Backbone RMSD Research Articles

A further leap of improvement in tertiary structure prediction in CASP13 prompts new routes for future assessments.

We present our assessment of tertiary structure predictions for hard targets in Critical Assessment of Structure Prediction round 13 (CASP13). The analysis includes (a) assignment and discussion of best models through scores-aided visual inspection of models for each evaluation unit (EU); (b) ranking of predictors resulting from this evaluation and from global scores; and (c) evaluation of progress, state of the art, and current limitations of protein structure prediction. We witness a sizable improvement in tertiary structure prediction building on the progress observed from CASP11 to CASP12, with (a) top models reaching backbone RMSD <3 å for several EUs of size <150 residues, contributed by many groups; (b) at least one model that roughly captures global topology for all EUs, probably unprecedented in this track of CASP; and (c) even quite good models for full, unsplit targets. Better structure predictions are brought about mainly by improved residue-residue contact predictions, and since this CASP also by distance predictions, achieved through state-of-the-art machine learning methods which also progressed to work with slightly shallower alignments compared to CASP12. As we reach a new realm of tertiary structure prediction quality, new directions are proposed and explored for future CASPs: (a) dropping splitting into EUs, (b) rethinking difficulty metrics probably in terms of contact and distance predictions, (c) assessing also side chains for models of high backbone accuracy, and (d) assessing residue-wise and possibly residue-residue quality estimates.

Molecular dynamics simulation of the interaction between human CD38 and some quinoline derivative inhibitors using reactive force field

AbstractThe paper presented initial calculated results obtained by molecular dynamics simulations of some CD38‐ micro and nanomolar inhibitor systems in vacuum using reactive force field ReaxFF. The ReaxFF software integrated in SCM's ADF has been used. The analysis and processing of results has been supplemented by VMD, CHIMERA and some external support softwares. The initial results showed that there are some associations between the inhibitor activity and the parameters compared apo and complex configurations. In particular, the higher the activity, the greater the difference in protein backbone RMSD between apo and complex. Nanomolar inhibitor molecules approached closer to the AC1 active site residues, especially GLU146 than micromolar one. In addition, the averaged and maximum fluctuation value of residues is also proportional to inhibitory activity. These can be considered suggestions for continuing to clarify the mechanism of CD38 inhibition of different ligand types supporting to the prediction and recommendation of new high active inhibitors

Extensive benchmark of rDock as a peptide-protein docking tool.

Peptide-protein interactions are ubiquitous in living cells and essential to a wide range of biological processes, as well as pathologies such as cancer or cardiovascular disease. Yet, obtaining reliable binding mode predictions in peptide-protein docking remains a great challenge for most computational docking programs. The main goal of this study was to assess the performance of the small molecule docking program rDock in comparison to other widely used small molecule docking programs, using 100 peptide-protein systems with peptides ranging from 2 to 12 residues. As we used two large independent benchmark sets previously published for other small-molecule docking programs (AutoDockVina benchmark and LEADSPEP), the performance of rDock could directly be compared to the performances of AutoDockVina, Surflex, GOLD, and Glide, as well as to the peptide docking protocol PIPER-FlexPepDock and the webserver HPepDock. Our benchmark reveals that rDock can dock the 100 peptides with an overall backbone RMSD below 2.5 Å in 58.5% of the cases (76% for the 47 systems of the AutoDockVina benchmark set and 43% for the 53 systems of the LEADSPEP benchmark set). More specifically, rDock docks up to 11-residue peptides with a backbone RMSD below 2.5 Å in 60.75% of the cases. rDock displays higher accuracy than most available small molecule docking programs for 6-10-residue peptides and can sometimes perform similarly to the peptide docking tool, especially at a high level of exhaustiveness (100 or 150 runs). Its performance, as is the case for many other unguided small molecule docking tools, is compromised when the peptides adopt secondary structures upon binding. However, our analyses suggest that rDock could be used for predicting how medium-sized biologically relevant peptides bind to their respective protein targets when the latter bind in an extended mode.

