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.

Structural characterization of intrinsically disordered proteins by the combined use of NMR and SAXS

2012 ◽  
Vol 40 (5) ◽  
pp. 955-962 ◽  
Author(s):  
Nathalie Sibille ◽  
Pau Bernadó
Keyword(s):  
Intrinsically Disordered Proteins ◽  
Dynamic Models ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Main Tool ◽  
Structural Features ◽  
Disordered Proteins ◽  
Dimensional Structure ◽  
Intrinsically Disordered ◽  
Conformational Preferences

In recent years, IDPs (intrinsically disordered proteins) have emerged as pivotal actors in biology. Despite IDPs being present in all kingdoms of life, they are more abundant in eukaryotes where they are involved in the vast majority of regulation and signalling processes. The realization that, in some cases, functional states of proteins were partly or fully disordered was in contradiction to the traditional view where a well defined three-dimensional structure was required for activity. Several experimental evidences indicate, however, that structural features in IDPs such as transient secondary-structural elements and overall dimensions are crucial to their function. NMR has been the main tool to study IDP structure by probing conformational preferences at residue level. Additionally, SAXS (small-angle X-ray scattering) has the capacity to report on the three-dimensional space sampled by disordered states and therefore complements the local information provided by NMR. The present review describes how the synergy between NMR and SAXS can be exploited to obtain more detailed structural and dynamic models of IDPs in solution. These combined strategies, embedded into computational approaches, promise the elucidation of the structure–function properties of this important, but elusive, family of biomolecules.

Structural biology and structure–function relationships of membrane proteins

2018 ◽  
Vol 47 (1) ◽  
pp. 47-61 ◽  
Author(s):  
Rosana Reis ◽  
Isabel Moraes
Keyword(s):  
Membrane Proteins ◽  
Structure Function ◽  
Structural Biology ◽  
Drug Targets ◽  
Three Dimensional ◽  
Data Bank ◽  
Technical Advances ◽  
Medical Importance ◽  
G Protein Coupled ◽  
Important Drug

Abstract The study of structure–function relationships of membrane proteins (MPs) has been one of the major goals in the field of structural biology. Many Noble Prizes regarding remarkable accomplishments in MP structure determination and biochemistry have been awarded over the last few decades. Mutations or improper folding of these proteins are associated with numerous serious illnesses. Therefore, as important drug targets, the study of their primary sequence and three-dimensional fold, combined with cell-based assays, provides vital information about their structure–function relationships. Today, this information is vital to drug discovery and medicine. In the last two decades, many have been the technical advances and breakthroughs in the field of MP structural biology that have contributed to an exponential growth in the number of unique MP structures in the Protein Data Bank. Nevertheless, given the medical importance and many unanswered questions, it will never be an excess of MP structures, regardless of the method used. Owing to the extension of the field, in this brief review, we will only focus on structure–function relationships of the three most significant pharmaceutical classes: G protein-coupled receptors, ion channels and transporters.

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.

MLDB: macromolecule ligand database

2009 ◽  
Vol 43 (1) ◽  
pp. 200-202 ◽  
Author(s):  
S. E. Saravanan ◽  
R. Karthi ◽  
K. Sathish ◽  
K. Kokila ◽  
R. Sabarinathan ◽  
...  
Keyword(s):  
Protein Data Bank ◽  
Structural Biology ◽  
Scientific Community ◽  
Three Dimensional ◽  
Data Bank

MLDB (macromolecule ligand database) is a knowledgebase containing ligands co-crystallized with the three-dimensional structures available in the Protein Data Bank. The proposed knowledgebase serves as an open resource for the analysis and visualization of all ligands and their interactions with macromolecular structures. MLDB can be used to search ligands, and their interactions can be visualized both in text and graphical formats. MLDB will be updated at regular intervals (weekly) with automated Perl scripts. The knowledgebase is intended to serve the scientific community working in the areas of molecular and structural biology. It is available free to users around the clock and can be accessed at http://dicsoft2.physics.iisc.ernet.in/mldb/.

scholarly journals Analysis of Three-Dimensional Space Expansion Characteristics in Old Industrial Area Renewal Using GIS and Barista: A Case Study of Tiexi District, Shenyang, China

2019 ◽  
Vol 11 (7) ◽  
pp. 1860 ◽  
Author(s):  
Yanyan Xu ◽  
Miao Liu ◽  
Yuanman Hu ◽  
Chunlin Li ◽  
Zaiping Xiong
Keyword(s):  
Dimensional Space ◽  
Urban Expansion ◽  
Three Dimensional ◽  
Industrial Area ◽  
Urban Morphology ◽  
Average Height ◽  
Landscape Index ◽  
The North ◽  
Gis Tools ◽  
Wide Range

