secondary structure assignment database

If you use the DSSP software or databank please cite the appropriate paper:

	Joosten RP, te Beek TAH, Krieger E, Hekkelman ML, Hooft RWW, Schneider R, Sander C, Vriend A series of PDB related databases for everyday needs. Nuc. Acids Res. 2010; 39:D411-D419.
	Kabsch W, Sander C. Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 1983; 22:2577-2637.

Using DSSP data

DSSP provides an elaborate description of the secondary structure elements in a protein structure, including backbone hydrogen bonding and the topology of β-sheets. The most popular feature is the per-residue assignment of secondary structure with a single character code:

H = α-helix
B = residue in isolated β-bridge
E = extended strand, participates in β ladder
G = 3 10 -helix
I = π-helix
P = κ-helix (poly-proline II helix)
T = hydrogen-bonded turn

The full DSSP output is provided in two formats. The legacy DSSP format was origianlly designed for structures that were in PDB-formatted models. Now, 40 years later, the PDB format has become obsolete as it cannot capture the large structure models that modern structural biology methods can provide. The mmCIF format is the data format of choice for structural biology as it has no size limitations for structure models and it can hold extensive annotations and metadata. DSSP now writes its data straight to these mmCIF files by default. The legacy DSSP format can still be written but only for structure models that fit.

DSSP format

The output from DSSP contains secondary structure assignments and other information. Extract from 3kew.dssp (header):

The first few lines are taken from the input model file, then some general statistics about the model and hydrogen bonding are given. The histograms describe the distribution of sizes of secondary structure elements. For instance, this structure has three helices, one short one consisting of 4 residues and two longer ones of 16 and 17 residues. Note that beta sheets are described as a collection of ladders, rather than strands. Ladders can be seen as two strands together with the hydrogen bonds as the rungs of the ladder. More formal definitions are given in the Kabsch and Sander paper.

The model statistics are followed by a detailed per-residue description. Extract from 3kew.dssp (continued):

Below is a brief description of the data columns. More details are described in the Kabsch and Sander paper.

Two columns of residue numbers. First column is DSSP's sequential residue number, starting at the first residue actually in the model set and including chain breaks; this number is used to refer to residues throughout. The second column gives the numbering as is used in the structure model 'residue number','insertion code' and 'chain identifier'; these are given for reference only.

One letter amino acid code, non standard residues are marked as X . CYS in an SS-bridge are marked by a lower case letter. So when cysteines are bridged, then the first bridged cysteine in the sequence and its partner elsewhere in the sequence are marked a . The next bridged cysteine, that is not yet marked, and its partner are both marked b , etcetera. Unbridged cysteines remain marked as C .

The first column (under the S ) gives aone-letter summary of secondary structure, intended to approximate crystallographers' intuition. This summary is based on the next 8 columns, which are the principal result of DSSP analysis of the atomic coordinates. More details in the Kabsch and Sander paper.

BP1 and BP2

Residue numbers of the first and (if available) second beta bridge partner. The letter marked the B-sheet that contains the bridges.

Effects leading to larger than expected values: solvent exposure calculation ignores unusual residues, like ACE, or residues with incomplete backbone. it also ignores HETATOMS, like a heme or metal ligands. Also, side chains may not have all atoms explicitly modeled.
Effects leading to smaller than expected values: in complexes, e.g. a dimer, solvent exposure is for the entire assembly, not for the monomer. Also, atom OXT of c-terminal residues is treated like a side chain atom if it is listed as part of the last residue.
Unknown or non-standard residues are named X on output and are not checked for the expected number of sidechain atoms.
All explicit water molecules, like other hetatoms, are ignored.

N-H-->O etc.

Hydrogen bonds; e.g. -3,-1.4 means that this residue (i) has its HN atom H-bonded to O of residue i-3 with an electrostatic H-bond energy of -1.4 kcal/mol. There are two columns for each type of H-bond, to allow for bifurcated H-bonds. Note: The marked H-bonds are the best and second best candidate. The second best and even the best (in rare occasions) may be unrealistically por H-bonds.

The cosine of angle between C=O of residue i and C=O of residue i-1. For α-helices, TCO is near +1, for β-sheets TCO is near -1. These values are descriptive and not used for structure definition.

Virtual bond angle (bend angle) defined by the three Cα atoms of residues i-2, i, and i+2. Used to define bends (structure code S ).

Virtual torsion angle (dihedral angle) defined by the four Cα atoms of residues i-1, i, i+1, and i+2. Used to define chirality (structure code + or - ).

PHI and PSI

The peptide backbone torsion angles as described in the IUPAC standard

X-CA, Y-CA, and Z-CA

Just a copy of the Cα atom coordinates in the structure model

DSSP data in mmCIF files

The mmCIF-formatted DSSP output caries the same information as the DSSP format but in a more scalable way and with a formal description caputered in an mmCIF dictionary. It is designed to be machine readable. Developers who create software to read these annotations can use our extension to the mmCIF dictionary on GitHub. Note: For sake of speed the solvent accessibility is not calculated by default when using mmCIF output. The command-line switch --calculate-accessibility can be used to switch this feature on.

Remote Access

STRIDE -- A web server for secondary structure assignment from known atomic coordinates of proteins

It implements a knowledge-based algorithm that makes combined use of hydrogen bond energy and statistically derived backbone torsional angle information and is optimized to return resulting assignments in maximal agreement with crystallographers' designations.
The web server allows visualization of the secondary structure, as well as contact and Ramachandran maps for any file uploaded by the user with atomic coordinates in the Protein Data Bank (PDB) format.
A searchable database of STRIDE assignments for the latest PDB release is also provided.
protein structures
protein secondary structures
protein secondary structure analysis tool
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Application to assign secondary structure to proteins

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This is a rewrite of DSSP, now offering full mmCIF support. The difference with previous releases of DSSP is that it now writes out an annotated mmCIF file by default, storing the secondary structure information in the _struct_conf category.

