Perspectives in biological physics: The nDDB project for a neutron Dynamics Data Bank for biological macromolecules

2013 ◽  
Vol 36 (7) ◽  
Author(s):  
Leonid Rusevich ◽  
Victoria García Sakai ◽  
Bruno Franzetti ◽  
Mark Johnson ◽  
Francesca Natali ◽  
...  
Keyword(s):  
Data Bank ◽  
Biological Macromolecules ◽  
Biological Physics

scholarly journals Protein dynamics revealed by NMR relaxation methods

2018 ◽  
Vol 2 (1) ◽  
pp. 93-105 ◽  
Author(s):  
Fa-An Chao ◽  
R. Andrew Byrd
Keyword(s):  
Protein Dynamics ◽  
Structural Biology ◽  
Dynamic Models ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Data Bank ◽  
Biological Macromolecules ◽  
Relaxation Methods ◽  
Genomic Databases ◽  
Wide Range

Structural biology often focuses primarily on three-dimensional structures of biological macromolecules, deposited in the Protein Data Bank (PDB). This resource is a remarkable entity for the worldwide scientific and medical communities, as well as the general public, as it is a growing translation into three-dimensional space of the vast information in genomic databases, e.g. GENBANK. There is, however, significantly more to understanding biological function than the three-dimensional co-ordinate space for ground-state structures of biomolecules. The vast array of biomolecules experiences natural dynamics, interconversion between multiple conformational states, and molecular recognition and allosteric events that play out on timescales ranging from picoseconds to seconds. This wide range of timescales demands ingenious and sophisticated experimental tools to sample and interpret these motions, thus enabling clearer insights into functional annotation of the PDB. NMR spectroscopy is unique in its ability to sample this range of timescales at atomic resolution and in physiologically relevant conditions using spin relaxation methods. The field is constantly expanding to provide new creative experiments, to yield more detailed coverage of timescales, and to broaden the power of interpretation and analysis methods. This review highlights the current state of the methodology and examines the extension of analysis tools for more complex experiments and dynamic models. The future for understanding protein dynamics is bright, and these extended tools bring greater compatibility with developments in computational molecular dynamics, all of which will further our understanding of biological molecular functions. These facets place NMR as a key component in integrated structural biology.

scholarly journals RCSB Protein Data Bank tools for 3D structure-guided cancer research: human papillomavirus (HPV) case study

Oncogene ◽  
2020 ◽  
Vol 39 (43) ◽  
pp. 6623-6632
Author(s):  
David S. Goodsell ◽  
Stephen K. Burley
Keyword(s):  
Human Papillomavirus ◽  
Protein Data Bank ◽  
3D Structure ◽  
Healthcare Providers ◽  
Data Bank ◽  
Data Repository ◽  
Biological Macromolecules ◽  
Biologic Drugs ◽  
Related Proteins

Abstract Atomic-level three-dimensional (3D) structure data for biological macromolecules often prove critical to dissecting and understanding the precise mechanisms of action of cancer-related proteins and their diverse roles in oncogenic transformation, proliferation, and metastasis. They are also used extensively to identify potentially druggable targets and facilitate discovery and development of both small-molecule and biologic drugs that are today benefiting individuals diagnosed with cancer around the world. 3D structures of biomolecules (including proteins, DNA, RNA, and their complexes with one another, drugs, and other small molecules) are freely distributed by the open-access Protein Data Bank (PDB). This global data repository is used by millions of scientists and educators working in the areas of drug discovery, vaccine design, and biomedical and biotechnology research. The US Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) provides an integrated portal to the PDB archive that streamlines access for millions of worldwide PDB data consumers worldwide. Herein, we review online resources made available free of charge by the RCSB PDB to basic and applied researchers, healthcare providers, educators and their students, patients and their families, and the curious public. We exemplify the value of understanding cancer-related proteins in 3D with a case study focused on human papillomavirus.

scholarly journals Protein Data Bank (PDB): Database of Three-Dimensional Structural Information of Biological Macromolecules