Determination and analysis of agonist and antagonist potential of naturally occurring flavonoids for estrogen receptor (ER\u03b1) by various parameters and molecular modelling approach

Most estrogen receptor α (ERα) ligands target the ligand binding domain (LBD). Agonist 17β-estradiol (E2) and tamoxifen (TM, known SERM), bind to the same site within the LBD. However, structures of ligand-bound complexes show that E2 and TM induce different conformations of helix 12 (H12). During the molecular modelling studies of some naturally occurring flavonoids such as quercetin, luteolin, myricetin, kaempferol, naringin, hesperidin, galangin, baicalein and epicatechin with human ERα (3ERT and 1GWR), we observed that most of the ligands bound to the active site pocket of both 3ERT and 1GWR. The docking scores, interaction analyses, and conformation of H12 provided the data to support for the estrogenic or antiestrogenic potential of these flavonoids to a limited degree. Explicit molecular dynamics for 50 ns was performed to identify the stability and compatibility pattern of protein-ligand complex and RMSD were obtained. Baicalein, epicatechin, and kaempferol with 1GWR complex showed similar RMSD trend with minor deviations in the protein backbone RMSD against 1GWR-E2 complex that provided clear indications that ligands were stable throughout the explicit molecular simulations in the protein and outcome of naringin-3ERT complex had an upward trend but stable throughout the simulations and all molecular dynamics showed stability with less than overall 1 Å deviation throughout the simulations. To examine their estrogenic or antiestrogenic potential, we studied the effect of the flavonoids on viability, progesterone receptor expression and 3xERE/3XERRE-driven reporter gene expression in ERα positive and estrogen responsive MCF-7 breast cancer cells. Epicatechin, myricetin, and kaempferol showed estrogenic potential at 5 µM concentration.

Asymmetric protein design from conserved supersecondary structures

Computational design with supersecondary structures as building blocks has proven effective in the construction of new proteins with controlled geometries. So far, this approach has primarily exploited amplification, effectively harnessing the internal folding propensity of self-compatible fragments to achieve sufficient enthalpy for folding. Here we exploit an interface-driven strategy to depart from the repeat design realm, constructing an asymmetric, globular domain from heterologous supersecondary structures. We report the successful design of a dRP lyase domain fold, which agrees with the experimental NMR structure at atomic accuracy (backbone RMSD of 0.94 Å). Our results show that the residual folding information within conserved fragments, combined with efficient interface-directed sampling, can effectively yield globular proteins with novel sequences and biophysical properties.

Definition of the R-superfamily of conotoxins: Structural convergence of helix-loop-helix peptidic scaffolds

The F14 conotoxins define a four-cysteine, three-loop conotoxin scaffold that produce tightly folded structures held together by two disulfide bonds with a CCCC arrangement (conotoxin framework 14). Here we describe the precursors of the F14 conotoxins from the venom of Conus anabathrum and Conus villepinii. Using transcriptomic and cDNA cloning analysis, the full-length of the precursors of flf14a and flf14b from the transcriptome of C. anabathrum revealed a unique signal sequence that defines the new conotoxin R-superfamily. Using the signal sequence as a primer, we cloned seven additional previously undescribed toxins of the R-superfamily from C. villepinii. The propeptide regions of the R-conotoxins are unusually long and with prevalent proline residues in repeating pentads which qualifies them as Pro-rich motifs (PRMs), which can be critical for protein-protein interactions or they can be cleaved to release short linear peptides that may be part of the envenomation mélange. Additionally, we determined the three-dimensional structure of vil14a by solution 1H-NMR and found that the structure of this conotoxin displays a cysteine-stabilized α-helix-loop-helix (Cs α/α) fold. The structure is well-defined over the helical regions (backbone RMSD for residues 2–13 and 17–26 is 0.63 ± 0.14 Å), with conformational flexibility in the triple Gly region of the second loop as well as the N- and C- termini. Structurally, the F14 conotoxins overlap with the Cs α/α scorpion toxins and other peptidic natural products, and in spite of their different exogenomic origins, there is convergence into this scaffold from several classes of living organisms that express these peptides.

Fragger: a protein fragment picker for structural queries.

Protein modeling and design activities often require querying the Protein Data Bank (PDB) with a structural fragment, possibly containing gaps. For some applications, it is preferable to work on a specific subset of the PDB or with unpublished structures. These requirements, along with specific user needs, motivated the creation of a new software to manage and query 3D protein fragments. Fragger is a protein fragment picker that allows protein fragment databases to be created and queried. All fragment lengths are supported and any set of PDB files can be used to create a database. Fragger can efficiently search a fragment database with a query fragment and a distance threshold. Matching fragments are ranked by distance to the query. The query fragment can have structural gaps and the allowed amino acid sequences matching a query can be constrained via a regular expression of one-letter amino acid codes. Fragger also incorporates a tool to compute the backbone RMSD of one versus many fragments in high throughput. Fragger should be useful for protein design, loop grafting and related structural bioinformatics tasks.

