Article Figures and data Abstract Editor's evaluation Introduction Results and discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Cancer mutations in Ras occur predominantly at three hotspots: Gly 12, Gly 13, and Gln 61. Previously, we reported that deep mutagenesis of H-Ras using a bacterial assay identified many other activating mutations (Bandaru et al., 2017). We now show that the results of saturation mutagenesis of H-Ras in mammalian Ba/F3 cells correlate well with the results of bacterial experiments in which H-Ras or K-Ras are co-expressed with a GTPase-activating protein (GAP). The prominent cancer hotspots are not dominant in the Ba/F3 data. We used the bacterial system to mutagenize Ras constructs of different stabilities and discovered a feature that distinguishes the cancer hotspots. While mutations at the cancer hotspots activate Ras regardless of construct stability, mutations at lower-frequency sites (e.g. at Val 14 or Asp 119) can be activating or deleterious, depending on the stability of the Ras construct. We characterized the dynamics of three non-hotspot activating Ras mutants by using NMR to monitor hydrogen-deuterium exchange (HDX). These mutations result in global increases in HDX rates, consistent with destabilization of Ras. An explanation for these observations is that mutations that destabilize Ras increase nucleotide dissociation rates, enabling activation by spontaneous nucleotide exchange. A further stability decrease can lead to insufficient levels of folded Ras – and subsequent loss of function. In contrast, the cancer hotspot mutations are mechanism-based activators of Ras that interfere directly with the action of GAPs. Our results demonstrate the importance of GAP surveillance and protein stability in determining the sensitivity of Ras to mutational activation. Editor's evaluation This is a well executed study that provides significant new insights and connections between protein structure, stability and function. Numerous sites of mutation are identified that activate the small GTPase Ras beyond the few cancer "hot spots" that predominate cancer genomics data. While cancer causing mutations selectively alter regulatory interactions with GTPase-activating proteins, careful biophysical analysis presented here leads to the conclusion that Ras is also activated by mutations that decrease stability (increase dynamics) short of unfolding. Thus, protein sensitivity to activating mutations can depend on the stability threshold in addition to regulatory interactions with binding partners. https://doi.org/10.7554/eLife.76595.sa0 Decision letter eLife's review process Introduction The small GTPase Ras (Figure 1A) cycles between active GTP-bound and inactive GDP-bound states (Figure 1B; Wittinghofer and Vetter, 2011). There are four principal isoforms of human Ras (H-Ras, N-Ras, and two splice variants of K-Ras; referred to collectively as 'Ras'). GTP-bound Ras binds to the Ras-binding domains (RBDs) of effector proteins, such as Raf kinases and PI-3 kinase (PI3K), triggering signaling cascades that result in cell proliferation (Ehrhardt et al., 2002; Pylayeva-Gupta et al., 2011; Schubbert et al., 2007). Ras proteins have weak intrinsic GTPase activity (Ehrhardt et al., 2002). In the cell, Ras activity is controlled by two kinds of regulators: GTPase-activating proteins (GAPs) and guanine nucleotide-exchange factors (GEFs). GAPs stimulate the hydrolysis of GTP, thereby converting Ras to the inactive GDP-bound state (Ahmadian et al., 1997). Spontaneous exchange of GDP for GTP is slow, and nucleotide exchange and re-activation of Ras is accelerated by GEFs (Bandaru et al., 2019; Boriack-Sjodin et al., 1998; Ehrhardt et al., 2002; Harrison et al., 2016; Vetter and Wittinghofer, 2001). Figure 1 with 1 supplement see all Download asset Open asset Ras G-domain, the switching cycle, and schematics of the two selection assays. (A) The three principal sites of cancer mutations in Ras, referred to as the three cancer hotspots – Gly 12, Gly 13, and Gln 61 – are shown in the K-Ras structure. The C-terminal helix extension is indicated. PDB ID: 2MSD (Mazhab-Jafari et al., 2015). (B) Ras cycles between signaling-active GTP-bound and signaling-inactive GDP-bound states. (C) The bacterial-two-hybrid system couples the C-Raf-RBD•Ras-GTP interaction to the transcription of an antibiotic resistance gene (Bandaru et al., 2017). Ras is fused to the N-terminal domain of the α-subunit of the E. coli RNA polymerase. C-Raf-RBD is fused to the λ-cI protein. The GAP and the GEF can be co-expressed in the system. E. coli cells are transformed with a DNA library of 'unselected' variants. The bacteria are grown in the presence of an antibiotic for 9 hr, then the DNA library of 'selected' variants is isolated. Next-generation sequencing (NGS) is used to count the frequency of each variant in the unselected and selected samples. (D) Ba/F3 assay for Ras activity. Mutant H-Ras libraries are transfected into HEK 293T cells to generate a retroviral library of mutants. Ba/F3 cells are transduced with the retroviral library. After 24 hours, a fraction of the cells are used as the unselected population, and the remainder of the cells – the selected population – are cultured for 7 days in the absence of IL-3 before harvesting them by centrifugation. The genomic DNA of the selected and unselected populations is isolated and sequenced using NGS. The relative enrichment scores are calculated using the selected and unselected counts (see Equation 1). The two activities associated with Ras – the enzymatic activity that results in the hydrolysis of GTP, and the signaling activity that enables GTP-bound Ras to bind to effector proteins – have opposing outcomes. The enzymatic activity switches off the signaling activity, and mutations that damage the catalytic center of Ras or that increase the rate of spontaneous nucleotide exchange lead to increased signaling activity. We use the terms 'activity' and 'activation' to refer to the signaling activity of Ras. Ras is mutated frequently in cancers and some hyperproliferative developmental disorders (e.g. Noonan, Costello, and cardio-facio-cutaneous syndromes) (Li et al., 2018; Prior et al., 2020; Prior et al., 2012; Young et al., 2009). Data from cancer genomics show that most mutations occur at just three sites in Ras (Gly 12, Gly 13, and Gln 61), with the K-Ras isoform being mutated more frequently than H-Ras or N-Ras (Figure 1—figure supplement 1A, B; Tate et al., 2019). We refer to these three residues as the 'cancer hotspot' sites. In previous work, we used single-site saturation mutagenesis to assess the mutational-fitness landscape of the G-domain of H-Ras (H-Ras2-166) by employing a high-throughput bacterial two-hybrid assay (Bandaru et al., 2017). The assay couples the transcription of an antibiotic-resistance factor to the binding of Ras to the RBD of C-Raf, and reports on the signaling activity of Ras (Figure 1C). We expected mutations at Gly 12, Gly 13, and Gln 61 to be more activating than other substitutions, reflecting the frequencies of mutations observed in cancer (Figure 1—figure supplement 1A). To our surprise, the bacterial screens identified multiple signal-activating mutations in Ras, with relative enrichment scores similar to those for mutations at the three cancer hotspots. Several factors could potentially explain the difference in the mutational spectrum of Ras in cancer compared to that observed in the bacterial assay. First, the bacterial assay does not provide the complete biological context for Ras function. Ras is not membrane-localized in this system, and it is divorced from its normal complement of effector proteins. The distribution of cancer mutations reflects the mutagenic ability of specific carcinogens and the context-specific effects of Ras isoforms in different mammalian cells (Cook et al., 2021; Li et al., 2018; Prior et al., 2020). Analysis of the context-specific effects led to the proposal that there are 'sweet spots' at the intersection of these properties that are selected for in different cancers (Li et al., 2018). Nevertheless, the difference between the very narrow mutational profile of Ras in cancer and the much broader range of mutations that activate Ras in our previous deep-mutational scans is striking, and it motivated us to examine whether saturation mutagenesis could identify factors that may account for this discrepancy. To address concerns that the broad spectrum of activating mutations seen in the bacterial assay might be artifacts of this bacterial system, we carried out saturation mutagenesis of full-length H-Ras (H-Ras1-188) expressed in mammalian Ba/F3 cells (Figure 1D). The murine Ba/F3 hematopoietic cell line is dependent on the cytokine interleukin-3 (IL-3) for growth, but the IL-3 dependence can be bypassed by the expression of activated variants of tyrosine kinases, such as BCR-Abl (Daley and Baltimore, 1988; Mandanas et al., 1993; Warmuth et al., 2007). The Ba/F3 system is a robust assay for screening activating mutations in tyrosine kinases (Hoover et al., 2001; Lee and Shah, 2015; Watanabe-Smith et al., 2017). Cytokine independence can also be conferred on Ba/F3 cells by activated mutants of Ras (Awad, 2021; Hoover et al., 2001; White et al., 2016), providing the basis for our Ras saturation-mutagenesis screens. We compared the mutational-fitness landscape of full-length H-Ras1-188 in Ba/F3 cells to data obtained from bacterial saturation-mutagenesis screens done for H-Ras in the absence of GAP and GEF regulators ('unregulated Ras'), in the presence of both a GAP and a GEF ('Ras+GAP+GEF'), and in the presence of a GAP alone ('Ras+GAP'). While the first two conditions yield similar patterns of mutational sensitivity, the Ras+GAP condition leads to starkly different results. The GAP switches off Ras signaling activity, and