1998 ◽  
Vol 54 (6) ◽  
pp. 1078-1084 ◽  
Author(s):  
Joel L. Sussman ◽  
Dawei Lin ◽  
Jiansheng Jiang ◽  
Nancy O. Manning ◽  
Jaime Prilusky ◽  
...  
Keyword(s):  
Nucleic Acids ◽  
Protein Data Bank ◽  
Structural Information ◽  
National Laboratory ◽  
Three Dimensional ◽  
Data Bank ◽  
Brookhaven National Laboratory ◽  
Biological Macromolecules

The Protein Data Bank (PDB) at Brookhaven National Laboratory, is a database containing experimentally determined three-dimensional structures of proteins, nucleic acids and other biological macromolecules, with approximately 8000 entries. Data are easily submittedviaPDB's WWW-based toolAutoDep, in either mmCIF or PDB format, and are most conveniently examinedviaPDB's WWW-based tool3DB Browser.

scholarly journals New developments in crystallography: exploring its technology, methods and scope in the molecular biosciences

2017 ◽  
Vol 37 (4) ◽  
Author(s):  
John R. Helliwell
Keyword(s):  
Crystal Structure ◽  
Data Bank ◽  
Crystal Structure Analysis ◽  
Public Understanding ◽  
Biological Macromolecules ◽  
Hydrogen Atoms ◽  
X Ray ◽  
The Public ◽  
X Ray Crystallography ◽  
Chemical Catalysis

Since the Protein Data Bank (PDB) was founded in 1971, there are now over 120,000 depositions, the majority of which are from X-ray crystallography and 90% of those made use of synchrotron beamlines. At the Cambridge Structure Database (CSD), founded in 1965, there are more than 800,000 ‘small molecule’ crystal structure depositions and a very large number of those are relevant in the biosciences as ligands or cofactors. The technology for crystal structure analysis is still developing rapidly both at synchrotrons and in home labs. Determination of the details of the hydrogen atoms in biological macromolecules is well served using neutrons as probe. Large multi-macromolecular complexes cause major challenges to crystallization; electrons as probes offer unique advantages here. Methods developments naturally accompany technology change, mainly incremental but some, such as the tuneability, intensity and collimation of synchrotron radiation, have effected radical changes in capability of biological crystallography. In the past few years, the X-ray laser has taken X-ray crystallography measurement times into the femtosecond range. In terms of applications many new discoveries have been made in the molecular biosciences. The scope of crystallographic techniques is indeed very wide. As examples, new insights into chemical catalysis of enzymes and relating ligand bound structures to thermodynamics have been gained but predictive power is seen as not yet achieved. Metal complexes are also an emerging theme for biomedicine applications. Our studies of coloration of live and cooked lobsters proved to be an unexpected favourite with the public and schoolchildren. More generally, public understanding of the biosciences and crystallography’s role within the field have been greatly enhanced by the United Nations International Year of Crystallography coordinated by the International Union of Crystallography. This topical review describes each of these areas along with illustrative results to document the scope of each methodology.

ACMS: a database of alternate conformations found in the atoms of main and side chains of protein structures

2019 ◽  
Vol 52 (4) ◽  
pp. 910-913 ◽  
Author(s):  
R. Santhosh ◽  
P. Chandrasekaran ◽  
Daliah Michael ◽  
K. Rangachari ◽  
Namrata Bankoti ◽  
...  
Keyword(s):  
High Resolution ◽  
Knowledge Base ◽  
Crystal Structures ◽  
Protein Structures ◽  
Protein Molecule ◽  
Data Bank ◽  
Side Chain ◽  
Biological Macromolecules ◽  
Conformational Ensembles ◽  
User Friendly

Proteins are usually dynamic biological macromolecules, thereby exhibiting a large number of conformational ensembles which influence the association with their neighbours and interacting partners. Most of the side-chain atoms and a few main-chain atoms of the high-resolution crystal structures deposited in the Protein Data Bank adopt alternate conformations. This kind of conformational behaviour prompted the authors to explore the relationship, if any, between the alternate conformations and the function of the protein molecule. Thus, a knowledge base of the alternate conformations of the main- and side-chain atoms of protein structures has been developed. It provides a detailed description of the alternate conformations of various residues for more than 60 000 high-resolution crystal structures. The proposed knowledge base is very user friendly and has various flexible options. The knowledge base will be updated periodically and can be accessed at http://iris.physics.iisc.ac.in/acms.

