Equilibria between conformational states of the Ras oncogene protein revealed by high pressure crystallography

Girard, Éric; Lopes, Rui Pedro; Spoerner, Michael; Dhaussy, Anne-Claire; Prangé, Thierry; Kalbitzer, Hans Robert; Colloc’h, N.

doi:10.1039/d1sc05488k

Cited by 23 publications

(35 citation statements)

References 66 publications

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“…3 G and H ). Originally, Y32in.3P-ON and Y71in.3P-R were not suggested to bind to GAPs (rather an unidentified GTP-bound “state 3”) (36,37). Furthermore, we found that slight positional variations of Y32 in Y32in.3P-ON structures influence whether the catalytic GAP “arginine (R)-finger” (6) of NF1 can enter the RAS active site: when Y32 is within 4.5 Å of the GTP γ-phosphate ( Fig.…”

Section: Resultsmentioning

confidence: 99%

“…To do so, we analyzed RAS structures by their SW1 and SW2 configurations based on the backbone dihedral angle values of these loops: φ (phi), ψ (psi), and ω (omega). Since RAS structures in the PDB displayed the most dihedral variability on the Ramachandran map (35) (φ versus ψ plot) in residues [25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40] and residues 56-76 (SW2), we selected these residue ranges to analyze (Supplementary Fig. S1).…”

Section: Resultsmentioning

confidence: 99%

“…Includes the RAS GTP-binding (G) domain (residues 1-166). SW1 (residues [25][26][27][28][29][30][31][32][33][34][35][36][37][38][39][40] and SW2 (residues 56-76) loops highlighted. Supplementary Figure S2.…”

Section: Figures and Tables Supplementary Figures And Tablesmentioning

confidence: 99%

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Defining An Expanded RAS Conformational Landscape Based on Over 700 Experimentally Determined Structures of KRAS, NRAS, and HRAS

Parker

Meyer

Golemis

et al. 2022

Preprint

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RAS (KRAS, NRAS, and HRAS) proteins have widespread command of cellular circuitry and are high-priority drug targets in cancers and other diseases. Effectively targeting RAS proteins requires an exact understanding of their active, inactive, and druggable conformations, and the structural impact of mutations. Here we define an expanded classification of RAS conformations by clustering all 699 available human KRAS, NRAS, and HRAS structures in the Protein Data Bank (PDB) by the arrangement of their catalytic switch 1 (SW1) and switch 2 (SW2) loops. This enabled us to clearly define the geometry of closely related RAS conformations, many of which were not previously described. We determined the catalytic impact of the most common RAS mutations and identified several novel druggable RAS conformations. Our study expands the topography of characterized RAS conformations and will help inform future structure-guided RAS drug design.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

See 1 more Smart Citation

Defining An Expanded RAS Conformational Landscape Based on Over 700 Experimentally Determined Structures of KRAS, NRAS, and HRAS

Parker

Meyer

Golemis

et al. 2022

Preprint

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“…Flexibility underscores many aspects of protein function such as ligand binding, catalysis and allostery (Buhrman et al, 2010;Krojer et al, 2020;Henzler-Wildman & Kern, 2007;Eisenmesser et al, 2005). Rather than a single static structure, proteins exist as an ensemble of states, which repopulate in response to different perturbations and environments (Fraser et al, 2011;Girard et al, 2022;Russi et al, 2017). Developing comprehensive movies of protein motion can communicate a deeper understanding of the relationship between structure and function and reveal new opportunities to design therapeutics (Carlson, 2002;Meagher & Carlson, 2004).…”

Section: Introductionmentioning

confidence: 99%

FLEXR: automated multi-conformer model building using electron-density map sampling

Stachowski¹,

Fischer²

2023

Acta Crystallogr D Struct Biol

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Protein conformational dynamics that may inform biology often lie dormant in high-resolution electron-density maps. While an estimated ∼18% of side chains in high-resolution models contain alternative conformations, these are underrepresented in current PDB models due to difficulties in manually detecting, building and inspecting alternative conformers. To overcome this challenge, we developed an automated multi-conformer modeling program, FLEXR. Using Ringer-based electron-density sampling, FLEXR builds explicit multi-conformer models for refinement. Thereby, it bridges the gap of detecting hidden alternate states in electron-density maps and including them in structural models for refinement, inspection and deposition. Using a series of high-quality crystal structures (0.8–1.85 Å resolution), we show that the multi-conformer models produced by FLEXR uncover new insights that are missing in models built either manually or using current tools. Specifically, FLEXR models revealed hidden side chains and backbone conformations in ligand-binding sites that may redefine protein–ligand binding mechanisms. Ultimately, the tool facilitates crystallographers with opportunities to include explicit multi-conformer states in their high-resolution crystallographic models. One key advantage is that such models may better reflect interesting higher energy features in electron-density maps that are rarely consulted by the community at large, which can then be productively used for ligand discovery downstream. FLEXR is open source and publicly available on GitHub at https://github.com/TheFischerLab/FLEXR.

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“…Akasaka hypothesized early on that an equilibrium structure at higher pressure should correspond to one of the fluctuating structures at ambient pressure. , The fact that these low-lying excited conformeral substates are populated under high pressure implies that these states have a lower partial molar volume, for example due to hydration of water-accessible void space and pressure-sensitive cavities within the protein structure. For example, Kalbitzer et al have found that the proto-oncogenic protein Ras, which is involved in various signal transduction pathways that control proliferation, differentiation, and apoptosis, can adopt different CSs that are able to bind to Ras interaction partners (ref and references therein), and this information can be used to devise inhibitors for drug-development.…”

mentioning

confidence: 99%

Harnessing Pressure-Axis Experiments to Explore Volume Fluctuations, Conformational Substates, and Solvation of Biomolecular Systems

Oliva

Winter

2022

J. Phys. Chem. Lett.

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Intrinsic thermodynamic fluctuations within biomolecules are crucial for their function, and flexibility is one of the strategies that evolution has developed to adapt to extreme environments. In this regard, pressure perturbation is an important tool for mechanistically exploring the causes and effects of volume fluctuations in biomolecules and biomolecular assemblies, their role in biomolecular interactions and reactions, and how they are affected by the solvent properties. High hydrostatic pressure is also a key parameter in the context of deep-sea and subsurface biology and the study of the origin and physical limits of life. We discuss the role of pressure-axis experiments in revealing intrinsic structural fluctuations as well as high-energy conformational substates of proteins and other biomolecular systems that are important for their function and provide some illustrative examples. We show that the structural and dynamic information obtained from such pressure-axis studies improves our understanding of biomolecular function, disease, biological evolution, and adaptation.

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Equilibria between conformational states of the Ras oncogene protein revealed by high pressure crystallography

Abstract: In this work, we experimentally investigate the allosteric transitions between conformational states on the Ras oncogene protein using high pressure crystallography. Ras protein is a small GTPase involved in central...

Cited by 23 publications

References 66 publications

Defining An Expanded RAS Conformational Landscape Based on Over 700 Experimentally Determined Structures of KRAS, NRAS, and HRAS

Defining An Expanded RAS Conformational Landscape Based on Over 700 Experimentally Determined Structures of KRAS, NRAS, and HRAS

FLEXR: automated multi-conformer model building using electron-density map sampling

Harnessing Pressure-Axis Experiments to Explore Volume Fluctuations, Conformational Substates, and Solvation of Biomolecular Systems

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