Protein structures given in PDB and SNP's

Protein structures given in PDB and SNP's

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There are millions of proteins given in PDB, the sequence for which we can download in FASTA format. There are also hundreds of SNP's given in NCBI dbSNP. My question is whether the proteins in PDB incorporate the SNP's into their structure? If not, is there a way to visualize protein structure using any tool after a SNP on the protein? I know that tools like SIFT exist but they only say whether or not a SNP is harmful or not. They don't comment on the structure of the protein in anyway.

Swiss PDB Viewer allows you to mutate residues in an existing structure and explore the effects.

I'm pretty sure that UCSF Chimera does too.

Solving the 3D structure of a protein is hard and a lot of work, doing that for every common SNP of a protein would be excessive in most cases. So you generally won't find such structures unless the structure of the specific mutated version is particularly interesting.

In many cases it is also not structurally interesting what happens, there is no point in trying to get the 3D structure if an SNP leads to a frameshift or an early stop codon.

What you can do is simply load the PDB structure of the wildtype protein into a viewer like PyMol and look at the amino acid that is changes by the SNP. Read the associated paper to find out if that residue is important in some way. This won't be always possible, but if e.g. the amino acid is in the catalytic center of an enzyme, this would explain how the SNP affect the function of the protein.

check out the sequence page at RCSB PDB, it can show SNPs mapped onto 3D for some of the proteins (you need to enable the SNP annotations in the drop-down)


DOIs for PDB structures follow the format: 10.2210/pdbXXXX/pdb, where XXXX is replaced with the PDB ID (e.g., 10.2210/pdb4hhb/pdb). DOI citations should include the entry authors, deposition year, structure title, and DOI.

A PDB structure with a corresponding publication should be referenced by PDB ID and cited using both the corresponding DOI and publication.

DOI Citation:
Ormo, M., Remington, S.J. (1996) Green fluorescent protein from Aequorea victoria doi: 10.2210/pdb1ema/pdb

Literature Citation:
Ormo, M., Cubitt, A.B., Kallio, K., Gross, L.A., Tsien, R.Y., Remington, S.J. (1996) Crystal structure of the Aequorea victoria green fluorescent protein Science 273: 1392-1395 doi: 10.1126/science.273.5280.1392

A PDB structure without a corresponding publication should be referenced by PDB ID and cited using the DOI Citation (entry authors, deposition year, structure title, and DOI):

PDB ID: 1ci0
DOI Citation:
Shi, W., Ostrov, D.A., Gerchman, S.E., Graziano, V., Kycia, H., Studier, B., Almo, S.C., Burley, S.K., New York SGX Research Center for Structural Genomics (NYSGXRC) (1999) PNP Oxidase from Saccharomyces cerevisiae doi: 10.2210/pdb1ci0/pdb

RCSB PDB should be referenced with the URL and the following citation:

H.M. Berman, J. Westbrook, Z. Feng, G. Gilliland, T.N. Bhat, H. Weissig, I.N. Shindyalov, P.E. Bourne.
(2000) The Protein Data Bank Nucleic Acids Research, 28: 235-242.

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Image from the RCSB PDB ( of PDB ID 1BNA (H.R. Drew, R.M. Wing, T. Takano, C. Broka, S. Tanaka, K. Itakura, R.E.Dickerson) (1981) Structure of a B-DNA dodecamer: conformation and dynamics Proc.Natl.Acad.Sci.USA 78: 2179-2183).

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Image of 1AOI (K. Luger, A.W. Mader, R.K. Richmond, D.F. Sargent, T.J. Richmond (1997) Crystal structure of the core particle at 2.8Å resolution Nature 389: 251-260) created with NGL (A.S. Rose, A.R. Bradley, Y. Valasatava, J.D. Duarte, A. Prlić, P.W. Rose (2018) NGL viewer: web-based molecular graphics for large complexes. Bioinformatics 34: 3755–3758).

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Methods for Determining Atomic Structures

Several methods are currently used to determine the structure of a protein, including X-ray crystallography, NMR spectroscopy, and electron microscopy. Each method has advantages and disadvantages. In each of these methods, the scientist uses many pieces of information to create the final atomic model. Primarily, the scientist has some kind of experimental data about the structure of the molecule. For X-ray crystallography, this is the X-ray diffraction pattern. For NMR spectroscopy, it is information on the local conformation and distance between atoms that are close to one another. In electron microscopy, it is an image of the overall shape of the molecule.

In most cases, this experimental information is not sufficient to build an atomic model from scratch. Additional knowledge about the molecular structure must be added. For instance, we often already know the sequence of amino acids in a protein, and we know the preferred geometry of atoms in a typical protein (for example, the bond lengths and bond angles). This information allows the scientist to build a model that is consistent with both the experimental data and the expected composition and geometry of the molecule.

When looking at PDB entries, it is always good to be a bit critical. Keep in mind that the structures in the PDB archive are determined using a balanced mixture of experimental observation and knowledge-based modeling. It often pays to take a little extra time to confirm for yourself that the experimental evidence for a particular structure supports the model as represented and the scientific conclusions based on the model.

