Methodology To Probe Subunit Interactions in Ribonucleotide Reductases

Ribonucleotide reductases (RNRs) catalyze the conversion of nucleotides to deoxynucleotides, providing the monomeric precursors required for DNA replication and repair. <i>Escherichia coli</i> RNR is a 1:1 complex of two homodimeric subunits, α2 and β2. The interactions between α2 and β2 are thought to be largely associated with the C-terminal 20 amino acids (residues 356−375) of β2. To study subunit interactions, a single reactive cysteine has been introduced into each of 15 positions along the C-terminal tail of β2. Each cysteine has been modified with the photo-cross-linker benzophenone (BP) and the environmentally sensitive fluorophore dimethylaminonaphthalene (DAN). Each construct has been purified to homogeneity and characterized by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS−PAGE) and electrospray ionization mass spectrometry (ESI-MS). Each BP-β2 has been incubated with 1 equiv of α2 and photolyzed, and the results have been analyzed quantitatively by SDS−PAGE. Each DAN-β2 was incubated with a 50-fold excess of α2, and the emission maximum and intensity were measured. A comparison of the results from the two sets of probes reveals that sites with the most extensive cross-linking are also associated with the greatest changes in fluorescence. Titration of four different DAN-β2 variants (351, 356, 365, and 367) with α2 gave a <i>K</i>_d ≈ 0.4 μM for subunit interaction. Disruption of the interaction of the α2–DAN-β2 complex is accompanied by a decrease in fluorescence intensity and can serve as a high-throughput screen for inhibitors of subunit interactions

ClinVar CFTR variant data.

Variants in the cystic fibrosis transmembrane conductance regulator gene (CFTR) result in cystic fibrosis–a lethal autosomal recessive disorder. Missense variants that alter a single amino acid in the CFTR protein are among the most common cystic fibrosis variants, yet tools for accurately predicting molecular consequences of missense variants have been limited to date. AlphaMissense (AM) is a new technology that predicts the pathogenicity of missense variants based on dual learned protein structure and evolutionary features. Here, we evaluated the ability of AM to predict the pathogenicity of CFTR missense variants. AM predicted a high pathogenicity for CFTR residues overall, resulting in a high false positive rate and fair classification performance on CF variants from the CFTR2.org database. AM pathogenicity score correlated modestly with pathogenicity metrics from persons with CF including sweat chloride level, pancreatic insufficiency rate, and Pseudomonas aeruginosa infection rate. Correlation was also modest with CFTR trafficking and folding competency in vitro. By contrast, the AM score correlated well with CFTR channel function in vitro–demonstrating the dual structure and evolutionary training approach learns important functional information despite lacking such data during training. Different performance across metrics indicated AM may determine if polymorphisms in CFTR are recessive CF variants yet cannot differentiate mechanistic effects or the nature of pathophysiology. Finally, AM predictions offered limited utility to inform on the pharmacological response of CF variants i.e., theratype. Development of new approaches to differentiate the biochemical and pharmacological properties of CFTR variants is therefore still needed to refine the targeting of emerging precision CF therapeutics.</div

AlphaMissense prediction of CFTR variants of unknown significance (VUS).

