PDB-Explorer: a web-based interactive map of the protein data bank in shape space
© Jin et al. 2015
Received: 29 July 2015
Accepted: 14 October 2015
Published: 23 October 2015
The RCSB Protein Data Bank (PDB) provides public access to experimentally determined 3D-structures of biological macromolecules (proteins, peptides and nucleic acids). While various tools are available to explore the PDB, options to access the global structural diversity of the entire PDB and to perceive relationships between PDB structures remain very limited.
A 136-dimensional atom pair 3D-fingerprint for proteins (3DP) counting categorized atom pairs at increasing through-space distances was designed to represent the molecular shape of PDB-entries. Nearest neighbor searches examples were reported exemplifying the ability of 3DP-similarity to identify closely related biomolecules from small peptides to enzyme and large multiprotein complexes such as virus particles. The principle component analysis was used to obtain the visualization of PDB in 3DP-space.
A chemical space classification of PDB based on molecular shape was obtained using a new atom-pair 3D-fingerprint for proteins and implemented in a web-based database exploration tool comprising an interactive color-coded map of the PDB chemical space and a nearest neighbor search tool. The PDB-Explorer website is freely available at www.cheminfo.org/pdbexplorer and represents an unprecedented opportunity to interactively visualize and explore the structural diversity of the PDB.
KeywordsProtein data bank 3D-fingerprint Visualization Chemical space Molecular shape
One of the striking features of biomolecules is their extremely large diversity spanning from small organic molecules such as metabolites and drugs to large supramolecular complexes such as the ribosome or viral particles. A vast amount of knowledge about these biomolecules has been collected in various public databases, in particular the Protein Data Bank (PDB) which collects over 100,000 different 3-dimensional (3D) structures of biological macromolecules determined by X-ray crystallography, NMR spectroscopy and electron microscopy [1–4]. Despite of this vast amount of information, the overall structural diversity available in the PDB is difficult to perceive. Indeed various tools are available to search the PDB for analogs of specific proteins according to similarities in evolutionary history, sequences, secondary structures and subdomains [5–12]. In the case of 3D-SURFER [13, 14] the PDB is classified according to similarities in protein surface allowing to search for shape analogs among PDB-entries. The CATH [7, 8] contains a subset of the PDB which is directly visible via an overview interface using a hierarchical classification by structural domains. However none of these interfaces provides a direct, global yet comprehensive overview of the PDB irrespective of a specific query, which would be desirable to understand its overall contents.
Herein we report a new exploration tool for the PDB called PDB-Explorer which addresses the need for a global perception of the database by giving direct access to all PDB-entries via an interactive color-coded map representing its entire contents in molecular shape space. This application follows the principle of our recently reported MQN-mapplet and SMIfp-mapplet applications designed to visualize the chemical space of small organic molecules [15–18]. Each individual PDB-entry is placed on the map of the PDB-Explorer according to its 3D-shape as encoded by a new fingerprint called 3DP featuring a generalized version of our recently reported 3D-atom pair fingerprints for small molecules [19, 20]. The PDB-Explorer provides an unprecedented global view of the PDB allowing a detailed exploration of its entire content in a curiosity-driven manner with or without specific queries. This tool is freely available at www.cheminfo.org/pdbexplorer and should greatly facilitate the perception and understanding of the overall diversity of proteins and biological assemblies available in the PDB.
The X-ray structures in PDB-Explorer were downloaded from http://www.rcsb.org. The water molecules and hydrogen atoms of each PDB molecule were removed at the beginning. If the number of atoms assigned as “HETATM” occupied more than 20 % of total heavy atom count, this molecule was not included in the database.
3D protein atom-pair fingerprint (3DP)
Principal component analysis (PCA)
The PCA calculation used the source code from Java program developed based on the tutorial of Lindsay I. Smith (http://www.cs.otago.ac.nz/cosc453/student_tutorials/principal_components.pdf). The Java source code uses mathematical functions from the JSci (A science API for Java: http://jsci.sourceforge.net/) library.