only mutations that enable Ras to evade GAP control allow cell proliferation. The mutational profile of H-Ras in the mammalian Ba/F3 cell line closely resembles the results of the bacterial screens using H-Ras co-expressed with a GAP. These results point to the importance of GAP surveillance in controlling Ras activity in Ba/F3 cells, and also demonstrate that the bacterial assay is a reliable indicator of the effects of mutations on Ras function. Strikingly, just like in the bacterial assay, the mammalian experiments reveal additional gain-of-function mutations with similar levels of activation as mutations at the cancer hotspots. The importance of a special feature associated with the cancer hotspots emerged from the comparison of mutational profiles for longer and shorter H-Ras constructs using the bacterial assay. The shorter construct – residues 2–166, the construct typically used in crystallographic studies of H-Ras (Pai et al., 1990) – corresponds to the core G-domain of H-Ras and was used in our previous saturation-mutagenesis study. The longer construct spans residues 2–180 (H-Ras2-180), and we found that it is more stable. Our earlier study had characterized several mutations outside the hotspots that activate Ras to varying degrees, but are not prominent in cancer (Bandaru et al., 2017). We now report the analysis of protein dynamics for three of these mutations (H27G, L120A, and Y157Q) by hydrogen-deuterium exchange (HDX) measured by nuclear magnetic resonance (NMR). The mutants show increased HDX rates throughout the protein relative to wild-type Ras, consistent with destabilization. The saturation-mutagenesis data show that several infrequent cancer mutations (e.g. at Val 14 or Asp 119) are deleterious in the shorter construct and become activating in the longer Ras construct. We infer that these activating mutations have a destabilizing effect that only the longer Ras construct can accommodate, allowing the increased signaling capacity to be manifested. In contrast, the effect of mutations at the three cancer hotspots is independent of the Ras construct stability. We also present the results of saturation-mutagenesis experiments for K-Ras, which yield similar mutational patterns as for H-Ras. Our analysis shows that many activating mutations impact the thermodynamic stability of Ras, and the destabilizing effect of the mutations correlates with their low observed frequency in cancer. Results and discussion Saturation-mutagenesis of H-Ras in mammalian Ba/F3 Cells Ba/F3 cells were transduced with a retroviral library of variants of full-length human H-Ras and allowed to grow for a day in the presence of IL-3. Then, a fraction of the cells were harvested and used as the 'unselected' population. The remainder of the cells were grown for a week without IL-3 in the medium (the 'selected' population). The DNA from both cell populations was harvested and sequenced to count the occurrence of each particular variant. The effect of Ras mutations on fitness is quantified by relative enrichment scores (ΔExi), also referred to as fitness values (Equation 1; see Materials and methods): (1) ΔExi=log10[cix,selectedcix,unselected]−median(log10[Cwt,selected⊘Cwt,unselected]) The first term of Equation 1 is the logarithm of the ratio of counts (c) of observing codons representing each amino acid x at each position i in the selected and unselected samples. The second term of Equation 1 is the median of the ordered list of logarithms of the elements of the vector obtained by conducting pair-wise division, denoted ⊘, between the selected and unselected counts (Cwt,selected and Cwt,unselected, respectively) for the variants that are synonymous with the wild-type (wt) allele. A Ras variant with an enrichment score of zero propagates in the assay at the same rate as the wild-type variants. Variants with scores of ±1 propagate ten-fold faster or slower than wild-type variants, respectively. The experiment was repeated twice, once while varying residues 2–160 (the core G-domain; the remaining 29 residues were not varied), and once while varying residues 2–188. The resulting fitness values are shown in the form of a heatmap in Figure 2A, averaged over the two replicates (Figure 2—figure supplement 1A). Each entry in the matrix indicates the fitness score for substituting a particular residue in Ras with one of the 20 amino acids, with shades of red and blue indicating gain or loss-of-function relative to wild-type, respectively. Figure 2 with 2 supplements see all Download asset Open asset Mutational tolerance of Ras in mammalian Ba/F3 cells and the bacterial Ras+GAP experiment. (A) The fitness data from saturation-mutagenesis experiments are shown in the form of a matrix, where each row of the matrix represents one of the twenty natural amino acids, and each column displays a residue of the protein (Bandaru et al., 2017). Each entry in the matrix represents, in color-coded form, the relative enrichment score (ΔExi) for the corresponding variant (see Equation 1). The data are normalized using the distribution of enrichment scores of all the synonymous wild-type sequences, so the median of the distribution has a value of zero. Shades of red and blue indicate gain and loss-of-function, respectively, relative to wild-type. Green indicates variants that were not represented in the library. Stop codons are labeled as '*', and the bottom strip displays the functional effect of all amino acid substitutions at each position (⟨ΔExi⟩x) – the average taken over each column. The relative enrichment values are provided in the GitHub repository. The secondary structural elements of Ras are displayed below each matrix. The top heatmap shows the data for saturation mutagenesis of H-Ras1-188 in mammalian Ba/F3 cells. Only the enrichment scores for variants within residues 2 and 160 are displayed in the heatmap, calculated as the mean of two biological replicates. The next four heatmaps show the data for H-Ras2-166, H-Ras2-180, K-Ras2-165, and K-Ras2-173 in the bacterial Ras+GAP experiments. The enrichment values shown are the mean of two, four, three, and four biological replicates, respectively. (B) The area under the curve (AUC) of receiver operating characteristic (ROC) graphs is used to determine which of the four Ras+GAP experiments better predicts the enrichment scores of mutations in the mammalian Ba/F3 cell experiment. There are several positions in H-Ras at which multiple substitutions lead to a strong gain-of-function. These residues include the cancer hotspots (Gly 12, Gly 13, and Gln 61), as well as several other residues that are not as frequently found to be mutated in cancer (e.g. Val 14, Arg 68, Lys 117, and Asp 119). The fact that several amino acid substitutions at each of these sites lead to increased fitness suggests that the mutations disrupt inhibitory interactions. Positions at which mutations lead to a strong loss-of-function are sparse in the dataset. Residues in the hydrophobic core of the protein, for which mutations to polar residues are expected to decrease the stability of the protein, show little or no evidence for loss of fitness when mutated. For example, the sidechains of Leu 19, Leu 79, Val 81, and Val 114 pack together in the hydrophobic core of Ras. These residues tolerate substitutions by many polar residues with no apparent reduction in fitness with respect to wild-type Ras. Since only mutations that bypass the IL-3 dependence promote cell growth in the assay, and wild-type H-Ras does not promote growth (Figure 2—figure supplement 1B), a neutral mutation can barely be distinguished from a deleterious mutation. The mutational profile for Ras in Ba/F3 cells resembles that for Ras co-expressed with a GAP in the bacterial assay The two properties of the Ba/F3 dataset noted above, namely strong activation by many mutations at specific sites and a general sparsity of sites where mutations lead to loss-of-function, are reminiscent of the mutational profile for H-Ras2-166 co-expressed with a GAP (H-Ras2-166+GAP) in the bacterial assay (Bandaru et al., 2017). The GAP inactivates wild-type Ras by stimulating GTP-hydrolysis. Under these conditions, the assay is not sensitive to the effects of mutations that further reduce the activity of Ras by destabilizing the protein. Mutations that disrupt the interaction with the GAP, such as substitutions of Gly 12 or Gly 13, or that compromise the catalytic activity of Ras, such as substitutions of Gln 61, are strongly activating. We used receiver operating characteristic (ROC) curves to make a quantitative determination of which of the three different bacterial experiments [H-Ras2-166+GAP (Figure 2A), H-Ras2-166+GAP+GEF (Bandaru et al., 2017), or unregulated H-Ras2-166 (Figure 3A)] best matches the results of the Ba/F3 screen (Figure 2B). To generate a ROC curve, the fitness data for individual mutations in a particular bacterial dataset (e.g. H-Ras2-166+GAP) are used to predict the fitness of mutations in the Ba/F3 experiment. A variable threshold value of fitness is used, and for each threshold value, mutations in the bacterial dataset with a fitness value greater than that threshold are considered to predict activation in Ba/F3 data. Mutations with a fitness score greater than 1.5 times the standard deviation in the Ba/F3 dataset are considered activating (i.e. true positives). For each of the bacterial datasets, an ROC curve is generated by graphing the fraction of true positives versus the fraction of false positives at various threshold settings, and the estimated area under the curve (AUC) gives a measure of the overall prediction accuracy. For a perfect correlation between the bacterial data and the Ba/F3 data, the AUC would be 1.0. The analysis shows that the Ras+GAP dataset most accurately predicts the H-Ras1-188 in Ba/F3 cells dataset. The AUC is 0.67 for the unregulated