5B). We found that 7 of the designed proteins were able to be expressed in the ∆poc4 deletion background, with 3 of the 7 expressed designs showing significant rescue of thermotolerance at 42 °C and one with partial rescue (Figs. 5C-E, Supplementary Figs. 16A-B). This data is further supported by immunoprecipitation, where we observed stronger associations with both Irc25 and the proteasome -subunits with the functional Seq2523 design than the partially functional Seq2212 design (Supplementary Fig. 16C).

That some, but not all, designs were able to rescue ∆poc4 suggested the structural features of the Poc4 fold substantially contribute to but do not fully explain the functional constraints on Poc4. During the design, we selected for interaction with Irc25 but not the rest of the proteasome. We hypothesized that examining Poc4 in the context of the remainder of the 20S proteasome would identify structural determinants that would allow for Poc4 function. Due to computational constraints, we used AlphaFold Server to predict the structure of 466 designs in complex with the 20S proteasome subunits, and then computed the max pDockQ2 score between Poc4 and Pup2. We observed that the median score was 0.05 and only 41 (8.7%) had scores above the previously published34 threshold of 0.2 (Fig. 6A). To enrich for designs with better pDockQ2 scores, we trained a regression model to predict pDockQ2 based on ESM2 embeddings of the Poc4 designs using H2O AutoML. Using this ML predictor, we selected an additional 136 top scoring designs to prospectively fold with the AlphaFold Server and observed an improved median pDockQ2 of 0.13, with 33 designs giving a pDockQ2 > 0.2 (Fig. 6A, Supplementary Fig. 17A, AUROC = 0.73).

To identify the most important interactions underlying the pDockQ2 scores, we first computed PLiP interaction features37, summarized as the counts across all Pup2 residues by the 8 interaction types, yielding 77 features. We then trained a regression-ML model to predict the pDockQ2 scores from the interaction features and estimated the top SHAP features. The top features were hydrophobic interactions with Pup2 residues 94, 97, and 101, followed by polar interactions with residues 101 and 102 (Fig. 6B, Supplementary Figs. 17B-C). Inspecting these features for the wildtype C. auris and S. cerevisiae complexes and the 7 tested designs, we found that for the wildtype protein and designs that fully or partially recover function, sheets 5 and 6 of Poc4 (Res41-Res58) pack against helix-2 of Pup2 (Res83-Res102), thus allowing K24 and Y44 in WT-Poc4 and the Poc4 designs to form H-bonds with the C-terminal backbone carbonyl of helix-2 of Pup2 (Y102 and D104, respectively) (Figs. 6C-F, Supplementary Fig. 18). To quantify this observation, we defined the Pup2-Poc4 packing distance to be the distance between the C-terminal of helix-2 Pup2 (A83, Cα) and the C-terminal of helix-2 of Poc4 (Res63/Cα). Plotting the pDockQ2 against packing distance, we see a spearm rank correlation of -.65 (Fig. 6G), suggesting that tight packing is a requirement for good pDockQ2 scores. Assessing the structural features of the 7 experimentally tested designs, we can discriminate between non-functional designs and those that partially or fully recover activity. Notably, of the designs that fully or partially recover activity, the design with partial recovery of activity has a higher score than those that fully recover activity, consistent with pDockQ2 being a good but incomplete predictor of function.

Methods
Strains and Culture Conditions:
A list of all strains used in this study is included in Supplementary Data 1. Clinical C. auris isolates were obtained through the CDC Antibiotic Resistance Isolate Bank. Unless specified, cells were cultured at 30°C in YPD liquid media (1% yeast extract, 2% peptone, 2% dextrose), with constant shaking. For solid medium, 2% agar was used. All strains were maintained as frozen stocks in 25% glycerol at -80°C.

Genomic DNA Extraction:
Genomic DNA was isolated using a PCA extraction method. Yeast cells were cultured overnight in YPD liquid at 30°C and harvested by centrifugation. Cells were resuspended in lysis buffer (2% (v/v) Triton X-100, 1% (w/v) SDS, 100mM NaCl, 10mM Tris-Cl, 1mM EDTA) and disrupted by bead beating. Released DNA was extracted into PCA and then into chloroform. The resulting DNA was then purified by ethanol precipitation and resuspended in water before treatment with RNase A. RNase was heat-in activated and extracted DNA was further purified by ethanol precipitation and resuspended in water.

Primers and Plasmids:
A list of all plasmids used in this study is included in Supplementary Data 2. A list of all primers used in this study is included in Supplementary Data 3. Cassettes for transformation of C. auris were maintained in the multiple cloning site of the pUC19 cloning vector and assembled from fragments using the NeBuilder HIFI DNA Assembly Master Mix (NEB #E2621) or the Codex DNA Gibson Assembly Ultra Master Mix (Codex DNA #GA1200) according to the manufacturers’ instructions. All plasmid assemblies were confirmed by Nanopore sequencing.

Plasmid and Strain Construction:
pTO301/CauTO467: The plasmid backbone was amplified from pTO139 using oTO590 and oTO591. The NAT cassette was amplified from pTO137 using oTO847 and oTO668. The NAT cassette was flanked by 500bp of regions homologous to the regions immediately up and downstream of POC4 (B9J08_000884) amplified from C. auris AR0382 genomic DNA using oTO1734-oTO1735 and oTO1736-oTO1737, respectively. The repair cassette was amplified using oTO18 and oTO19 and transformed into AR0382 to generate CauTO467 and CauTO468 from independent transformations.

pTO306/CauTO497: The plasmid backbone was amplified from pTO139 using oTO590 and oTO591. The ADH1 terminator and NEO cassette was amplified from pTO169 using oTO1066 and oTO668. The 500bp upstream and ORF of POC4 (B9J08_000884) was amplified from C. auris genomic DNA using oTO1734 and oTO1842, while the downstream 500bp of homologous sequence was amplified from oTO1736 and oTO1737. The repair cassette was amplified using oTO18 and oTO19 and transformed into CauTO467 to generate CauTO497.

pTO315/CauTO496: The plasmid backbone was amplified from pTO139 using oTO590 and oTO591. The NAT cassette was amplified from pTOR137 using oTO847 and oTO668. The NAT cassette was flanked by 500bp of regions homologous to the regions immediately up and downstream of IRC25 (B9J08_003917) amplified from C. auris genomic DNA using oTO1928-oTO1929 and oTO1930-oTO1931, respectively. The repair cassette was amplified using oTO18 and oTO19 and transformed into AR0382 to generate CauTO496.

pTO322/CauTO550: The plasmid backbone was amplified from pTO139 using oTO590 and oTO591. The ADH1 terminator and NEO cassette was amplified from pTO169 using oTO1066 and oTO668. The NEO cassette was flanked upstream by the ORF of IRC25 (B9J08_003917) and 500 bp of upstream sequence, which was amplified from C. auris genomic DNA using oTO1928 and oTO1980. A downstream flanking sequence was amplified from C. auris genomic DNA using oTO1930-oTO1931. The repair cassette was amplified using oTO18-oTO19 and was transformed into CauTO496 to generate CauTO550.

pTO324/CauTO546: The plasmid backbone was amplified from pTO139 using oTO590 and oTO591. The NAT cassette was amplified from pTO137 using oTO874 and oTO668. The NAT cassette was flanked by 500bp of regions homologous to the regions immediately upstream and downstream of RPN4 (B9J08_003372) amplified from C. auris genomic DNA using oTO1983-oTO1984 and oTO1985-oTO1986, respectively. The repair cassette was amplified using oTO18 and oTO19 and transformed into AR0382 to generate CauTO546.

pTO346/CauTO604: The plasmid backbone was amplified from pTO139 using oTO590 and oTO591. The NAT cassette was amplified from pTO137 using oTO874 and oTO668. The NAT cassette was flanked by 500bp of regions homologous to the regions immediately upstream and downstream of PRE9 (B9J08_002268) amplified from C. auris genomic DNA using oTO2125-oTO2126 and oTO2133-oTO2134, respectively. The repair cassette was amplified using oTO18 and oTO19 and transformed into AR0382 to generate CauTO604.

pTO370/CauTO629: The plasmid backbone was amplified from pTO139 using oTO590 and oTO591. The ADH1 terminator and NEO cassette was amplified from pTO169 using oTO1066 and oTO668. The NEO cassette was flanked upstream by the ORF of PRE9 (B9J08_002268) and 500bp of upstream sequence, which was amplified from C. auris genomic DNA using oTO2125 and oTO2210. A downstream homologous flanking sequences was amplified from C. auris genomic DNA using oTO2133 and oTO2134. The repair cassette was amplified using oTO18 and oTO19 and transformed into CauTO604 to generate CauTO629.

pTO325/CauTO552/CauTOC943: The entire pTO306 vector was amplified in two overlapping fragments using overlapping backbone-specific primers oTO1427 and oTO1428 paired with oTO1958 and oTO1959, respectively. oTO1958 and oTO1959 contain the C-terminus of POC4 with an ALFA epitope tag directly before the stop codon. The repair cassette was amplified using oTO18-oTO19 and transformed into CauTO467 and CauTO496 to generate CauTO552 and CauTO943, respectively.

pTO341/CauTO591: The POC4 complementation vector was amplified from pTO306 using oTO2106 and oTO1066. A CUG-optimized and C-terminal ALFA-tagged POC4 gene based off S. cerevisiae S288C POC4 was obtained as a gene fragment from Twist Biosciences (San Francisco, California, USA) and assembled with the amplified fragment to generate pTO341. The repair cassette was amplified using oTO18-oTO19 and transformed into CauTO467 to generate CauTO591.

pTO350/CauTO611: 1000bp of promoter sequence upstream of TEF1 (B9J08_003610) was amplified from C. auris genomic DNA using oTO1168 and oTO1169. The entire pTO325 cassette was amplified with pTO2178 and oTO2179 and assembled to incorporate pTEF1 directly upstream of the ScPOC4 ORF. The repair cassette was amplified using oTO18 and oTO19 and transformed into CauTO467 to generate CauTO611.

pTO352/CauTO612: 1000bp of promoter sequence upstream of TEF1 (B9J08_003610) was amplified from C. auris genomic DNA using oTO1168 and oTO1169. The entire pTO325 cassette was amplified with oTO2179 and oTO2184 and assembled to incorporate pTEF1 directly upstream of the POC4 ORF. The repair cassette was amplified using oTO18 and oTO19 and transformed into CauTO467 to generate CauTO612.

pTO381/CauTO689: The IRC25 deletion cassette was amplified from pTO315 using oTO1427 and oTO2343 and combined with the NEO cassette from pTO322 amplified using oTO669 and oTO1428. The repair cassette was amplified using oTO18 and oTO19 and transformed into CauTO467 to generate CauTO689.

pTO435/CauTO804/CauTO805/CauTO806/CauTO807/CauTO808/CauTO942: The IRC25 complementation cassette was amplified into three fragments to incorporate a C-terminal 4xFLAG construct. The first fragment was amplified from pTO322 using oTO2717 and oTO2749, while the second fragment was amplified using oTO2748 and oTO2718. The HYG resistance cassette was amplified using oTO2719 and oTO2720. The repair cassette was amplified using oTO18 and oTO19 and transformed into CauTO496 to generate CauTO804. The repair cassette was transformed into CauTO552, CauTO611, CauTO799, CauTO800, and CauTO467 to generate CauTO805, CauTO806, CauTO807, CauTO808, and CauTO942 respectively.