A. Conservation of residue in CFTR mapped on the structure (PDBID 5UAK) [25,26]. The abundance of green, representing low conservations scores in the TMDs stands in notable contrast the AM score predictions of pathogenicity in the TMDs. B. An overlay of the active state CFTR (PDB ID 6MSM) [30] and the AlphaFold prediction for CFTR [29] showing nearly perfect alignment of all resolved residues (1–409,435–637, 845–889, 900–1173, 1202–1451). We calculated the root mean squared deviations (RMSD) of carbon backbone atoms between these two models in Chimera and found an RMSD of just 2.5 Å. C. Variants of unknown significance (VUS) displayed on CFTR structure (PDBID 5UAK) [25] demonstrates all unknown variants are in the transmembrane domains. Benign predicted mutations are shown in green, ambiguous predicted mutations in grey, and pathogenic predicted mutations are shown in purple. The two pathogenic predicted mutations both occur in transmembrane helix 8 (TH8) shown in orange. D. Receiver operating characteristic curve for AlphaMissense predictions of 115 Clinvar variants presented in the AlphaMissense benchmark. The average performance between pathogenic and benign variants is 95.8% as previously presented [21]. E. Receiver operating characteristic curve for AlphaMissense predictions of 209 variants downloaded directly from Clinvar [24], including 96 overlapping variants from the AlphaMissense benchmark. Again, the average performance is 95.8%. F. Receiver operating characteristic curve for AlphaMissense predictions of 113 variants downloaded directly from Clinvar [24] that did not overlap with variants from the AlphaMissense benchmark. Despite, not being trained on these ClinVar data, average performance is 95.8%. G. Overlap between AlphaMissense ClinVar benchmark set and our extended ClinVar set–showing 115 variants from AM and an additional 113 variants considered in F. Performance of AlphaMissense is very good across all permutations of ClinVar data considered. H. Due to the high number of VUS predictions in ClinVar6 for CFTR missense mutations, we plotted the AlphaMissense score for all 1277 VUSs in ClinVar. We show 728 benign, 181 ambiguous, and 368 pathogenic variants as predicted by AM. Data is available in S2 Table. (TIF)</p

Deep mutational scanning CFTR data.

Variants in the cystic fibrosis transmembrane conductance regulator gene (CFTR) result in cystic fibrosis–a lethal autosomal recessive disorder. Missense variants that alter a single amino acid in the CFTR protein are among the most common cystic fibrosis variants, yet tools for accurately predicting molecular consequences of missense variants have been limited to date. AlphaMissense (AM) is a new technology that predicts the pathogenicity of missense variants based on dual learned protein structure and evolutionary features. Here, we evaluated the ability of AM to predict the pathogenicity of CFTR missense variants. AM predicted a high pathogenicity for CFTR residues overall, resulting in a high false positive rate and fair classification performance on CF variants from the CFTR2.org database. AM pathogenicity score correlated modestly with pathogenicity metrics from persons with CF including sweat chloride level, pancreatic insufficiency rate, and Pseudomonas aeruginosa infection rate. Correlation was also modest with CFTR trafficking and folding competency in vitro. By contrast, the AM score correlated well with CFTR channel function in vitro–demonstrating the dual structure and evolutionary training approach learns important functional information despite lacking such data during training. Different performance across metrics indicated AM may determine if polymorphisms in CFTR are recessive CF variants yet cannot differentiate mechanistic effects or the nature of pathophysiology. Finally, AM predictions offered limited utility to inform on the pharmacological response of CF variants i.e., theratype. Development of new approaches to differentiate the biochemical and pharmacological properties of CFTR variants is therefore still needed to refine the targeting of emerging precision CF therapeutics.</div

AlphaMissense prediction correlations with cystic fibrosis patient pathogenicity metrics by diagnosis.

A. AM score plotted against sweat chloride levels in milliequivalents per liter (mEq/L) for 85 missense variants classified as CF causing. The linear correlation (Pearson Coefficient r = 0.21, Spearman Coefficient ρ = 0.33) is reduced compared to the complete data set correlation shown in Fig 2A. B. AM score plotted against sweat chloride levels for 33 missense variants classified as variants of variable clinical consequence (VVCC). The linear correlation (Pearson Coefficient r = -0.12, Spearman Coefficient ρ = -0.11) is statistically insignificant. C. AM score plotted against pancreatic insufficiency rates in percent for 83 missense variants classified as CF causing. The correlation (Pearson Coefficient r = 0.32, Spearman Coefficient ρ = 0.44) was similar to the entire dataset in Fig 2B. D. AM score plotted against pancreatic insufficiency rates for 30 missense variants classified as VVCC. The correlation for these data (Pearson Coefficient r = -0.21, Spearman Coefficient ρ = -0.22) was statistically insignificant. E. AM score plotted against pseudomonas infection rates for 82 missense variants classified as CF-causing. Linear correlation is reduced compared to the entire data set presented in Fig 2C (Pearson Coefficient r = 0.33, Spearman Coefficient ρ = 0.36). F. AM score plotted against pseudomonas infection rates in percent for 28 missense variants classified as VVCC. Linear correlation was insignificant (Pearson Coefficient r = 0.13, Spearman Coefficient ρ = 0.28). (TIF)</p

AlphaMissense correlation with CFTR <i>in vitro</i> data from spatial covariance study.