H-Ras2-166 dataset (Figure 3—figure supplement 1) and 0.63 for H-Ras2-166+GAP+GEF (Figure 2—figure supplement 2B). For H-Ras2-166+GAP, the AUC is substantially higher at 0.84 (Figure 2B). Given that Ras is predominantly GDP-bound in vivo (Zhao et al., 2020), it is logical that the bacterial Ras+GAP experiment – where the GAP promotes a GDP-bound state – closely resembles the mammalian Ba/F3 cell experiment. Figure 3 with 1 supplement see all Download asset Open asset Mutational tolerance of Ras long and short constructs in the unregulated bacterial experiment. (A) H-Ras2-166, H-Ras2-180, K-Ras2-165, and K-Ras2-173 in the unregulated experiment. The relative enrichment values (ΔExi) shown are the mean of three, four, two, and four biological replicates, respectively. Stop codons are labeled as '*', and the bottom strip displays the functional effect of all amino acid substitutions at each position (<ΔExi>x) – the average taken over each column. (B–C) Comparison of the mutational tolerance of residues in the hydrophobic core of K-Ras in the shorter and longer constructs. The enrichment scores for the hydrophobic core residues are shown for the two K-Ras constructs in B, and mapped onto K-Ras structure in C. PDB ID: 4OBE (Hunter et al., 2015). Extension of the C-terminal helix in Ras improves the correlation of bacterial mutagenesis data with the Ba/F3 dataset The Ba/F3 experiments use full-length H-Ras, including the lipid-modified C-terminal hypervariable region that confers membrane anchorage. The bacterial experiments use a construct of H-Ras that spans residues 2–166, corresponding to the core G domain of H-Ras (Pai et al., 1990). This construct lacks 22 C-terminal residues, including the CAAX motif, where post-translational modifications occur. Membrane-anchorage of Ras is not possible within the context of the bacterial assay because the two-hybrid readout of Ras activity relies on the interaction between fusion proteins containing Ras and Raf-RBD bound to DNA. We tested the effects of extending the C-terminal boundary of the Ras construct by conducting saturation-mutagenesis experiments with the bacterial assay using an H-Ras construct spanning residues 2–180 (Figure 2A). Based on the crystal structure of the K-Ras isoform (Cruz-Migoni et al., 2019), we expect that extending the H-Ras construct in this way lengthens the C-terminal helix of H-Ras by two helical turns or more (Figure 1A). The H-Ras2-180+GAP dataset improves the ROC AUC score for predicting the Ba/F3 data to 0.95, compared to 0.84 for the shorter construct (Figure 2B). There are specific sites for which mutations in the bacterial H-Ras2-166+GAP experiment demonstrate a different activation profile than the H-Ras1-188 in Ba/F3 cells experiment (Figure 2A). For example, most mutations of Asp 119 are activating in Ba/F3 cells and H-Ras2-180+GAP, but these mutations are neutral or slightly inactivating in the bacterial assay with shorter H-Ras2-166+GAP. Mutations at the cancer hotspots are activating in all three datasets (Figure 2A and B). We also performed saturation mutagenesis of K-Ras in the presence of a GAP in bacteria using two constructs, a shorter one spanning residues 2–165 (K-Ras2-165) and a longer one spanning residues 2–173 (K-Ras2-173) (Figure 2A), corresponding to a construct used in recent crystallographic studies (Cruz-Migoni et al., 2019). The K-Ras datasets are similar to the H-Ras datasets (Figure 2A). The ROC AUC for predicting the Ba/F3 data for shorter K-Ras2-165+GAP is 0.75, and the AUC increases to 0.93 for longer K-Ras2-173+GAP (Figure 2B). These data indicate that K-Ras behaves similarly to H-Ras regarding mutational tolerance. This finding is clinically relevant because the ClinVar review panel categorizes new Ras variants found in genomic studies as disease-causing or not, based on the assumption that the pathogenicity of analogous variants in the H-Ras and K-Ras genes are correlated (Landrum et al., 2018). We carried out saturation-mutagenesis screens in bacteria for unregulated H-Ras and K-Ras (i.e. no co-expression of GAP and GEF) for the longer and shorter constructs (Figure 3A). Wild-type Ras generates a signal in the absence of the GAP (Coyle and Lim, 2016), and substitution of residues in the hydrophobic core by polar residues results in measurable decreases in signaling, in contrast to the Ras+GAP experiments. The data show that the longer H-Ras2-180 and K-Ras2-173 constructs are less sensitive to mutations of residues in the hydrophobic core than the shorter constructs (e.g. see mutations of Phe 82, Figure 3B–C). We also conducted screens for K-Ras in the presence of a GAP and a GEF, and the mutational landscape presents the same patterns described for the unregulated experiments (Figure 2—figure supplement 2A). Ras mutations and construct length impact fold stability We measured the stability of two H-Ras constructs bound to GDP, one corresponding to the core G-domain (residues 1–166), and one in which the C-terminal end of the construct is extended by seven residues (residues 1–173) using two assays with purified Ras proteins. In the first assay, we carried out a urea titration and monitored the equilibrium unfolding transition by following the circular dichroism (CD) signal at 222 nm. In the second assay, we also monitored the urea-induced unfolding using pulse proteolysis. Under pulse conditions, all the unfolded protein is cleaved, and the native protein remains undigested (Kim et al., 2009; Park and Marqusee, 2005; Samelson et al., 2016). The fraction of folded protein can be estimated by measuring the intensity of the band corresponding to full-length Ras on an SDS/PAGE gel. The intensities of the bands at each urea concentration are then fit to a two-state denaturation model, with the urea-dependence (the m-values determined by CD) used to determine midpoint urea concentration (Cm). The stabilities (ΔGunf) determined by pulse proteolysis are in close agreement with those determined by CD. When monitored by CD, the values of ΔGunf for the shorter and longer H-Ras constructs are 22.2 ± 1.6 kJ.mol–1 and 29.9 ± 1.4 kJ.mol–1, respectively (Figure 4A). When measured by pulse proteolysis, the shorter and longer constructs have values of ΔGunf of 24.3 ± 1.3 kJ.mol–1 and 31.1 ± 1.5 kJ.mol–1, respectively (Figure 4A). Both assays indicate that truncating the C-terminal helix destabilizes H-Ras by ~7 kJ.mol–1. This effect is consistent with the known ability of terminal-helix stabilization to help maintain the entire protein fold (Rosemond et al., 2018). Figure 4 Download asset Open asset Thermodynamic stability measurements. (A) The shorter H-Ras1-166 construct has an unfolding free-energy change (ΔGunf) of 22.2 ± 1.6 kJ⋅mol-1, and the longer H-Ras1-173 construct has a ΔGunf of 29.9 ± 1.4 kJ⋅mol-1 when measured by circular dichroism (left). When measured by pulse proteolysis (right), the shorter construct has a ΔGunf of 24.3 ± 1.3 kJ⋅mol-1, and the longer construct has a ΔGunf of 31.1 ± 1.5 kJ⋅mol-1. Both assays indicate that truncating the C-terminal helix destabilizes H-Ras by ~7 kJ⋅mol-1. The CD measurements were conducted at 25 °C, using 35.5 μM GDP and 0.5 μM Ras. CD signal error bars are ± two times the standard deviation of four 15 second reads. (B) Pulse proteolysis measurements of three cancer hotspots mutants (G12V, G13D, Q61L) and two stability-dependent gain-of-function mutants (K117N, D119A). The ΔGunf for G13D, K117N, and D119A mutants in the H-Ras1-173 construct are 22.1 ± 1.5 kJ⋅mol-1, 6.8 ± 0.5 kJ⋅mol-1, and 6.2 ± 0.8 kJ⋅mol-1, respectively. The G12V and Q61L variants were studied in the H-Ras1-166 construct. The ΔGunf for G12V, Q61L, and new replicates of wild-type are 28.3 ± 4.3 kJ⋅mol-1, 23.9 ± 1.0 kJ⋅mol-1, and 23.5 ± 1.0 kJ⋅mol-1, respectively. Hence, these cancer hotspot mutations are not destabilizing. (C) Pulse proteolysis measurements of H-Ras1-173 and K-Ras1-173. K-Ras1-173 has a ΔGunf of 24.2 ± 0.1 kJ⋅mol-1; hence, H-Ras1-173 is more stable than K-Ras1-173 by ~7 kJ⋅mol-1. The proteolysis experiments in A-C were conducted at 25 °C, using 100 μM GDP and 1.6 μM Ras. Midpoint marker error bars are ± the standard deviation of the estimated midpoint concentration (ΔGunf/m) across pulse proteolysis replicates. Using the pulse proteolysis assay, we measured the stability of three cancer hotspot mutants (Q61L, G12V, G13D), and two infrequent – or absent – mutants (K117N, and D119A) (Figure 4B). The stabilities of the Q61L and G12V variants of H-Ras1-166 are indistinguishable from that of wild-type (ΔGunf of 28.3 ± 4.3 kJ.mol–1 for G12V and 23.9 ± 1.0 kJ.mol–1 for Q61L). For the G13D, K117N, and D119A variants of H-Ras1-173, the values of ΔGunf are 22.1 ± 1.5 kJ.mol–1, 6.8 ± 0.5 kJ.mol–1, and 6.2 ± 0.8 kJ.mol–1, respectively. G13D destabilizes Ras by a moderate amount, ~ 10 kJ.mol–1, comparable to the effect of shortening the C-terminal tail. The K117N and D119A mutations destabilized Ras much more substantially, by ~25 kJ.mol–1. Mutations at Lys 117 and Asp 119 as well as mutations at other sites (e.g. Val 14, Phe 28, Leu 120, Ala 146, Lys 147, and Phe 156), increase the rate of intrinsic nucleotide release (Baker et al., 2013; Bandaru et al., 2017; Bera et al., 2019; Cirstea et al., 2013; Cool et al., 1999; Gelb and Tartaglia, 2006; Poulin et al., 2019; Quilliam et al., 1995; Reinstein et al., 1991). Furthermore, two such mutations – V14I and A146T – have been shown to facilitate nucleotide exchange by destabilization and opening of the GTP-binding site (Bera et al., 2019; Poulin et al., 2019). Hence, stability and nucleotide affinity in Ras are coupled, consistent with Ras stability being dependent on nucleotide binding (Zhang and Matthews, 1998a; Zhang and Matthews, 1998b). We use the term 'stability-dependent gain-of-function' mutations to denote the subset of mutations that switch from an activating