scholarly journals Molecular Skin Surface-Based Transformation Visualization between Biological Macromolecules

2017 ◽  
Vol 2017 ◽  
pp. 1-12 ◽  
Author(s):  
Ke Yan ◽  
Bing Wang ◽  
Holun Cheng ◽  
Zhiwei Ji ◽  
Jing Huang ◽  
...  
Keyword(s):  
Protein Structures ◽  
Computational Cost ◽  
Data Bank ◽  
Skin Surface ◽  
Transformation Process ◽  
Molecular Surface ◽  
Biological Macromolecules ◽  
Dynamic Simulations ◽  
Macromolecular Dynamics ◽  
Union Of Balls

Molecular skin surface (MSS), proposed by Edelsbrunner, is a C2 continuous smooth surface modeling approach of biological macromolecules. Compared to the traditional methods of molecular surface representations (e.g., the solvent exclusive surface), MSS has distinctive advantages including having no self-intersection and being decomposable and transformable. For further promoting MSS to the field of bioinformatics, transformation between different MSS representations mimicking the macromolecular dynamics is demanded. The transformation process helps biologists understand the macromolecular dynamics processes visually in the atomic level, which is important in studying the protein structures and binding sites for optimizing drug design. However, modeling the transformation between different MSSs suffers from high computational cost while the traditional approaches reconstruct every intermediate MSS from respective intermediate union of balls. In this study, we propose a novel computational framework named general MSS transformation framework (GMSSTF) between two MSSs without the assistance of union of balls. To evaluate the effectiveness of GMSSTF, we applied it on a popular public database PDB (Protein Data Bank) and compared the existing MSS algorithms with and without GMSSTF. The simulation results show that the proposed GMSSTF effectively improves the computational efficiency and is potentially useful for macromolecular dynamic simulations.

scholarly journals A public database of macromolecular diffraction experiments

2016 ◽  
Vol 72 (11) ◽  
pp. 1181-1193 ◽  
Author(s):  
Marek Grabowski ◽  
Karol M. Langner ◽  
Marcin Cymborowski ◽  
Przemyslaw J. Porebski ◽  
Piotr Sroka ◽  
...  
Keyword(s):  
Experimental Data ◽  
Diffraction Data ◽  
Distributed Storage ◽  
Protein Structure Determination ◽  
Data Bank ◽  
Scientific Integrity ◽  
Biological Macromolecules ◽  
Data Sets ◽  
X Ray ◽  
Unrestricted Access

The low reproducibility of published experimental results in many scientific disciplines has recently garnered negative attention in scientific journals and the general media. Public transparency, including the availability of `raw' experimental data, will help to address growing concerns regarding scientific integrity. Macromolecular X-ray crystallography has led the way in requiring the public dissemination of atomic coordinates and a wealth of experimental data, making the field one of the most reproducible in the biological sciences. However, there remains no mandate for public disclosure of the original diffraction data. The Integrated Resource for Reproducibility in Macromolecular Crystallography (IRRMC) has been developed to archive raw data from diffraction experiments and, equally importantly, to provide related metadata. Currently, the database of our resource contains data from 2920 macromolecular diffraction experiments (5767 data sets), accounting for around 3% of all depositions in the Protein Data Bank (PDB), with their corresponding partially curated metadata. IRRMC utilizes distributed storage implemented using a federated architecture of many independent storage servers, which provides both scalability and sustainability. The resource, which is accessibleviathe web portal at http://www.proteindiffraction.org, can be searched using various criteria. All data are available for unrestricted access and download. The resource serves as a proof of concept and demonstrates the feasibility of archiving raw diffraction data and associated metadata from X-ray crystallographic studies of biological macromolecules. The goal is to expand this resource and include data sets that failed to yield X-ray structures in order to facilitate collaborative efforts that will improve protein structure-determination methods and to ensure the availability of `orphan' data left behind for various reasons by individual investigators and/or extinct structural genomics projects.

scholarly journals Check your metal - not every density blob is a water molecule

2014 ◽  
Vol 70 (a1) ◽  
pp. C1483-C1483
Author(s):  
Heping Zheng ◽  
Mahendra Chordia ◽  
David Cooper ◽  
Ivan Shabalin ◽  
Maksymilian Chruszcz ◽  
...  
Keyword(s):  
Coordination Chemistry ◽  
Metal Binding ◽  
Binding Sites ◽  
Metal Ion ◽  
Protein Structures ◽  
Data Bank ◽  
Careful Examination ◽  
Biological Macromolecules ◽  
Metal Binding Sites ◽  
Heterogeneous Chemical