pTO421/CauTO799: The POC4 high-expression complementation vector was amplified from pTO350 using oTO1169 and oTO1066. The Seq2523 protein was synthesized as a CUG-optimized gene fragment containing a C-terminal ALFA tag from Twist Biosciences and assembled with the complementation vector to generate pTO421. The repair cassette was amplified using oTO18 and oTO19 and transformed into CauTO467 to generate CauTO799.

pTO422/CauTO800: The POC4 high-expression complementation vector was amplified from pTO350 using oTO1169 and oTO1066. The Seq2212 protein was synthesized as a CUG-optimized gene fragment containing a C-terminal Alfa tag from Twist Biosciences and assembled with the complementation vector to generate pTO422. The repair cassette was amplified using oTO18 and oTO19 and transformed into CauTO467 to generate CauTO800.

pTO423/CauTO801: The POC4 high-expression complementation vector was amplified from pTO350 using oTO1169 and oTO1066. The Seq1379 protein was synthesized as a CUG-optimized gene fragment containing a C-terminal Alfa tag from Twist Biosciences and assembled with the complementation vector to generate pTO423. The repair cassette was amplified using oTO18 and oTO19 and transformed into CauTO467 to generate CauTO801.

pTO424/CauTO802: The POC4 high-expression complementation vector was amplified from pTO350 using oTO1169 and oTO1066. The Seq2350 protein was synthesized as a CUG-optimized gene fragment containing a C-terminal Alfa tag from Twist Biosciences and assembled with the complementation vector to generate pTO424. The repair cassette was amplified using oTO18 and oTO19 and transformed into CauTO467 to generate CauTO802.

pTO425/CauTO803: The POC4 high-expression complementation vector was amplified from pTO350 using oTO1169 and oTO1066. The Seq1823 protein was synthesized as a CUG-optimized gene fragment containing a C-terminal Alfa tag from Twist Biosciences and assembled with the complementation vector to generate pTO425. The repair cassette was amplified using oTO18 and oTO19 and transformed into CauTO467 to generate CauTO803.

pTO463/CauTO957: The POC4 high-expression complementation vector was amplified from pTO350 using oTO1169 and oTO1066. The Seq1910 protein was synthesized as a CUG-optimized gene fragment containing a C-terminal ALFA tag from Twist Biosciences and assembled with the complementation vector to generate pTO447. The repair cassette was amplified using oTO18 and oTO19 and transformed into CauTO467 to generate CauTO957.

pTO464/CauTO958: The POC4 high-expression complementation vector was amplified from pTO350 using oTO1169 and oTO1066. The Seq2714 protein was synthesized as a CUG-optimized gene fragment containing a C-terminal ALFA tag from Twist Biosciences and assembled with the complementation vector to generate pTO447. The repair cassette was amplified using oTO18 and oTO19 and transformed into CauTO467 to generate CauTO958.

pTO465/CauTO959: The POC4 high-expression complementation vector was amplified from pTO350 using oTO1169 and oTO1066. The Seq1269 protein was synthesized as a CUG-optimized gene fragment containing a C-terminal ALFA tag from Twist Biosciences and assembled with the complementation vector to generate pTO447. The repair cassette was amplified using oTO18 and oTO19 and transformed into CauTO467 to generate CauTO959.

pTO467/CauTO960: The POC4 high-expression complementation vector was amplified from pTO350 using oTO1169 and oTO1066. The Seq1407 protein was synthesized as a CUG-optimized gene fragment containing a C-terminal ALFA tag from Twist Biosciences and assembled with the complementation vector to generate pTO447. The repair cassette was amplified using oTO18 and oTO19 and transformed into CauTO467 to generate CauTO960.

C. auris Transformation:
C. auris transformation was performed using a transient-Cas9 expression system as described previously 63. Transformation repair cassettes were amplified from assembled plasmids. The Cas9 expression cassette was amplified from pTO135 with oTO40 and oTO41. Cassettes for the expression of sgRNA targeting specific loci were amplified from pTO136 using overlap extension PCR to change the gRNA sequence. All linear PCR products were purified using a Zymo DNA Clean & Concentrator kit (Zymo Research, D4034) according to the manufacturer’s instructions.

To prepare competent C. auris cells, a single colony was inoculated into liquid YPD and incubated overnight at 30 °C with gentle shaking. Cells were harvested by centrifugation and resuspended in TE Buffer and 100 mM lithium acetate. Cells were further incubated at 30 °C for 1 hour with constant shaking before DTT was added to the cells at a final concentration of 25 mM before further incubating at 30 °C for an additional 30 minutes. Cells were harvested by centrifugation at 4 °C before being washed once with ice-cold water and once with ice-cold 1 M Sorbitol. Harvested cells were resuspended in ice-cold 1 M Sorbitol and kept on ice for immediate use or stored at -80 °C for future use.

Electroporation was performed by adding 50 µL of competent cells to a pre-chilled electro-cuvette (2mm-gap) with 500 ng of each of the PCR-amplified Cas9, sgRNA, and repair cassettes. Cells were electroporated using a Bio-Rad MicroPulser Electroporator using the pre-defined P. pastoris (PIC) protocol (2.0 kV, 1 pulse). Electroporated cells were immediately recovered in 1M sorbitol and then resuspended in YPD for a 2-hour outgrowth at 30 °C with constant shaking. Outgrowth cells were plated onto selective media. For repair cassettes containing the NAT marker, cells were selected on YPD plates containing 200µg/mL nourseothricin with incubation at 30 °C for 2 days. For repair cassettes containing the NEO marker, cells were selected on YPD plates containing 1 mg/mL G418 with incubation at 30 °C for 2 days. For repair cassettes containing the HYG marker, cells were selected on YPD plates containing 800 µg/mL Hygromycin B with incubation at 30 °C for 2 days.

Transformant colonies were passaged to isolation and correct incorporation of the repair cassette was confirmed for each by colony PCR using Phire Plant Direct PCR Master Mix (F160; Thermo Fisher Scientific) according to the manufacturer’s instructions. Each mutant was confirmed with at least three independent PCR reactions with distinct primer sets specific to the mutation site and compared to parental strains.

Phylogenetic Analysis:
The protein sequences used in the phylogenetic analysis are available in Supplementary Data 4. Sequence homologs of the indicated genes were identified using the S. cerevisiae amino acid sequence as the query using NCBI BLAST (https://blast.ncbi.nlm.nih.gov/Blast.cgi). For CauPOC4 homologs, the C. auris POC4 amino acid sequence was used instead. The sequence was individually queried against each of the listed species using the blastp algorithm in the non-redundant protein sequences (nr) database under default parameters. Hits were identified by having reciprocal best matches and an E-value less than 0.0001. Syntenic genes were identified in the listed species using both the Candida Gene Order Browser and the Yeast Gene Order Browser 64,65.

For each gene, the homologous sequences were first aligned using muscle5 and trimmed using trimAI (parameters: -gt 0.7 -cons 60) and then manually adjusted to remove unalignable sites from downstream analyses 66,67. The curated sequence files used in downstream analyses are provided in Supplementary Data 4. These alignment files were used to infer the maximum likelihood phylogeny for each gene using the best-fit model of sequence evolution and rate variation parameters using the IQTree2 software and the implemented ModelFinder function 68,69. This method provided a direct estimate of the evolutionary distance between pairs of sequences in the alignment.

Per-residue conservation scores were calculated from these alignments using the AL2CO method with the following settings: unweighted sequences, sum-of-pairs conservation method, BLOSUM62 scoring matrix without transformation, P window size of 1, gap fraction of 0.5 70. Scores were visualized onto the C. auris Poc4 and Irc25 AlphaFold3 models using ChimeraX.

Homology analysis:
For sequence-based homology, 5,417 protein coding sequences from FungiDB (version 68) CaurisB8441 were searched using BlastP (Protein-Protein BLAST 2.12.0+) against all 572,970 Swiss-Prot (version 2025_R01). For structure-based homology, the same protein coding sequences were mapped to structures in the AFDB (v4, model creation date: 2022-06-01) as follows. First, the sequences were mapped to locus tags in the NCIB GCA_002759435.3_Cand_auris_B8441_V3 genome yielding 5,395 one-to-one matches. Note FungiDB CaurisB8441 ids have the form B9J08_###### (6 numbers), while GCA_002759435.3_Cand_auris_B8441_V3 ids have the form B9J08_##### (5 numbers). Then GCA_002759435.3_Cand_auris_B8441_V3 locus tags were mapped UniPort entries for the UP000230249 Proteome, where all ids mapped 1-1. Each UniProt entry was then mapped to UniParc ids, which uniquely identifies the sequence. Then, the AFDB was queried for structures for C. auris, yielding 12,017 structures and their pLDDT scores were recorded. For each AFDB structure the corresponding UniProt entry was mapped its UniParc entry and de-duplicated. Joining C. auris protein and AFDB structures by UniParc ids yielded 4,360 AFDB structures for C. auris proteins. We then used Foldseek (downloaded 2/2025, Foldseek and MMseq version 9-427df8a) to search for structure homologues in the pre-defined Alphafold/Swiss-Prot reference database, using foldseek easy-search command with default parameters otherwise. To compare sequence vs structure homology, for each C. auris gene, we computed the maximum BlastP and Foldseek bit score across Swiss-Prot targets.

Structural Predictions:
Protein models of mid assembly proteasome assembly complex were predicted using AlphaFold 3 (https://alphafoldserver.com/ 5/2024) with default parameters. For each structure, the top ranking model was visualized with ChimeraX and Predicted aligned error (PAE) plots were made with PAE Viewer 71,72. Predicted intermolecular interactions between chains were identified using PISA 73. pDockQ2 scores were calculated between all chains in a given structure using ipSAE as an average across 5 models 74. Poc4 chaperone topology was determined using Pro-origami under default parameters 75.

Protein Design:
As an initial structure for Poc4, the C. auris Poc4 and Irc25 sequences were jointly folded with AlphFold3 (https://alphafoldserver.com/ 5/2024) with default parameters and the top ranking structured was used, having scores pTM: 0.89, ipTM: 0.91, has_clash: 0.0, fraction_disordered: 0.01, and ranking_socre: 0.91. Then given this structure, Frame2Seq (version 0.0.5) was used to generate designs for the Poc4 chain, generated excluding cysteine, varying temperature in [0.01, 0.1, 1, 10], and either using no additional constraints, fixing conserved residues determined by the multiple sequence alignment [18, 24, 26, 42, 44, 52, 57, 67, 76, 78, 79, 83, 85, 86, 89], or alternatively fixing the Poc4 residues at the Poc4-Irc25 interface [1, 3, 5, 12, 14, 16, 18, 24, 25, 26, 28, 30, 32, 33, 34, 35, 36, 37, 38, 39, 42, 44, 55, 56, 57, 58, 83, 85, 87]. From the temperature=1.0 and fixinterface parameters, 5000 sequences were generated, and each was folded with AlphaFold2. ParaFold was used to distribute first the MSA generation and then the folding tasks onto the University of Michigan Great Lakes CPU and GPU HPC cluster queues 76. Designs were evaluated by the Frame2Seq Score, AlphaFold2 pLDDT, sequence identity to the native Poc4, and diversity among the designs. To visualize the similarity between designs, Poc4 and structural homologues, ESM2 embeddings for the Poc4 Foldseek hits, members of pfam PF10448, and the designs were generated using the esm2_t33_650M_UR50D model, by averaging the per-residue representation in the 33rd layer for the up to 1022 first residues in the sequence. The EMS2 embeddings were then projected to 2-dimensions using UMAP (v0.5.7) with parameters a=1, b=1.8, metric=”cosine”.