PDB-maps generation and color-coding
PCA of the 3DP-similarity fingerprint space of PDB database was carried out, and the PC-1 and PC-2 values were computed for each molecule in database. The PC-1 and PC-2 values were binned onto the 2D-grid of size 300 × 300 using the same absolute bin size on the PC-1 and PC-2. The largest (PCmax) and smallest (PCmin) PC values appearing in the PC-1 or PC-2 values were used to define the value range ΔPC = PCmax − PCmin and set the binning scale as ΔPC/300. Afterwards, each molecule was assigned to a point (or bin) on this 2D-grid.
Each of the grid point was color coded according to the average and standard deviation of the molecular property at that grid point using the Hue-Saturation-Lightness (HSL) color space, with the Hue value (blue-cyan-green-yellow-red-magenta) representing the average value and the Saturation (fading to grey) representing the standard deviation.
The calculation of normalized principal moment of inertia (nPMI1, nPMI2) was implemented by an in-house Java program written based on the work from Sauer and Schwarz . The position in the (nPMI1, nPMI2) triangle was color coded using the RGB color space assigning the distance to each triangle summit as the relative R, G, and B values.
Results and discussion
Design of the protein shape fingerprint 3DP
In view of a global analysis of the PDB we set out to identify a fingerprint encoding the 3D-structure of biomacromolecules since it is known to play an important role in their biological function, their interaction with other molecules, [22–25] and their evolution [26–29]. While 3D-SURFER uses a 121-dimensional scalar fingerprint to encode the shape of the molecular surface of proteins using 3D Zernike descriptors, [13, 14] we searched for a simpler yet more detailed encoding considering not only the shape of the molecular surface, but also the atom types and the internal structure of the protein. Inspired by the concept of atom-pair fingerprints proposed by Carhart,  Sheridan  and Schneider  to encode pharmacophores in small organic molecules, we recently reported a detailed analysis establishing the suitability of atom-pair fingerprints for 3D-shape and pharmacophore similarity searches in very large databases such as ChEMBL  and ZINC  using both topological distances read from the 2D-structures  and through-space distance read from the 3D-structures . While topological distances cannot be extracted easily from the structures of macromolecules or even do not exist within non-covalent assemblies, an atom-pair analysis of macromolecules should be possible using through-space distances which can be directly computed from the atomic coordinates available in each pdb file. An atom pair 3D-fingerprint, here called 3DP, was therefore envisioned to encode 3D-structures in the PDB.
Because most PDB-entries contain thousands of atoms which would require explicit calculation of many millions of atom pair distances (Fig. 1d), the 3DP calculation was simplified by computing the fingerprint using formal “sum atoms”. A maximum of 1728 sum atoms (resulting in a maximum of 1.5 million sum atom pairs) were defined for each PDB-entry by fitting its biological unit into a 12×12×12 grid, using the average coordinates of each atom category within each box as the sum atom coordinates and the number of category atoms within this box as its relative weight. 3DP bit values computed with sum atoms were essentially indistinguishable from those computed with actual atoms.
The 3DP calculation was performed 91,223 X-ray structures downloaded from the PDB in September 2014 (Additional file 1: Supplement 1), considering in each case the biological assembly as defined by the authors . The 3DP fingerprint had a high resolution, with 99.99 % of PDB molecules having unique 3DP fingerprints. The average bit values peaked at 33.76 Å (B20, B122) for all atoms and hydrophobic atom pairs and at 39.83 Å (B55, B89) for positive and negative charge atom pairs, while the corresponding standard deviation covered almost the entire bit value range (Fig. 1c).
3DP encodes protein conformations
3DP analysis of the RSCB protein databank
To facilitate access to PDB-entries a graphical user interface was created based on an interactive color-coded map representing the 3DP chemical space using the Mapplet principle previously reported for small molecule databases, by which database entries are displayed in a visualization window as the mouse cursor moves on the map, and connects to a fingerprint similarity search window to allow nearest neighbor searches [15–18]. Although 78 % of the data variability was represented in (PC1, PC2)-plane obtained by principal component analysis (PCA) of the 3DP dataset, this direct PCA map contained many scattered pixels with uneven occupancies and was not suitable as an interface (data not shown). We therefore generated an alternative representation of 3DP by similarity mapping, which produces more compact and evenly populated maps with a fairly good rendering for various chemical spaces [18, 48, 49].