With rapid urban development in China in the last two decades, 3D characteristics have been the main feature of urban morphology. Nevertheless, the vast majority of urban growth research has only focused on area expansion horizontally, with few studies conducted in a 3D perspective. In this paper, the characteristics of 3D expansion that occurred in Tiexi from 1997 to 2011 were evaluated based on geographic information system (GIS) tools, remote-sensing images, and Barista software. Landscape index, the spatiotemporal distribution of changes in buildings’ renewal modes and variations in city skylines as well as the relationship between number and size of high-rise buildings are the specific phenomena and data utilized to quantify the 3D urban expansion. The results showed that the average height of Tiexi increased by 0.69 m annually, the average urban capacity increased by 490.15 m3 annually, and space congestion degree increased by 0.11% annually. The average annual increase of the building evenness index was 36.43. The renewal area occupied up to 75.38% of the total area. The change of the skyline was more consistent with the east–west direction. The change in the south direction was significant, while in the north direction it was relatively slow. The overall shape of the city was that of a weak pyramid, with the angle of the top of the pyramid gradually becoming larger. The methods proposed in this paper laid a foundation for a wide range of study of 3D urban morphology changes.

Dynamic Simulation of Multibody Mechanical Systems Using the Vector-Network Model

1988 ◽  
Vol 12 (1) ◽  
pp. 21-30 ◽  
Author(s):  
M.J. Richard
Keyword(s):  
Dynamic Models ◽  
Analytical Procedure ◽  
Dimensional Space ◽  
Digital Simulation ◽  
Three Dimensional ◽  
General Purpose ◽  
New Approach ◽  
Network Method ◽  
Definition Of ◽  
Three Dimensional Space

Pressing technological problems have created a growing interest in the development of dynamic models for the digital simulation of multibody systems. This paper describes a new approach to the problem of motion prediction. An extension of the “vector-network” method to rigid body systems in three-dimensional space is introduced. The entire procedure is a basic application of concepts of graph theory in which laws of vector dynamics are combined. The analytical procedure was successfully implemented within a general-purpose digital simulation program since, from a minimal definition of the mechanism, it will automatically predict the behavior of the system as output, thereby giving the impression that the equations governing the motion of the mechanical system have been completely formulated and solved by the computer. Simulations of the response of a rail vehicle which demonstrate the validity, applicability and self-formulating aspect of the automated model are provided.

Large-scale dynamics in turbulent mixing and the three-dimensional space–time behaviour of outer fluid interfaces

2002 ◽  
Vol 471 ◽  
pp. 381-408 ◽  
Author(s):  
HARIS J. CATRAKIS ◽  
ROBERTO C. AGUIRRE ◽  
JESUS RUIZ-PLANCARTE ◽  
ROBERT D. THAYNE ◽  
BRENDA A. McDONALD ◽  
...  
Keyword(s):  
Large Scale ◽  
Dimensional Space ◽  
Three Dimensional ◽  
Space Time ◽  
Mixing Efficiency ◽  
Fluid Interfaces ◽  
Ambient Fluid ◽  
Wide Range ◽  
Dimensional Space Time ◽  
Three Dimensional Space

Experiments have been conducted to investigate turbulent mixing and the dynamics of outer fluid interfaces, i.e. the interfaces between mixed fluid and pure ambient fluid. A novel six-foot-diameter octagonal-tank flow facility was developed to enable the optical imaging of fluid interfaces above the mixing transition, corresponding to fully developed turbulence. Approximately 10003 whole-field three-dimensional space– time measurements of the concentration field were recorded using laser-induced- fluorescence digital-imaging techniques in turbulent jets at a Reynolds number of Re ∼ 20 000, Schmidt number of Sc ∼ 2000, and downstream distance of ∼ 500 nozzle diameters. Multiple large-scale regions of spatially nearly uniform-concentration fluid are evident in instantaneous visualizations, in agreement with previous findings above the mixing transition. The ensemble-averaged probability density function of concentration is found to exhibit linear dependence over a wide range of concentration thresholds. This can be accounted for in terms of the dynamics of large-scale well- mixed regions. Visualization of the three-dimensional space–time concentration field indicates that molecular mixing of entrained pure ambient fluid is dynamically initiated and accomplished in the vicinity of the unsteady large scales. Examination of the outer interfaces shows that they are dynamically confined primarily near the instantaneous large-scale boundaries of the flow. This behaviour is quantified in terms of the probability density of the location of the outer interfaces relative to the flow centreline and the probability of pure ambient fluid as a function of distance from the centreline. The current measurements show that the dynamics of outer interfaces above the mixing transition is significantly different from the behaviour below the transition, where previous studies have shown that unmixed ambient fluid can extend across a wide range of transverse locations in the flow interior. The present observations of dynamical confinement of the outer interfaces to the unsteady large scales, and considerations of entrainment, suggest that the mechanism responsible for this behaviour must be the coupling of large-scale flow dynamics with the presence of small-scale structures internal to the large-scale structures, above the mixing transition. The dynamics and structure of the outer interfaces across the entire range of space–time scales are quantified in terms of a distribution of generalized level-crossing scales. The outer-interface behaviour determines the mixing efficiency of the flow, i.e. fraction of mixed fluid. The present findings indicate that the large-scale dynamics of the outer interfaces above the mixing transition provides the dominant contribution to the mixing efficiency. This suggests a new way to quantify the mixing efficiency of turbulent flows at high Reynolds numbers.