Fragger: a protein fragment picker for structural queries

Protein modeling and design activities often require querying the Protein Data Bank (PDB) with a structural fragment, possibly containing gaps. For some applications, it is preferable to work on a specific subset of the PDB or with unpublished structures. These requirements, along with specific user needs, motivated the creation of a new software to manage and query 3D protein fragments. Fragger is a protein fragment picker that allows protein fragment databases to be created and queried. All fragment lengths are supported and any set of PDB files can be used to create a database. Fragger can efficiently search a fragment database with a query fragment and a distance threshold. Matching fragments are ranked by distance to the query. The query fragment can have structural gaps and the allowed amino acid sequences matching a query can be constrained via a regular expression of one-letter amino acid codes. Fragger also incorporates a tool to compute the backbone RMSD of one versus many fragments in high throughput. Fragger should be useful for protein design, loop grafting and related structural bioinformatics tasks.

Fragger: a protein fragment picker for structural queries.

Protein modeling and design activities often require querying the Protein Data Bank (PDB) with a structural fragment, possibly containing gaps. For some applications, it is preferable to work on a specific subset of the PDB or with unpublished structures. These requirements, along with specific user needs, motivated the creation of a new software to manage and query 3D protein fragments. Fragger is a protein fragment picker that allows protein fragment databases to be created and queried. All fragment lengths are supported and any set of PDB files can be used to create a database. Fragger can efficiently search a fragment database with a query fragment and a distance threshold. Matching fragments are ranked by distance to the query. The query fragment can have structural gaps and the allowed amino acid sequences matching a query can be constrained via a regular expression of one-letter amino acid codes. Fragger also incorporates a tool to compute the backbone RMSD of one versus many fragments in high throughput. Fragger should be useful for protein design, loop grafting and related structural bioinformatics tasks.

Quantitative Protein Topography Measurements by High Resolution Hydroxyl Radical Protein Footprinting Enable Accurate Molecular Model Selection

We report an integrated workflow that allows mass spectrometry-based high-resolution hydroxyl radical protein footprinting (HR-HRPF) measurements to accurately measure the absolute average solvent accessible surface area (<SASA>) of amino acid side chains. This approach is based on application of multi-point HR-HRPF, electron-transfer dissociation (ETD) tandem MS (MS/MS) acquisition, measurement of effective radical doses by radical dosimetry, and proper normalization of the inherent reactivity of the amino acids. The accuracy of the resulting <SASA> measurements was tested by using well-characterized protein models. Moreover, we demonstrated the ability to use <SASA> measurements from HR-HRPF to differentiate molecular models of high accuracy (<3 Å backbone RMSD) from models of lower accuracy (>4 Å backbone RMSD). The ability of <SASA> data from HR-HRPF to differentiate molecular model quality was found to be comparable to that of <SASA> data obtained from X-ray crystal structures, indicating the accuracy and utility of HR-HRPF for evaluating the accuracy of computational models.

Structure of human POFUT1, its requirement in ligand-independent oncogenic Notch signaling, and functional effects of Dowling-Degos mutations.

Protein O-fucosyltransferase-1(POFUT1), which transfers fucose residues to acceptor sites on serine and threonine residues of epidermal growth factor-like repeats of recipient proteins, is essential for Notch signal transduction in mammals. Here, we examine the consequences of POFUT1 loss on the oncogenic signaling associated with certain leukemia-associated mutations of human Notch1, report the structures of human POFUT1 in free and GDP-fucose bound states, and assess the effects of Dowling-Degos mutations on human POFUT1 function. CRISPR-mediated knockout of POFUT1 in U2OS cells suppresses both normal Notch1 signaling, and the ligand-independent signaling associated with leukemogenic mutations of Notch1. Normal and oncogenic signaling are rescued by wild-type POFUT1 but rescue is impaired by an active-site R240A mutation. The overall structure of the human enzyme closely resembles that of the Caenorhabditis elegans protein, with an overall backbone RMSD of 0.93 Å, despite primary sequence identity of only 39% in the mature protein. GDP-fucose binding to the human enzyme induces limited backbone conformational movement, though the side chains of R43 and D244 reorient to make direct contact with the fucose moiety in the complex. The reported Dowling-Degos mutations of POFUT1, except for M262T, fail to rescue Notch1 signaling efficiently in the CRISPR-engineered POFUT1-/- background. Together, these studies identify POFUT1 as a potential target for cancers driven by Notch1 mutations and provide a structural roadmap for its inhibition.

