XFEL and NMR Structures of Francisella Lipoprotein Reveal Conformational Space of Drug Target against Tularemia

Zook, James; Shekhar, Mrinal; Hansen, Debra T.; Conrad, Chelsie E.; Grant, Thomas D.; Gupta, Chitrak; White, Thomas A.; Barty, Anton; Basu, Shibom; Zhao, Yun; Zatsepin, Nadia A.; Ishchenko, Andrii; Batyuk, Alex; Gati, Cornelius; Li, Chufeng; Galli, Lorenzo; Coe, Jesse; Hunter, Mark S.; Liang, Meng; Weierstall, Uwe; Nelson, Garret B.; James, Daniel; Stauch, Benjamin; Craciunescu, Felicia M.; Thifault, Darren; Liu, Wei; Cherezov, Vadim; Singharoy, Abhishek; Fromme, Petra

doi:10.1016/j.str.2020.02.005

Cited by 10 publications

(12 citation statements)

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“…At lower resolutions (≥5 Å), the converged statistics favor closed state over the open state. This result is in stark contrast to NMR that favors the open state to the close state by a population ratio of 2:1 63.…”

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confidence: 79%

Data-guided Multi-Map variables for ensemble refinement of molecular movies

Vant

Sarkar

Fiorin

et al. 2020

Preprint

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Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. Here, the 3-dimensional electron density of a protein, as it would be deter-mined by cryo-EM or X-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous density-driven molecular dynamics methodologies that determine only the best map-model fits, our work uses the recently developed Multi-Map methodology to monitor concerted move-ments within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along reaction coordinates derived from electron densities can serve to induce conformational transitions between known intermediates. The simulated path-ways appear reversible, with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein DataBank. We find that the best quantitative agreement with experimental free-energy differences is obtained using medium resolution (∼5 Å) density information cou-pled to comparatively large structural transitions. Practical considerations for generating transitions with multiple intermediate atomic density distributions are also discussed.

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confidence: 79%

Data-guided Multi-Map variables for ensemble refinement of molecular movies

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Sarkar

Fiorin

et al. 2020

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“…As visualized in Fig. 2 and noted in discussions of prior simulations, 63 the transition in FLPP3 depends on the rotation of Tyr83 from packing in the interior to becoming solvent-exposed. This relatively subtle shift is difficult to capture in the context of low-resolution electron densities, unlike the much larger conformational changes for ADK and CODH (Fig.…”

Section: B Steering MD Along Low-resolution Multi-map Variables Produces Complete Transitionsmentioning

confidence: 64%

“…[88][89][90] A similar analysis indicates that the A state would be favored in both CODH and FLPP3. For FLPP3 specifically, where the NMR-derived open state represented by state B is known to be more prevalent, 63 this is further evidence that this reaction coordinate is not reliable in capturing relatively modest structural rearrangements.…”

Section: B Steering MD Along Low-resolution Multi-map Variables Produces Complete Transitionsmentioning

confidence: 96%

“…The carbon monoxide dehydrogenase (CODH) A and B states are taken from chains D and C of the PDBID 1OAO 62 structure. The FLPP3 A and B states are drawn from the crystal structure PDBID 6PNY 63 and the NMR structure PDBID 2MU4, 64 respectively. The flipped tyrosine residue, Tyr83, is highlighted within the FLPP3 structure.…”

Section: Steered Molecular Dynamics (Smd)mentioning

confidence: 99%

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Data-guided Multi-Map variables for ensemble refinement of molecular movies

Vant

Sarkar

Streitwieser

et al. 2020

The Journal of Chemical Physics

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Driving molecular dynamics simulations with data-guided collective variables offer a promising strategy to recover thermodynamic information from structure-centric experiments. Here, the 3-dimensional electron density of a protein, as it would be determined by cryo-EM or X-ray crystallography, is used to achieve simultaneously free-energy costs of conformational transitions and refined atomic structures. Unlike previous densitydriven molecular dynamics methodologies that determine only the best map-model fits, our work uses the recently developed Multi-Map methodology to monitor concerted movements within equilibrium, non-equilibrium, and enhanced sampling simulations. Construction of all-atom ensembles along chosen values of the Multi-Map variable enables simultaneous estimation of average properties, as well as real-space refinement of the structures contributing to such averages. Using three proteins of increasing size, we demonstrate that biased simulation along reaction coordinates derived from electron densities can serve to induce conformational transitions between known intermediates. The simulated pathways appear reversible, with minimal hysteresis and require only low-resolution density information to guide the transition. The induced transitions also produce estimates for free energy differences that can be directly compared to experimental observables and population distributions. The refined model quality is superior compared to those found in the Protein DataBank. We find that the best quantitative agreement with experimental freeenergy differences is obtained using medium resolution (∼5 Å) density information coupled to comparatively large structural transitions. Practical considerations for generating transitions with multiple intermediate atomic density distributions are also discussed.2