Structural features analysis:
To characterize the structural basis for successful Poc4, we analyzed the pDockQ2 score between an additional 602 Poc4 designs and Pup2 in AlphaFold3 predicted proteasome complexes. To do this we generated an additional 500,000 Frame2Seq sequences and filtered for Frame2Seq score < 0.6 yielding 44,119 designs (8.8%). From these we randomly sampled 5,141 sequences from the lowest 10,000 by percent sequence recovery (so that percent recovery ranged between 57-63%), used AlphaFold2 to re-fold the Poc4-Irc25 complex, filtered for pLDDT > 96, yielding 2,268 designs (44%). From these we randomly sampled 466 designs and co-folded each with the 10 other components of the C. auris proteasome complex on the AlphaFold Server and computed pDockQ2 scores for each of the 5 generated sampled conformations for each complex.

To compute the pDockQ2 score of Pup2 and Poc4 in each complex, we used the IPSAE (v3 03/2025) package with default pae_cutoff=15 and dist_cutoff=15 parameters, and since pDockQ2 is an asymmetric measure, we used the max over Pup2 vs. Poc4 and Poc4 vs. Pup2. We observed the median pDockQ2 score was of 0.05 and 41 had a pDockQ2 score > 0.2. To balance the distribution of pDockQ2 scores for comparative analysis, we trained a regression model to predict pDockQ2 based on ESM2 embeddings of the Poc4 designs using H2O AutoML (v3.44.0.3). The best performing model over 5-fold cross validation by RMSD was a Gradient Boosted Model, with an RMSD 0.061. Using this model, we selected the top 131 designs and similarly folded these on the AlphaFold Server and computed pDockQ2 scores, yielding a median pDockQ2 of 0.13 and 33 with pDockQ2 > 0.2 over this second set.

To identify specific interactions that explain the pDockQ2 scores, for each complex we computed PLiP (v3.0.0) interaction features. Since the Pup2 sequence is invariant, for each Pup2 residue and 8 interaction types [hydrophobic_packing, pi_stacking, and hbond_pdon, hbond_ldon, saltbridge_pneg, saltbridge_lneg, and pication_pdon, picaton_ldon] we counted the number of interactions with any residue of Poc4, where for the purposes of PLiP, Pup2 is the “protein” and Poc4 is the “ligand”, yielding 77 non-zero features. Then we trained an H2O AutoML regression-ML model. The best performing model over 5-fold cross validation by RMSD was a Gradient Boosted Model, with an RMSD 0.041. To identify important features, using the fit model, we computed SHapley Additive exPlanation features using the TreeSHAP algorithm from H2O.

Growth Assays:
Spot assays were performed by growing fungal cells overnight in liquid YPD media at 30 °C with constant shaking. Cell culture density was normalized to an OD of 1 in sterile water and diluted 10-fold. 5µL of each dilution were spotted onto YPD plates and incubated at 30 °C, 37 °C, or 42 °C for 2 days before imaging on a BioRad gel dock. Each plate image is representative of at least 3 biological replicates.

Kinetic growth assays were performed by growing fungal cells overnight in 200µL of YPD in a 96 well plate at 30 °C, then subcultured into fresh media using a sterile pinner. Growth curves were performed on a BioTek LogPhase600 Plate Reader at the indicated temperatures for 24 hours with shaking at 500 rpm and OD measurements taken every 10 minutes. A minimum of 4 biological replicates, each with 3 technical replicates was performed per strain per growth condition. Growth statistics, (rate, carrying capacity, and AUC) were calculated using the growthcurver R package. Growth curves were plotted in GraphPad Prism v11.

Minimum Inhibitory Concentration (MIC) Assays
Standard compound sensitivity testing was evaluated by broth microdilution MIC testing in 96 well, flat-bottom microtiter plates. All compounds were dissolved in DMSO. Tested MG-132 (Cayman Chemical, 10012628) and bortezomib (Cayman Chemical, 10008822) concentrations ranged from 3.125 µM to 200µM. Tested fluconazole (Cayman Chemical, 11594), caspofungin (GoldBio, C-520-10), and amphotericin B (GoldBio, A-560-250), concentrations ranged from 0.04-64 µg/mL, 0.08-80 ng/mL, and 0.04-64 µg/mL, respectively. Assays were set up in a total volume of 200 µL of YPD per well with 2-fold serial dilutions of the test compound. Following inoculation, plates were covered and incubated statically at the indicated temperature. Growth was quantified by measuring OD with a BioTek 800 TS Absorbance Reader at an endpoint of 24 hours. Relative growth was calculated for each strain by dividing the optical density at a given concentration, by the optical density of an untreated control on the same plate. All strains were assessed with 3 biological replicates in technical duplicates. Dose-response curves were plotted in GraphPad Prism v11.

Co-Immunoprecipitation
Strains were inoculated in YPD and subcultured to an OD of 0.05 in 100 mL of fresh YPD. Cultures were grown for 6 hours at 37 °C in 250 mL Erlenmeyer flasks with 150 rpm shaking until mid-log phase. Cells were collected by centrifugation at 1500 x g washed in 1mL sterile water, transferred to 1.5mL screw-cap tubes, then flash frozen and stored at -80 °C.

Cell pellets were resuspended in 1mL of lysis buffer (20 mM Tris pH 7.5, 100 mM KCl, 5 mM MgCl, 20% glycerol, and 1X HALT protease inhibitor cocktail (Thermo Fisher Scientific, 87786) added fresh before use). The tube was filled with acid-washed glass beads until the beads were just below the meniscus at the top of the tube to limit foaming during bead beating. Cells were disrupted by bead beating three times for 4 minutes, with 7-minute incubation on ice between cycles. Lysates were recovered by a stacked transfer and clarified by centrifugation at 18,000 x g for 10 min at 4 °C. Protein concentrations were determined by Bradford assay.

Anti-ALFA immunoprecipitations were performed with ALFA Selector PE magnetic agarose beads (NanoTag Biotechnologies, N1515). For each reaction, 20 µL of magnetic agarose bead slurry was washed 2 times in 1 mL ice-cold lysis buffer. Beads were collected by magnetic separation between each wash step. 1mL of protein lysates normalized to a total protein level of 2mg and added to the washed beads. Reactions were incubated with end-over-end rotation for 2 hours at 4 °C. The samples were then washed 3 times in 1mL ice-cold lysis buffer, transferred to clean tubes, and washed again twice with 1 mL ice-cold lysis buffer, and one final time with 1mL ice-cold Tris-buffered saline (TBS). The washed beads were then resuspended in 100 µL of Laemmli sample buffer, incubated at 95 °C for 5 min, shaking at 500 rpm. Supernatant was collected and subject to western immunoblotting on SDS-PAGE gels.

Protein Extraction
Strains were inoculated overnight in YPD and subcultured to an OD of 0.1 in 10 mL of fresh media, incubated for 5 hours with shaking at 30 °C. Following sub-culture, cells were harvested by centrifugation, then washed once with sterile water. Cells were resuspended in lysis buffer (50 mM HEPES pH 7.4, 150 mM NaCl, 5 mM EDTA, 1% Triton X-100, 100mM NaF, 1 mM PMSF, 1X HALT protease inhibitor cocktail (Thermo Scientific, 87786)) and lysed by bead beating. Following lysis, lysates were clarified by centrifugation and protein concentration was determined by Bradford assay.

Western Blotting
Protein levels were normalized to 25 µg and boiled in 1x Laemmli sample buffer for 5 minutes before loading on 4-20% SDS-PAGE gels (Bio-Rad, #4561094). Following separation, proteins were transferred to polyvinylidene difluoride (PVDF) membrane (Bio-Rad, #162-0177) for 15 minutes using a semi-dry transfer system. Blots were blocked with 5% bovine serum albumin (Sigma-Aldrich, A7030) in phosphate-buffered saline with 0.1% Tween-20 (PBS-T).

The molecular weight was approximated by electrophoresis of marker proteins in either the PageRuler pre-stained protein ladder (Thermo Scientific, 26616) or PageRuler Plus pre-stained protein ladder (Thermo Scientific, 26619). ALFA epitopes were detected using camelid anti-ALFA Licor 800CW primary antibody (NanoTag Biotechnologies, N1502-Li800-L) at a 1:5000 dilution in blocking solution. FLAG epitopes were detected using 1:1000 dilution rabbit anti-FLAG primary antibody (Sigma-Aldrich, F7425-.2MG). Blots were washed with PBS-T and incubated with 1:15000 goat anti-rabbit IgG IRDye-680RD (LI-COR Biosciences, 926-68071) or 1:15000 goat anti-rabbit IgG IRDye-800CW (LI-COR Biosciences, 926-32211). Ubiquitin epitopes were detected with 1:1000 dilution mouse anti-Ubiquitin primary antibody (Invitrogen, 13-1600). Blots were washed with PBS-T and incubated with 1:15000 dilution anti-mouse IgG IRDye-800CW secondary antibody (LI-COR Biosciences, 926-33210) before detecting signals using a LI-COR Odyssey scanner. Protein levels were normalized to total protein loading using Revert 700 total protein stain (LI-COR Biosciences, 926-11011). Proteasome -subunits were detected using a primary antibody specific to a conserved peptide in the 20S alpha proteasome proteins Pre1, Pre2, Pre3, Pre5, Pre6, and Pre7 at a 1:3000 dilution in blocking solution (AbCam, antibody ID: AB_2171376). Following washing, blots were incubated with 1:15000 dilution goat anti-mouse IgG HRP secondary antibody (EDM Millipore, 12-348) before detecting signals using a ThermoFisher iBright 1500 imager. For quantification, band and total protein intensity were measured using ImageJ. Band intensities were normalized to the total protein signal in each lane. In each case, three biological replicates were quantified. All uncropped blots are provided in Source Data.