Exploring PDB using the PDB-Explorer
The PDB-Explorer allows the rapid analysis and overview of the entire PDB as well as detailed searches around selected PDB-entries using 3DP similarity as a guiding principle. Its use is exemplified with three case studies detailed below which further demonstrate the remarkable ability of 3DP to classify proteins according to their 3D structure.
Comparing 3DP with protein structure alignment tools
The performance of 3DP was compared with three protein structure alignment tools, Fr-TMalign [60, 61], SPalign  and MATT . Fr-TMalign is applied to pairwise structure alignment based on fragment similarity, while SPalign is designed for detecting proteins with similar fold and similar function of DNA or RNA binding. MATT (Multiple Alignment with Translations and Twists) is a program to align multiple protein structures allowing certain flexibility between fragments. These alignment methods are computationally intensive and therefore only applicable to a limited number of comparisons. They are size independent and focus on backbone alignment resulting in a focus on secondary structures. On the other hand 3DP is size dependent and considers all protein atoms indiscriminately, resulting in a sensitivity to the overall shape rather than to secondary structures. Remarkably, 3DP allows an essentially instantaneous comparison with the entire PDB when using the PDB-Explorer website.
In a first comparative study, all pairwise alignment scores were computed for the ten domain movement frames for glutamine binding protein and compared with CBD3DP. The data showed that CBD3DP, which performs comparably to overall structure RMSD as dicussed above (Fig. 3), had similar trend but higher sensitivity to conformer differences than Fr-TMalign or SPalign. MATT was highly sensitive to small conformational changes and classified all non-identical conformer pairs as low scoring (Fig. 10c).
A further comparison of 3DP with structure alignment tools was carried out for 50 homologous CDK2 proteins (Fig. 4) and 50 non-CDK2 decoy proteins. The 100 structures were in similar size range from 2100–2600 heavy atoms, and decoys consisted of non-homologous proteins with pairwise sequence identity lower than 30 %. Alignment scores and 3DP distances were computed for the 1225 CDK2 pairs and the 2500 CDK2-decoy pairs (Fig. 10d). 3DP made a relatively clear cut between CDK2 pairs and CDK2-decoy cross-pairs at CBD3DP = 750, with all CDK2 pairs found within the range CBD3DP < 1000. However the 3DP comparison recognized some decoys such as 1A8E (serum transferrin) as CDK2-like due to an overall similar shape, although this decoy had a clearly different fold as correctly analyzed by each of the three alignment tools (Fig. 10e, left). The three alignment methods correctly assigned a high score to all CDK2 pairs, but also returned a high core with part of the CDK2-decoys which were not recognized as CDK2 like by 3DP. For example decoy 4W9X, which is a non-CDK2 kinase, clearly showed a partly homologous fold to CDK2 leading to a high alignment score, but also showed substantial differences with the presence of a central helix and an extended terminal absent from CDK2 which resulted in a relatively high 3DP-distance to CDK2s such as 3PY1 (Fig. 10e, right).
The 3D-structure of biomolecules in the PDB were encoded in the 136-dimensional 3D atom-pair fingerprint 3DP counting the number of atom pairs at increasing distance intervals for all atoms, positively charged, negatively charged, and hydrophobic atoms. The 3DP fingerprint perceives the spatial distribution of shape, hydrophobicity and charges in molecular objects across a very broad size range. 3DP nearest neighbors are shown in various examples to be closely related shape and fold analogs.
Availability of supporting data
The data sets supporting the results of this article are included within the article and its additional file.
This work was supported financially by the University of Berne, the Swiss National Science Foundation, and the NCCR TransCure.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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