Cancer mutations in Ras occur predominantly at three hotspots: Gly 12, Gly 13, and Gln 61. Previously, we reported that deep mutagenesis of H-Ras using a bacterial assay identified many other activating mutations (Bandaru et al., 2017). We now show that the results of saturation mutagenesis of H-Ras in mammalian Ba/F3 cells correlate well with the results of bacterial experiments in which H-Ras or K-Ras are co-expressed with a GTPase-activating protein (GAP). The prominent cancer hotspots are not dominant in the Ba/F3 data. We used the bacterial system to mutagenize Ras constructs of different stabilities and discovered a feature that distinguishes the cancer hotspots. While mutations at the cancer hotspots activate Ras regardless of construct stability, mutations at lower-frequency sites (e.g. at Val 14 or Asp 119) can be activating or deleterious, depending on the stability of the Ras construct. We characterized the dynamics of three non-hotspot activating Ras mutants by using NMR to monitor hydrogen-deuterium exchange (HDX). These mutations result in global increases in HDX rates, consistent with destabilization of Ras. An explanation for these observations is that mutations that destabilize Ras increase nucleotide dissociation rates, enabling activation by spontaneous nucleotide exchange. A further stability decrease can lead to insufficient levels of folded Ras - and subsequent loss of function. In contrast, the cancer hotspot mutations are mechanism-based activators of Ras that interfere directly with the action of GAPs. Our results demonstrate the importance of GAP surveillance and protein stability in determining the sensitivity of Ras to mutational activation.