X-ray Crystallography

Most of the structures included in the PDB archive were determined using X-ray crystallography. For this method, the protein is purified and crystallized, then subjected to an intense beam of X-rays. The proteins in the crystal diffract the X-ray beam into one or another characteristic pattern of spots, which are then analyzed (with some tricky methods to determine the phase of the X-ray wave in each spot) to determine the distribution of electrons in the protein. The resulting map of the electron density is then interpreted to determine the location of each atom. The PDB archive contains two types of data for crystal structures. The coordinate files include atomic positions for the final model of the structure, and the data files include the structure factors (the intensity and phase of the X-ray spots in the diffraction pattern) from the structure determination. You can create an image of the electron density map using tools like the Astex viewer, which is available through a link on the Structure Summary page.

X-ray crystallography can provide very detailed atomic information, showing every atom in a protein or nucleic acid along with atomic details of ligands, inhibitors, ions, and other molecules that are incorporated into the crystal. However, the process of crystallization is difficult and can impose limitations on the types of proteins that may be studied by this method. For example, X-ray crystallography is an excellent method for determining the structures of rigid proteins that form nice, ordered crystals. Flexible proteins, on the other hand, are far more difficult to study by this method because crystallography relies on having many, many molecules aligned in exactly the same orientation, like a repeated pattern in wallpaper. Flexible portions of protein will often be invisible in crystallographic electron density maps, since their electron density will be smeared over a large space. This is described in more detail on the page about missing coordinates.

Biological molecule crystals are finicky: some form perfect, well-ordered crystals and others form only poor crystals. The accuracy of the atomic structure that is determined depends on the quality of these crystals. In perfect crystals, we have far more confidence that the atomic structure correctly reflects the structure of the protein. Two important measures of the accuracy of a crystallographic structure are its resolution, which measures the amount of detail that may be seen in the experimental data, and the R-value, which measures how well the atomic model is supported by the experimental data found in the structure factor file.

The experimental electron density from a structure of DNA is shown here (PDB entry 196d), along with the atomic model that was generated based on the data. The contours surround regions with high densities of electrons, which correspond to the atoms in the molecule.

As part of the biocuration process, the wwPDB generates Validation Reports that provide an assessment of structure quality using widely accepted standards and criteria. These Reports include an "executive” summary image of key quality indicators to help non-experts interpret these reports. For more information, visit

Exploring Biological Structure and Function using X-ray Free Electron Lasers (XFEL)

New technology, termed serial femtosecond crystallography, is revolutionizing the methods of X-ray crystallography. A free electron X-ray laser (XFEL) is used to create pulses of radiation that are extremely short (lasting only femtoseconds) and extremely bright. A stream of tiny crystals (nanometers to micrometers in size) is passed through the beam, and each X-ray pulse produces a diffraction pattern from a crystal, often burning it up in the process. A full data set is compiled from as many as tens of thousands of these individual diffraction patterns. The method is very powerful because it allows scientists to study molecular processes that occur over very short time scales, such as the absorption of light by biological chromophores.

Structures of photoactive yellow protein were determined by serial femtosecond crystallography after illumination, capturing the isomerization of the chromophore after it absorbs light. Structures included in this movie include: 5hd3 (ground state), 5hdc (100-400 femtoseconds after illumination), 5hdd (800-1200 femtoseconds), 5hds (3 picoseconds), 4b9o (100 picoseconds), 5hd5 (200 nanoseconds) and 1ts0 (1 millisecond). For more, see Molecule of the Month on Photoactive Yellow Protein.

NMR Spectroscopy

NMR spectroscopy may be used to determine the structure of proteins. The protein is purified, placed in a strong magnetic field, and then probed with radio waves. A distinctive set of observed resonances may be analyzed to give a list of atomic nuclei that are close to one another, and to characterize the local conformation of atoms that are bonded together. This list of restraints is then used to build a model of the protein that shows the location of each atom. The technique is currently limited to small or medium proteins, since large proteins present problems with overlapping peaks in the NMR spectra.

A major advantage of NMR spectroscopy is that it provides information on proteins in solution, as opposed to those locked in a crystal or bound to a microscope grid, and thus, NMR spectroscopy is the premier method for studying the atomic structures of flexible proteins. A typical NMR structure will include an ensemble of protein structures, all of which are consistent with the observed list of experimental restraints. The structures in this ensemble will be very similar to each other in regions with strong restraints, and very different in less constrained portions of the chain. Presumably, these areas with fewer restraints are the flexible parts of the molecule, and thus do not give a strong signal in the experiment.

In the PDB archive, you will typically find two types of coordinate entries for NMR structures. The first includes the full ensemble from the structural determination, with each structure designated as a separate model. The second type of entry is a minimized average structure. These files attempt to capture the average properties of the molecule based on the different observations in the ensemble. You can also find a list of restraints that were determined by the NMR experiment. These include things like hydrogen bonds and disulfide linkages, distances between hydrogen atoms that are close to one another, and restraints on the local conformation and stereochemistry of the chain.

Some of the restraints used to solve the structure of a small monomeric hemoglobin are shown here, using software from the BioMagResBank 1 . The protein (1vre and 1vrf) is shown in green, and restraints are shown in yellow.

