scholarly journals Efficient protein tertiary structure retrievals and classifications using content based comparison algorithms

2007 ◽  
Author(s):  
◽  
Pin-Hao Chi
Keyword(s):  
Protein Structure ◽  
Real Time ◽  
High Throughput ◽  
High Efficiency ◽  
Tertiary Structure ◽  
Protein Structures ◽  
Three Dimensional ◽  
Comparison Algorithms ◽  
High Level ◽  
Protein Structure Retrieval

Functionally important sites of proteins are potentially conserved to specific three-dimensional structural folds. To understand the structure-to-function relationship, life sciences researchers and biologists have a great need to retrieve similar structures from protein databases and classify these structures into the same protein fold. Traditional protein structure retrieval and classification methods are known to be either computationally expensive or labor intensive. In the past decade, more than 35000 protein structures have been identified. To meet the needs of fast retrieval and classifying high-throughput protein data, our research covers three main subjects: (1) Real-time global protein structure retrieval: We introduce an image-based approach that extracts signatures of three-dimensional protein structures. Our high-level protein signatures are then indexed by multi-dimensional indexing trees for fast retrieval. (2) Real-time global protein structure classification: An advanced knowledge discovery and data mining (KDD) model is proposed to convert high-level protein signature into itemsets for mining association rules. The advantage of this KDD approach is to effectively reveal the hidden knowledge from similar protein tertiary structures and quickly suggest possible SCOP domains for a newly-discovered protein. In addition, we develop a non-parametric classifier, E-Predict, that can rapidly assign known SCOP folds and recognize novel folds for newly-discovered proteins. (3) Efficient local protein structure retrieval and classification: We propose a novel algorithm, namely, the Index-based Protein Substructure Alignment (IPSA), that constructs a two-layer indexing tree to capture the obscured similarity of protein substructures in a timely fashion. Our research works exhibit significantly high efficiency with reasonably high accuracy and will benefit the study of high-throughput protein structure-function evolutionary relationships.

Prediction of Structural and Functional Aspects of Protein

2014 ◽  
pp. 317-333
Author(s):  
Arun G. Ingale
Keyword(s):  
Protein Structure ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Protein Structures ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Sequence Information ◽  
Predict Protein Structure ◽  
Basic Ideas

To predict the structure of protein from a primary amino acid sequence is computationally difficult. An investigation of the methods and algorithms used to predict protein structure and a thorough knowledge of the function and structure of proteins are critical for the advancement of biology and the life sciences as well as the development of better drugs, higher-yield crops, and even synthetic bio-fuels. To that end, this chapter sheds light on the methods used for protein structure prediction. This chapter covers the applications of modeled protein structures and unravels the relationship between pure sequence information and three-dimensional structure, which continues to be one of the greatest challenges in molecular biology. With this resource, it presents an all-encompassing examination of the problems, methods, tools, servers, databases, and applications of protein structure prediction, giving unique insight into the future applications of the modeled protein structures. In this chapter, current protein structure prediction methods are reviewed for a milieu on structure prediction, the prediction of structural fundamentals, tertiary structure prediction, and functional imminent. The basic ideas and advances of these directions are discussed in detail.

scholarly journals Prediction of Structural and Functional Aspects of Protein

2017 ◽  
pp. 551-568
Author(s):  
Arun G. Ingale
Keyword(s):  
Protein Structure ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Protein Structures ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Sequence Information ◽  
Predict Protein Structure ◽  
Basic Ideas

To predict the structure of protein from a primary amino acid sequence is computationally difficult. An investigation of the methods and algorithms used to predict protein structure and a thorough knowledge of the function and structure of proteins are critical for the advancement of biology and the life sciences as well as the development of better drugs, higher-yield crops, and even synthetic bio-fuels. To that end, this chapter sheds light on the methods used for protein structure prediction. This chapter covers the applications of modeled protein structures and unravels the relationship between pure sequence information and three-dimensional structure, which continues to be one of the greatest challenges in molecular biology. With this resource, it presents an all-encompassing examination of the problems, methods, tools, servers, databases, and applications of protein structure prediction, giving unique insight into the future applications of the modeled protein structures. In this chapter, current protein structure prediction methods are reviewed for a milieu on structure prediction, the prediction of structural fundamentals, tertiary structure prediction, and functional imminent. The basic ideas and advances of these directions are discussed in detail.

