Profiling of drug resistance in Src kinase at scale uncovers a regulatory network coupling autoinhibition and catalytic domain dynamics.

Kinase inhibitors are effective cancer therapies, but resistance often limits clinical efficacy. Despite the cataloging of numerous resistance mutations, our understanding of kinase inhibitor resistance is still incomplete. Here, we comprehensively profiled the resistance of ∼3,500 Src tyrosine kinase mutants to four different ATP-competitive inhibitors. We found that ATP-competitive inhibitor resistance mutations are distributed throughout Src's catalytic domain. In addition to inhibitor contact residues, residues that participate in regulating Src's phosphotransferase activity were prone to the development of resistance. Unexpectedly, we found that a resistance-prone cluster of residues located on the top face of the N-terminal lobe of Src's catalytic domain contributes to autoinhibition by reducing catalytic domain dynamics, and mutations in this cluster led to resistance by lowering inhibitor affinity and promoting kinase hyperactivation. Together, our studies demonstrate how drug resistance profiling can be used to define potential resistance pathways and uncover new mechanisms of kinase regulation.

Molecular determinants of Hsp90 dependence of Src kinase revealed by deep mutational scanning.

Hsp90 is a molecular chaperone involved in the refolding and activation of numerous protein substrates referred to as clients. While the molecular determinants of Hsp90 client specificity are poorly understood and limited to a handful of client proteins, strong clients are thought to be destabilized and conformationally extended. Here, we measured the phosphotransferase activity of 3929 variants of the tyrosine kinase Src in both the presence and absence of an Hsp90 inhibitor. We identified 84 previously unknown functionally dependent client variants. Unexpectedly, many destabilized or extended variants were not functionally dependent on Hsp90. Instead, functionally dependent client variants were clustered in the αF pocket and ß1-ß2 strand regions of Src, which have yet to be described in driving Hsp90 dependence. Hsp90 dependence was also strongly correlated with kinase activity. We found that a combination of activation, global extension, and general conformational flexibility, primarily induced by variants at the αF pocket and ß1-ß2 strands, was necessary to render Src functionally dependent on Hsp90. Moreover, the degree of activation and flexibility required to transform Src into a functionally dependent client varied with variant location, suggesting that a combination of regulatory domain disengagement and catalytic domain flexibility are required for chaperone dependence. Thus, by studying the chaperone dependence of a massive number of variants, we highlight factors driving Hsp90 client specificity and propose a model of chaperone-kinase interactions.

Massively parallel characterization of CYP2C9 variant enzyme activity and abundance.

CYP2C9 encodes a cytochrome P450 enzyme responsible for metabolizing up to 15% of small molecule drugs, and CYP2C9 variants can alter the safety and efficacy of these therapeutics. In particular, the anti-coagulant warfarin is prescribed to over 15 million people annually and polymorphisms in CYP2C9 can affect individual drug response and lead to an increased risk of hemorrhage. We developed click-seq, a pooled yeast-based activity assay, to test thousands of variants. Using click-seq, we measured the activity of 6,142 missense variants in yeast. We also measured the steady-state cellular abundance of 6,370 missense variants in a human cell line by using variant abundance by massively parallel sequencing (VAMP-seq). These data revealed that almost two-thirds of CYP2C9 variants showed decreased activity and that protein abundance accounted for half of the variation in CYP2C9 function. We also measured activity scores for 319 previously unannotated human variants, many of which may have clinical relevance.

Multiplexed measurement of variant abundance and activity reveals VKOR topology, active site and human variant impact.

Vitamin K epoxide reductase (VKOR) drives the vitamin K cycle, activating vitamin K-dependent blood clotting factors. VKOR is also the target of the widely used anticoagulant drug, warfarin. Despite VKOR's pivotal role in coagulation, its structure and active site remain poorly understood. In addition, VKOR variants can cause vitamin K-dependent clotting factor deficiency or alter warfarin response. Here, we used multiplexed, sequencing-based assays to measure the effects of 2,695 VKOR missense variants on abundance and 697 variants on activity in cultured human cells. The large-scale functional data, along with an evolutionary coupling analysis, supports a four transmembrane domain topology, with variants in transmembrane domains exhibiting strongly deleterious effects on abundance and activity. Functionally constrained regions of the protein define the active site, and we find that, of four conserved cysteines putatively critical for function, only three are absolutely required. Finally, 25% of human VKOR missense variants show reduced abundance or activity, possibly conferring warfarin sensitivity or causing disease.

Elucidating the Molecular Determinants of Aß Aggregation with Deep Mutational Scanning.

Despite the importance of Aß aggregation in Alzheimer's disease etiology, our understanding of the sequence determinants of aggregation is sparse and largely derived from in vitro studies. For example, in vitro proline and alanine scanning mutagenesis of Aß40 proposed core regions important for aggregation. However, we lack even this limited mutagenesis data for the more disease-relevant Aß42 Thus, to better understand the molecular determinants of Aß42 aggregation in a cell-based system, we combined a yeast DHFR aggregation assay with deep mutational scanning. We measured the effect of 791 of the 798 possible single amino acid substitutions on the aggregation propensity of Aß42 We found that ∼75% of substitutions, largely to hydrophobic residues, maintained or increased aggregation. We identified 11 positions at which substitutions, particularly to hydrophilic and charged amino acids, disrupted Aß aggregation. These critical positions were similar but not identical to critical positions identified in previous Aß mutagenesis studies. Finally, we analyzed our large-scale mutagenesis data in the context of different Aß aggregate structural models, finding that the mutagenesis data agreed best with models derived from fibrils seeded using brain-derived Aß aggregates.

A Combined Approach Reveals a Regulatory Mechanism Coupling Src's Kinase Activity, Localization, and Phosphotransferase-Independent Functions.