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“…Francisella lipoprotein Flpp3 is a 108 amino acids long membrane-interacting protein that serves as a target for drug development against tularemia(34). In this case, we had two datasets: one at high resolution (1.8 Å) from our Serial Femtosecond X-ray (SFX) crystallography experiments of Flpp3 (See Supplementary Information and (35), and a synthetic one at low resolution (5.0 Å). The point of this test was to see if we could use the low-resolution data to achieve the high-resolution structure.…”

Section: B Test On a Soluble Lipoprotein With A Uniformly High-resolu-mentioning

confidence: 99%

CryoFold: determining protein structures and ensembles from cryo-EM data

Shekhar

Terashi

Gupta

et al. 2019

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1 Cryo-EM is a powerful method for determining biomolecular structures. But, unlike Xray crystallography or solution-state NMR, which are data-rich, cryo-EM can be data-poor.Cryo-EM routinely gives electron density information to about 3-5Å and the resolution often varies across the structure. So, it has been challenging to develop an automated computer algorithm that converts the experimental density maps to complete molecular structures. We address this challenge with CryoFold, a computational method that finds the chain trace from the density maps using MAINMAST, then performs molecular dynamics simulations using ReMDFF, a resolution-exchange flexible fitting protocol, accelerated by MELD, which uses low-information data to broaden the relevant conformational searching of secondary and tertiary structures. We describe four successes of structure determinations, including for membrane proteins and large molecules. CryoFold handles input data that is heterogeneous, and even sparse. The software is automated, and is available to the public via a python-based graphical user interface. IntroductionCryo-electron microscopy (cryo-EM) has emerged to be one of the most successful methods for determining the structures of proteins and other biomolecules. It has produced more than 8000 structures in less than two decades. Cryo-EM serves a niche -such as large complexes or membrane proteins or molecules that are not easily crystallizable -that traditional methods, such as X-ray diffraction, electron or neutron scattering, or NMR often cannot handle.Similar to X-ray crystallography, cryo-EM data produces electron density maps. To deter-2 mine molecular structures from these maps requires automated computer algorithms. Development of such methods however, has been a major bottleneck. Unlike X-ray crystallography, which is normally high-resolution (data rich), cryo-EM is often mid-resolution (data poor). As a consequence, application of the popular X-ray refinement protocol PHENIX to cryo-EM data enables models that are between 47-71% complete 1 . Another popular de-novo refinement method, Rosetta, builds an initial model by assembling fragment structures, and then optimizes this model in all-atom details by fitting to an EM map. While it is generally more challenging for the EM variants of Rosetta to automatically fold β-sheets into electron density maps 2 , it also requires that at least 70% of the Cα atoms be placed correctly 3-5 . Molecular Dynamics (MD) simulations using an atomistic force field 6, 7 ensure that structures are consistent with physical forces, but MD is computationally expensive and can determine wrong structures that are not native [8][9][10] . Therefore, MD is sometimes augmented with external information such as evolutionary covariance 11, 12 or homology-based starting models 13, 14 . Nonetheless, these additions can introduce new discrepancies that are refractory to automated fixes 5, 15 .Here, we describe CryoFold, an atomistic-physical algorithm that derives protein structures from cryo-EM data. ...

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XFEL and NMR Structures of Francisella Lipoprotein Reveal Conformational Space of Drug Target against Tularemia

Abstract: Highlights d X-ray free-electron laser unveils alternative protein structure of lipoprotein d Advanced molecular dynamics explore conformational space among solved structures d Virtual ligand screening shows possible lead fragments for potential drug therapies

Cited by 10 publications

References 50 publications

Data-guided Multi-Map variables for ensemble refinement of molecular movies

Data-guided Multi-Map variables for ensemble refinement of molecular movies

Data-guided Multi-Map variables for ensemble refinement of molecular movies

CryoFold: determining protein structures and ensembles from cryo-EM data

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