Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

HPDB-Haskell library for processing atomic biomolecular structures in Protein Data Bank format.

ABSTRACT:

Background

Protein DataBank file format is used for the majority of biomolecular data available today. Haskell is a lazy functional language that enjoys a high-level class-based type system, a growing collection of useful libraries and a reputation for efficiency.

Findings

I present a fast library for processing biomolecular data in the Protein Data Bank format. I present benchmarks indicating that this library is faster than other frequently used Protein Data Bank parsing programs. The proposed library also features a convenient iterator mechanism, and a simple API modeled after BioPython.

Conclusion

I set a new standard for convenience and efficiency of Protein Data Bank processing in a Haskell library, and release it to open source.

SUBMITTER: Gajda MJ

PROVIDER: S-EPMC3879085 | biostudies-literature | 2013 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

HPDB-Haskell library for processing atomic biomolecular structures in Protein Data Bank format.

Gajda Michał Jan MJ

BMC research notes 20131123

<h4>Background</h4>Protein DataBank file format is used for the majority of biomolecular data available today. Haskell is a lazy functional language that enjoys a high-level class-based type system, a growing collection of useful libraries and a reputation for efficiency.<h4>Findings</h4>I present a fast library for processing biomolecular data in the Protein Data Bank format. I present benchmarks indicating that this library is faster than other frequently used Protein Data Bank parsing program ...[more]

PMID: 24267035

Similar Datasets

Restraint Validation of Biomolecular Structures Determined by NMR in the Protein Data Bank.

Project description:Biomolecular structure analysis from experimental NMR studies generally relies on restraints derived from a combination of experimental and knowledge-based data. A challenge for the structural biology community has been a lack of standards for representing these restraints, preventing the establishment of uniform methods of model-vs-data structure validation against restraints and limiting interoperability between restraint-based structure modeling programs. The NMR exchange (NEF) and NMR-STAR formats provide a standardized approach for representing commonly used NMR restraints. Using these restraint formats, a standardized validation system for assessing structural models of biopolymers against restraints has been developed and implemented in the wwPDB OneDep data deposition-validation-biocuration system. The resulting wwPDB Restraint Violation Report provides a model vs. data assessment of biomolecule structures determined using distance and dihedral restraints, with extensions to other restraint types currently being implemented. These tools are useful for assessing NMR models, as well as for assessing biomolecular structure predictions based on distance restraints.

| S-EPMC10849500 | biostudies-literature

Waterless structures in the Protein Data Bank.

Project description:The absence of solvent molecules in high-resolution protein crystal structure models deposited in the Protein Data Bank (PDB) contradicts the fact that, for proteins crystallized from aqueous media, water molecules are always expected to bind to the protein surface, as well as to some sites in the protein interior. An analysis of the contents of the PDB indicated that the expected ratio of the number of water molecules to the number of amino-acid residues exceeds 1.5 in atomic resolution structures, decreasing to 0.25 at around 2.5 Å resolution. Nevertheless, almost 800 protein crystal structures determined at a resolution of 2.5 Å or higher are found in the current release of the PDB without any water molecules, whereas some other depositions have unusually low or high occupancies of modeled solvent. Detailed analysis of these depositions revealed that the lack of solvent molecules might be an indication of problems with either the diffraction data, the refinement protocol, the deposition process or a combination of these factors. It is postulated that problems with solvent structure should be flagged by the PDB and addressed by the depositors.

| S-EPMC11533996 | biostudies-literature

Mining the Protein Data Bank to inspire fragment library design.

Project description:The fragment approach has emerged as a method of choice for drug design, as it allows difficult therapeutic targets to be addressed. Success lies in the choice of the screened chemical library and the biophysical screening method, and also in the quality of the selected fragment and structural information used to develop a drug-like ligand. It has recently been proposed that promiscuous compounds, i.e., those that bind to several proteins, present an advantage for the fragment approach because they are likely to give frequent hits in screening. In this study, we searched the Protein Data Bank for fragments with multiple binding modes and targeting different sites. We identified 203 fragments represented by 90 scaffolds, some of which are not or hardly present in commercial fragment libraries. By contrast to other available fragment libraries, the studied set is enriched in fragments with a marked three-dimensional character (download at 10.5281/zenodo.7554649).

| S-EPMC9950109 | biostudies-literature

Validation of Structures in the Protein Data Bank.