In nitrogenase biosynthesis, the iron-molybdenum cofactor (FeMo-co) is externally assembled at scaffold proteins and delivered to the NifDK nitrogenase component by the NafY metallochaperone. Here we have used nuclear magnetic resonance, molecular dynamics, and functional analysis to elucidate the environment and coordination of FeMo-co in NafY. H121 stands as the key FeMo-co ligand. Regions near FeMo-co diverge from H121 and include the η1, α1, α2 helical lobe and a narrow path between H121 and C196.

Advancement of hyperpolarized 129 Xe MRI technology toward clinical settings demonstrates the considerable interest in this modality for diagnostic imaging. The number of contrast agents, termed biosensors, for 129 Xe MRI that respond to specific biological targets, has grown and diversified. Directly functionalized xenon-carrying macrocycles, such as the large family of cryptophane-based biosensors, are good for localization-based imaging and provide contrast before and after binding events occur. Noncovalently functionalized constructs, such as cucurbituril- and cyclodextrin-based biosensors, benefit from commercial availability and optimal exchange dynamics for CEST imaging. In this work, we report the first directly functionalized cucurbituril used as a xenon biosensor. Biotinylated cucurbit[7]uril (btCB7) gives rise to a 129 Xe hyperCEST response at the unusual shift of δ=28 ppm when bound to its protein target with substantial CEST contrast. We posit that the observed chemical shift is due to the deformation of btCB7 upon binding to avidin, caused by proximity to the protein surface. Conformational searches and molecular dynamics (MD) simulations support this hypothesis. This construct combines the strengths of both families of biosensors, enables a multitude of biological targets through avidin conjugation, and demonstrates the advantages of functionalized cucurbituril-based biosensors.