Another new feature in this version of DSSP is that it now defines Poly-Proline helices as well.

The DSSP program was designed by Wolfgang Kabsch and Chris Sander to standardize secondary structure assignment. DSSP is a database of secondary structure assignments (and much more) for all protein entries in the Protein Data Bank (PDB). DSSP is also the program that calculates DSSP entries from PDB entries.

DSSP does not predict secondary structure.

Requirements

A good, modern compiler is needed to build the mkdssp program since it uses many new C++20 features.

The new makefile for dssp will take care of downloading and building all requirements automatically. So in theory, building is as simple as:

See manual page for more info. Or even better, see the DSSP website .

Contributors 3

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Protein secondary structure assignment using residual networks

Original Paper
Published: 23 August 2022
Volume 28 , article number 269 , ( 2022 )

Cite this article

Jisna Vellara Antony ORCID: orcid.org/0000-0001-5210-9583 1 ,
Roosafeed Koya ORCID: orcid.org/0000-0002-6018-4580 1 ,
Pulinthanathu Narayanan Pournami ORCID: orcid.org/0000-0002-8846-2044 1 ,
Gopakumar Gopalakrishnan Nair ORCID: orcid.org/0000-0002-4801-9259 1 &
Jayaraj Pottekkattuvalappil Balakrishnan ORCID: orcid.org/0000-0002-9924-9046 1

598 Accesses

3 Citations

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Proteins are constructed from amino acid sequences. Their structural classifications include primary, secondary, tertiary, and quaternary, with tertiary and quaternary structures influencing protein function. Because a protein’s structure is inextricably connected to its biological function, machine learning algorithms that can better anticipate the structures have the potential to lead to new scientific discoveries in human health and improve our capacity to develop new treatments. Protein secondary structure assignment enriches the structural and functional understanding of proteins. It helps in protein structure comparison and classification studies, besides facilitating secondary and tertiary structure prediction systems. Several secondary structure assignment methods have been developed since the 1980s, most of which are based on hydrogen bond analysis and atomic coordinate features. However, the assignment process becomes complex when protein data includes missing atoms. Deep neural networks are often referred to as universal function approximators because they can approximate any function to produce the desired output when properly designed and trained. Optimised deep learning architectures have already proven their ability to increase performance in a wide range of problems. Recently, the ResNet architecture has garnered significant interest due to its applicability in various areas, including image classification and protein contact map prediction. The proposed model, which is based on the ResNet architecture, assigns secondary structures using Cα atom coordinates. The model achieved an accuracy of 94% when evaluated against the benchmark and independent test sets. The findings encourage the development of new deep learning-based methods that are more generalised across various protein learning tasks. Furthermore, it allows computational biologists to delve deeper into integrating these techniques with experimental methods. The model codes are available at: https://github.com/jisnava/ResNet_for_Structure_Assignments/ .

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U-Net: Convolutional Networks for Biomedical Image Segmentation

Deep Learning: A Comprehensive Overview on Techniques, Taxonomy, Applications and Research Directions

Review of deep learning: concepts, CNN architectures, challenges, applications, future directions

Data availability.

The data is available at: https://github.com/jisnava/ResNet_for_Structure_Assignments/ .

Code availability

The model codes are made open at: https://github.com/jisnava/ResNet_for_Structure_Assignments/ .

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Acknowledgements

The authors thank the Centre for Computational Modelling and Simulation (CCMS) and Central Computer Centre (CCC) at the National Institute of Technology Calicut, for providing the NVIDIA DGX station facility to train the deep neural network architectures.

It is part of my (V. A. Jisna) PhD work at the National Institute of Technology Calicut, India. The research is funded by the Ministry of Human Resource Development, India.

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Jisna Vellara Antony, Roosafeed Koya, Pulinthanathu Narayanan Pournami, Gopakumar Gopalakrishnan Nair & Jayaraj Pottekkattuvalappil Balakrishnan

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Jisna Vellara Antony (JVA) did the conceptualisation and dataset construction. JVA and Roosafeed Koya (RK) implemented the models. Jayaraj Pottekkattuvalappil Balakrishnan (JPB), Pulinthanathu Narayanan Pournami (PNP), and Gopakumar Gopalakrishnan Nair (GGN) supervised the project. All authors read and approved the final manuscript.

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Antony, J.V., Koya, R., Pournami, P.N. et al. Protein secondary structure assignment using residual networks. J Mol Model 28 , 269 (2022). https://doi.org/10.1007/s00894-022-05271-z

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Knowledge about protein structure assignment enriches the structural and functional understanding of proteins. Accurate and reliable structure assignment data is crucial for secondary structure prediction systems. Since the ’80s various methods based on hydrogen bond analysis and atomic coordinate geometry, followed by Machine Learning, have been employed in protein structure assignment. However, the assignment process becomes challenging when missing atoms are present in protein files. Our model develops a multi-class classifier program named DLFSA for assigning protein Secondary Structure Elements(SSE) using Convolutional Neural Networks(CNN). A fast and efficient GPU based parallel procedure extracts fragments from protein files. The model implemented in this work is trained with a subset of protein fragments and achieves 88.1% and 82.5% train and test accuracy, respectively. Our model uses only C α coordinates for secondary structure assignments. The model is successfully tested on a few full-length proteins also. Results from the fragment-based studies demonstrate the feasibility of applying deep learning solutions for structure assignment problems.