Statistics and Reproducibility:
Statistical analyses were carried out using GraphPad Prism v11. Data are presented as mean ± standard deviation from biological replicates. Unless otherwise noted, experiments were performed in at least three independent biological replicates with at least three technical replicates yielding similar results. All blots or images are representative of at least three independent experiments. Statistical significance among different groups was calculated using one-way ANOVA, with either Tukey or Dunnett’s post hoc tests for multiple comparisons as appropriate. *p ≤ 0.05; **p ≤ 0.01; ***p ≤ 0.001; n.s., p > 0.05. Specific p-values are listed in Source Data.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "The manuscript \"Deep homology and design of proteasome chaperone proteins in Candida auris\" by Rapala et al. presents an interesting study combining computational and experimental approaches to investigate protein evolution in fungi, with a particular focus on proteasome chaperone proteins in Candida auris. The authors employ state-of-the-art computational methods including protein structure prediction (AF2, AF3), 3D structure search (FoldSeek), and protein sequence design (Frame2Seq), complemented by experimental validation to achieve several notable objectives:\n- assign a function to an uncharacterised protein\n- infer the different evolutionary rates of that protein compared to its interacting partners\n- show that a fungi ortholog of that protein with low sequence similarity can compensate for its loss in vivo\n- design de novo proteins with the same fold\n- show that one designed sequence 40 mutations away can retain the function of the wild type.\nThis work provides valuable insights into the Candida auris proteome and offers a compelling proof-of-concept for computational protein design with in vivo validation. The computational methodology is well-designed and the integration of structural and functional analyses strengthens the study.\nHowever, I would like to raise an important point regarding the interpretation of the de novo design results that merits further discussion. The experimental outcomes present an intriguing paradox: while only one of five computationally designed sequences (with ~60% similarity to wild-type and conserved functional interface residues) successfully rescued function, the S. cerevisiae ortholog with merely 20% sequence similarity to C. auris achieved functional complementation. This suggests that evolutionary constraints important for function may not be fully captured by the Frame2Seq approach. A discussion of this apparent discrepancy and its implications for our understanding of sequence-function relationships would enhance the manuscript's impact.\nOther specific comments :\n- When the expression levels are different for two interacting proteins (as is the case here), does it still make sense to think that their only function is determined by their interaction?\n- Could the authors comment on the conservation of interface residues between POC4 and Irc25 across the two fungal species, particularly regarding the \"expected predicted hydrogen bonds\"?\n- The selection criteria for the five designed sequences could be clarified. Additionally, the 5,000 designed sequences mentioned in the text do not appear to be available in the GitHub repository. Would AF3-derived metrics (dockQ, iPTM) provide useful criteria for sequence selection?\n- I do not quite understand the purpose of the UMAP analysis. What does it bring compared to an analysis of sequence similarity of edit distances? Plus, are ESM2 embeddings expected to be of good quality for designed sequences givent hat ESM2 performs very poorly in predicting thermodynamic stability changes unpon mutations in de novo designed sequences (MEGA dataset)?\n- The statement \"In the absence of a change in structure...\" appears to require additional experimental support.\nMinor comments:\n- Several figure legends in the Supplementary Material contain errors (e.g., Fig. S7)\n- What is the evolutionary conservation pattern for the three highlighted residues in Fig. S7? Pymol alignment suggests D90 in Sce corresponds to D62 rather than S63 in Cau\n- Brief explanations of Frame2Seq methodology and dockQ2 scoring rationale would benefit non-expert readers\n- The match rate of 1/3 for UniParc entries with the C. auris proteome seems low - could this be clarified? (Note: \"UniPort\" typo on p.30)\n- The methodology for determining conserved residues could be described\n- Information on computational costs, particularly for structural prediction of 5,000 sequences, would be valuable for reproducibility", "reviewer_2": "In their manuscript, Rapala et al. report on a proteasome chaperone complex, Poc4-Irc25, showing high structural conservation but low sequence conservation. They characterize the function of this new protein directly in Candida auris, validating its predicted role in proteasome assembly and conserved physical interactions. The authors then show that despite low sequence conservation, the Saccharomyces cerevisiae ortholog of Poc4 can complement the C. auris deletion. Finally, then use a generative model to create new proteins distant in sequence but with a conserved structure and show that at least one of these artificial sequences can complement the C. auris deletion. Overall, I enjoyed the manuscript: I think the direct investigation of Poc4 function in C. auris was well done, considering the added difficulty of working in this pathogen. The authors show convincingly the usefulness of a structure-based approach to cover blind spots in sequence alignment searches. On the other hand, I am not entirely convinced by the framing the authors used regarding the structural and functional evolution of their model protein, as well as the relevance of their synthetic homologs. Here are my comments:\n1. The authors state (lines 22-23), that structural conservation despite high sequence divergence in Poc4 is a case of neutral evolution. This is not demonstrated directly by the results: the only thing that is shown is that some molecular functions are maintained, without any information in regard to the fitness effects of the changes. It would take a lot more data to conclude with a good level of certainty that all these changes were strictly neutral in terms of fitness and of other molecular properties that were not measured.\n2. Lines (120-125, 269-270): There might also be other non-structural constraints on sequence evolution that explain the high rate of divergence: higher local mutation rates, or constraints on specific codons due to GC content or tRNA abundance. Was the rate of synonymous mutations the same as non-synonymous mutations?\n3. Figure 2D: As mentioned by the authors, the switch from ScPoc4 to CauPoc4 sequence homology matches correlates very well with the CTG clade. Is there any reason why this might be the case? Was this switch associated with a mutational burst in general?\n4. Lines (120-125): The phylogeny shown does not clearly support the author's statement on faster evolution of Poc4 vs Irc25, except for a subset of CTG clade species. A more quantitative measurement would be better.\n5. The structure of the S. cerevisiae Poc4-Irc25 complex has been solved experimentally (Yashiroda et al, PMID 18278057). Is there a reason why the authors used the AlphaFold prediction instead of the solved structure? Any major differences between the prediction and the known structure?\n6. Additionally, some of the observations made here by the authors echo what had been observed for the relationship between S. cerevisiae Irc25 and human PSMG3 (aka PAC3), which also shows very low sequence identity but high structural similarity (Yashiroda et al, PMID 18278057). Interestingly, both Poc4 and Irc25 showed similar levels of similarity to PSMG3. I think this should be discussed in the text and might point towards Poc4 and Irc25 being highly diverged paralogs. Is there any evidence for this? No need to fully address the question in this manuscript, just food for thought.\n7. Figure 4: the Poc4-Irc25-Pup2 complex has also been solved (Yashiroda et al, PMID 18278057). Please validate the AlphaFold predictions and comment on any changes observed. The structure of the PSMG3-PSMG4 complex has also been solved (Satoh et al, PMID 31067643) and might also prove useful regarding how function is conserved via structure.\n8. Figure 4: Please consider providing a colormap showing residue conservation on both Poc4 and Irc25 structures.\n9. Lines 172-173: ref 25 (Takagi et al) performed alanine scanning of residues required for Poc4 binding to Pre6 (the alpha-4 subunit) binding, not Pup2 (alpha 5) if I understand their figure 3 correctly.\n10. Also Figure 4: Was there any rationale behind folding the entire proteasome core particle instead of just Poc4-Irc25-Pup2? Is the average ipTM of the subcomplex similar to the rest, or higher/lower?\n11. I was not convinced by the author’s idea that the artificial sequences generated by the authors were distinct from natural Poc4 homologs. In their design process, they fix 29 residues (the Poc4-Irc25 interface as well as the cysteine residues). This means that the resulting sequences should have at minimum 29/111 = 26% identity. This is higher than what exists with the S. cerevisiae homolog, which they show can complement. The 1/5 sequence that does complement has ~60%, much higher than that. What fraction of these fixed residues are also at or near the Poc4-Pup2 interface? And are these residues evolving more slowly in general?\n12. Data from Le Tallec et al (PMID 17707236) suggests that the murine orthologs of PSMG3-PSMG4 stabilize one another, as knockdown of either one decreased the abundance of the other. Has this been shown in yeast? If so, this might make Irc25 binding as important as Pup2 or Pre6 binding in terms of molecular function.\n13. Most importantly, while interesting, the synthetic sequence approach does not contribute to understanding why this protein complex can tolerate such high levels of sequence divergence. Using highly diverse synthetic sequences to determine what residues or properties are important to maintain function would be an interesting approach, but the authors do not push their analysis far enough. There is not enough information presented on what substitutions were made and where they occurred in the structure to understand why one sequence worked, while the others failed. As it stands, I don’t think this experiment provides any concrete biological insights that were not already discernible from the S. cerevisiae complementation experiment. I think the authors should perform additional experimental and computational work to really dissect the molecular mechanisms at play here using this approach to justify its inclusion in the manuscript.", "reviewer_3": "This is an interesting paper by O’Meara and colleagues, using proteasome chaperone proteins in Candida auris to explore the constraints of sequence-structure-function relationships in protein evolution. To do this, the others first perform phylogenetic analysis of divergent sequences separated by vast evolutionary time, and then design artificial proteasome chaperones to maintain a conserved structure and rescue mutant phenotypes.\nThe work is well executed, and the manuscript is well written, leading to the conclusion that protein folds remain conserved over substantive evolutionary time, and that it is the fold rather than sequence that is driving function. While this is an interesting conclusion, it is not novel. As just some exmaples, Betts and colleagues showed that at the gene level, there are cases where gene structures remain similar even with minimal protein sequence similarity, and where sequence alignment is only possible by using protein tertiary structures (Betts et al., EMBO J. 20 (2001), 5354). Thornton showed that enzymes with diverged functions maintain regions of highly conserved active site structure (Riziotis et al., J. Mol. Biol. 435 (2023), 168254). Tsonis and colleagues perform detailed analysis of three-dimensional structure conservation in non-homologous/unrelated proteins, arguing that conservation of three-dimensional structure might be more important than the primary amino acid sequence (Sousounis et al., Hum. Genomics 6 (2012), 10). Fu and coworkers demonstrate from proteome-wide structural analysis that structure remains highly conserved across distant species, also pointing out with appropriate references that the fact that protein structure is more conserved than primary amino acid sequence and is the determinant of biological function is well accepted (see Zhang et al., 33 (2023), 1975, and references cited therein). There are numerous examples from ancestral sequence reconstruction that show that structure is highly conserved across broad evolutionary time, and dictates functon(Choi and Kim, Proc. Natl. Acad. Sci. USA 103 (2006), 14056; Merkl and Sterner, Biol. Chem. 397 (2015), 1; Risso et al., Nat. Commun. 8 (2017), 16113, among others).\nI still believe the work is interesting as a case study, and is valuable as a showcase of what we can learn from protein design. The key insights that it provides, however, are not novel, beyond providing insight into structure-function relationships in these specific chaperones, as the broader conclusions are well established in the field. As such, this work is more suited to a specialist journal rather than the broad readership of Nature Communications.