3D Electron Microscopy

Electron microscopy, frequently referred to as 3DEM, is also used to determine 3D structures of large macromolecular assemblies. A beam of electrons and a system of electron lenses is used to image the biomolecule directly. Several tricks are required to obtain a 3D structure from 2D projection images produced by transmission electron microscopes. The most commonly used technique today involves imaging of many thousands of different single particles preserved in a thin layer of non-crystalline ice (cryo-EM). Provided these views show the molecule in myriad different orientations, a computational approach akin to that used for computerized axial tomography or CAT scans in medicine will yield a 3D mass density map. With a sufficient number of single particles, the 3DEM maps can then be interpreted by fitting an atomic model of the macromolecule into the map, just as macromolecular crystallographers interpret their electron density maps. In a restricted number of cases, electron diffraction from 2D or 3D crystals or helical assemblies of biomolecules can be used determine 3D structures with an electron microscope using an approach very similar to that of X-ray crystallography. Finally, 3DEM techniques are gaining prominence in studying biological assemblies inside cryo-preserved cells and tissues using electron tomography. This method involves recording images at different tilt angles and averaging the images across multiple copies of the biological assembly in situ.

In terms of molecular and atomic detail, both single-particle 3DEM and electron diffraction methods are now yielding structures at resolution limits comparable to macromolecular crystallography (i.e., enabling visualization of amino acid sidechains, surface water molecules, and non-covalently bound ligands). Cryo-electron tomography provides structural information at slightly lower resolution (i.e., protein domains and secondary structural elements). In calendar 2016, PDB depositions of 3DEM structures exceeded those coming from NMR spectroscopy for the first time.

Recent dramatic advances in the power of 3DEM reflect the convergence of a number of technologies, including sample preparation/preservation in vitreous ice, improved electron optics, phase plates to enhance electron image contrast, direct electron detectors, improved data processing software, and faster computers. This fortuitous convergence parallels the acceleration of macromolecular crystallography that occurred in the 1990s, when crystal freezing, synchrotron radiation beamlines, image plate and CCD detectors, improved data processing software, and faster computers came together in an earlier perfect storm for structural biology.

In work focused on very large macromolecular assemblies, where lower resolution is the norm, 3DEM data are increasingly being combined with information from X-ray crystallography, NMR spectroscopy, mass spectrometry, chemical cross-linking, fluorescence resonance energy transfer, and various computational techniques to sort out the atomic details. This practice of fusing multiple experimental approaches is often referred to as Integrative or Hybrid Methods (I/HM). They have proven very useful for multimolecular structures such as complexes of ribosomes, tRNA and protein factors, and muscle actomyosin structures. A prototype data repository, PDB-Dev, operating in parallel with the PDB is now available for archiving of I/HM structures and data.

This cryo-EM map of beta-galactosidase was built from over 90,000 images of the molecule frozen in ice, which was detailed enough to provide an atomic model. The cryoEM map is at EMDataBank entry EMD-2984, and the atomic coordinates are in PDB entry 5a1a.
Image courtesy of Veronica Falconieri and Siriam Subramaniam, National Cancer Institute.

Integrative Modeling

Researchers are interested in studying larger and more complex systems, and use every technique available to do so. The structural biology community has had particular success in recent years by using an approach, termed &ldquointegrative modeling.&rdquo The idea is to combine information from a variety of methods, each good for studying a particular aspect of the system, to create an overall picture of the assembly.

For instance, combining spectroscopic or chemical crosslinking data that identify distances between components in an assembly, with low resolution electron microscopy data that give information on the overall shape of a complex, has become an effective strategy in integrative modeling. In addition to traditional structural biology methods such as X-ray crystallography, NMR spectroscopy and electron microscopy, experimental methods such as small angle solution scattering, Forster resonance energy transfer, chemical crosslinking, mass spectrometry, electron paramagnetic resonance spectroscopy, and other biophysical techniques have been used in integrative modeling studies. A key aspect of integrative modeling is that the resulting structural models do not always comprise of atomic coordinates and can contain regions of coarse-grained beads that represent multiple atoms. This is due to the fact that different kinds of experiments provide information at different levels of resolution.

An example of integrative modeling is the structure of the nuclear pore complex (NPC) from budding yeast determined using data from chemical crosslinking, small angle solution scattering and electron microscopy experiments. The NPC is an eight-fold symmetric assembly consisting of 552 copies of 32 different proteins belonging to the nucleoporin family. The overall shape of the NPC is obtained from a low resolution electron microscopy map. Extensive data from chemical crosslinking experiments provide information regarding the proximities and orientations of the nucleoporins within the assembly. Small angle scattering profiles for some of the nucleoporins are available and structures of several component nucleoporins and their sub-complexes have been obtained using experimental methods and/or computational modeling. All available information are gathered and combined together using computational algorithms to build the integrative model of the entire complex. This model of the NPC is archived in a prototype repository for integrative structural models, called PDB-Dev (accession code: PDBDEV_00000012). PDB-Dev has been created so that structural models determined using integrative modeling approaches can be collected, archived and made available to the public in a standard way.

Introduction to Biological Assemblies and the PDB Archive

When exploring Structure Summary pages on the RCSB PDB website, you will notice images and coordinate files for the "Biological Assembly" and the "Asymmetric Unit". In many PDB entries, these are the same. However, for some entries (mostly those solved by X-ray crystallography), you may notice a difference between the asymmetric unit and the biological assembly. If you have wondered whether the coordinates for the given structure represent the biologically-relevant assembly, read on to find out more about the meaning of these terms and how the corresponding data are archived in the files.