NMR-based automated protein structure determination

NMR spectra analysis for protein structure determination can now in many cases be performed by automated computational methods. This overview of the computational methods for NMR protein structure analysis presents recent automated methods for signal identification in multidimensional NMR spectra, sequence-specific resonance assignment, collection of conformational restraints, and structure calculation, as implemented in the CYANA software package. These algorithms are sufficiently reliable and integrated into one software package to enable the fully automated structure determination of proteins starting from NMR spectra without manual interventions or corrections at intermediate steps, with an accuracy of 1–2 Å backbone RMSD in comparison with manually solved reference structures.

FlexPepDock lessons from CAPRI peptide-protein rounds and suggested new criteria for assessment of model quality and utility.

ABSTRACTCAPRI rounds 28 and 29 included, for the first time, peptide‐receptor targets of three different systems, reflecting increased appreciation of the importance of peptide‐protein interactions. The CAPRI rounds allowed us to objectively assess the performance of Rosetta FlexPepDock, one of the first protocols to explicitly include peptide flexibility in docking, accounting for peptide conformational changes upon binding. We discuss here successes and challenges in modeling these targets: we obtain top‐performing, high‐resolution models of the peptide motif for cases with known binding sites but there is a need for better modeling of flanking regions, as well as better selection criteria, in particular for unknown binding sites. These rounds have also provided us the opportunity to reassess the success criteria, to better reflect the quality of a peptide‐protein complex model. Using all models submitted to CAPRI, we analyze the correlation between current classification criteria and the ability to retrieve critical interface features, such as hydrogen bonds and hotspots. We find that loosening the backbone (and ligand) RMSD threshold, together with a restriction on the side chain RMSD measure, allows us to improve the selection of high‐accuracy models. We also suggest a new measure to assess interface hydrogen bond recovery, which is not assessed by the current CAPRI criteria. Finally, we find that surprisingly much can be learned from rather inaccurate models about binding hotspots, suggesting that the current status of peptide–protein docking methods, as reflected by the submitted CAPRI models, can already have a significant impact on our understanding of protein interactions. Proteins 2017; 85:445–462. © 2016 The Authors Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

Abstract 2170: Molecular modeling of novel peptide-receptor interaction for targeted drug delivery of prostate cancer

Abstract Prostate Cancer (PCa) is the second leading cause of cancer-related deaths among men in the United States. Due to the harsh side effects of conventional chemo- and radiotherapies, targeted drug delivery is now gaining the focus of cancer researchers. The key for success of any newly developed targeted drug delivery systems is the novel design of targeting peptides which have high binding affinities to differentially over-expressed receptors on the surface of PCa cells. Two over-expressed such receptors, which can be targeted to the cell surface of PCa cells are: Gonadotropin Releasing Hormone Receptor (GnRH-R), and Prostate Specific Membrane Antigen (PSMA). The analysis done from molecular dynamics simulation data gave an important information about each interaction; such as RMSD, The number of contacts between receptor and peptide within a cutoff distance of 5 Å and the binding free energies, ΔGGBSA of the interactions. In all systems, the back bone RMSD deviation of the receptor was calculated using the last 10 ns of the sampling process and averaged over all trajectories. The RMSD data deviated between 1.22 - 2.51 Å. The free binding energies or ΔGGBSA was calculated from the last 10 ns of the sampling process. The QH1 system has the more negative ΔGGBSA -36.15 kcal mol-1 and the QH4 system has the least negative ΔGGBSA of -18.4 kcal mol-1 among the eight systems of GnRH-R. QH2 system exhibits a highly interactive hydrogen bond (bond distance is 2.65 Å) between 134th position of the receptor amino acid sequence GLU and 5th position of the qh2 peptide's TYR. The ΔGGBSA is for the qh2 system is – 34.92 kcal mol-1. In the PSMA and its targeting peptide interactions, T2IA has the least negative ΔGGBSA of -47.37 kcal mol-1. A salt bridge was observed between the 10th position of the T2IA peptide sequence ARG and the 328 position of the 3RBU receptor's GLU. Based on our molecular modeling studies, we have determined the best targeting peptides among all the newly designed peptides. The binding efficiency of the targeting peptides with the lowest binding energies will be further investigated surface plasmon resonance (SPR) in near future. Citation Format: Ahmad Salam, Vincent Hembrick, Jesse Jaynes, Timothy Turner, Mohamed Abdalla. Molecular modeling of novel peptide-receptor interaction for targeted drug delivery of prostate cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2170.