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts."}, "author_response": "We thank the reviewers for their thoughtful suggestions, which have helped us to\nprepare a stronger manuscript for a revised submission. Please find below a detailed\npoint by point response to individual reviewer comments.\nHighlights of the revised submission include:\n1) Expanded introduction and discussion to make sure to include additional context\nfor our work.\n2) Testing of an additional designs and the identification of three additional artificial\nsequences that can rescue thermosensitivity.\n3) Further exploration of the relationship between pDockQ2 scores of the designed\nstructures in the context of the entire proteasome and the ability to rescue,\nincluding generating an ML model to predict pDockQ2 scores.\n4) Quantification of the evolutionary rate and visualization of conservation on the\nPoc4 structure.\nReviewer #1 (Remarks to the Author)\nThe manuscript \"Deep homology and design of proteasome chaperone proteins in\nCandida auris\" by Rapala et al. presents an interesting study combining computational\nand experimental approaches to investigate protein evolution in fungi, with a particular\nfocus on proteasome chaperone proteins in Candida auris. The authors employ state-\nof-the-art computational methods including protein structure prediction (AF2, AF3), 3D\nstructure search (FoldSeek), and protein sequence design (Frame2Seq),\ncomplemented by experimental validation to achieve several notable objectives:\n- assign a function to an uncharacterised protein\n- infer the different evolutionary rates of that protein compared to its interacting partners\n- show that a fungi ortholog of that protein with low sequence similarity can compensate\nfor its loss in vivo\n- design de novo proteins with the same fold\n- show that one designed sequence 40 mutations away can retain the function of the\nwild type.\nThis work provides valuable insights into the Candida auris proteome and offers a\ncompelling proof-of-concept for computational protein design with in vivo validation. The\ncomputational methodology is well-designed and the integration of structural and\nfunctional analyses strengthens the study.\nResponse: Many thanks!\nHowever, I would like to raise an important point regarding the interpretation of the de\nnovo design results that merits further discussion. The experimental outcomes present\nan intriguing paradox: while only one of five computationally designed sequences (with\n~60% similarity to wild-type and conserved functional interface residues) successfully\nrescued function, the S. cerevisiae ortholog with merely 20% sequence similarity to C.\nauris achieved functional complementation. This suggests that evolutionary constraints\nimportant for function may not be fully captured by the Frame2Seq approach. A\ndiscussion of this apparent discrepancy and its implications for our understanding of\nsequence-function relationships would enhance the manuscript's impact.\nResponse: We agree that this point is of critical importance. Our initial interpretation is\nthat there were additional constraints that were not captured in our first design\nschematic. We alluded to the pDockQ2 scores as being discriminatory in the initial\nmanuscript, but we only had 5 designs that we scored using this approach. In the\nrevised manuscript, we folded and scored an additional 602 designs in complex with the\nentire proteasome, and this identified that only 74 were above the previously identified\nthreshold. To explore whether this was a discriminatory threshold for function, we\ncloned, expressed, and tested an additional 4 designs that were close to that score.\nImportantly, 2 were able to rescue the thermotolerance defect of the mutant (NEW\nFIGURE 5).\nThis helps bolster the idea that the structure of the assembly chaperone needs to\ninclude a good docking with the rest of the proteasome. However, it is likely that there\nare additional constraints that are not captured in our approach, as we have not yet\nachieved 100% functionality of our designed proteins. We have significantly expanded\nthe discussion to include these ideas and limitations.\nLINE 412: We also determined that not all of the designed artificial chaperones\nwere functional, suggesting additional constraints that were not captured in our\noriginal approach. Additional experiments regarding the biochemical properties,\nsuch as stability or aggregation potential, of the designed proteins may help\nexplain the different functional capacity of our designs. We find that\ncomputational measures of protein docking are sensitive enough to identify\npotential differences between functional and non-functional designs. Wildtype\nand designs that fully or partially recover function, form hydrophobic pack against\nPup2. Interestingly, the two designs that formed the highest quality interactions\nwith Pup2 only partially recovered function, suggesting perhaps that moderately\nstrong interactions facilitate transient chaperoning functional role. This\nobservation, along with other studies that directly integrate diffusion and docking\nmodels into protein design workflows54,61, suggests that modeling endogenous\nprotein-protein interactions of designed sequences is a critical step in identifying\nprotein designs with desired activity54\nOther specific comments :\n- When the expression levels are different for two interacting proteins (as is the case\nhere), does it still make sense to think that their only function is determined by their\ninteraction?\nResponse: We think this may be part of the differential stability or translation of the\ntarget – IRC25 lacks the large UTR of POC4, which we hypothesize modulates protein\ntranslation. However, the field is missing the global proteomics analysis that would allow\nfor a determination of total protein levels for these two proteins.\nFor the reviewer, we include here a view of the RNAseq read maps at the POC4 and\nIRC25 loci.\nPoc4:\nIrc25:\n- Could the authors comment on the conservation of interface residues between POC4\nand Irc25 across the two fungal species, particularly regarding the \"expected predicted\nhydrogen bonds\"?\nResponse: There are 5 residues at the interface between POC4 and IRC25 that are\nhighly conserved. We have included an analysis of the protein conservation scores\nacross the protein structure, and this highlights these residues. (Supplemental Figure\n13). We have clarified this point in the text.\nLINE 219: Notably, in addition to the conserved hydrogen bonds between the\nIrc25 and Poc4 protein along the dimerization interface, we observe interactions\nbetween sheets 5 and 6 of Poc4 and helix-2 of Pup2, with polar interactions at\nthe N-termini, hydrophobic packing along each helix, and the C-termini\nhydrophobically pack against each other, with the distance the N-termini of each\nhelix (defined by the C-alpha atom of 83 of Pup2, and the C-alpha of 63 of Poc4)\nbeing 18.1 Å for S. cerevisiae and 19.3 Å for C. auris, suggesting that Poc4-\nproteasome interactions are crucial for chaperone activity (Figure 4B,\nSupplemental Figure 13).\nAdded how predicted hydrogen bonds were identified to the methods\nLINE 963: Predicted intermolecular interactions between chains were identified\nusing PISA 73.\n- The selection criteria for the five designed sequences could be clarified. Additionally,\nthe 5,000 designed sequences mentioned in the text do not appear to be available in\nthe GitHub repository. Would AF3-derived metrics (dockQ, iPTM) provide useful criteria\nfor sequence selection?\nResponse: Thank you for this suggestion. We have put the designed sequences on\nGitHub and expanded Figure 5A to include a schematic of the selection criteria.\nAs described above, in our previous fig 5, we showed that there is some discriminatory\nvalue for AF3 pDockQ scores in the designs that work. Due to the computational costs\nand the recent release of the code at the time, we did not run this for all 5,000 designs.\nIn the revised manuscript, we took an additional subset of designs, determined their\npDockQ scores, and then tested an additional subset for whether these were sufficient\nto function in the cell. We found two additional designs that were able to rescue the\nmutant (FIGURE 5) on solid media, and one design with partial rescue in liquid media.\nWe also examined iPTM and did not observe a correlation between iPTM and\nsuccessful rescue. We also generated a ML model to identify features that predicted\ngood pDockQ2 scores.\nLINE 262: Given the higher conservation of the 29 residues at the Poc4 and\nIrc25 dimerization interface, we first predicted the Poc4 and Irc25 dimer using\nAlphaFold3 and then designed the remaining 82 positions of Poc4 considering\nany residue type except cysteine. To do this, we used Frame2Seq, a state-of-the-\nart masked language model for sequence design36, which only considers the\npredicted backbone geometry of Poc4, and the predicted interaction with Irc25.\nWe wanted to achieve a level of sequence diversity comparable to natural\nvariation, so we used the default temperature parameter of 1.0 (Supplemental\nFigure 15A). We generated 5,000 designs, refolded each using AlphaFold2 and\nobserved that for the 82 variable residues, recovery of the native Poc4 sequence\nranged between 50-70 percent identity and 98.9% had an average pLDDT score\n> 90, suggesting the scaffold is designable by Frame2Seq (Supplemental Figure\n15A). While this level of divergence is less than the 20% sequence conservation\nfor S. cerevisiae to C. auris, to sample these sequences through unbiased deep\nmutational scanning would require testing > 25^19 = 3.6e25 sequences.\nLINE 283: From these, we sampled 70 sequences for closer inspection,\nchoosing 9 designs for experimental testing, with 61 to 64% sequence identity to\nC. auris Poc4 but without homology by BlastP to other proteins (Figure 5B). We\nfound that 7 of the designed proteins were able to be expressed in the ∆poc4\ndeletion background, with 3 of the 7 expressed designs showing significant\nrescue of thermotolerance at 42 °C and one with partial rescue (Figure 5C-E,\nSupplemental Figure 16A-B).\n- I do not quite understand the purpose of the UMAP analysis. What does it bring\ncompared to an analysis of sequence similarity of edit distances? Plus, are ESM2\nembeddings expected to be of good quality for designed sequences given that ESM2\nperforms very poorly in predicting thermodynamic stability changes upon mutations in\nde novo designed sequences (MEGA dataset)?\nResponse: In a multiple sequence alignment, adding thousands of designs to a tree\nmakes it unwieldy. The goal of the UMAP analysis was to look at these designs and\ntheir relatedness to the native proteins, potentially demonstrating the distinctness of the\nprotein designs. Given a representation of the space of all proteins, we would expect\nthat there is clustering based on sequence similarity and structure similarity which can\nbe captured in ESM2. We observe a clear Poc4 cluster and an Irc25 cluster. We then\nwanted to know whether our designs would ‘fill in the gaps’ of this sequence space. We\nagree that ESM2 is not fully sensitive to these changes, but to the extent that we can\nsee a distinct cluster of the designed structures compared to the native proteins, it is\nuseful. This suggests that our designs are fundamentally different, in some way, from\nnative proteins. We have added to the text to help clarify these points, but also moved\nthis projection to Supplemental Figure 15B. Additionally, we have included a new\nphylogeny of a subset of the designs to help highlight the sequence distances of these\ndesigns (FIGURE 5B).\nLine 275: To assess how the design sequences relate to naturally occurring\nPoc4 sequences, we leverage embedding sequences into the continuous space\nlearned by the ESM2 protein language model. In addition to the native C. auris,\nPoc4 and Irc25 sequences, and the re-designed Poc4, we also embedded the\northologous sequences identified through Foldseek and the POC3_POC4 pfam\nfamily (PF10448) and used UMAP to project the embedded representations to 2-\ndimensions. We observed clustering among the Poc4 homologs and among the\nIrc25 homologs. However, the designed structures appeared to be a distinct\ncluster (Supplemental Figure 15B), which gave us confidence that our designs were\ndistinct from natural Poc4 chaperones.\n- The statement \"In the absence of a change in structure...\" appears to require\nadditional experimental support.\nResponse: We have re-written to “In the absence of a predicted change in structure”.\nWe agree that experimental support, such as a new X-ray crystal, would be needed for\nthe original sentence, but this is beyond the scope of what we can add to this\nmanuscript.\nMinor comments:\n- Several figure legends in the Supplementary Material contain errors (e.g., Fig. S7)\nResponse: Thank you—we have fixed these errors.\n- What is the evolutionary conservation pattern for the three highlighted residues in Fig.