The primary coordinate file of a crystal structure typically contains just one crystal asymmetric unit and may or may not be the same as the biological assembly. This introduction describes the terms asymmetric unit and biological assembly, lists where information about these can be found in various files formats (PDB and mmCIF), and explains how biological assembly files in the PDB archive are derived. Since the PDBML format is derived from the mmCIF format file, a separate discussion of this format is not included here.

Table of Contents

Asymmetric Unit

The asymmetric unit is the smallest portion of a crystal structure to which symmetry operations can be applied in order to generate the complete unit cell (the crystal repeating unit). Symmetry operations most common to crystals of biological macromolecules are rotations, translations and screw axes (combinations of rotation and translation).

Application of crystallographic symmetry operations to an asymmetric unit yields one unit cell that when translated in three dimensions makes up the entire crystal.

Below is a simple example. The asymmetric unit (green upward arrow) is rotated 180 degrees about a two-fold crystallographic symmetry axis (black oval) to produce a second copy (purple downward arrow). Together the two arrows comprise the unit cell. The unit cell is then translationally repeated in three directions to make a 3-dimensional crystal.

The asymmetric unit contains the unique part of a crystal structure. It is used by the crystallographer to refine the coordinates of the structure against the experimental data and may not necessarily represent a whole biologically functional assembly.

A crystal asymmetric unit may contain:

  • one biological assembly
  • a portion of a biological assembly
  • multiple biological assemblies

The content of the asymmetric unit depends on the crystallized molecule's position(s) and its conformations within the unit cell. Depending on the crystallization conditions and local packing two distinct scenarios may occur:

  • Copies of the macromolecule or complex within a crystal unit cell have identical conformations and occupy symmetry-related positions. As a result, the biological assembly may either be composed of one copy of the macromolecule/complex or it may be composed of two or more symmetry related molecules/complexes coming together to form a larger assembly.
  • Copies of the macromolecule or complex take on slightly different conformations and occupy unique positions in the crystal asymmetric unit. As a result, each of the different positions of the macromolecule/complex may correspond to structurally similar but not identical biological assemblies.

Hemoglobin, a molecule with four protein chains (two alpha-beta dimers), provides good examples from PDB entries for each of these cases:

Asymmetric unit with one biological assembly Asymmetric unit with a portion of a biological assembly Asymmetric unit with multiple biological assemblies
Entry 2hhb contains one hemoglobin molecule (4 chains) in the asymmetric unit. Entry 1out contains half a hemoglobin molecule (2 chains) in the asymmetric unit. A crystallographic two-fold axis generates the other 2 chains of the hemoglobin molecule. Entry 1hv4 contains two hemoglobin molecules (8 chains) in the asymmetric unit.

Biological Assembly

The biological assembly (also sometimes referred to as the biological unit) is the macromolecular assembly that has either been shown to be or is believed to be the functional form of the molecule. For example, the functional form of hemoglobin has four chains.

Depending on the particular crystal structure, symmetry operations consisting of rotations, translations or their combinations may need to be performed in order to obtain the complete biological assembly. Alternately, a subset of the deposited coordinates may need to be selected to represent the biological assembly. Thus, a biological assembly may be built from:

  • one copy of the asymmetric unit
  • multiple copies of the asymmetric unit
  • a portion of the asymmetric unit

Hemoglobin is used again to demonstrate each of these cases:

Biological assembly composed of one copy of the asymmetric unit Biological assembly composed of multiple copies of the asymmetric unit Multiple biological assemblies in the asymmetric unit
In entry 2hhb, the biological assembly is equivalent to the asymmetric unit. In entry 1out the biological assembly includes two asymmetric units. In entry 1hv4 the biological assembly is one-half of the asymmetric unit.
No operations are necessary. Application of a crystallographic symmetry operation (a 180 rotation around a crystallographic two-fold axis) produces the complete biological assembly. The entry contains two structurally similar, but not entirely identical copies of the biological assembly within the crystal asymmetric unit.

A biological assembly is not always a multi-chain grouping.

For example, the functional unit of dihydrofolate reductase (shown here from entry 7dfr) is a monomer and the biological assembly also contains only one chain.

A molecule may occasionally appear to be multimeric within a crystal based on crystal packing. However, there may be no evidence or biological relevance in support of a multimeric state in solution. When the entry is processed, all probable assemblies are computed based on the buried surface area and interaction energies. These predicted assemblies may or may not coincide with what the author considers to be the biologically relevant assembly for the molecule. The biological assemblies reported in the entry include a remark to explain whether it is "author provided", "software determined" or both.

For example, the T4 lysozyme structure presented in entry 3fad has a single chain in the asymmetric unit. Normally, lysozyme functions as a monomer. The "author provided" and also the "software determined" biological assembly for this entry is a monomer. Based on crystal packing, buried surface area and interaction energies, the software (PISA 1 ) predicts that this specific mutant/crystal form of T4 lysozyme may form a dimer. The assemblies defined for PDB entry 3fad are shown below:

Asymmetric unit (monomer) Author & Software Determined Biological Assembly (monomer) Software Determined Biological Assembly (dimer)
The asymmetric unit is a monomer. These are the deposited coordinates. The "author provided" and "software determined" biological assemblies are both monomers. The software, PISA, predicts that this molecule may also form a dimer. Hence the second biological assembly is only "software determined".

