scholarly journals Introducing site-specific cysteines into nanobodies for mercury labelling allowsde novophasing of their crystal structures

2017 ◽  
Vol 73 (10) ◽  
pp. 804-813 ◽  
Author(s):  
Simon Boje Hansen ◽  
Nick Stub Laursen ◽  
Gregers Rom Andersen ◽  
Kasper R. Andersen
Keyword(s):  
Structure Determination ◽  
De Novo ◽  
Protein Complexes ◽  
Protein Structures ◽  
Phase Information ◽  
X Ray Crystallography ◽  
Isomorphous Replacement ◽  
High Quality Protein ◽  
Radiation Induced

The generation of high-quality protein crystals and the loss of phase information during an X-ray crystallography diffraction experiment represent the major bottlenecks in the determination of novel protein structures. A generic method for introducing Hg atoms into any crystal independent of the presence of free cysteines in the target protein could considerably facilitate the process of obtaining unbiased experimental phases. Nanobodies (single-domain antibodies) have recently been shown to promote the crystallization and structure determination of flexible proteins and complexes. To extend the usability of nanobodies for crystallographic work, variants of the Nb36 nanobody with a single free cysteine at one of four framework-residue positions were developed. These cysteines could be labelled with fluorophores or Hg. For one cysteine variant (Nb36-C85) two nanobody structures were experimentally phased using single-wavelength anomalous dispersion (SAD) and single isomorphous replacement with anomalous signal (SIRAS), taking advantage of radiation-induced changes in Cys–Hg bonding. Importantly, Hg labelling influenced neither the interaction of Nb36 with its antigen complement C5 nor its structure. The results suggest that Cys–Hg-labelled nanobodies may become efficient tools for obtainingde novophase information during the structure determination of nanobody–protein complexes.

scholarly journals Role of Computational Methods in Going beyond X-ray Crystallography to Explore Protein Structure and Dynamics

2018 ◽  
Vol 19 (11) ◽  
pp. 3401 ◽  
Author(s):  
Ashutosh Srivastava ◽  
Tetsuro Nagai ◽  
Arpita Srivastava ◽  
Osamu Miyashita ◽  
Florence Tama
Keyword(s):  
Protein Dynamics ◽  
Computational Methods ◽  
Protein Structures ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
X Ray ◽  
X Ray Crystallography ◽  
Insight Into

Protein structural biology came a long way since the determination of the first three-dimensional structure of myoglobin about six decades ago. Across this period, X-ray crystallography was the most important experimental method for gaining atomic-resolution insight into protein structures. However, as the role of dynamics gained importance in the function of proteins, the limitations of X-ray crystallography in not being able to capture dynamics came to the forefront. Computational methods proved to be immensely successful in understanding protein dynamics in solution, and they continue to improve in terms of both the scale and the types of systems that can be studied. In this review, we briefly discuss the limitations of X-ray crystallography in studying protein dynamics, and then provide an overview of different computational methods that are instrumental in understanding the dynamics of proteins and biomacromolecular complexes.

scholarly journals Using iterative fragment assembly and progressive sequence truncation to facilitate phasing and crystal structure determination of distantly related proteins

2016 ◽  
Vol 72 (5) ◽  
pp. 616-628 ◽  
Author(s):  
Yan Wang ◽  
Jouko Virtanen ◽  
Zhidong Xue ◽  
John J. G. Tesmer ◽  
Yang Zhang
Keyword(s):  
Success Rate ◽  
Structure Determination ◽  
Protein Targets ◽  
Search Models ◽  
X Ray Crystallography ◽  
Structure Genomics ◽  
Related Proteins ◽  
Structure Assembly ◽  
Sequence Truncation

Molecular replacement (MR) often requires templates with high homology to solve the phase problem in X-ray crystallography.I-TASSER-MRhas been developed to test whether the success rate for structure determination of distant-homology proteins could be improved by a combination of iterative fragmental structure-assembly simulations with progressive sequence truncation designed to trim regions with high variation. The pipeline was tested on two independent protein sets consisting of 61 proteins from CASP8 and 100 high-resolution proteins from the PDB. After excluding homologous templates,I-TASSERgenerated full-length models with an average TM-score of 0.773, which is 12% higher than the best threading templates. Using these as search models,I-TASSER-MRfound correct MR solutions for 95 of 161 targets as judged by having a TFZ of >8 or with the final structure closer to the native than the initial search models. The success rate was 16% higher than when using the best threading templates.I-TASSER-MRwas also applied to 14 protein targets from structure genomics centers. Seven of these were successfully solved byI-TASSER-MR. These results confirm that advanced structure assembly and progressive structural editing can significantly improve the success rate of MR for targets with distant homology to proteins of known structure.

scholarly journals An Integrative Approach to Determine 3D Protein Structures Using Sparse Paramagnetic NMR Data and Physical Modeling

2021 ◽  
Vol 8 ◽  
Author(s):  
Kari Gaalswyk ◽  
Zhihong Liu ◽  
Hans J. Vogel ◽  
Justin L. MacCallum
Keyword(s):  
Structure Determination ◽  
Residual Dipolar Couplings ◽  
Chemical Shifts ◽  
Protein Structures ◽  
Physical Modelling ◽  
Paramagnetic Nmr ◽  
Integrative Approach ◽  
Nmr Methods ◽  
Muscle Myosin