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The authors have declared no competing interest.

jayarajpb{at}nitc.ac.in , prayagh.m{at}gmail.com

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Secondary structure assignment tool

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DSSP is a database of secondary structure assignments (and much more) for all protein entries in the Protein Data Bank (PDB)

STRIDE Protein secondary structure assignment with stride, Basic assignment, Visual assignment, Contact map, Ramachandran Plot

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1 Inserm U1134, Paris, France, Université Paris Diderot, Sorbonne Paris Cité, UMR_S 1134, Paris, France, Institut National de la Transfusion Sanguine, Paris, France and Laboratory of Excellence GR-Ex, Paris, France Inserm U1134, Paris, France, Université Paris Diderot, Sorbonne Paris Cité, UMR_S 1134, Paris, France, Institut National de la Transfusion Sanguine, Paris, France and Laboratory of Excellence GR-Ex, Paris, France Inserm U1134, Paris, France, Université Paris Diderot, Sorbonne Paris Cité, UMR_S 1134, Paris, France, Institut National de la Transfusion Sanguine, Paris, France and Laboratory of Excellence GR-Ex, Paris, France.
2 Inserm U1134, Paris, France, Université Paris Diderot, Sorbonne Paris Cité, UMR_S 1134, Paris, France, Institut National de la Transfusion Sanguine, Paris, France and Laboratory of Excellence GR-Ex, Paris, France Inserm U1134, Paris, France, Université Paris Diderot, Sorbonne Paris Cité, UMR_S 1134, Paris, France, Institut National de la Transfusion Sanguine, Paris, France and Laboratory of Excellence GR-Ex, Paris, France Inserm U1134, Paris, France, Université Paris Diderot, Sorbonne Paris Cité, UMR_S 1134, Paris, France, Institut National de la Transfusion Sanguine, Paris, France and Laboratory of Excellence GR-Ex, Paris, France Inserm U1134, Paris, France, Université Paris Diderot, Sorbonne Paris Cité, UMR_S 1134, Paris, France, Institut National de la Transfusion Sanguine, Paris, France and Laboratory of Excellence GR-Ex, Paris, France.
3 Inserm U1134, Paris, France, Université Paris Diderot, Sorbonne Paris Cité, UMR_S 1134, Paris, France, Institut National de la Transfusion Sanguine, Paris, France and Laboratory of Excellence GR-Ex, Paris, France Inserm U1134, Paris, France, Université Paris Diderot, Sorbonne Paris Cité, UMR_S 1134, Paris, France, Institut National de la Transfusion Sanguine, Paris, France and Laboratory of Excellence GR-Ex, Paris, France Inserm U1134, Paris, France, Université Paris Diderot, Sorbonne Paris Cité, UMR_S 1134, Paris, France, Institut National de la Transfusion Sanguine, Paris, France and Laboratory of Excellence GR-Ex, Paris, France Inserm U1134, Paris, France, Université Paris Diderot, Sorbonne Paris Cité, UMR_S 1134, Paris, France, Institut National de la Transfusion Sanguine, Paris, France and Laboratory of Excellence GR-Ex, Paris, France [email protected].
PMID: 25380779
PMCID: PMC4224144
DOI: 10.1093/database/bau102

The polyproline helix type II (PPII) is a regular protein secondary structure with remarkable features. Many studies have highlighted different crucial biological roles supported by this local conformation, e.g. in the interactions between biological macromolecules. Although PPII is less frequently present than regular secondary structures such as canonical alpha helices and beta strands, it corresponds to 3-10% of residues. Up to now, PPII is not assigned by most popular assignment tools, and therefore, remains insufficiently studied. PolyprOnline database is, therefore, dedicated to PPII structure assignment and analysis to facilitate the study of PPII structure and functional roles. This database is freely accessible from www.dsimb.inserm.fr/dsimb_tools/polyproline.

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v.2014; 2014

PolyprOnline: polyproline helix II and secondary structure assignment database

Romain chebrek.

1 Inserm U1134, Paris, France, 2 Université Paris Diderot, Sorbonne Paris Cité, UMR_S 1134, Paris, France, 3 Institut National de la Transfusion Sanguine, Paris, France and 4 Laboratory of Excellence GR-Ex, Paris, France

Sylvain Leonard

Alexandre g. de brevern, jean-christophe gelly.

The polyproline helix type II (PPII) is a regular protein secondary structure with remarkable features. Many studies have highlighted different crucial biological roles supported by this local conformation, e.g. in the interactions between biological macromolecules. Although PPII is less frequently present than regular secondary structures such as canonical alpha helices and beta strands, it corresponds to 3–10% of residues. Up to now, PPII is not assigned by most popular assignment tools, and therefore, remains insufficiently studied. PolyprOnline database is, therefore, dedicated to PPII structure assignment and analysis to facilitate the study of PPII structure and functional roles. This database is freely accessible from www.dsimb.inserm.fr/dsimb_tools/polyproline .

Introduction

Fifty percent of local protein conformations are constituted of the two regular secondary structure, i.e. α helices and β sheets, while the remaining protein structure is essentially constituted of turns that can overlap the two previous local conformation, and coil ( 1 ). Regular secondary structures are fundamental descriptor for the analysis and the understanding of the structure and function of proteins at a molecular level. As such, they are automatically used to visualize the protein 3D structures with popular software like PyMOL ( 2 ), VMD ( 3 ) or Chimera ( 4 ). Thus, the secondary structures assignment is an essential step for studying protein architecture, folding and for the prediction of 3D protein structure. Besides α helices and β sheets, a number of other regular secondary structures are often ignored, despite their importance in biological processes ( 5 ). Among other regular secondary structures the polyproline II helix (PPII) is of significant interest. PPII conformation was primarily identified in the 1950s in collagen helix by Pauling and Corey ( 6 ), and in structures containing many repeating proline amino acids ( 7 ). It was not until the end of the 1990s that this conformation has been demonstrated to occur frequently in globular protein ( 8 ), with a very high conservation ratio of 80–100% in proteins families sharing 20% sequence identity or more, a ratio close to the conservation found for α helices and β strands ( 9 ). Depending on the tools used for the assignment of secondary structures, their frequency varies in the range of 3–10% of all conformations with a common core of more than 1.6% assignment shared by all tools ( 10 ). Other studies have shown similar frequency, Adzhubei and co-workers in a recent review ( 11 ) estimated about 2% of residues in Protein Databank to be in PPII-helices of length 3 and more residues. For historical reasons, this conformation had been called ‘polyproline helix’, although most PPIIs comprised non-proline residues and some even contain no proline at all ( 8 ).