In the web file download options, various versions of the biological assembly files are marked as (A) for author provided and (S) for software determined.

Viral capsid crystal structures often contain only part of the crystal asymmetric unit. These entries require non-crystallographic symmetry operators to be applied to the deposited coordinates in order to generate the crystal asymmetric unit.

Icosahedral virus capsids have a complex symmetry with 60 equivalent positions generated by 5-fold, 3-fold, and 2-fold rotation operations that intersect at a single central point. The deposited coordinates for an icosahedral virus crystal structure most often consist of the unique chain(s) for the icosahedral asymmetric unit and a set of non-crystallographic symmetry operators to generate the crystal asymmetric unit. Additional crystallographic symmetry operators may be needed to generate the biological assembly and/or the crystallographic unit cell. The various assemblies for an icosahedral virus crystal structure are illustrated for the case of PDB entry 1qqp below:

Icosahedral asymmetric unit Crystal asymmetric unit Biological Assembly Crystallographic unit cell
The deposited coordinates represent 1 icosahedral asymmetric unit. This unit is represented by ribbons in all views. The crystal asymmetric unit is pentameric. The biological assembly is an icosahedron (as show above). The complete crystal unit cell contains 2 icosahedral virus particles.

In addition to crystal structures of virus capsids, the PDB archive holds virus structures determined by electron microscopy, fiber diffraction and solid state NMR. In all cases of assemblies with regular point or helical symmetry, the PDB entry includes the coordinates of the repeating unit and the appropriate crystallographic and/or non-crystallographic symmetry operators required to generate the biological assembly.

For example, in the fiber diffraction structure of filamentous bacteriophage PF1, in entry 1ql2, the asymmetric unit contains 3 helices while the biological assembly is a helical virus, generated by applying matrices that represent the helical rotation and translation.

Biological Assembly Description in mmCIF and PDB Format Files

Instructions for Generating Biological Assemblies in mmCIF Format Files

In mmCIF format files, details about the structural elements that form each biological assembly are found in the pdbx_struct_assembly, pdbx_struct_assembly_gen and pdbx_struct_oper_list categories. The first two categories describe the generation of each biological assembly for the structure and present details about it, while the third one lists the transformations required for generating the biological assembly. The category pdbx_struct_assembly_gen links the transformations in pdbx_struct_oper_list with the chains to which they apply (note that the chain identifiers are the asym_ids used throughout the mmCIF file). Any specific biological assembly related remarks from the authors are stored in the struct_biol category.

A Simple Example - Entry 3c70

In the pdbx_struct_oper_list category, the 1_555 notation is crystallographic shorthand to describe a particular symmetry operator (the number before the underscore) and any required translation (the three numbers following the underscore). Symmetry operators are defined by the space group and the translations are given for the three-unit cell axis (a, b, and c) where 5 indicates no translation and numbers higher or lower signify the number of unit cell translations in the positive or negative direction. For example, 4_565 indicates the use of symmetry operator 4 followed by a one-unit cell translation in the positive b direction.

Example of a Viral Capsid -- Entry 2bfu

In the case of viruses and other complex assemblies with non-crystallographic symmetry, the biological assembly is more complex and may also be composed of many sub-assemblies. The data items in pdbx_struct_assembly list all the possible sub-assemblies, while those in _pdbx_struct_assembly_gen list the process of generating these assemblies. The struct_oper_list category gives a list of matrices (both crystallographic and non-crystallographic operators) required to create the various biological assemblies from the given coordinate file. This list also includes the matrices: "P" to transform the deposited coordinates to a standard point frame, and "X0" which is the transformation required to move the deposited coordinates into the crystal frame 2 . Thus, the deposited coordinates may be transferred to either the standard or crystal frames using these matrices.

The data category _pdbx_struct_oper_list is used for all viruses and holds the matrices for BIOMT records that appear in REMARK 350 of the PDB format file. In cases where the assembly definition listed in struct_oper_list requires sequential multiplication of matrices (example entry 1m4x), the pdbx_struct_oper provides the final list of matrices which are applied to the deposited coordinates. In all data blocks shown below, the matrices 5-58 were edited out for brevity. In addition to these categories, non-crystallographic symmetry (NCS) symmetry operators are listed in the _struct_ncs_oper category.

Please see the mmCIF dictionary for additional details and further information on the mmCIF format.

Instructions for Generating Biological Assemblies in PDB Format Files

In PDB format files, information about the biological assembly is given in REMARKs 300 and 350. REMARK 300 provides a free text remark regarding the biological assembly and may include specific comments provided by the author. REMARK 350, on the other hand presents all transformations (rotational and translational), both crystallographic and non-crystallographic, that are needed to generate the biological assembly. In addition to transformation information provided by the author, descriptions of potential assemblies that can be computationally determined are also provided when available. Author-provided and software-determined biological assemblies are marked appropriately.