Project description:The Worldwide PDB recently launched a deposition, biocuration, and validation tool: OneDep. At various stages of OneDep data processing, validation reports for three-dimensional structures of biological macromolecules are produced. These reports are based on recommendations of expert task forces representing crystallography, nuclear magnetic resonance, and cryoelectron microscopy communities. The reports provide useful metrics with which depositors can evaluate the quality of the experimental data, the structural model, and the fit between them. The validation module is also available as a stand-alone web server and as a programmatically accessible web service. A growing number of journals require the official wwPDB validation reports (produced at biocuration) to accompany manuscripts describing macromolecular structures. Upon public release of the structure, the validation report becomes part of the public PDB archive. Geometric quality scores for proteins in the PDB archive have improved over the past decade.

| S-EPMC5718880 | biostudies-literature

Icosahedral virus structures and the protein data bank.

Project description:The structural study of icosahedral viruses has a long and impactful history in both crystallographic methodology and molecular biology. The evolution of the Protein Data Bank has paralleled and supported these studies providing readily accessible formats dealing with novel features associated with viral particle symmetries and subunit interactions. This overview describes the growth in size and complexity of icosahedral viruses from the first early studies of small RNA plant viruses and human picornaviruses up to the larger and more complex bacterial phage, insect, and human disease viruses such as Zika, hepatitis B, Adeno and Polyoma virus. The analysis of icosahedral viral capsid protein domain folds has shown striking similarities, with the beta jelly roll motif observed across multiple evolutionarily divergent species. The icosahedral symmetry of viruses drove the development of noncrystallographic symmetry averaging as a powerful phasing method, and the constraints of maintaining this symmetry resulted in the concept of quasi-equivalence in viral structures. Symmetry also played an important early role in demonstrating the power of cryo-electron microscopy as an alternative to crystallography in generating atomic resolution structures of these viruses. The Protein Data Bank has been a critical resource for assembling and disseminating these structures to a wide community, and the virus particle explorer (VIPER) was developed to enable users to easily generate and view complete viral capsid structures from their asymmetric building blocks. Finally, we share a personal perspective on the early use of computer graphics to communicate the intricacies, interactions, and beauty of these virus structures.

| S-EPMC8081926 | biostudies-literature

Protein Data Bank Japan (PDBj): maintaining a structural data archive and resource description framework format.

Project description:The Protein Data Bank Japan (PDBj, http://pdbj.org) is a member of the worldwide Protein Data Bank (wwPDB) and accepts and processes the deposited data of experimentally determined macromolecular structures. While maintaining the archive in collaboration with other wwPDB partners, PDBj also provides a wide range of services and tools for analyzing structures and functions of proteins, which are summarized in this article. To enhance the interoperability of the PDB data, we have recently developed PDB/RDF, PDB data in the Resource Description Framework (RDF) format, along with its ontology in the Web Ontology Language (OWL) based on the PDB mmCIF Exchange Dictionary. Being in the standard format for the Semantic Web, the PDB/RDF data provide a means to integrate the PDB with other biological information resources.

| S-EPMC3245181 | biostudies-literature

Exploring the universe of protein structures beyond the Protein Data Bank.

Project description:It is currently believed that the atlas of existing protein structures is faithfully represented in the Protein Data Bank. However, whether this atlas covers the full universe of all possible protein structures is still a highly debated issue. By using a sophisticated numerical approach, we performed an exhaustive exploration of the conformational space of a 60 amino acid polypeptide chain described with an accurate all-atom interaction potential. We generated a database of around 30,000 compact folds with at least of secondary structure corresponding to local minima of the potential energy. This ensemble plausibly represents the universe of protein folds of similar length; indeed, all the known folds are represented in the set with good accuracy. However, we discover that the known folds form a rather small subset, which cannot be reproduced by choosing random structures in the database. Rather, natural and possible folds differ by the contact order, on average significantly smaller in the former. This suggests the presence of an evolutionary bias, possibly related to kinetic accessibility, towards structures with shorter loops between contacting residues. Beside their conceptual relevance, the new structures open a range of practical applications such as the development of accurate structure prediction strategies, the optimization of force fields, and the identification and design of novel folds.

| S-EPMC2973819 | biostudies-literature

Atomic Motif Recognition in (Bio)Polymers: Benchmarks From the Protein Data Bank.