Conformational control in peptoids, N-substituted glycines, is crucial for the design and synthesis of biologically-active compounds and atomically-defined nanomaterials. While there are a growing number of structural studies in solution, most have been performed with conformationally-constrained short sequences (e.g., sterically-hindered sidechains or macrocyclization). Thus, the inherent degree of heterogeneity of unconstrained peptoids in solution remains largely unstudied. Here, we explored the folding landscape of a series of simple peptoid tetramers in aqueous solution by NMR spectroscopy. By incorporating specific 13 C-probes into the backbone using bromoacetic acid-2-13 C as a submonomer, we developed a new technique for sequential backbone assignment of peptoids based on the 1,n-Adequate pulse sequence. Unexpectedly, two of the tetramers, containing an N-(2-aminoethyl)glycine residue (Nae), had preferred conformations. NMR and molecular dynamics studies on one of the tetramers showed that the preferred conformer (52%) had a trans-cis-trans configuration about the three amide bonds. Moreover, >80% of the ensemble contained a cis amide bond at the central amide. The backbone dihedral angles observed fall directly within the expected minima in the peptoid Ramachandran plot. Analysis of this compound against similar peptoid analogs suggests that the commonly used Nae monomer plays a key role in the stabilization of peptoid structure via a side-chain-to-main-chain interaction. This discovery may offer a simple, synthetically high-yielding approach to control peptoid structure, and suggests that peptoids have strong intrinsic conformational preferences in solution. These findings should facilitate the predictive design of folded peptoid structures, and accelerate application in areas ranging from drug discovery to biomimetic nanoscience.