Spatial structure of fibrinopeptide B in water solution with DPC micelles by NMR spectroscopy

Fibrinopeptide B (GluFib) is one of the factors of thrombosis. Normal blood protein soluble, fibrinogen (fibrinopeptide A and fibrinopeptide B), is transformed into the insoluble, fibrin, which in the form of filaments adheres to the vessel wall at the site of injury, forming a grid. However, the spatial structure of this peptide has not been established till now. In this article, GluFib peptide is investigated together with dodecylphosphocholine (DPC) micelles which were used for mimicking the environment of peptide in blood vessels. The spatial structure was obtained by applying 1D and 2D 1H–1H NMR spectroscopy (TOCSY, NOESY). It was shown that the fibrinopeptide B does not have a secondary structure but we can distinguish the fragment Gly 9 – Arg 14 with a good convergence (the backbone RMSD for the Gly9 – Arg14 is 0.18 ± 0.08 Å).

Computational Analysis of the Domain Architecture and Substrate-Gating Mechanism of Prolyl Oligopeptidases from Shewanella woodyi and Identification of Probable Lead Molecules.

Prolyl oligopeptidases (POPs) are serine proteases found in prokaryotes and eukaryotes which hydrolyze the peptide bond containing proline. The current study focuses on the analysis of POP sequences, their distribution and domain architecture in Shewanella woodyi, a Gram-negative, luminous bacterium which causes celiac sprue and similar infections in marine organisms. The POP undergoes huge interdomain movement, which allows possible route for the entry of any substrate. Hence, it offers an opportunity to understand the mechanism of substrate gating by studying the domain architecture and possibility to identify a probable drug target. In the present study, the POP sequence was retrieved from GenBank database and the best homologous templates were identified by PSI-BLAST search. The three-dimensional structures of the closed and open forms of POP from S. woodyi, which are not available in native form, were generated by homology modeling. The ideal lead molecules were screened by computer-aided virtual screening, and the binding potential of the best leads toward the target was studied by molecular docking. The domain architecture of the POP revealed that it has a propeller domain consists of [Formula: see text]-sheets, surrounded by [Formula: see text]-helices and [Formula: see text] hydrolase domain with catalytic triad containing Ser-564, Asp-646 and His-681. The hypothetical models of open and closed POP showed backbone RMSD value of 0.56 and 0.65Å, respectively. Ramachandran plot of the open and closed POP conformations accounts for 99.4 and 98.7% residues in the favoured region, respectively. Our study revealed that propeller domain comes as an insert between N-terminal and C-terminal [Formula: see text] hydrolase domain. Molecular docking, drug likeness properties and ADME prediction suggested that KUC-103481N and Pramiracetum can be used as probable lead molecules toward the POP from S. woodyi.

Solution NMR and molecular dynamics reveal a persistent alpha helix within the dynamic region of PsbQ from photosystem II of higher plants.

ABSTRACTThe extrinsic proteins of photosystem II of higher plants and green algae PsbO, PsbP, PsbQ, and PsbR are essential for stable oxygen production in the oxygen evolving center. In the available X‐ray crystallographic structure of higher plant PsbQ residues S14‐Y33 are missing. Building on the backbone NMR assignment of PsbQ, which includes this “missing link”, we report the extended resonance assignment including side chain atoms. Based on nuclear Overhauser effect spectra a high resolution solution structure of PsbQ with a backbone RMSD of 0.81 Å was obtained from torsion angle dynamics. Within the N‐terminal residues 1–45 the solution structure deviates significantly from the X‐ray crystallographic one, while the four‐helix bundle core found previously is confirmed. A short α‐helix is observed in the solution structure at the location where a β‐strand had been proposed in the earlier crystallographic study. NMR relaxation data and unrestrained molecular dynamics simulations corroborate that the N‐terminal region behaves as a flexible tail with a persistent short local helical secondary structure, while no indications of forming a β‐strand are found. Proteins 2015; 83:1677–1686. © 2015 The Authors. Proteins: Structure, Function, and Bioinformatics Published by Wiley Periodicals, Inc.