A Simple Example - Entry 3c70

In the entry 3c70, REMARK 300 is a free text remark followed by REMARK 350 which includes the transformations required to generate the biological dimer from the deposited coordinates.

In this example, the asymmetric unit is composed of a single chain (chain A). The biological dimer is generated from two copies of the asymmetric unit. The first copy is identical to the deposited asymmetric unit (note the identity operation in green). The second copy is generated by applying a crystallographic symmetry operation consisting of a rotation matrix (red) and a translation vector (blue). Note that this biological assembly is both author provided and software (PISA) predicted.

An Example from a Viral Capsid -- Entry 2bfu

In this example the deposited coordinates include two chains (L and S) that comprise the icosahedral asymmetric unit (1/60th of the complete virus capsid). REMARK 300 is a free text remark while REMARK 350 provides the transformations required for generating the icosahedral virus. Note: matrices 5 through 58 in REMARK 350 have been omitted here for brevity.

The crystallographic asymmetric unit of entry 2bfu is composed of 10 chains (chains L, S and four other copies of each chain generated by the following matrices):

The first matrix is a unit matrix and corresponds to the deposited coordinates. Since these are already given in the PDB format file, they are flagged with "1" on the right hand side of the matrix. The other four matrices generate a five-fold symmetric sub-assembly of the virus.

Note: Not all PDB or mmCIF coordinate files contain information regarding generation of the assumed biological assembly.

Displaying and Downloading Biological Assembly Coordinate Files

wwPDB-created coordinate files for the biological assemblies (or biological units) are archived in the directory data/biounit/coordinates.

These files can also be accessed from the RCSB PDB website. For any given entry, the default view on the Structure Summary page shows the biological assembly. The forward and backward arrows at the top of the visualization box allow toggling between the asymmetric unit and biological assembly images. In the case that there are multiple biological assemblies for the entry, the forward arrow can be used to browse through all of them. The biological assembly files can be downloaded from the "Download Files" menu options on the top right corner. For an example see entry 2bfu.

Specific databases, such as PISA 1 may also be used to study the biological assemblies of PDB entries.


Shuchismita Dutta, Rachel Kramer Green, and Catherine L. Lawson


1 E. Krissinel and K. Henrick (2007) Inference of macromolecular assemblies from crystalline state. J. Mol. Biol. 372: 774-797.

2 C.L. Lawson, S. Dutta, J.D. Westbrook, K. Henrick, H.M. Berman (2008) Representation of viruses in the remediated PDB archive. Acta Cryst. D64: 874-882

About PDB-101

PDB-101 helps teachers, students, and the general public explore the 3D world of proteins and nucleic acids. Learning about their diverse shapes and functions helps to understand all aspects of biomedicine and agriculture, from protein synthesis to health and disease to biological energy.

Why PDB-101? Researchers around the globe make these 3D structures freely available at the Protein Data Bank (PDB) archive. PDB-101 builds introductory materials to help beginners get started in the subject ("101", as in an entry level course) as well as resources for extended learning.

VarSite: Disease variants and protein structure

VarSite is a web server mapping known disease-associated variants from UniProt and ClinVar, together with natural variants from gnomAD, onto protein 3D structures in the Protein Data Bank. The analyses are primarily image-based and provide both an overview for each human protein, as well as a report for any specific variant of interest. The information can be useful in assessing whether a given variant might be pathogenic or benign. The structural annotations for each position in the protein include protein secondary structure, interactions with ligand, metal, DNA/RNA, or other protein, and various measures of a given variant's possible impact on the protein's function. The 3D locations of the disease-associated variants can be viewed interactively via the 3dmol.js JavaScript viewer, as well as in RasMol and PyMOL. Users can search for specific variants, or sets of variants, by providing the DNA coordinates of the base change(s) of interest. Additionally, various agglomerative analyses are given, such as the mapping of disease and natural variants onto specific Pfam or CATH domains. The server is freely accessible to all at:

Keywords: 3D protein structure CATH ClinVar PDB Pfam UniProt VarMap VarSite disease variants gnomAD molecular interactions natural variants schematic diagrams.

© 2019 The Authors. Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

Designer proteins helping biomedicine

Reblogging this blog post

Professor Meiering and her colleagues were able to incorporate both structure and function into the design process by using bioinformatics to leverage information from nature. They then analyzed what they made and measured how long it took for the folded, functional protein to unfold and breakdown.

Using a combination of biophysical and computational analyses, the team discovered this kinetic stability can be successfully modeled based on the extent to which the protein chain loops back on itself in the folded structure. Because their approach to stability is also quantitative, the protein’s stability can be adjusted to naturally break down when it is no longer needed.

Broom A, Ma SM, Xia K, Rafalia H, Trainor K, Colón W, Gosavi S, & Meiering EM (2015). Designed protein reveals structural determinants of extreme kinetic stability. Proceedings of the National Academy of Sciences of the United States of America, 112 (47), 14605-10 PMID: 26554002

WS-SNPs&GO: a web server for predicting the deleterious effect of human protein variants using functional annotation

Background: SNPs&GO is a method for the prediction of deleterious Single Amino acid Polymorphisms (SAPs) using protein functional annotation. In this work, we present the web server implementation of SNPs&GO (WS-SNPs&GO). The server is based on Support Vector Machines (SVM) and for a given protein, its input comprises: the sequence and/or its three-dimensional structure (when available), a set of target variations and its functional Gene Ontology (GO) terms. The output of the server provides, for each protein variation, the probabilities to be associated to human diseases.