Women and some racial and ethnic groups remain underrepresented in chemistry departments across the United States, and generally, efforts to improve representation have resulted in minimal or no improvements in the last 10 years. Here, we present the outcomes of a graduate-student-led initiative that sought to assess the issues affecting inclusivity, diversity, and wellness within the Department of Chemistry at the University of California, Berkeley. We report how the results of a department-tailored academic climate survey were used to develop a method to foster open, productive discussion among graduate students, postdoctoral researchers, and faculty. This event format led to an improved understanding of the challenges facing our community members, as well as the identification of strategies that can be used to make the Department of Chemistry more welcoming for all members. We report the success of this student-led effort to highlight the value of assessing diversity and inclusion at the department-level, as well as the benefits of using community data to stimulate productive, evidence-based discussions. Furthermore, we envision that these methods can be implemented within any research-focused academic community to promote positive cultural change.

The development of sensitive and chemically selective MRI contrast agents is imperative for the early detection and diagnosis of many diseases. Conventional responsive contrast agents used in 1 H MRI are impaired by the high abundance of protons in the body. 129 Xe hyperCEST NMR/MRI comprises a highly sensitive complement to traditional 1 H MRI because of its ability to report specific chemical environments. To date, the scope of responsive 129 Xe NMR contrast agents lacks breadth in the specific detection of small molecules, which are often important markers of disease. Herein, we report the synthesis and characterization of a rotaxane-based 129 Xe hyperCEST NMR contrast agent that can be turned on in response to H2 O2 , which is upregulated in several disease states. Added H2 O2 was detected by 129 Xe hyperCEST NMR spectroscopy in the low micromolar range, as well as H2 O2 produced by HEK 293T cells activated with tumor necrosis factor.

We report a (129)Xe NMR relaxation-based sensing approach that exploits changes in the bulk xenon relaxation rate induced by slowed tumbling of a cryptophane-based sensor upon target binding. The amplification afforded by detection of the bulk dissolved xenon allows sensitive detection of targets. The sensor comprises a xenon-binding cryptophane cage, a target interaction element, and a metal chelating agent. Xenon associated with the target-bound cryptophane cage is rapidly relaxed and then detected after exchange with the bulk. Here we show that large macromolecular targets increase the rotational correlation time of xenon, increasing its relaxation rate. Upon binding of a biotin-containing sensor to avidin at 1.5 μM concentration, the free xenon T2 is reduced by a factor of 4.

Bacterial sigma factors are subunits of RNA polymerase that direct the holoenzyme to specific sets of promoters in the genome and are a central element of regulating transcription. Most polymerase holoenzymes open the promoter and initiate transcription rapidly after binding. However, polymerase containing the members of the σ54 family must be acted on by a transcriptional activator before DNA opening and initiation occur. A key domain in these transcriptional activators forms a hexameric AAA+ ATPase that acts through conformational changes brought on by ATP hydrolysis. Contacts between the transcriptional activator and σ54 are primarily made through an N-terminal σ54 activator interacting domain (AID). To better understand this mechanism of bacterial transcription initiation, we characterized the σ54 AID by NMR spectroscopy and other biophysical methods and show that it is an intrinsically disordered domain in σ54 alone. We identified a minimal construct of the Aquifex aeolicus σ54 AID that consists of two predicted helices and retains native-like binding affinity for the transcriptional activator NtrC1. Using the NtrC1 ATPase domain, bound with the non-hydrolyzable ATP analog ADP-beryllium fluoride, we studied the NtrC1–σ54 AID complex using NMR spectroscopy. We show that the σ54 AID becomes structured after associating with the core loops of the transcriptional activators in their ATP state and that the primary site of the interaction is the first predicted helix. Understanding this complex, formed as the first step toward initiation, will help unravel the mechanism of σ54 bacterial transcription initiation.

The essential principles of nuclear magnetic resonance for the analysis of biomolecules are conveyed in this SnapShot.

We report the reagentless cleavage of prevalent beta-O-4 linkages in lignin model compounds, as well as the cleavage of several types of organosolv lignins, catalyzed by commercially available Pd/C. Such lignin fragmentation occurred without added reagent if the indigenous double bonds were reduced first or it occurred under conditions in which just 1 atm of hydrogen was added to the system to reduce C=C bonds of the original lignin sample in situ prior to fragmentation. A detailed view of the sites of cleavage of lignin samples from various sources was gained by HSQC NMR experiments. Complex model compounds were prepared and shown to form simpler arenes and substituted phenols HO under catalytic conditions without added reagents. The hydrogen generated in situ from alcohol functionalities provides the reductant for concomitant hydrogenolysis of C-O bonds in beta aryl ethers. Decarbonylation of primary alcohols also occurred, and this process resulted in significant amounts of aromatic products containing substituents bearing one fewer carbon atom than the original linkages in lignin. The fragmentations of synthetic lignin and several organosolv lignins derived from Miscanthus giganteus and pine tree were conducted. Because the lignins contain alkenes that accept the hydrogen, two procedures involving reduction of the alkenes prior to C-O bond cleavage were developed. The first procedure involves reduction of the alkenes, followed by catalytic cleavage of C-O bonds after saturation of the C-C bonds; a second involves cleavage of lignin samples in the presence of 1 atm of hydrogen to saturate the alkenes before cleavage in situ. These protocols convert solid lignin to monomeric phenolic compounds with 20 mol % catalyst or to an oil (with 5 mol % Pd/C loading) having favorable viscosity parameters upon blending with a renewable organic solvent.