In term of local structure conformation, Polyproline II is a left-handed helical conformation with average dihedral angle values of Φ = −75° and Ψ = +145°. Unlike classical regular secondary structures, PPIIs are not usually associated with conventional stabilizing internal hydrogen bonds due to this extremely extended conformation. PPII is a far more extended helix than classical α-helix (5.4 Å/turn, 3.6 residues per turn) and has a helical pitch of 9.3 Å/turn and 3 residues per turn. Thanks to this over extended conformation and high solvent exposure, residues in PPII may lead to potential interactions with other molecular partners. Thus, it was suggested that they might have an important functional role, particularly in protein–protein or protein–nucleic acid interactions and recognition ( 12 , 13 ). Regrettably, PPIIs are still insufficiently studied. In fact, PPII assignment is not done with the most common method of secondary structure assignment such as Dictionary of Protein Secondary Structure (DSSP; 14) and STRIDE ( 15 ), and therefore, newly solved protein structures are not assigned with PPII in Protein DataBank ( 16 ). Here we introduce a new assignment method and a dedicated webserver for PPII.

Aim and overview of database

The PolyprOnline database ( http://www.dsimb.inserm.fr/dsimb_tools/polyproline ) contains secondary structure assignments on a large subset of the Protein Databank. It also allows to dynamically handle any new user submitted structures. Unlike other databases established for protein secondary structure analysis, PolyprOnline particularly focalize on PPII, an assignment that is rarely documented in experimentally solved structures as well as in services and tools dedicated to the analysis of protein structures. For instance, 2struc ( http://2struc.cryst.bbk.ac.uk/about/ ) assigns protein in three secondary states using six different algorithms ( 17 ), but none of them address PPII assignment. More general tools such as PDBsum ( 18 ) give assignment by one method, PROMOTIF ( 19 ) in this case, with no details about PPII. As previously mentioned, this assignment is especially important since this conformation is the third most abundant regular secondary structure just behind α-helix and β-strand, and it is also involved in various function related to molecular interactions such as protein–protein and protein–nucleic-acid binding. However assignment using different tools show discrepancy thus our database provide assignments with the four main methods developed so far ( 10 ).

Results and features

The data flow and processing step performed by the system are summarized in Figure 1 .

An external file that holds a picture, illustration, etc.
Object name is bau102f1p.jpg

Data flow in PolyprOnline system. Access to the system can be done in two ways: through ‘Simple query’ for the analysis of one or more protein structures from their PDB code and through ‘Advanced query’ for performing more complex queries using different criteria such as resolution (Å), protein length, minimal and maximal number or percentage of residues in PPII conformation assigned by a particular tool. The last type of advanced query allows local structure search on specific positions using secondary structure patterns. It is also possible to dynamically upload and process a PDB file if it is absent of the database. The query is then processed to be interpreted by our Database Management System. In the case where a PDB structure is not found in the database, a PDB file can be downloaded from the Protein Databank website and dynamically processed by the system. PolyprOnline webserver offers the following outputs to display results: Summary of all protein identified by PDB code, title, size, resolution and PPII content, printed in a sortable table according to the values in different columns ( Figure 2 ). From this table, individual protein data analysis can be accessed individually ( Figure 3 ).

Through the main interface, two types of search are possible. Both searches are detailed in text of Figure 1 : simple search (analysis of one or more protein structure) and advanced search based on specific criteria to perform more complex queries. One of the most interesting features is the ability to perform secondary structure pattern query. This search is useful to look for a fragment of specified conformation contained in protein structures using a simple regular expression pattern. Pattern search uses the classical rules for regular expressions. It is possible to use conformation code letters (e.g . HHHH-PPEEE), and introduce wildcard (e.g . HHH**PP*-). It is also possible to specify the minimal and the maximal conformation length (e.g . PPPX{1,8}PP).

The PolyprOnline webserver offers the following outputs:

A table of sortable results

Results are displayed in a table that can be sorted accordingly to the values in different columns ( Figure 2 ). Results in the table can also be directly downloaded in text format. All proteins in the table are identifiable by PDB code, title, size, resolution and PPII content. You can also download the assignment of each protein in classical fasta format.

An external file that holds a picture, illustration, etc.
Object name is bau102f2p.jpg

Results. On the top of the table a pie chart displaying statistics of secondary structure content for each tool of all entries is dynamically generated. The table gives information on each selected protein chain. Each line corresponds to a PDB chain and each column to attribute values describing every entry. Alphabetical (PDB, Title) or numerical (length, resolution, PPII number and percentage) ordering and re-ordering of entries in ascending or descending order is possible. Another possibility is to do a free text search through a specific field. Each detailed analysis can be accessed from this table.

Individual protein data and analysis

The PolyprOnline web server provides access to different assignment methods and allows visualization of both regular secondary structure and PPII helix ( Figure 3 ). We have recently underlined the discrepancies between the three different secondary structure methods able to assign PPIIs, and proposed a novel PPII assignment using the de facto standard DSSP assignment method ( 10 , 14 ). To better visualize the secondary structure and PPII assignments given by PROSS ( 21 ), SEGNO ( 22 ), XTLSSTR ( 23 ) and our DSSP-PPII ( 10 , 14 ), they are all displayed at the bottom of sequence One letter code is used to represent specific conformation. Letters are coloured accordingly to more general class of secondary structure (e.g. helix residue in red, strand in green, PPII helix in blue non-regular secondary structure in grey, coil being in dark grey colour) for a fast visualization of overall local structures. All data from protein structure analysed can be downloaded.