Results: The server consists of two main components, including updated versions of the sequence-based SNPs&GO (recently scored as one of the best algorithms for predicting deleterious SAPs) and of the structure-based SNPs&GO(3d) programs. Sequence and structure based algorithms are extensively tested on a large set of annotated variations extracted from the SwissVar database. Selecting a balanced dataset with more than 38,000 SAPs, the sequence-based approach achieves 81% overall accuracy, 0.61 correlation coefficient and an Area Under the Curve (AUC) of the Receiver Operating Characteristic (ROC) curve of 0.88. For the subset of

6,600 variations mapped on protein structures available at the Protein Data Bank (PDB), the structure-based method scores with 84% overall accuracy, 0.68 correlation coefficient, and 0.91 AUC. When tested on a new blind set of variations, the results of the server are 79% and 83% overall accuracy for the sequence-based and structure-based inputs, respectively.


Protein structure data in Protein Data Bank (PDB) [1] are widely used in studies of protein function and evolution, and they serve as a basis for protein structure prediction. The number of entries in PDB has been increasing rapidly. However, there are two barriers in large-scale usage of PDB data, especially in an automatic fashion. The first barrier is that a large number of protein chains in PDB are highly similar in terms of sequence or structure. For example, many PDB files contain identical chains. Hence, a light version of PDB may be useful. In addition, PDB users often need to obtain a set of PDB chains satisfying some criteria such as structure resolution and sequence length, or they may need to select a representative from a group of similar sequences/structures. The second barrier in large-scale usage of PDB data is that many PDB files have issues due to inconsistency of data and standards as well as missing residues, so that automated retrieval and analysis are often difficult. For example, the sequence in a PDB header is sometimes inconsistent with that in the 3D coordinate part. Another example is that some residues in PDB are modified, and the residue types cannot be easily mapped to the original amino acids. One more issue is that many PDB files have incomplete coordinates containing some residues or atoms without 3D coordinates. This may be due to un-resolved electron density maps. However, it creates problems for a systematic data analysis of large-scale PDB files. Furthermore, if someone likes to perform molecular dynamics simulation or other computational analysis of a given PDB file, it may require preprocessing the file to add coordinates of missing atoms. If the pre-processed PDB files are readily available for download, it may help many simulation users.

Currently, several websites are available to address the first barrier. The PDB website itself can remove similar sequences with specific levels of mutual sequence identity. Other websites such as PDB-Select [2], ASTRAL [3], PDB-REPRDB [4] and PISCES [5] have similar functions, all of which allow users to download a pre-defined chain list or generate a customized list with some sequence or structure criteria. However, the derived chain lists from these websites are typically not updated weekly following the release of hundreds of PDB files each week. Release of non-redundant structure datasets is even slower. For example, the widely used protein structure classification database SCOP [6], which involves extensive manual annotations, was updated years ago (1.75 release in June 2009). It would be useful to incorporate automatic SCOP classification for newly released PDB files, even if the classification quality is suboptimal. In addition, the second barrier in large-scale usage of PDB data, as illustrated above, has not been addressed systematically.

In this paper, we introduce MUFOLD-DB which comprehensively integrates processed PDB data, predicted SCOP classification and additional computational data, e.g. DSSP [7] secondary structure and PSI-BLAST [8] sequence profile. MUFOLD-DB provides a friendly web interface for users to browse, search and download these data. Compared to other databases, MUFOLD-DB has the following unique features:

(1) Users can search a PDB sequence against several derived sequence databases by using BLAST with specified parameters and browse all the hit sequences.

(2) Users can generate a customized list from the entire PDB sequences by setting the filtering parameters, which include full or partial SCOP address, experimental method (e.g., X-Ray or NMR), sequence length, structure resolution (only applied to X-Ray structures), deposit date, and mutual sequence identity level from 90, 80 to 30 percent. This can be used for a non-redundant template database in developing protein energy function and template-based protein structure prediction.

(3) Users can input a list of chain names to browse the corresponding information and quickly get the representatives of the involved clusters after clustering with seven levels of mutual sequence identity, from 90 to 30 percent. This utility can be used to cluster a set of sequences to reduce redundancy.

(4) MUFOLD-DB carefully processes the PDB sequence and structure to provide users clean data which is much easier to manipulate than the original PDB files. Structures of missing regions with less than 7 residues in PDB chains are predicted by high-quality loop modelling using MODELLER [9], to help structure prediction and function analysis.

(5) Multiple data are provided for users to download including sequence, predicted SCOP classification, cleaned PDB format file, and PDB files with loop modelling. Pre-computed sequence and SCOP representative datasets are also provided. These files can be retrieved through a command line without going through a web browser.

(6) Users can view each chain in details. Besides the basic information from PDB files, evolutional information represented as sequence logo, secondary structure, disorder region, and three-dimensional structure visualization with JMol are provided.

(7) The database is automatically updated every week following the weekly release of PDB.