scholarly journals Structural Biology in the Clouds: The WeNMR-EOSC Ecosystem

2021 ◽  
Vol 8 ◽  
Author(s):  
Rodrigo V. Honorato ◽  
Panagiotis I. Koukos ◽  
Brian Jiménez-García ◽  
Andrei Tsaregorodtsev ◽  
Marco Verlato ◽  
...  
Keyword(s):  
Structural Biology ◽  
Dynamic Properties ◽  
Three Dimensional ◽  
Open Science ◽  
Biological Macromolecules ◽  
Web Based ◽  
Cellular Processes ◽  
User Friendly ◽  
Insight Into ◽  
Gaining Insight

Structural biology aims at characterizing the structural and dynamic properties of biological macromolecules at atomic details. Gaining insight into three dimensional structures of biomolecules and their interactions is critical for understanding the vast majority of cellular processes, with direct applications in health and food sciences. Since 2010, the WeNMR project (www.wenmr.eu) has implemented numerous web-based services to facilitate the use of advanced computational tools by researchers in the field, using the high throughput computing infrastructure provided by EGI. These services have been further developed in subsequent initiatives under H2020 projects and are now operating as Thematic Services in the European Open Science Cloud portal (www.eosc-portal.eu), sending >12 millions of jobs and using around 4,000 CPU-years per year. Here we review 10 years of successful e-infrastructure solutions serving a large worldwide community of over 23,000 users to date, providing them with user-friendly, web-based solutions that run complex workflows in structural biology. The current set of active WeNMR portals are described, together with the complex backend machinery that allows distributed computing resources to be harvested efficiently.

scholarly journals Peering into the Abyss with Evolutionary Telescopes: How protein structure-telescopes can look further back in time (and why sequence-telescopes cannot)

2021 ◽  
Author(s):  
AJITH HARISH
Keyword(s):  
Structural Biology ◽  
Scientific Inquiry ◽  
Evolutionary Biology ◽  
Three Dimensional ◽  
Data Bank ◽  
Golden Jubilee ◽  
Transformative Impact ◽  
3D Shapes ◽  
Broad Interest ◽  
Field Of Inquiry

This year marks the Golden Jubilee celebrations of the Protein Data Bank (PDB), which catalogs three-dimensional (3D) shapes of organic macromolecules and showcases a structural view of biology. In celebrating this occasion, much has been written about the transformative impact of PDB on a broad range of fields of scientific inquiry and how structural biology transformed the study of the fundamental processes of life. Yet, the transforming influence of PDB on one field of inquiry of broad interest—the reconstruction of the distant evolutionary past—has gone almost unnoticed. Here, I review recent advances to highlight how insights and tools of structural biology are bearing on the data required for the empirical resolution of vigorously debated and apparently contradicting theories in evolutionary biology.

scholarly journals A distance geometry-based description and validation of protein main-chain conformation

IUCrJ ◽  
2017 ◽  
Vol 4 (5) ◽  
pp. 657-670 ◽  
Author(s):  
Joana Pereira ◽  
Victor S. Lamzin
Keyword(s):  
Main Chain ◽  
Dimensional Space ◽  
Distance Geometry ◽  
Protein Structures ◽  
Three Dimensional ◽  
Principal Component ◽  
Data Bank ◽  
Conformational Space ◽  
Protein Backbone ◽  
Space Forms

Understanding the protein main-chain conformational space forms the basis for the modelling of protein structures and for the validation of models derived from structural biology techniques. Presented here is a novel idea for a three-dimensional distance geometry-based metric to account for the fine details of protein backbone conformations. The metrics are computed for dipeptide units, defined as blocks of Cαi−1—Oi−1—Cαi—Oi—Cαi+1atoms, by obtaining the eigenvalues of their Euclidean distance matrices. These were computed for ∼1.3 million dipeptide units collected from nonredundant good-quality structures in the Protein Data Bank and subjected to principal component analysis. The resulting new Euclidean orthogonal three-dimensional space (DipSpace) allows a probabilistic description of protein backbone geometry. The three axes of the DipSpace describe the local extension of the dipeptide unit structure, its twist and its bend. By using a higher-dimensional metric, the method is efficient for the identification of Cαatoms in an unlikely or unusual geometrical environment, and its use for both local and overall validation of protein models is demonstrated. It is also shown, for the example of trypsin proteases, that the detection of unusual conformations that are conserved among the structures of this protein family may indicate geometrically strained residues of potentially functional importance.

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