Multiple layers of regulation modulate the activity and localization of protein kinases. However, many details of kinase regulation remain incompletely understood. Here, we apply saturation mutagenesis and a chemical genetic method for allosterically modulating kinase global conformation to Src kinase, providing insight into known regulatory mechanisms and revealing a previously undiscovered interaction between Src's SH4 and catalytic domains. Abrogation of this interaction increased phosphotransferase activity, promoted membrane association, and provoked phosphotransferase-independent alterations in cell morphology. Thus, Src's SH4 domain serves as an intramolecular regulator coupling catalytic activity, global conformation, and localization, as well as mediating a phosphotransferase-independent function. Sequence conservation suggests that the SH4 domain regulatory interaction exists in other Src-family kinases. Our combined approach's ability to reveal a regulatory mechanism in one of the best-studied kinases suggests that it could be applied broadly to provide insight into kinase structure, regulation, and function.

Expression and Functional Characterization of Breast Cancer-Associated Cytochrome P450 4Z1 in Saccharomyces cerevisiae.

CYP4Z1 is an "orphan" cytochrome P450 (P450) enzyme that has provoked interest because of its hypothesized role in breast cancer through formation of the signaling molecule 20-hydroxyeicosatetraenoic acid (20-HETE). We expressed human CYP4Z1 in Saccharomyces cerevisiae and evaluated its catalytic capabilities toward arachidonic and lauric acids (AA and LA). Specific and sensitive mass spectrometry assays enabled discrimination of the regioselectivity of hydroxylation of these two fatty acids. CYP4Z1 generated 7-, 8-, 9-, 10-, and 11-hydroxy LA, whereas the 12-hydroxy metabolite was not detected. HET0016, the prototypic CYP4 inhibitor, only weakly inhibited laurate metabolite formation (IC50 ∼15 µM). CYP4Z1 preferentially oxidized AA to the 14(S),15(R)-epoxide with high regioselectivity and stereoselectivity, a reaction that was also insensitive to HET0016, but neither 20-HETE nor 20-carboxy-AA were detectable metabolites. Docking of LA and AA into a CYP4Z1 homology model was consistent with this preference for internal fatty acid oxidation. Thus, human CYP4Z1 has an inhibitor profile and product regioselectivity distinct from most other CYP4 enzymes, consistent with CYP4Z1's lack of a covalently linked heme. These data suggest that, if CYP4Z1 modulates breast cancer progression, it does so by a mechanism other than direct production of 20-HETE.

Molecular mechanisms of system responses to novel stimuli are predictable from public data.

Systems scale models provide the foundation for an effective iterative cycle between hypothesis generation, experiment and model refinement. Such models also enable predictions facilitating the understanding of biological complexity and the control of biological systems. Here, we demonstrate the reconstruction of a globally predictive gene regulatory model from public data: a model that can drive rational experiment design and reveal new regulatory mechanisms underlying responses to novel environments. Specifically, using ∼ 1500 publically available genome-wide transcriptome data sets from Saccharomyces cerevisiae, we have reconstructed an environment and gene regulatory influence network that accurately predicts regulatory mechanisms and gene expression changes on exposure of cells to completely novel environments. Focusing on transcriptional networks that induce peroxisomes biogenesis, the model-guided experiments allow us to expand a core regulatory network to include novel transcriptional influences and linkage across signaling and transcription. Thus, the approach and model provides a multi-scalar picture of gene dynamics and are powerful resources for exploiting extant data to rationally guide experimentation. The techniques outlined here are generally applicable to any biological system, which is especially important when experimental systems are challenging and samples are difficult and expensive to obtain-a common problem in laboratory animal and human studies.

Global analysis of condition-specific subcellular protein distribution and abundance.

Cellular control of protein activities by modulation of their abundance or compartmentalization is not easily measured on a large scale. We developed and applied a method to globally interrogate these processes that is widely useful for systems-level analyses of dynamic cellular responses in many cell types. The approach involves subcellular fractionation followed by comprehensive proteomic analysis of the fractions, which is enabled by a data-independent acquisition mass spectrometry approach that samples every available mass to charge channel systematically to maximize sensitivity. Next, various fraction-enrichment ratios are measured for all detected proteins across different environmental conditions and used to group proteins into clusters reflecting changes in compartmentalization and relative conditional abundance. Application of the approach to characterize the response of yeast proteins to fatty acid exposure revealed dynamics of peroxisomes and novel dynamics of MCC/eisosomes, specialized plasma membrane domains comprised of membrane compartment occupied by Can1 (MCC) and eisosome subdomains. It also led to the identification of Fat3, a fatty acid transport protein of the plasma membrane, previously annotated as Ykl187.

Asymmetric positive feedback loops reliably control biological responses.

Positive feedback is a common mechanism enabling biological systems to respond to stimuli in a switch-like manner. Such systems are often characterized by the requisite formation of a heterodimer where only one of the pair is subject to feedback. This ASymmetric Self-UpREgulation (ASSURE) motif is central to many biological systems, including cholesterol homeostasis (LXRα/RXRα), adipocyte differentiation (PPARγ/RXRα), development and differentiation (RAR/RXR), myogenesis (MyoD/E12) and cellular antiviral defense (IRF3/IRF7). To understand why this motif is so prevalent, we examined its properties in an evolutionarily conserved transcriptional regulatory network in yeast (Oaf1p/Pip2p). We demonstrate that the asymmetry in positive feedback confers a competitive advantage and allows the system to robustly increase its responsiveness while precisely tuning the response to a consistent level in the presence of varying stimuli. This study reveals evolutionary advantages for the ASSURE motif, and mechanisms for control, that are relevant to pharmacologic intervention and synthetic biology applications.