Project description:Rationalizing the structure and structure-property relations for complex materials such as polymers or biomolecules relies heavily on the identification of local atomic motifs, e.g., hydrogen bonds and secondary structure patterns, that are seen as building blocks of more complex supramolecular and mesoscopic structures. Over the past few decades, several automated procedures have been developed to identify these motifs in proteins given the atomic structure. Being based on a very precise understanding of the specific interactions, these heuristic criteria formulate the question in a way that implies the answer, by defining a list of motifs based on those that are known to be naturally occurring. This makes them less likely to identify unexpected phenomena, such as the occurrence of recurrent motifs in disordered segments of proteins, and less suitable to be applied to different polymers whose structure is not driven by hydrogen bonds, or even to polypeptides when appearing in unusual, non-biological conditions. Here we discuss how unsupervised machine learning schemes can be used to recognize patterns based exclusively on the frequency with which different motifs occur, taking high-resolution structures from the Protein Data Bank as benchmarks. We first discuss the application of a density-based motif recognition scheme in combination with traditional representations of protein structure (namely, interatomic distances and backbone dihedrals). Then, we proceed one step further toward an entirely unbiased scheme by using as input a structural representation based on the atomic density and by employing supervised classification to objectively assess the role played by the representation in determining the nature of atomic-scale patterns.

| S-EPMC6482324 | biostudies-literature

A History of Molecular Chaperone Structures in the Protein Data Bank.

Project description:Thirty years ago a class of proteins was found to prevent the aggregation of Rubisco. These proteins' ability to prevent unwanted associations led to their being called chaperones. These chaperone proteins also increased in expression as a response to heat shock, hence their label as heat shock proteins (Hsps). However, neither label encompasses the breadth of these proteins' functional capabilities. The term "unfoldases" has been proposed, as this basic function is shared by most members of this protein family. Onto this is added specializations that allow the different family members to perform various cellular functions. This current article focuses on the resolved structural bases for these functions. It reviews the currently available molecular structures in the Protein Data Bank for several classes of Hsps (Hsp60, Hsp70, Hsp90, and Hsp104). When possible, it discusses the complete structures for these proteins, and the types of molecular machines to which they have been assigned. The structures of domains and the associated functions are discussed in order to illustrate the rationale for the proposed unfoldase function.

| S-EPMC6940948 | biostudies-literature

Protein Data Bank Japan: Improved tools for sequence-oriented analysis of protein structures.

Project description:Protein Data Bank Japan (PDBj) is the Asian hub of three-dimensional macromolecular structure data, and a founding member of the worldwide Protein Data Bank. We have accepted, processed, and distributed experimentally determined biological macromolecular structures for over two decades. Although we collaborate with RCSB PDB and BMRB in the United States, PDBe and EMDB in Europe and recently PDBc in China for our data-in activities, we have developed our own unique services and tools for searching, exploring, visualizing and analyzing protein structures. We have recently introduced a new UniProt-integrated portal to provide users with a quick overview of their target protein and shows a recommended structure with integrated data from various internal and external resources. The portal page helps users identify known genomic variations of their protein of interest and provide insights into how these modifications might impact the structure, stability and dynamics of the protein. Furthermore, the portal page also helps users to select the optimal structure to use for further analysis. We have also introduced another service to explore proteins using experimental and computational approaches, which enables experimental structural biologists to increase their insight to help them to more efficiently design their experimental studies. With these new additions, we have enhanced our service portfolio to benefit both experimental and computational structural biologists in their search to interpret protein structures, their dynamics and function.

| S-EPMC11837027 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data