A. Spatial covariance data from a previous study [46] for 62 missense variants plotted against AlphaMissense scores. Y axis represents the trafficking index as measured by a western blot trafficking assay when HEK293T cells were incubated at 37 ºC. A slight inverse linear correlation was observed (Pearson Coefficient r = -0.46, Spearman Coefficient ρ = -0.44). B. Spatial covariance data for 62 missense variants using the same trafficking index in A. except at 27 ºC, plotted against AlphaMissense scores. Again, an inverse linear correlation was observed (Pearson Coefficient r = -0.48, Spearman Coefficient ρ = -0.49) albeit slightly higher than at 37 ºC. C. AlphaMissense scores correlated with the spatial covariance data but using chloride conductance index described in [46], which measured channel activity at 37 ºC. We observed an increased correlation (Pearson Coefficient r = -0.58, Spearman Coefficient ρ = -0.54). D. AlphaMissense scores correlated with chloride conductance index at 27 ºC. We observed a slight correlation (Pearson Coefficient r = -0.50, Spearman Coefficient ρ = -0.53). (TIF)</p

Alternative prediction method performance and dataset overlap.

A. Receiver operating characteristic curve for ESM predictions [39] of 169 CFTR missense variants including 110 CF causing, 41 variable clinical consequence (VVCC), and 18 non-CF causing variants. For the pathogenic curve (violet), we considered a pathogenic prediction of a CF-causing variant a true positive. For the ambiguous curve (grey)—we considered the ambiguous prediction a VVCC a true positive. For the benign curve (bluegreen)–we considered the benign prediction of a non-CF causing variant as a true positive. B. Receiver operating characteristic curve calculated the same as in A. but using EVE missense variant predictions [40] of 169 CFTR missense variants colored as shown in A. C. Venn diagrams depicting the overlap of various datasets used throughout the study. We considered our expanded ClinVar dataset, the deep mutational scanning (DMS) dataset [23], our curated CFTR2 dataset, and the missense variants from the Bihler et al. dataset [33]. (TIF)</p

Distributions of experimental data and error from Bihler et al. study for filtering purposes.

A. Histogram of the distribution of C-B band ratio of all 585 missense variants from the Bihler et al. study [33]. B. Histogram of the distribution of C-B band ratio SEM for all 585 missense variants from the Bihler et al. study. Variants with an SEM greater than 30 were excluded from analysis due to lack of experimental reproducibility and for plotting clarity. C. FSK %WT distribution plotted as a histogram for all 585 missense variants from the Bihler et al. study [33]. D. FSK %WT SEM distribution plotted as a histogram for all 585 missense variants from the Bihler et al. study. Variants with an SEM greater than 20 were excluded from analysis due to lack of experimental reproducibility and for plotting clarity. (TIF)</p

Deep mutational scanning data for VX-661 and VX-445 response colored by AlphaMissense pathogenicity score.

A. Basal CFTR surface immune staining versus VX-661 CFTR cell surface immune staining intensity [23]. Pathogenic variants score from 0.56–1.00 (violet), ambiguous variants score from 0.34–0.56 (grey), and benign variants score 0.04–0.34 (green). Error bars represent standard deviation. The distribution of pathogenicity colors throughout the plots suggested that AM pathogenicity prediction score failed to predict the VX-661 response. B. Basal CFTR surface immune staining versus VX-445 CFTR cell surface immune staining intensity. Colored the same as in A. Error bars represent standard deviation. Again, AM score failed to predict VX-445 response. C. Basal CFTR surface immune staining versus VX-661 + VX-445 CFTR cell surface immune staining intensity. Colored the same as in A. Error bars represent standard deviation. Finally, AM score failed to predict the combination of VX-661 and VX-445 response on a variant basis. (TIF)</p

CFTR2.org Variants of Unknown Significance (VUS).

Seven missense variants of unknown significance (VUS) from the CFTR2.org database with their respective AM scores and predicted pathogenicity. Variants D923N and M952T are predicted to be pathogenic.</p