An external file that holds a picture, illustration, etc.
Object name is bau102f3p.jpg

Detailed analysis of a protein structure (3KWEA; 25 ). ( A ) Sequence and analysis of secondary structures using four different protein secondary structure assignment methods are printed on a 1D alignment. One letter code is used to represent a specific conformation. Letters are coloured accordingly to more general class of secondary structure (i.e. helix residue in red, strand in green, PII helix in blue and non-regular secondary structure in grey). ( B ) Ramachandran plots give the distribution of φ and ψ torsion angles of PPII amino acids for each method. The most frequent areas for α-helix and β-sheet are shown in the background of the plot (represented by a colour scale). Statistics about areas were derived from our previous study. Residues assigned as PPIIs are represented as white points. ( C ) Full 3D structure visualization and animation using a JMol applet of different assignment can be dynamically displayed (Cα trace only, cartoon). Local conformations are coloured with the same colour scheme as used for the 1D alignment in (A; i.e. helix residue in red, strand in green, PII helix in blue and non-regular secondary structure in grey).

Ramachandran plots give the distribution of φ and ψ torsion angles for each assignment method. The most frequent areas for α-helix and β-sheet are shown in the background of the plot (represented by a colour scale). Statistics about areas were derived from our previous study ( 10 ). Residues assigned as PPIIs are represented as white points. The image is mouse sensitive and gives additional information on residue number, nature and φ and ψ angle values of assigned as PPII. Indeed assignments provided by the various tools can be quite different between them. Ramachandran plot lets to visually inspect φ and ψ angle PPII value distributions and help the user to apprehend the relevance of each assignment.

Visualization and manipulation of three dimensional protein structures is allowed thanks to a JMol applet ( 24 ). It displays the assignment of secondary structures by all of the four methods and details about positions of secondary structures with a particular emphasis on PPII. This visualization can also be useful to observe difference between assignments directly in protein structure.

Protein structures dataset

A subset of the experimental protein structures extracted from the PDB was selected based on the resolution methods (RX), quality of structures (resolution lower than 3.0 Å and R-factor lower than 1.0) limited redundancy (proteins share no more than 90% of identity between each others) using webserver PISCES ( 20 ). The full list of selected structures comprised 24 761 protein chains and is available on database. The list is regularly updated.

Assignment of PPII and other secondary structures

Currently, there is a limited number of tools for assigning PPII number. The tools available today are XTLSSTR, PROSS (version September 2004) and SEGNO (version 3.1). We have added our PPII DSSP-based program DSSP (CMBI version 2000) developed in our laboratory to this list ( 10 ). As we have previously explained, the use of multiple tools is necessary because it has been shown that PPII assignments using several methods yielded different results ( 10 ).

Secondary structures assigned by PROSS ( 21 ) are as follow: α helix (H), β turn (T), β strand (E), PPII (P), and coil (C). Assignments are based exclusively on Φ and Ψ dihedral angles.

The algorithm XTLSSTR ( 23 ) uses two angles and three distances to assign secondary structure from coordinates of PDB files. It assign secondary structures: α helix (H and h), 3 10 helix (G and g), hydrogen bonded β turn (T), non-hydrogen-bonded β turn (N), Extended β strand (E and e) and PPII (P and p)

SEGNO ( 22 ) uses also the Φ and Ψ dihedral angles coupled with other angles to assign the secondary structures. It assign α helix (H), β-strand (E and e), isolated β-strand (B and b) 3 10 helix (G and g), π-helix (I), coil (O, coded as ‘-’ in this database) and PPII (P and p).

DSSP-PPII is a new method for PPII assignment recently developed in our laboratory ( 10 ). It is based on the most popular secondary assignment tools: DSSP ( 14 ). DSSP assignment is based on the identification of precise hydrogen bond patterns corresponding to regular secondary structures. Assignment strategy of PPII is based on simple set of basic rules to have the highest agreement with PROSS, SEGNO and XTLSSTR methods. PPII are assigned solely in the coil region for at least two consecutive amino acids in coil with Φ = −75° ± ε and Ψ = +145° ± ε with ε = 29°. Basic assignment of secondary structure in DSSP defines eight types of secondary structures: α helix (H), extended β strand in parallel and or anti-parallel β-sheet conformation (E), isolated β-strand (B), 310 helix (G), Pi helix (I), bend (S) and coil (O, coded as ‘-’ in this database). This is the basic assignment to which helix PPII (P) has been added.

Web interface and Database

Database management server used by our system is MySQL. The PolyprOnline web interface has been written mainly in PHP, Perl, R and Javascript programming languages.

Conclusion and interesting case study

To better understand structure/function and structure/architecture relationships, the advanced search interface of PolyprOnline can be used to find proteins with a high content of PPII. Thus a query launched on the basis of PPII frequency or containing long PPII helix can highlight different properties and peculiarities. It can be noted that proteins with the highest content of PPII have an over-frequency of functions related to interaction mechanisms and/or binding, which is consistent with observations in ( 11 ). For example, Figure 4 provided some examples involved in various function such as cell adhesion (B), self binding (C) or binding to cyclin-dependent kinases (A), neurotoxicity, an effect that involved blockade of acetylcholine receptors (D) and anti-freeze effect where solvent interaction is fundamental (E). With more than 72% of residues in PPII conformation, this anti-freeze protein contains the highest percentage of PPII of our database. It can also be noted, in these examples, that the organization of these PPII present characteristics of this regular conformation: rather isolated and exposed prolines for cyclin-dependant kinase regulation subunit (A), and the characteristics of other regular secondary structures: (i) similarities with α helix motifs such as PPII-beta-beta motif in Thrombospondin (B) and Atratoxin of cobra venom (D), (ii) and analogy with both alpha and beta motif such in GTP-binding protein obg (C) and snow flea anti-freeze protein (E) where PPII arrangements appear as a six anti-parallel PPII helices bundle. All theses PPII have in common a broad exposure to the solvent as it has already been highlighted in previous studies ( 11 ). Please note that these proteins are extreme cases in term of PPII content and are provided for illustrative purposes. The largest continuous PPII helix, of 13 residues long, is found in a protein Lyase (2VK8A; 31 ). This quick analysis highlights the utility of PolyprOnline database for PPII study.