Metals play vital roles in both the mechanism and architecture of biological macromolecules, and are the most frequently encountered ligands (i.e. non-solvent heterogeneous chemical atoms) in the determination of macromolecular crystal structures. However, metal coordinating environments in protein structures are not always easy to check in routine validation procedures, resulting in an abundance of misidentified and/or suboptimally modeled metal ions in the Protein Data Bank (PDB). We present a solution to identify these problems in three distinct yet related aspects: (1) coordination chemistry; (2) agreement of experimental B-factors and occupancy; and (3) the composition and motif of the metal binding environment. Due to additional strain introduced by macromolecular backbones, the patterns of coordination of metal binding sites in metal-containing macromolecules are more complex and diverse than those found in inorganic or organometallic chemistry. These complications make a comprehensive library of "permitted" coordination chemistry in protein structures less feasible, and the usage of global parameters such as the bond valence method more practical, in the determination and validation of metal binding environments. Although they are relatively infrequent, there are also cases where the experimental B-factor or occupancy of a metal ion suggests careful examination. We have developed a web-based tool called CheckMyMetal [1](http://csgid.org/csgid/metal_sites/) for the quick validation of metal binding sites. Moreover, the acquired knowledge of the composition and spatial arrangement (motif) of the coordinating atoms around the metal ion may also help in the modeling of metal binding sites in macromolecular structures. All of the studies described herein were performed using the NEIGHBORHOOD SQL database [2], which connects information about all modeled non-solvent heterogeneous chemical motifs in PDB structure by vectors describing all contacts to neighboring residues and atoms. NEIGHBORHOOD has broad applications for the validation and data mining of ligand binding environments in the PDB.

scholarly journals RCSB Protein Data Bank: powerful new tools for exploring 3D structures of biological macromolecules for basic and applied research and education in fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences

2020 ◽  
Vol 49 (D1) ◽  
pp. D437-D451 ◽  
Author(s):  
Stephen K Burley ◽  
Charmi Bhikadiya ◽  
Chunxiao Bi ◽  
Sebastian Bittrich ◽  
Li Chen ◽  
...  
Keyword(s):  
Protein Data Bank ◽  
Data Bank ◽  
Resonance Spectroscopy ◽  
Biological Macromolecules ◽  
Host Cell Proteins ◽  
Global Pandemic ◽  
3D Electron Microscopy ◽  
Fundamental Biology ◽  
Basic And Applied Research ◽  
Research And Education

Abstract The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB), the US data center for the global PDB archive and a founding member of the Worldwide Protein Data Bank partnership, serves tens of thousands of data depositors in the Americas and Oceania and makes 3D macromolecular structure data available at no charge and without restrictions to millions of RCSB.org users around the world, including >660 000 educators, students and members of the curious public using PDB101.RCSB.org. PDB data depositors include structural biologists using macromolecular crystallography, nuclear magnetic resonance spectroscopy, 3D electron microscopy and micro-electron diffraction. PDB data consumers accessing our web portals include researchers, educators and students studying fundamental biology, biomedicine, biotechnology, bioengineering and energy sciences. During the past 2 years, the research-focused RCSB PDB web portal (RCSB.org) has undergone a complete redesign, enabling improved searching with full Boolean operator logic and more facile access to PDB data integrated with >40 external biodata resources. New features and resources are described in detail using examples that showcase recently released structures of SARS-CoV-2 proteins and host cell proteins relevant to understanding and addressing the COVID-19 global pandemic.

Protein Data Bank (PDB): A Database of 3D Structural Information of Biological Macromolecules

2002 ◽  
Author(s):  
Joel L. Sussman ◽  
Frances C. Bernstein ◽  
Jiansheng Jiang ◽  
Michael Libeson ◽  
Dawei Lin ◽  
...  
Keyword(s):  
Protein Data Bank ◽  
Structural Information ◽  
Data Bank ◽  
Biological Macromolecules
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