Paramagnetic nuclear magnetic resonance (NMR) methods have emerged as powerful tools for structure determination of large, sparsely protonated proteins. However traditional applications face several challenges, including a need for large datasets to offset the sparsity of restraints, the difficulty in accounting for the conformational heterogeneity of the spin-label, and noisy experimental data. Here we propose an integrative approach to structure determination combining sparse paramagnetic NMR with physical modelling to infer approximate protein structural ensembles. We use calmodulin in complex with the smooth muscle myosin light chain kinase peptide as a model system. Despite acquiring data from samples labeled only at the backbone amide positions, we are able to produce an ensemble with an average RMSD of ∼2.8 Å from a reference X-ray crystal structure. Our approach requires only backbone chemical shifts and measurements of the paramagnetic relaxation enhancement and residual dipolar couplings that can be obtained from sparsely labeled samples.

scholarly journals CryoEM structure determination of small protein complexes with the Volta phase plate

2017 ◽  
Vol 73 (a1) ◽  
pp. a137-a137
Author(s):  
Maryam Khoshouei ◽  
Radostin Danev ◽  
Mazdak Radjainia ◽  
Wolfgang Baumeister
Keyword(s):  
Structure Determination ◽  
Protein Complexes ◽  
Phase Plate ◽  
Small Protein

scholarly journals Structure determination of GPCRs: cryo-EM compared with X-ray crystallography

2021 ◽  
Author(s):  
Javier García-Nafría ◽  
Christopher G. Tate
Keyword(s):  
Structural Biology ◽  
Structure Determination ◽  
Drug Targets ◽  
Cellular Systems ◽  
Single Family ◽  
Structure Based Drug Design ◽  
X Ray ◽  
Surface Receptors ◽  
X Ray Crystallography

G protein-coupled receptors (GPCRs) are the largest single family of cell surface receptors encoded by the human genome and they play pivotal roles in co-ordinating cellular systems throughout the human body, making them ideal drug targets. Structural biology has played a key role in defining how receptors are activated and signal through G proteins and β-arrestins. The application of structure-based drug design (SBDD) is now yielding novel compounds targeting GPCRs. There is thus significant interest from both academia and the pharmaceutical industry in the structural biology of GPCRs as currently only about one quarter of human non-odorant receptors have had their structure determined. Initially, all the structures were determined by X-ray crystallography, but recent advances in electron cryo-microscopy (cryo-EM) now make GPCRs tractable targets for single-particle cryo-EM with comparable resolution to X-ray crystallography. So far this year, 78% of the 99 GPCR structures deposited in the PDB (Jan–Jul 2021) were determined by cryo-EM. Cryo-EM has also opened up new possibilities in GPCR structural biology, such as determining structures of GPCRs embedded in a lipid nanodisc and multiple GPCR conformations from a single preparation. However, X-ray crystallography still has a number of advantages, particularly in the speed of determining many structures of the same receptor bound to different ligands, an essential prerequisite for effective SBDD. We will discuss the relative merits of cryo-EM and X-ray crystallography for the structure determination of GPCRs and the future potential of both techniques.

scholarly journals Protein shape sampled by ion mobility mass spectrometry consistently improves protein structure prediction

2021 ◽  
Author(s):  
SM Bargeen Alam Turzo ◽  
Justin Thomas Seffernick ◽  
Amber D Rolland ◽  
Micah T Donor ◽  
Sten Heinze ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Protein Structure ◽  
Ion Mobility ◽  
Structure Determination ◽  
Tertiary Structure ◽  
De Novo ◽  
Structural Information ◽  
Collision Cross Section ◽  
Protein Structures ◽  
Protein Shape

Among a wide variety of mass spectrometry (MS) methodologies available for structural characterizations of proteins, ion mobility (IM) provides structural information about protein shape and size in the form of an orientationally averaged collision cross-section (CCS). While IM data have been predominantly employed for the structural assessment of protein complexes, CCS data from IM experiments have not yet been used to predict tertiary structure from sequence. Here, we are showing that IM data can significantly improve protein structure determination using the modeling suite Rosetta. The Rosetta Projection Approximation using Rough Circular Shapes (PARCS) algorithm was developed that allows for fast and accurate prediction of CCS from structure. Following successful rigorous testing for accuracy, speed, and convergence of PARCS, an integrative modelling approach was developed in Rosetta to use CCS data from IM experiments. Using this method, we predicted protein structures from sequence for a benchmark set of 23 proteins. When using IM data, the predicted structure improved or remained unchanged for all 23 proteins, compared to the predicted models in the absence of CCS data. For 15/23 proteins, the RMSD (root-mean-square deviation) of the predicted model was less than 5.50 Å, compared to only 10/23 without IM data. We also developed a confidence metric that successfully identified near-native models in the absence of a native structure. These results demonstrate the ability of IM data in de novo structure determination.

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