An external file that holds a picture, illustration, etc.
Object name is bau102f4p.jpg

Some examples of proteins with high number of PPII conformations revealed by PolyprOnline database. ( A ) Cyclin-dependant kinase regular subunit (1CKSA; 26 ), ( B ) Thrombospondin (1LSLA; 27 ), ( C ) GTP-binding protein OBG (1UDXA; 28 ), ( D ) Atratoxin (1V6PA; 29 ) and ( E ) Snow flea anti-freeze protein (2PNEA; 30 ). β sheets appear in cyan while α helices are in red with an internal face in yellow. PPII are in violet and pink for internal face. Some PPII arrangements are very well organized in anti-parallel six helix bundle such in Snow anti-freeze protein ( E ) or in GTP-binding protein OBG ( C ). Others architectures are remarkable: β-β-PPII or PPII-β-β architecture found in Thrombospondin ( B ) and Atratoxin ( D ) have a similar arrangement to well known motif β-β-α or α-β-β building with an α helix instead of PPII. Cyclin-dependant kinase regular subunit ( A ) does not show any PPII specific arrangement.

Acknowledgements

The authors would like to thank Stéphane Téletchéa for corrections and comments on the manuscript.

Funding : This work was supported by grants from the Ministry of Research (France); University Paris Diderot, Sorbonne Paris Cite' (France); the National Institute for Blood Transfusion (INTS, France); the Institute for Health and Medical Research (INSERM, France); and ‘Investissements d'avenir', Laboratory of Excellence GR-Ex (France) to R.C., S.L., A.G.B. and J.-C.G; Funding for open access charge: Institute for Health and Medical Research (INSERM, France).

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PolyprOnline: polyproline helix II and secondary structure assignment database

2014, Database

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Article Contents

Introduction, aim and overview of database, results and features, conclusion and interesting case study, acknowledgements.

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PolyprOnline: polyproline helix II and secondary structure assignment database

Citation details: Chebrek,R., Leonard,S., de Brevern,A.G., et al. PolyprOnline: polyproline helix II and secondary structure assignment database. Database (2014) Vol. 2014: article ID bau102; doi:10.1093/database/bau102

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Romain Chebrek, Sylvain Leonard, Alexandre G. de Brevern, Jean-Christophe Gelly, PolyprOnline: polyproline helix II and secondary structure assignment database, Database , Volume 2014, 2014, bau102, https://doi.org/10.1093/database/bau102

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The polyproline helix type II (PPII) is a regular protein secondary structure with remarkable features. Many studies have highlighted different crucial biological roles supported by this local conformation, e.g. in the interactions between biological macromolecules. Although PPII is less frequently present than regular secondary structures such as canonical alpha helices and beta strands, it corresponds to 3–10% of residues. Up to now, PPII is not assigned by most popular assignment tools, and therefore, remains insufficiently studied. PolyprOnline database is, therefore, dedicated to PPII structure assignment and analysis to facilitate the study of PPII structure and functional roles. This database is freely accessible from www.dsimb.inserm.fr/dsimb_tools/polyproline .

The data flow and processing step performed by the system are summarized in Figure 1 .

Data flow in PolyprOnline system. Access to the system can be done in two ways: through ‘Simple query’ for the analysis of one or more protein structures from their PDB code and through ‘Advanced query’ for performing more complex queries using different criteria such as resolution (Å), protein length, minimal and maximal number or percentage of residues in PPII conformation assigned by a particular tool. The last type of advanced query allows local structure search on specific positions using secondary structure patterns. It is also possible to dynamically upload and process a PDB file if it is absent of the database. The query is then processed to be interpreted by our Database Management System. In the case where a PDB structure is not found in the database, a PDB file can be downloaded from the Protein Databank website and dynamically processed by the system. PolyprOnline webserver offers the following outputs to display results: Summary of all protein identified by PDB code, title, size, resolution and PPII content, printed in a sortable table according to the values in different columns ( Figure 2 ). From this table, individual protein data analysis can be accessed individually ( Figure 3 ).

The PolyprOnline webserver offers the following outputs:

A table of sortable results

Results. On the top of the table a pie chart displaying statistics of secondary structure content for each tool of all entries is dynamically generated. The table gives information on each selected protein chain. Each line corresponds to a PDB chain and each column to attribute values describing every entry. Alphabetical (PDB, Title) or numerical (length, resolution, PPII number and percentage) ordering and re-ordering of entries in ascending or descending order is possible. Another possibility is to do a free text search through a specific field. Each detailed analysis can be accessed from this table.

Individual protein data and analysis

Detailed analysis of a protein structure (3KWEA; 25 ). ( A ) Sequence and analysis of secondary structures using four different protein secondary structure assignment methods are printed on a 1D alignment. One letter code is used to represent a specific conformation. Letters are coloured accordingly to more general class of secondary structure (i.e. helix residue in red, strand in green, PII helix in blue and non-regular secondary structure in grey). ( B ) Ramachandran plots give the distribution of φ and ψ torsion angles of PPII amino acids for each method. The most frequent areas for α-helix and β-sheet are shown in the background of the plot (represented by a colour scale). Statistics about areas were derived from our previous study. Residues assigned as PPIIs are represented as white points. ( C ) Full 3D structure visualization and animation using a JMol applet of different assignment can be dynamically displayed (Cα trace only, cartoon). Local conformations are coloured with the same colour scheme as used for the 1D alignment in (A; i.e. helix residue in red, strand in green, PII helix in blue and non-regular secondary structure in grey).