\nS7? Pymol alignment suggests D90 in Sce corresponds to D62 rather than S63 in Cau\nResponse: Thank you for pointing this out —we agree that this is the better perspective\non the critical residues. The new supplemental figure 13 also highlights the evolutionary\nconservation pattern for the residues across Poc4. Importantly, the 5 residues with the\nhighest sequence conservation among yeast species are not the 3 residues that have\nbeen functionally implicated in the Poc4 protein’s chaperone activity in S. cerevisiae. To\navoid confusion, we have removed the previous Fig S7.\n- Brief explanations of Frame2Seq methodology and dockQ2 scoring rationale would\nbenefit non-expert readers\nResponse: Thank you for this suggestion. We have greatly expanded these sections,\nand included a new schematic.\nLINE 233: The pDockQ2 score summarizes the predicted alignment error\nfrom AlphaFold3 over the interface residues within 15 Å between proteins, with\nscores above 0.2 corresponding to ‘Acceptable’ docking as defined by Critical\nAssessment of Predicted Interactions (CAPRI) community34,35\nLINE 264: To do this, we used Frame2Seq, a state-of-the-art masked\nlanguage model for sequence design36, which only considers the predicted\nbackbone geometry of Poc4, and the predicted interaction with Irc25. We wanted\nto achieve a level of sequence diversity comparable to natural variation, so we\nused the default temperature parameter of 1.0 (Supplemental Figure 15A). We\ngenerated 5,000 designs, refolded each using AlphaFold2 and observed that for\nthe 82 variable residues, recovery of the native Poc4 sequence ranged between\n50-70 percent identity and 98.9% had an average pLDDT score > 90, suggesting\nthe scaffold is designable by Frame2Seq (Supplemental Figure 15A). While this\nlevel of divergence is less than the 20% sequence conservation for S. cerevisiae\nto C. auris, to sample these sequences through unbiased deep mutational\nscanning would require testing > 25^19 = 3.6e25 sequences.\n- The match rate of 1/3 for UniParc entries with the C. auris proteome seems low - could\nthis be clarified? (Note: \"UniPort\" typo on p.30)\nThank you for pointing out these typos, we have corrected them. There are 5,417\npredicted protein coding genes in C. auris, and we were able to identify structures for\n4,360 of these proteins. We initially identified 12,017 structures representing different\ngenome assemblies. This represents a 4/5 match rate, rather than a 1/3.\n- The methodology for determining conserved residues could be described\nResponse: Thank you for this suggestion. We have greatly expanded these sections\nand included new references.\nLine 933: Per-residue conservation scores were calculated from these\nalignments using the AL2CO method with the following settings: unweighted sequences,\nsum-of-pairs conservation method, BLOSUM62 scoring matrix without transformation,\nwindow size of 1, gap fraction of 0.5 70. Scores were visualized onto the C. auris Poc4\nand Irc25 AlphaFold3 models using ChimeraX.\n- Information on computational costs, particularly for structural prediction of 5,000\nsequences, would be valuable for reproducibility\nResponse: Thank you for this suggestion. This is a constraint, especially for the\nalphafold3 analysis, but is not generally limiting for generating the designs. We mention\nthis computational constraint in the text (Line 294).\n(Remarks on code availability)\nI reviewed the documentation and files in the repo, but did not attempt to run the code.\nReviewer #2 (Remarks to the Author):\nIn their manuscript, Rapala et al. report on a proteasome chaperone complex,\nPoc4-Irc25, showing high structural conservation but low sequence conservation. They\ncharacterize the function of this new protein directly in Candida auris, validating its\npredicted role in proteasome assembly and conserved physical interactions. The\nauthors then show that despite low sequence conservation, the Saccharomyces\ncerevisiae ortholog of Poc4 can complement the C. auris deletion. Finally, then use a\ngenerative model to create new proteins distant in sequence but with a conserved\nstructure and show that at least one of these artificial sequences can complement the\nC. auris deletion. Overall, I enjoyed the manuscript: I think the direct investigation of\nPoc4 function in C. auris was well done, considering the added difficulty of working in\nthis pathogen. The authors show convincingly the usefulness of a structure-based\napproach to cover blind spots in sequence alignment searches.\nResponse: Many thanks!\nOn the other hand, I am not entirely convinced by the framing the authors used\nregarding the structural and functional evolution of their model protein, as well as the\nrelevance of their synthetic homologs. Here are my comments:\n1. The authors state (lines 22-23), that structural conservation despite high sequence divergence in Poc4 is a case of neutral evolution. This is not demonstrated directly by the results: the only thing that is shown is that some molecular functions are\nmaintained, without any information in regard to the fitness effects of the changes. It\nwould take a lot more data to conclude with a good level of certainty that all these\nchanges were strictly neutral in terms of fitness and of other molecular properties that\nwere not measured.\nResponse: Thank you for this suggestion. We have re-worded to clarify this point.\nLINE 23: Despite the large sequence divergence, we demonstrate\nconservation of function across hundreds of millions of years of evolution. Our\nresults corroborate that specific folds, and not the sequences, are required for\nfunction and demonstrate that the extensive degeneracy in mapping of\nprotein sequence to structure enables deep functional conservation, even as\nsignals of sequency homology rapidly erode.\n2. Lines (120-125, 269-270): There might also be other non-structural constraints\non sequence evolution that explain the high rate of divergence: higher local mutation\nrates, or constraints on specific codons due to GC content or tRNA abundance. Was the\nrate of synonymous mutations the same as non-synonymous mutations?\nResponse: Thank you for this suggestion for other explanatory factors. We examined\nlocal mutation rates by looking at the genomic region surrounding Poc4 and do not\nobserve a consistent high rate (Supplemental FIGURE 5). The C. auris version of Poc4\nis more GC rich (53%) than the C. albicans protein (33%) or S. cerevisiae protein\n(40%). However, the C. auris version of Pup2 is 49% GC, the C. albicans Pup2 is 34%\nGC, and the S. cerevisiae Pup2 is 40% GC, suggesting that Poc4 in each genome is\nsimilar to other proteins in the genome. Therefore, we do not believe the GC content\ncan explain Poc4 evolutionary rates. The tRNA abundance is unknown at this moment.\nWe have re-worded to clarify this point.\nLINE 156: To examine the possibility that POC4 is in a specifically\nmutagenic locus, we examined the sequence divergence of genes near POC4.\nWe failed to observe high rates of sequence divergence among genes near the\nPOC4 locus, suggesting that this divergence is not due to its presence in a\nmutational hotspot (Supplemental Figure 5).\n3. Figure 2D: As mentioned by the authors, the switch from ScPoc4 to CauPoc4\nsequence homology matches correlates very well with the CTG clade. Is there any\nreason why this might be the case? Was this switch associated with a mutational burst\nin general?\nResponse: We agree that the switch is interesting. It is possible that the lack of gene\nflow in the CTG clade exacerbates the mutational rate. We have included this into the\nresults and discussion.\nLINE 147: The lack of mating and gene flow in the CTG clade can allow for rapid\ndrift. However, this is not the only cause of rapid evolution of the chaperones as\nthe higher rate of evolution among the chaperone proteins is not unique to any\nspecies lineage but is true across all taxa (Fig. 2D, E). Importantly, we also\nobserve that Poc4 appears to be evolving faster than its co-chaperone Irc25\nwithin the CTG clade (Figure 2E, Supplemental Figure 2D).\nLINE 381: This may be additionally exacerbated in the CTG clade, as many of\nthese organisms do not regularly mate and allow for gene flow and\nrecombination; however, the long branch lengths in close relatives to S.\ncerevisiae, which do undergo mating and recombination, suggests it is not the\nonly factor47.\n4. Lines (120-125): The phylogeny shown does not clearly support the author's\nstatement on faster evolution of Poc4 vs Irc25, except for a subset of CTG clade\nspecies. A more quantitative measurement would be better.\nResponse: We have now added a quantitative measure of evolutionary rate\n(SUPPLEMENTAL FIGURE 2D). This more quantitative analysis shows that Reviewer\n2 is correct: among CTG species, Poc4 evolves more rapidly than Irc25 (Mann-Whitney\nU test, p = 0.05) and both proteasome chaperones evolve more rapidly than Pup2\n(Mann-Whitney U test, p < 0.001 for both). Collectively, the changes in the text better\nreflect the data and we believe collectively strengthen the broader claim that different\nparts of the proteasome machinery can evolve at different rates and create to certain\ncomponents becoming undetectable by sequence homology-based methods.\nLINE 150: Importantly, we also observe that Poc4 appears to be evolving faster\nthan its co-chaperone Irc25 within the CTG clade (Figure 2E, Supplemental\nFigure 2D).\n5. The structure of the S. cerevisiae Poc4-Irc25 complex has been solved\nexperimentally (Yashiroda et al, PMID 18278057). Is there a reason why the authors\nused the AlphaFold prediction instead of the solved structure? Any major differences\nbetween the prediction and the known structure?\n7. Figure 4: the Poc4-Irc25-Pup2 complex has also been solved (Yashiroda et al,\nPMID 18278057). Please validate the AlphaFold predictions and comment on any\nchanges observed. The structure of the PSMG3-PSMG4 complex has also been solved\n(Satoh et al, PMID 31067643) and might also prove useful regarding how function is\nconserved via structure.\nResponse: As there is no structure for the C. auris version, and to maintain consistency\nin the analysis, we used the AF predicted structure. However, we have added\nSupplemental Figure 12A to show that there is a strong overlap between the AF\npredicted model and solved structures for the S. cerevisiae complex. We have also\nupdated the text to show RMSD differences between structures.\nLINE 206: Starting with the S. cerevisiae complex as a baseline, we\nobserved high predicted structural quality and similarity with the subset of the\nlarger proteasome complex experimentally characterized by cryo-electron\nmicroscopy31–33 (Supplemental Figure 10A-B, ipTM = 0.78, RMSD = 1.159 Å to\n9D0T) and the Irc25-Poc4-Pup2 complex (RMSD = 0.646 Å to PDB: 2Z5C). This\nhelped build confidence that the computationally predicted structure recapitulates\nnative structures, and thus the quality of the prediction for the C. auris\nsequences. Using the same parameters, we folded the C. auris proteasome\ncomplex and also observed high predicted structural quality and structural\nsimilarity with the S. cerevisiae proteasome complex (Figure 4A, Supplemental\nFigure 11A, ipTM = 0.81, RMSD = 1.331 Å). Furthermore, we observe high\nstructural similarity between our predictions of the C. auris Irc25-Poc4-Pup2\ncomplex and experimental structures from S. cerevisiae and H. sapiens, giving\nus confidence in our ability to model these higher order interactions\n(Supplemental Figure 12).\n6. Additionally, some of the observations made here by the authors echo what\nhad been observed for the relationship between S. cerevisiae Irc25 and human PSMG3\n(aka PAC3), which also shows very low sequence identity but high structural similarity\n(Yashiroda et al, PMID 18278057). Interestingly, both Poc4 and Irc25 showed similar\nlevels of similarity to PSMG3. I think this should be discussed in the text and might point\ntowards Poc4 and Irc25 being highly diverged paralogs. Is there any evidence for this?\nNo need to fully address the question in this manuscript, just food for thought.\nResponse: We agree that this is an interesting point. We considered this, especially\ndue to the lack of synteny of Poc4, but had not previously included it in the manuscript\ndue to space constraints. This has been added to the text\nLINE 136: The similarity in structure between Irc25 and Poc4 and the human\nproteasome assembly chaperone protein PSMG3 also brings up the possibility\nthat Poc4 and Irc25 are highly diverged paralogs in the CTG clade.\n9. Lines 172-173: ref 25 (Takagi et al) performed alanine scanning of residues\nrequired for Poc4 binding to Pre6 (the alpha-4 subunit) binding, not Pup2 (alpha 5) if I\nunderstand their figure 3 correctly.\nWe thank the review for this clarification. We have removed the figure to prevent\nconfusion. As mentioned to reviewer 1, The new supplemental figure 13 also\nhighlights the evolutionary conservation pattern for the residues across Poc4.\nImportantly, the 5 residues with the highest sequence conservation among yeast\nspecies are not the 3 residues that have been functionally implicated in the Poc4\nprotein’s chaperone activity in S. cerevisiae.\n10. Also Figure 4: Was there any rationale behind folding the entire proteasome\ncore particle instead of just Poc4-Irc25-Pup2? Is the average ipTM of the subcomplex\nsimilar to the rest, or higher/lower?