In order to understand factors controlling the synthesis and deposition of cellulose, we have studied the Arabidopsis (Arabidopsis thaliana) double mutant shaven3 shaven3-like1 (shv3svl1), which was shown previously to exhibit a marked cellulose deficiency. We discovered that exogenous sucrose (Suc) in growth medium greatly enhances the reduction in hypocotyl elongation and cellulose content of shv3svl1 This effect was specific to Suc and was not observed with other sugars or osmoticum. Live-cell imaging of fluorescently labeled cellulose synthase complexes revealed a slowing of cellulose synthase complexes in shv3svl1 compared with the wild type that is enhanced in a Suc-conditional manner. Solid-state nuclear magnetic resonance confirmed a cellulose deficiency of shv3svl1 but indicated that cellulose crystallinity was unaffected in the mutant. A genetic suppressor screen identified mutants of the plasma membrane Suc/H(+) symporter SUC1, indicating that the accumulation of Suc underlies the Suc-dependent enhancement of shv3svl1 phenotypes. While other cellulose-deficient mutants were not specifically sensitive to exogenous Suc, the feronia (fer) receptor kinase mutant partially phenocopied shv3svl1 and exhibited a similar Suc-conditional cellulose defect. We demonstrate that shv3svl1, like fer, exhibits a hyperpolarized plasma membrane H(+) gradient that likely underlies the enhanced accumulation of Suc via Suc/H(+) symporters. Enhanced intracellular Suc abundance appears to favor the partitioning of carbon to starch rather than cellulose in both mutants. We conclude that SHV3-like proteins may be involved in signaling during cell expansion that coordinates proton pumping and cellulose synthesis.

We have synthesized targeted, selective, and highly sensitive (129)Xe NMR nanoscale biosensors using a spherical MS2 viral capsid, Cryptophane A molecules, and DNA aptamers. The biosensors showed strong binding specificity toward targeted lymphoma cells (Ramos line). Hyperpolarized (129)Xe NMR signal contrast and hyper-CEST (129)Xe MRI image contrast indicated its promise as highly sensitive hyperpolarized (129)Xe NMR nanoscale biosensor for future applications in cancer detection in vivo.

We report a CB6 rotaxane for the 129Xe hyperCEST NMR detection of matrix metalloprotease 2 (MMP-2) activity. MMP-2 is overexpressed in cancer tissue, and hence is a cancer marker. A peptide containing an MMP-2 recognition sequence was incorporated into the rotaxane, synthesized via CB6-promoted click chemistry. Upon cleavage of the rotaxane by MMP-2, CB6 became accessible for 129Xe@CB6 interactions, leading to protease-responsive hyperCEST activation.

The traditional structure-function paradigm has provided significant insights for well-folded proteins in which structures can be easily and rapidly revealed by X-ray crystallography beamlines. However, approximately one-third of the human proteome is comprised of intrinsically disordered proteins and regions (IDPs/IDRs) that do not adopt a dominant well-folded structure, and therefore remain "unseen" by traditional structural biology methods. This Perspective considers the challenges raised by the "Dark Proteome", in which determining the diverse conformational substates of IDPs in their free states, in encounter complexes of bound states, and in complexes retaining significant disorder requires an unprecedented level of integration of multiple and complementary solution-based experiments that are analyzed with state-of-the art molecular simulation, Bayesian probabilistic models, and high-throughput computation. We envision how these diverse experimental and computational tools can work together through formation of a "computational beamline" that will allow key functional features to be identified in IDP structural ensembles.

Structural characterization of amyloid rich in cross-β structures is crucial for unraveling the molecular basis of protein misfolding and amyloid formation associated with a wide range of human disorders. Elucidation of the β-sheet structure in noncrystalline amyloid has, however, remained an enormous challenge. Here we report structural analyses of the β-sheet structure in a full-length transthyretin amyloid using solid-state NMR spectroscopy. Magic-angle-spinning (MAS) solid-state NMR was employed to investigate native-like β-sheet structures in the amyloid state using selective labeling schemes for more efficient solid-state NMR studies. Analyses of extensive long-range (13)C-(13)C correlation MAS spectra obtained with selectively (13)CO- and (13)Cα-labeled TTR reveal that the two main β-structures in the native state, the CBEF and DAGH β-sheets, remain intact after amyloid formation. The tertiary structural information would be of great use for examining the quaternary structure of TTR amyloid.

Elucidation of structural changes involved in protein misfolding and amyloid formation is crucial for unraveling the molecular basis of amyloid formation. Here we report structural analyses of the amyloidogenic intermediate and amyloid aggregates of transthyretin using solution and solid-state nuclear magnetic resonance (NMR) spectroscopy. Our solution NMR results show that one of the two main β-sheet structures (CBEF β-sheet) is maintained in the aggregation-competent intermediate, while the other DAGH β-sheet is more flexible on millisecond time scales. Magic-angle-spinning solid-state NMR revealed that AB loop regions interacting with strand A in the DAGH β-sheet undergo conformational changes, leading to the destabilized DAGH β-sheet.