Protein structures dataset

Assignment of PPII and other secondary structures

Secondary structures assigned by PROSS ( 21 ) are as follow: α helix (H), β turn (T), β strand (E), PPII (P), and coil (C). Assignments are based exclusively on Φ and Ψ dihedral angles.

Web interface and Database

Database management server used by our system is MySQL. The PolyprOnline web interface has been written mainly in PHP, Perl, R and Javascript programming languages.

Some examples of proteins with high number of PPII conformations revealed by PolyprOnline database. ( A ) Cyclin-dependant kinase regular subunit (1CKSA; 26 ), ( B ) Thrombospondin (1LSLA; 27 ), ( C ) GTP-binding protein OBG (1UDXA; 28 ), ( D ) Atratoxin (1V6PA; 29 ) and ( E ) Snow flea anti-freeze protein (2PNEA; 30 ). β sheets appear in cyan while α helices are in red with an internal face in yellow. PPII are in violet and pink for internal face. Some PPII arrangements are very well organized in anti-parallel six helix bundle such in Snow anti-freeze protein ( E ) or in GTP-binding protein OBG ( C ). Others architectures are remarkable: β-β-PPII or PPII-β-β architecture found in Thrombospondin ( B ) and Atratoxin ( D ) have a similar arrangement to well known motif β-β-α or α-β-β building with an α helix instead of PPII. Cyclin-dependant kinase regular subunit ( A ) does not show any PPII specific arrangement.

The authors would like to thank Stéphane Téletchéa for corrections and comments on the manuscript.

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DOI: 10.1093/database/bau102
Corpus ID: 17521069

PolyprOnline: polyproline helix II and secondary structure assignment database

Romain Chebrek , Sylvain Léonard , +1 author Jean-Christophe Gelly
Published in Database J. Biol. Databases… 6 November 2014
Biology, Computer Science
Database: The Journal of Biological Databases and Curation

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Prediction of polyproline ii secondary structure propensity in proteins, structural and functional analyses of polyproline-ii helices in globular proteins, recent advances on polyproline ii, left-handed polyproline-ii helix revisited: proteins causing proteopathies, deciphering the backbone noncovalent interactions that stabilize polyproline ii conformation and reduce cis proline abundance in polyproline tracts., scot: rethinking the classification of secondary structure elements, force field effects in simulations of flexible peptides with varying polyproline ii propensity, plant polypeptide hormone systemin prefers polyproline ii conformation in solution, bert-ppii: the polyproline type ii helix structure prediction model based on bert and multichannel cnn, a linker of the proline-threonine repeating motif sequence is bimodal, 32 references, assignment of polyproline ii conformation and analysis of sequence – structure relationship.

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Polyproline-II helix in proteins: structure and function.

Conservation of polyproline ii helices in homologous proteins: implications for structure prediction by model building, left-handed polyproline ii helices commonly occur in globular proteins., secondary structure assignment that accurately reflects physical and evolutionary characteristics, local protein structures, bioinformatics applications note structural bioinformatics 2struc: the secondary structure server, pdbsum: summaries and analyses of pdb structures, assigning secondary structure from protein coordinate data, a physical basis for protein secondary structure., related papers.

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Database of secondary structure assignment (DSSP) and secondary
Database of secondary structure assignment (DSSP) and secondary
(PDF) PolyprOnline: polyproline helix II and secondary structure
Database of secondary structure assignment (DSSP) and secondary
Sequence alignment and secondary structure assignment. Alignment of the
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Secondary structure predictions