Protein structures given in PDB and SNP's - Biology

Experimental Data Snapshot

  • Resolution: 2.59 Å
  • R-Value Free: 0.298 
  • R-Value Work: 0.244 
  • R-Value Observed: 0.246 

wwPDB Validation   3D Report Full Report

Crystal structure of SARS-CoV-2 papain-like protease.

(2021) Acta Pharm Sin B 11: 237-245

  • PubMed: 32895623  Search on PubMedSearch on PubMed Central
  • DOI: 10.1016/j.apsb.2020.08.014
  • Primary Citation of Related Structures:  
    7CJD, 7CMD
  • PubMed Abstract: 

The pandemic of coronavirus disease 2019 (COVID-19) is changing the world like never before. This crisis is unlikely contained in the absence of effective therapeutics or vaccine. The papain-like protease (PLpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) plays essential roles in virus replication and immune evasion, presenting a charming drug target .

The pandemic of coronavirus disease 2019 (COVID-19) is changing the world like never before. This crisis is unlikely contained in the absence of effective therapeutics or vaccine. The papain-like protease (PLpro) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) plays essential roles in virus replication and immune evasion, presenting a charming drug target. Given the PLpro proteases of SARS-CoV-2 and SARS-CoV share significant homology, inhibitor developed for SARS-CoV PLpro is a promising starting point of therapeutic development. In this study, we sought to provide structural frameworks for PLpro inhibitor design. We determined the unliganded structure of SARS-CoV-2 PLpro mutant C111S, which shares many structural features of SARS-CoV PLpro. This crystal form has unique packing, high solvent content and reasonable resolution 2.5 Å, hence provides a good possibility for fragment-based screening using crystallographic approach. We characterized the protease activity of PLpro in cleaving synthetic peptide harboring nsp2/nsp3 juncture. We demonstrate that a potent SARS-CoV PLpro inhibitor GRL0617 is highly effective in inhibiting protease activity of SARS-CoV-2 with the IC 50 of 2.2±0.3 μmol/L. We then determined the structure of SARS-CoV-2 PLpro complex by GRL0617 to 2.6 Å, showing the inhibitor accommodates the S3-S4 pockets of the substrate binding cleft. The binding of GRL0617 induces closure of the BL2 loop and narrows the substrate binding cleft, whereas the binding of a tetrapeptide substrate enlarges the cleft. Hence, our results suggest a mechanism of GRL0617 inhibition, that GRL0617 not only occupies the substrate pockets, but also seals the entrance to the substrate binding cleft hence prevents the binding of the LXGG motif of the substrate.

Organizational Affiliation

NHC Key Laboratory of Systems Biology of Pathogens, Institute of Pathogen Biology, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China.

Protein structures given in PDB and SNP's - Biology

Database that groups biomedical literature, small molecules, and sequence data in terms of biological relationships.

A centralized page providing access and links to resources developed by the Structure Group of the NCBI Computational Biology Branch (CBB). These resources cover databases and tools to help in the study of macromolecular structures, conserved domains and protein classification, small molecules and their biological activity, and biological pathways and systems.

A collection of sequence alignments and profiles representing protein domains conserved in molecular evolution. It also includes alignments of the domains to known 3-dimensional protein structures in the MMDB database.

Contains macromolecular 3D structures derived from the Protein Data Bank, as well as tools for their visualization and comparative analysis.


This site provides full data records for CDD, along with individual Position Specific Scoring Matrices (PSSMs), mFASTA sequences and annotation data for each conserved domain. See the README file for full details.

This site contains ASN.1 data for all records in MMDB along with VAST alignment data and the non-redundant PDB (nr-PDB) data sets. See the README file for more information.


A stand-alone application for classifying protein sequences and investigating their evolutionary relationships. CDTree can import, analyze and update existing Conserved Domain (CDD) records and hierarchies, and also allows users to create their own. CDTree is tightly integrated with Entrez CDD and Cn3D, and allows users to create and update protein domain alignments.

A stand-alone application for viewing 3-dimensional structures from NCBI's Entrez retrieval service. Cn3D runs on Windows, Macintosh, and UNIX and can be configured to receive data from most popular web browsers. Cn3D simultaneously displays structure, sequence, and alignment, and has powerful annotation and alignment editing features.

Displays the functional domains that make up a given protein sequence. It lists proteins with similar domain architectures and can retrieve proteins that contain particular combinations of domains.

Identifies the conserved domains present in a protein sequence. CD-Search uses RPS-BLAST (Reverse Position-Specific BLAST) to compare a query sequence against position-specific score matrices that have been prepared from conserved domain alignments present in the Conserved Domain Database (CDD).

The Related Structures tool allows users to find 3D structures from the Molecular Modeling Database (MMDB) that are similar in sequence to a query protein. Although the query protein may not yet have a resolved structure, the 3D shape of a similar protein sequence can shed light on the putative shape and biological function of the query protein.

A computer algorithm that identifies similar protein 3-dimensional structures. Structure neighbors for every structure in MMDB are pre-computed and accessible via links on the MMDB Structure Summary pages. These neighbors can be used to identify distant homologs that cannot be recognized by sequence comparison alone.

Watch the video: Πόση πρωτεΐνη μπορούμε να απορροφήσουμε ανά γεύμα; (May 2022).


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