\nWe hypothesized that interactions between additional subunits would impact the\nPoc4-Irc25-Pup2 interactions and would better represent the mechanism of proteasome\nassembly. As mentioned in our response to reviewer 1, we did not observe any\ndifferences in ipTM across the complex in respect to the Poc4-Irc25-Pup2 chains. In\ngeneral, the ipTM scores of the different complexes were consistently around 0.8 and\nwe did not observe a correlation between ipTM and degree of rescue.\n8+11. I was not convinced by the author’s idea that the artificial sequences\ngenerated by the authors were distinct from natural Poc4 homologs. In their design\nprocess, they fix 29 residues (the Poc4-Irc25 interface as well as the cysteine residues).\nThis means that the resulting sequences should have at minimum 29/111 = 26%\nidentity. This is higher than what exists with the S. cerevisiae homolog, which they show\ncan complement. The 1/5 sequence that does complement has ~60%, much higher\nthan that. What fraction of these fixed residues are also at or near the Poc4-Pup2\ninterface? And are these residues evolving more slowly in general? Figure 4: Please\nconsider providing a colormap showing residue conservation on both Poc4 and Irc25\nstructures.\nResponse: We thank the reviewer for this suggestion. The UMAP (now Supplemental\nFigure 15B) suggests that the designed structures are distinct from the natural proteins,\nas described above for Reviewer 1. We have included additional text to highlight this\npoint.\nWe also tested an additional set of designed proteins for their ability to rescue and\nidentified three additional designs that are functional. The fixed residues in the design\nare between the Poc4 and Irc25 interface, and we did not fix the residues that are\nanticipated to interact with Pup2. To look at whether these residues are evolving more\nslowly, we used the approach from Kennard 2024 Current Biology to highlight the rate\nof evolution on the structure. This shows that the conserved residues are at the\ninterface with Poc4 and Irc25 and not with Pup2 (SUPPLEMENTAL FIGURE 13)\nLINE 275: To assess how the design sequences relate to naturally occurring\nPoc4 sequences, we leverage embedding sequences into the continuous space\nlearned by the ESM2 protein language model. In addition to the native C. auris,\nPoc4 and Irc25 sequences, and the re-designed Poc4, we also embedded the\northologous sequences identified through Foldseek and the POC3_POC4 pfam\nfamily (PF10448) and used UMAP to project the embedded representations to 2-\ndimensions. We observed clustering among the Poc4 homologs and among the\nIrc25 homologs. However, the designed structures appeared to be a distinct\ncluster (Supplemental Figure 15B), which gave us confidence that our designs were\ndistinct from natural Poc4 chaperones.\n12. Data from Le Tallec et al (PMID 17707236) suggests that the murine\northologs of PSMG3-PSMG4 stabilize one another, as knockdown of either one\ndecreased the abundance of the other. Has this been shown in yeast? If so, this might\nmake Irc25 binding as important as Pup2 or Pre6 binding in terms of molecular function.\nResponse: We thank the reviewer for this suggestion. We generated the strains and\nshowed that lack of one of the chaperones does not impact the levels of the other at the\nprotein level (Supplemental Figure 8). This has been added to the text.\nLINE 189: We also do not see differences in protein expression of either Poc4 or\nIrc25 upon deletion of the reciprocal co-chaperone, unlike murine PAC3 and\nPAC4 expressed in HEK293T cells23 (Supplemental Figure 8).\n13. Most importantly, while interesting, the synthetic sequence approach does\nnot contribute to understanding why this protein complex can tolerate such high levels\nof sequence divergence. Using highly diverse synthetic sequences to determine what\nresidues or properties are important to maintain function would be an interesting\napproach, but the authors do not push their analysis far enough. There is not enough\ninformation presented on what substitutions were made and where they occurred in the\nstructure to understand why one sequence worked, while the others failed. As it stands,\nI don’t think this experiment provides any concrete biological insights that were not\nalready discernible from the S. cerevisiae complementation experiment. I think the\nauthors should perform additional experimental and computational work to really\ndissect the molecular mechanisms at play here using this approach to justify its inclusion in the\nmanuscript.\nResponse: We thank the reviewer for this suggestion. We have expanded our tests of\ndesigns to more fully examine the relationship between docking of the dimer with the\nproteasome, and were able to identify three additional artificial chaperones that were\nable to complement the mutant strain. Using a ML model, we were able to identify\nsequence features that were associated with good pDockQ2 scores and function. To\nexplore this idea fully, we have generated a new Figure 6.\nLINE 291: That some, but not all, designs were able to rescue ∆poc4\nsuggested the structural features of the Poc4 fold substantially contribute to but\ndo not fully explain the functional constraints on Poc4. During the design, we\nselected for interaction with Irc25 but not the rest of the proteasome. We\nhypothesized that examining Poc4 in the context of the remainder of the 20S\nproteasome would identify structural determinants that would allow for Poc4\nfunction. Due to computational constraints, we used AlphaFold Server to predict\nthe structure of 466 designs in complex with the 20S proteasome subunits, and\nthen computed the max pDockQ2 score between Poc4 and Pup2. We observed\nthat median score was 0.05 and only 41 (8.7%) had scores above the previously\npublished threshold of 0.234 (Figure 6A). To enrich for designs with better\npDockQ2 scores, we trained a regression model to predict pDockQ2 based on\nESM2 embeddings of the Poc4 designs using H2O AutoML. Using this ML\npredictor, we selected an additional 131 top scoring designs to fold with the\nAlphaFold Server, and observed a median pDockQ2 of 0.13 and 33 with\npDockQ2 > 0.2 (FIG 6A, Sup Fig 17A).\nTo identify the most important interactions , we first computed PLiP\ninteraction features37, summarized as counts across all Pup2 residues by 8\ninteraction types, yielding 77 features. We then trained a regression-ML model to\npredict the pDockQ2 scores from the interaction features and estimated the top\nSHAP features. The top features were hydrophobic interactions with Pup2\nresidues 94, 97, and 101, followed by polar interactions with residues 101 and\n102 (Figure 6B, Sup Fig 17B-C). Inspecting these features for the wildtype C.\nauris and S. cerevisiae complexes and the 7 tested designs, we found that for\nthe wildtype and designs that fully or partially recover function, sheets 5 and 6 of\nPoc4 (Res41-Res58) packs against helix-2 of Pup2 (Res83-Res102), thus\nallowing K24 and Y44 in WT-Poc4 and the Poc4 designs to form H-bonds with\nthe C-terminal backbone carbonyl of helix-2 of Pup2 (Y102 and D104,\nrespectively) (Figure 6C-F). To quantify this observation, we defined the Pup2-\nPoc4 packing distance to be the distance between the C-terminal of helix-2 Pup2\n(A83, Cα) and the C-terminal of helix-2 of Poc4 (Res63/Cα). Plotting the\npDockQ2 against packing distance, we see a spearman rank correlation of -.65\n(Figure 6G), suggesting that tight packing is a requirement for good pDockQ2\nscores.\nWe have also expanded our discussion to clarify our goals from this approach:\nLINE 391: To explore this unsampled or otherwise evolutionarily\ninaccessible protein space, we leverage recent advances in protein design and\nprospective testing to evaluate the sufficiency of a specific fold to fulfill a function\nrequired for cellular survival.\nLINE 401: Through total protein re-design, it is possible to explore\nepistatic relationships between amino acids and potentially access high fitness\nvariants that are unlikely to emerge through stepwise evolutionary approaches.\nThis approach expands the sequence space of functional proteins beyond what\ncan be achieved through deep mutational scanning or natural and lab evolution\nof new traits and functions, as these single-step approaches can be limited by\nconstraints imposed by epistatic interactions within the protein 15,59,60\nLINE 433: It is also possible that redesign is only possible for proteins that\nalready show high rates of sequence divergence between organisms—there may\nbe higher degeneracy between sequence and structure in such proteins, making\nit possible for many alternative sequences to encode the same structure without\nincurring fitness costs.\nReviewer #3 (Remarks to the Author)\nThis is an interesting paper by O’Meara and colleagues, using proteasome chaperone\nproteins in Candida auris to explore the constraints of sequence-structure-function\nrelationships in protein evolution. To do this, the others first perform phylogenetic\nanalysis of divergent sequences separated by vast evolutionary time, and then design\nartificial proteasome chaperones to maintain a conserved structure and rescue mutant\nphenotypes.\nThe work is well executed, and the manuscript is well written, leading to the conclusion\nthat protein folds remain conserved over substantive evolutionary time, and that it is the\nfold rather than sequence that is driving function.\nWhile this is an interesting conclusion, it is not novel. As just some exmaples,\nBetts and colleagues showed that at the gene level, there are cases where gene\nstructures remain similar even with minimal protein sequence similarity, and where\nsequence alignment is only possible by using protein tertiary structures (Betts et al.,\nEMBO J. 20 (2001), 5354). Thornton showed that enzymes with diverged functions\nmaintain regions of highly conserved active site structure (Riziotis et al., J. Mol. Biol.\n435 (2023), 168254). Tsonis and colleagues perform detailed analysis of three-\ndimensional structure conservation in non-homologous/unrelated proteins, arguing that\nconservation of three-dimensional structure might be more important than the primary\namino acid sequence (Sousounis et al., Hum. Genomics 6 (2012), 10). Fu and\ncoworkers demonstrate from proteome-wide structural analysis that structure remains\nhighly conserved across distant species, also pointing out with appropriate references\nthat the fact that protein structure is more conserved than primary amino acid sequence\nand is the determinant of biological function is well accepted (see Zhang et al., 33\n(2023), 1975, and references cited therein). There are numerous examples from\nancestral sequence reconstruction that show that structure is highly conserved across\nbroad evolutionary time, and dictates functon(Choi and Kim, Proc. Natl. Acad. Sci. USA\n103 (2006), 14056; Merkl and Sterner, Biol. Chem. 397 (2015), 1; Risso et al., Nat.\nCommun. 8 (2017), 16113, among others).\nI still believe the work is\ninteresting as a case study,\nand is valuable as a\nshowcase of what we can\nlearn from protein design.\nThe key insights that it\nprovides, however, are not\nnovel, beyond providing\ninsight into structure-\nfunction relationships in\nthese specific chaperones,\nas the broader conclusions\nare well established in the\nfield. As such, this work is\nmore suited to a specialist\njournal rather than the\nbroad readership of Nature\nCommunications.\nResponse:\nThe reviewer\ncorrectly points out that several ancestral reconstruction studies have found structure to\nbe conserved over broad evolutionary time. However, we believe studies using\nancestral sequence reconstruction in fact highlight the value of the work we have\nundertaken here for two reasons.\nFirst, ancestral sequence reconstruction can only be done using homologous\nproteins in which the rate of sequence evolution (in terms of AA substitutions/site) is\nsufficiently slow such that the amino acid states at most sites can be confidently\ninferred. The preservation of sequence similarity in the evolutionary interval of interest is\na pre-requisite for high-confidence statistical inferences of ancestral sequences. The\nproteasome chaperones that are the subject of our study are in the category of\nmolecules that remain recalcitrant to the ASR framework because of their rapid rate of\nsequence evolution.\nTo demonstrate this, we reconstructed specific ancestral sequences using our\nalignment and the best-fit model of sequence evolution (as determined by AIC) and\nquantified the statistical confidence of inferred ancestral sequences for Poc4 (rapidly\nevolving proteasome chaperone) vs Pup2 (slow evolving core component). The results\ndemonstrate the limitation of ASR for studying rapidly evolving proteins—for example,\nancestral Poc4 sequence predicted to have existed in the common ancestor of the\npathogens C. auris and C. lusitaniae has 99/142 sites that are inferred as ambiguous\n(e.g., posterior probability of the maximum likelihood amino acid state < 0.8). The mean\nposterior probability across the inferred ancestral sequence is 0.55. Ancestral\nsequences that are reconstructed with such low confidence are generally not\nsynthesized for downstream experimental study. In contrast, the ancestral Pup2\nsequence from the same ancestor has only 4/233 ambiguous sites and the mean\nposterior probability across the inferred ancestral sequence is 0.975—the high\nconfidence with which this ancestral sequence can be reconstructed reflects its slower\nrate of evolution. Such slowly evolving proteins generally tend to be the subject of\nancestral reconstruction studies because the reliability of all downstream inferences\nabout protein functional evolution depend on the statistical confidence with which the\nsequences of the historical intermediates can be inferred.