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DSSP
Introduction. The DSSP program was designed by Wolfgang Kabsch and Chris Sander to standardize secondary structure assignment. DSSP is a database of secondary structure assignments (and much more) for all protein entries in the Protein Data Bank (PDB). DSSP is also the program that calculates DSSP entries from PDB entries.
Using DSSP data
Using DSSP data. DSSP provides an elaborate description of the secondary structure elements in a protein structure, including backbone hydrogen bonding and the topology of β-sheets. The most popular feature is the per-residue assignment of secondary structure with a single character code: H = α-helix. B = residue in isolated β-bridge.
DSSP
DSSP is a database of secondary structure assignments (and much more) for all protein entries in the Protein Data Bank (PDB). DSSP is also the name of the program that calculates DSSP entries from PDB entries. The above means there are actually two ways of looking at DSSP. First of all there are the precalculated DSSP files for each PDB entry.
STRIDE: a web server for secondary structure assignment from known
Here, we report a dedicated STRIDE web server and a database of secondary structure assignments. STRIDE WEB SERVER AND DATABASE The STRIDE web server, written in the python programming language, makes accessible all functions implemented in the STRIDE software and also provides several additional visualization tools ( Figure 1 ).
Stride Homepage
Stride Services. This server offers an interactive interface to the secondary structure assignment program STRIDE. The Method is presented in detail in: Frishman D, Argos P. Knowledge-Based Protein Secondary Structure Assignment Proteins: Structure, Function, and Genetics 23:566-579 (1995) When using this server, please cite: Heinig, M ...
STRIDE: Protein secondary structure assignment from atomic ...
It relies on database-derived recognition parameters with the crystallographers' secondary structure definitions as a standard-of- truth. Please see Frishman and Argos [1] for detailed description of the algorithm. Frishman,D & Argos,P. (1995) Knowledge-based secondary structure assignment. Proteins: structure, function and genetics, 23, 566-579.
STRIDE: a web server for secondary structure assignment from known
The STRIDE web server provides access to this tool and allows visualization of the secondary structure, as well as contact and Ramachandran maps for any file uploaded by the user with atomic coordinates in the Protein Data Bank (PDB) format. A searchable database of STRIDE assignments for the latest PDB release is also provided.
2Struc: the secondary structure server
Abstract. Summary: The defined secondary structure of proteins method is often considered the gold standard for assignment of secondary structure from three-dimensional coordinates. However, there are alternative methods. '2Struc: The Secondary Structure Server' has been created as a single point of access for eight different secondary ...
STRIDE -- A web server for secondary structure assignment from known
The web server allows visualization of the secondary structure, as well as contact and Ramachandran maps for any file uploaded by the user with atomic coordinates in the Protein Data Bank (PDB) format. A searchable database of STRIDE assignments for the latest PDB release is also provided.
DSSPcont: continuous secondary structure assignments for proteins
Hence, secondary structure assignments are important to assure the optimal yield of experimental structures and to cleverly select the targets for structural genomics. ... Users may also access a DSSPcont database of pre-calculated assignments for all PDB records; this database is updated weekly with all new PDB entries. The interface is very ...
GitHub
The DSSP program was designed by Wolfgang Kabsch and Chris Sander to standardize secondary structure assignment. DSSP is a database of secondary structure assignments (and much more) for all protein entries in the Protein Data Bank (PDB). DSSP is also the program that calculates DSSP entries from PDB entries. DSSP does not predict secondary ...
(PDF) STRIDE: a Web server for secondary structure assignment from
STRIDE is a software tool for secondary structure assignment from atomic resolution protein structures. It implements a knowledge-based algorithm that makes combined use of hydrogen bond energy ...
Protein secondary structure assignment revisited: a detailed analysis
When needed, secondary structure assignments are reduced to three classes ... KAKSI takes a PDB file as input and prints the assigned secondary structure (and other data of intereset) in an XML output K2R reads a KAKSI XML output file and outputs the data in various FASTA format files by default. K2R allows users to easily implement any new ...
Assigning secondary structure in proteins using AI
Knowledge about protein structure assignment enriches the structural and functional understanding of proteins. Accurate and reliable structure assignment data is crucial for secondary structure prediction systems. Since the 1980s, various methods based on hydrogen bond analysis and atomic coordinate geometry, followed by machine learning, have been employed in protein structure assignment ...
STRIDE: a web server for secondary structure assignment from known
Here, we report a dedicated STRIDE web server and a database of secondary structure assignments. STRIDE WEB SERVER AND DATABASE The STRIDE web server, written in the python programming language, makes accessible all functions implemented in the STRIDE software and also provides several additional visualization tools (Figure (Figure1). 1 ).
Protein secondary structure assignment using residual networks
Knowledge about the secondary structure assignment contributes to a better understanding of proteins. Pauling and Corey identified the fundamental protein secondary structure elements (SSE), known as α-helices and β-sheets, in 1951 [].Together with irregular substructures called coils or loops, these regular substructures (α-helices and β-sheets) form the three-state classification (Q3 ...
Assigning Secondary Structure in Proteins using AI
Knowledge about protein structure assignment enriches the structural and functional understanding of proteins. Accurate and reliable structure assignment data is crucial for secondary structure prediction systems. Since the ′80s various methods based on hydrogen bond analysis and atomic coordinate geometry, followed by Machine Learning, have been employed in protein structure assignment.
webservice
DSSP is a database of secondary structure assignments (and much more) for all protein entries in the Protein Data Bank (PDB) STRIDE Protein secondary structure assignment with stride, Basic assignment, Visual assignment, Contact map, Ramachandran Plot. protein-structure. webservice. Share.
PolyprOnline: polyproline helix II and secondary structure assignment
Although PPII is less frequently present than regular secondary structures such as canonical alpha helices and beta strands, it corresponds to 3-10% of residues. Up to now, PPII is not assigned by most popular assignment tools, and therefore, remains insufficiently studied. PolyprOnline database is, therefore, dedicated to PPII structure ...
PolyprOnline: polyproline helix II and secondary structure assignment
In fact, PPII assignment is not done with the most common method of secondary structure assignment such as Dictionary of Protein Secondary Structure (DSSP; 14) and STRIDE , and therefore, ... However assignment using different tools show discrepancy thus our database provide assignments with the four main methods developed so far .
PolyprOnline: polyproline helix II and secondary structure assignment
PolyprOnline: polyproline helix II and secondary structure assignment database. Sylvain Leonard. 2014, Database. See Full PDF Download PDF. See Full PDF ...
PolyprOnline: polyproline helix II and secondary structure assignment
Regrettably, PPIIs are still insufficiently studied. In fact, PPII assignment is not done with the most common method of secondary structure assignment such as Dictionary of Protein Secondary Structure (DSSP; 14) and STRIDE ( 15), and therefore, newly solved protein structures are not assigned with PPII in Protein DataBank ( 16). Here we ...
PolyprOnline: polyproline helix II and secondary structure assignment
The polyproline helix type II (PPII) is a regular protein secondary structure with remarkable features, but it is not assigned by most popular assignment tools, and therefore, remains insufficiently studied. The polyproline helix type II (PPII) is a regular protein secondary structure with remarkable features. Many studies have highlighted different crucial biological roles supported by this ...
Seeing Like a Data Structure
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PolyprOnline: polyproline helix II and secondary structure assignment database

Sylvain Leonard

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Protein structures dataset

Assignment of PPII and other secondary structures

Web interface and Database

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PolyprOnline: polyproline helix II and secondary structure assignment database

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PolyprOnline: polyproline helix II and secondary structure assignment database

A table of sortable results

Individual protein data and analysis

Protein structures dataset

Assignment of PPII and other secondary structures

Web interface and Database

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PolyprOnline: polyproline helix II and secondary structure assignment database

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41 Citations

Polyproline-II helix in proteins: structure and function.