Folding Atomistic Proteins in Explicit Solvent Using Simulated Tempering.

Following a previous report on a coarse-grained protein model in implicit solvent, we applied simulated tempering (ST) with on-the-fly Helmholtz free energy (weight factors) determination to the folding or aggregation of seven proteins with the CHARMM, OPLS, and AMBER protein, and the SPC and TIP3P water force fields. For efficiency and reliability, we also performed replica exchange molecular dynamics (REMD) simulations on the alanine di- and deca-peptide, and the dimer of the Aβ16-22 Alzheimer's fragment, and used experimental data and previous simulation results on the chignolin, beta3s, Trp-cage, and WW domain peptides of 10-37 amino acids. The sampling with ST is found to be more efficient than with REMD for a much lower CPU cost. Starting from unfolded or extended conformations, the WW domain and the Trp-cage peptide fold to their NMR structures with a backbone RMSD of 2.0 and 1 Å. Remarkably, the ST simulation explores transient non-native topologies for Trp-cage that have been rarely discussed by other simulations. Our ST simulations also show that the CHARMM22* force field has limitations in describing accurately the beta3s peptide. Taken together, these results open the door to the study of the configurations of single proteins, protein aggregates, and any molecular systems at atomic details in explicit solvent using a single normal CPU. They also demonstrate that our ST scheme can be used with any force field ranging from quantum mechanics to coarse-grain and atomistic.

Molecular dynamics simulation reveals insights into the mechanism of unfolding by the A130T/V mutations within the MID1 zinc-binding Bbox1 domain.

The zinc-binding Bbox1 domain in protein MID1, a member of the TRIM family of proteins, facilitates the ubiquitination of the catalytic subunit of protein phosphatase 2A and alpha4, a protein regulator of PP2A. The natural mutation of residue A130 to a valine or threonine disrupts substrate recognition and catalysis. While NMR data revealed the A130T mutant Bbox1 domain failed to coordinate both structurally essential zinc ions and resulted in an unfolded structure, the unfolding mechanism is unknown. Principle component analysis revealed that residue A130 served as a hinge point between the structured β-strand-turn-β-strand (β-turn-β) and the lasso-like loop sub-structures that constitute loop1 of the ββα-RING fold that the Bbox1 domain adopts. Backbone RMSD data indicate significant flexibility and departure from the native structure within the first 5 ns of the molecular dynamics (MD) simulation for the A130V mutant (>6 Å) and after 30 ns for A130T mutant (>6 Å). Overall RMSF values were higher for the mutant structures and showed increased flexibility around residues 125 and 155, regions with zinc-coordinating residues. Simulated pKa values of the sulfhydryl group of C142 located near A130 suggested an increased in value to ~9.0, paralleling the increase in the apparent dielectric constants for the small cavity near residue A130. Protonation of the sulfhydryl group would disrupt zinc-coordination, directly contributing to unfolding of the Bbox1. Together, the increased motion of residues of loop 1, which contains four of the six zinc-binding cysteine residues, and the increased pKa of C142 could destabilize the structure of the zinc-coordinating residues and contribute to the unfolding.

Structural heterogeneity in microcrystalline ubiquitin studied by solid-state NMR.

By applying [1-(13) C]- and [2-(13) C]-glucose labeling schemes to the folded globular protein ubiquitin, a strong reduction of spectral crowding and increase in resolution in solid-state NMR (ssNMR) spectra could be achieved. This allowed spectral resonance assignment in a straightforward manner and the collection of a wealth of long-range distance information. A high precision solid-state NMR structure of microcrystalline ubiquitin was calculated with a backbone rmsd of 1.57 to the X-ray structure and 1.32 Å to the solution NMR structure. Interestingly, we can resolve structural heterogeneity as the presence of three slightly different conformations. Structural heterogeneity is most significant for the loop region β1-β2 but also for β-strands β1, β2, β3, and β5 as well as for the loop connecting α1 and β3. This structural polymorphism observed in the solid-state NMR spectra coincides with regions that showed dynamics in solution NMR experiments on different timescales.