\nSecond, there are numerous cases of conservation of structure with divergence\nin function. Some examples are studies mentioned in Janet Thornton’s work, including\nthe specific paper referenced by the reviewer. Such cases are also found across ASR\nstudies, in which very few substitutions change the specificities of proteins (Siddiq et al.\n2017, Current Opinion in Structural Biology) or of their assemblies into complexes (\nPillai et al. 2022, Protein Science), while overall structural similarity between the functionally\ndistinct homologs largely remains. Directed evolution studies also suggest that broad\nstructural conservation of the type detected from solved structures or prediction\nmethods miss certain types of biochemical and cellular divergence—for example,\ndirected evolution of a NicA2 enzyme led to increased activity by 4 orders of magnitude\nwhile the structures of the initial and evolved proteins remained largely identical\n(Dulchavsky et al. 2023, Nat. Chem. Bio). In this case, the functionally important\nsubstitutions changed the structural dynamics of the proteins, something that largely\nremains beyond the realm of structure-based homology inference methods. As part of\nthis, we would argue that our experimental testing of chaperone function is especially\nimportant.\nWe want to emphasize again that this project’s key contributions are\ndemonstrating how recent advances a) enable structure-based methods to aid\nfunctional discovery in regions of sequence-structure space that were previously\nproblematic, b) expands the utility of sequence information in non-model systems – this\nallows structure/function information to try and keep pace with sequencing approaches,\nand c) enable experimental testing of predictions about sequence-structure-function\nrelationships using de novo design strategies and genetic experiments in the cellular\nenvironment. This work represents the first case where a designed protein replaces a\nnative functional protein in the cell, which is a key advance in protein design.\nImportantly, we have added additional experiments to show that it is not just the\nstructure of the monomer that is important, it is the structure of the entire protein\ncomplex. We were able to use this ML model to add additional filters to increase the\nchance of generating good pDockQ2 scores and thus functional proteins. This is a\ndemonstration of how the tools developed for protein docking can be used for\nprospective protein design.\nAdditionally, we want to highlight that proteasome assembly is critical for\neukaryotes and recent work on their structure and function were published in high\nimpact papers; the biology of these specific chaperones is of broad interest."}, {"round": 2, "reviewer_comments": {"reviewer_1": "The authors have satisfactorily addressed my concerns, I therefore recommend publication of the manuscript.", "reviewer_2": "I thank the authors for taking the time to review and address my comments on their manuscript. Most of my comments on the first sections of the manuscript were addressed satisfactorily. Here are my comments on the response to the points I previously raised and the updated text.\nComments 2.5 and 2.7: The new figure S12 provides a useful comparison with the solved structures, but are not really discussed in the text. Just providing RMSD across the entire complex does not provide any information on where the AF fold might diverge. Please actually discuss this instead of only providing the structural alignment. As an additional note, the supplementary material in the source file had very low resolution on my end, which might only be due to manuscript file processing but might be worth checking on the authors’ end as well.\nComment 2.6: My initial comment might have been unclear and should probably been split into two parts, the first re: the structural homology of s. cerevisiae Poc4/Irc25 with human PSMG3 despite high sequence divergence, and the second re: the potential paralog relationship between Poc4 and Irc25. While I agree the second part can definitely be considered outside the scope of this manuscript, I would have liked the authors to discuss the first part more.\nOne of the main messages of the manuscript is that structural alignment can overcome the limitations of sequence alignment for proteins evolving rapidly, using Poc4 as a representative test case. This is shown by the high confidence with which AF predicts C. auris Poc4 structure and how its fold provides a better prediction of function conservation compared to sequence alignment. However, in the specific case of Poc4, crystal structures of highly divergent homologs showing a conserved fold were presumably included in the AF training dataset (as they were deposited pre 2018), potentially providing a lot of information to the model that would not be available for most other protein families. I think this limitation of Poc4 as a model should be discussed in the manuscript, as it might provide reasons to think the approach is not as generalizable as suggested by the author.\nComment 2.8+11: The interface of Poc4 and Irc25 appears to overlap with their respective interface with Pup2. Are the authors certain that no residues they fixed are involved in both interfaces? Interpreting figure S13 is made difficult because of the absence of Pup2.\nComment 2.13: I think the addition of the docking analysis adds some new biological insights to the manuscript, even if the observations were not directly validated experimentally afterwards. As I mentioned in my first review, I think the first parts of the manuscript form a cool story that stands on its own. However, I am still not convinced by the relevance of the synthetic sequences as they were used here. As stated by the authors, the strength of these generative approaches is that they can allow for the exploration of larger sequence spaces, which would suggest they should be paired with high-throughput approaches to dissect the contributions of different features. Here, only seven sequences were tested experimentally. The limiting factor for this was probably how difficult it is to manipulate C. auris in the lab and generate mutants at a reasonable pace. C. auris is just not a very good model for this type of experiment with the currently available genetic manipulation toolbox. From my point of view, at this point in the story, synthetic sequences designed starting from scPoc4 or CauPoc4 would be equally suited to answer their questions, and the authors could have generated much more comprehensive results in S. cerevisiae.", "reviewer_3": "I appreciate the authors' response to my comments. I do believe the manuscript is well-executed and interesting; I still consider the novelty to be mainly of interest to specialists in the field, and not of the level of advance I would have expected to see in Nature Communications.", "reviewer_4": "I co-reviewed this manuscript with one of the reviewers who provided the listed reports. This is part of the Nature Communications initiative to facilitate training in peer review and to provide appropriate recognition for Early Career Researchers who co-review manuscripts.\nThe code is accesible and can be installed easily, it works and I just made a couple of tests. Everything looks ok."}, "author_response": "Reviewer #2 (Remarks to the Author)\nComments 2.5 and 2.7: The new figure S12 provides a useful comparison with the solved structures,\nbut are not really discussed in the text. Just providing RMSD across the entire complex does not\nprovide any information on where the AF fold might diverge. Please actually discuss this instead of\nonly providing the structural alignment. As an additional note, the supplementary material in the\nsource file had very low resolution on my end, which might only be due to manuscript file processing\nbut might be worth checking on the authors’ end as well.\nResponse: We thank the reviewer for this point and acknowledge that there are regions in the\nstructure with higher divergence in the AF model. Specifically, there are loop regions and disordered\ndomains among alpha subunits that are omitted from the experimental structures and AF3 does a\npoor job of predicting. Residues not present in the experimental structures are excluded from the\nRMSD calculation. Additionally, we also noticed the low resolution in Figure S12 and have fixed this\nissue and thank the reviewer for catching this.\nLINE 217: Although we observe discrepancies between the AF3 and experimental structures\nregarding loops and disordered regions, none of these regions are in the Pup2-Poc4-Irc25\nsubcomplex.\nComment 2.6: My initial comment might have been unclear and should probably been split into two\nparts, the first re: the structural homology of s. cerevisiae Poc4/Irc25 with human PSMG3 despite\nhigh sequence divergence, and the second re: the potential paralog relationship between Poc4 and\nIrc25. While I agree the second part can definitely be considered outside the scope of this\nmanuscript, I would have liked the authors to discuss the first part more.\nOne of the main messages of the manuscript is that structural alignment can overcome the limitations\nof sequence alignment for proteins evolving rapidly, using Poc4 as a representative test case. This is\nshown by the high confidence with which AF predicts C. auris Poc4 structure and how its fold\nprovides a better prediction of function conservation compared to sequence alignment. However, in\nthe specific case of Poc4, crystal structures of highly divergent homologs showing a conserved fold\nwere presumably included in the AF training dataset (as they were deposited pre 2018), potentially\nproviding a lot of information to the model that would not be available for most other protein families. I\nthink this limitation of Poc4 as a model should be discussed in the manuscript, as it might provide\nreasons to think the approach is not as generalizable as suggested by the author.\nResponse: We agree with this comment that in protein families where a crystal structure has not\nbeen solved, this approach may not be feasible. Our analysis was limited to those that have high\nconfidence structures, and as the AF training sets are updated, we would anticipate that future work\nwould be able to capture these relationships. We have updated the discussion to better reflect this\nlimitation.\nLINE 415: Additionally, our ability to generate high-confidence AlphaFold models of the C.\nauris Poc4 structure is due to experimentally determined structures of divergent homologs with\nconserved folds present in the AlphaFold training data. This bias may limit the feasibility of our\napproach for other protein families where a representative crystal structure has not been solved.\nComment 2.8+11: The interface of Poc4 and Irc25 appears to overlap with their respective interface\nwith Pup2. Are the authors certain that no residues they fixed are involved in both interfaces?\nInterpreting figure S13 is made difficult because of the absence of Pup2.\nResponse: There is a slight overlap between the Poc4-Irc25 interface and the Poc4-Pup2 interface.\nAs experimental mutagenesis and binding assays across this protein has not been performed, we\ncannot rule out for certain that the residues we fixed are involved in both interfaces. As noted in\nFigure 6, we observe packing of sheets 5 and 6 of Poc4 (Res41-58) against Helix 2 of Pup2 (Res83-\n102). As we fixed residues 42, 44, 55-58, it is possible that these residues contribute to binding to\nboth Pup2 and Poc4.\nComment 2.13: I think the addition of the docking analysis adds some new biological insights to the\nmanuscript, even if the observations were not directly validated experimentally afterwards. As I\nmentioned in my first review, I think the first parts of the manuscript form a cool story that stands on\nits own. However, I am still not convinced by the relevance of the synthetic sequences as they were\nused here. As stated by the authors, the strength of these generative approaches is that they can\nallow for the exploration of larger sequence spaces, which would suggest they should be paired with\nhigh-throughput approaches to dissect the contributions of different features. Here, only seven\nsequences were tested experimentally. The limiting factor for this was probably how difficult it is to\nmanipulate C. auris in the lab and generate mutants at a reasonable pace. C. auris is just not a very\ngood model for this type of experiment with the currently available genetic manipulation toolbox. From\nmy point of view, at this point in the story, synthetic sequences designed starting from scPoc4 or\nCauPoc4 would be equally suited to answer their questions, and the authors could have generated\nmuch more comprehensive results in S. cerevisiae.\nResponse: We too acknowledge the limitations of our system, but hope that the experimental\nframework that we have describe here will inspire others in more tractable systems."}]

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