scholarly journals A COMPARATIVE STUDY OF PROTEIN TERTIARY STRUCTURE PREDICTION METHODS

2014 ◽  
pp. 15-18
Author(s):  
CHANDRAYANI N. ROKDE ◽  
DR.MANALI KSHIRSAGAR
Keyword(s):  
Protein Structure ◽  
Structure Prediction ◽  
Tertiary Structure ◽  
Sequence Data ◽  
Protein Structures ◽  
Three Dimensional ◽  
Data Bank ◽  
Dimensional Structure ◽  
X Ray Crystallography ◽  
Protein Tertiary Structure Prediction

Protein structure prediction (PSP) from amino acid sequence is one of the high focus problems in bioinformatics today. This is due to the fact that the biological function of the protein is determined by its three dimensional structure. The understanding of protein structures is vital to determine the function of a protein and its interaction with DNA, RNA and enzyme. Thus, protein structure is a fundamental area of computational biology. Its importance is intensed by large amounts of sequence data coming from PDB (Protein Data Bank) and the fact that experimentally methods such as X-ray crystallography or Nuclear Magnetic Resonance (NMR)which are used to determining protein structures remains very expensive and time consuming. In this paper, different types of protein structures and methods for its prediction are described.

scholarly journals De novo protein structure prediction using ultra-fast molecular dynamics simulation

2018 ◽  
Author(s):  
Ngaam J. Cheung ◽  
Wookyung Yu
Keyword(s):  
Molecular Dynamics ◽  
Protein Structure ◽  
Molecular Dynamics Simulation ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
High Efficiency ◽  
Tertiary Structure ◽  
De Novo ◽  
Protein Structures ◽  
Dynamics Simulation

ABSTRACTModern genomics sequencing techniques have provided a massive amount of protein sequences, but experimental endeavor in determining protein structures is largely lagging far behind the vast and unexplored sequences. Apparently, computational biology is playing a more important role in protein structure prediction than ever. Here, we present a system of de novo predictor, termed NiDelta, building on a deep convolutional neural network and statistical potential enabling molecular dynamics simulation for modeling protein tertiary structure. Combining with evolutionary-based residue-contacts, the presented predictor can predict the tertiary structures of a number of target proteins with remarkable accuracy. The proposed approach is demonstrated by calculations on a set of eighteen large proteins from different fold classes. The results show that the ultra-fast molecular dynamics simulation could dramatically reduce the gap between the sequence and its structure at atom level, and it could also present high efficiency in protein structure determination if sparse experimental data is available.

scholarly journals Binocular stereovision omnidirectional motion handling robot

2020 ◽  
Vol 17 (3) ◽  
pp. 172988142092685
Author(s):  
Bo Tang ◽  
Li Jiang
Keyword(s):  
Real Time ◽  
High Efficiency ◽  
Recognition Rate ◽  
Three Dimensional ◽  
Image Feature ◽  
Software Framework ◽  
Matching Algorithm ◽  
Speeded Up Robust Features ◽  
Binocular Stereovision ◽  
The Relationship

Binocular stereovision has become one of the development trends of machine vision and has been widely used in robot recognition and positioning. However, the current research on omnidirectional motion handling robots at home and abroad is too limited, and many problems cannot be solved well, such as single operating systems, complex algorithms, and low recognition rates. To make a high-efficiency handling robot with high recognition rate, this article studies the problem of robot image feature extraction and matching and proposes an improved speeded up robust features (SURF) algorithm that combines the advantages of both SURF and Binary Robust Independent Elementary Features. The algorithm greatly simplifies the complexity of the algorithm. Experiments show that the improved algorithm greatly improves the speed of matching and ensures the real-time and robustness of the algorithm. In this article, the problem of positioning the target workpiece of the robot is studied. The three-dimensional (3-D) reconstruction of the target workpiece position is performed to obtain the 3-D coordinates of the target workpiece position, thereby completing the positioning work. This article designs a software framework for real-time 3-D object reconstruction. A Bayesian-based matching algorithm combined with Delaunay triangulation is used to obtain the relationship between supported and nonsupported points, and 3-D reconstruction of target objects from sparse to dense matches is achieved.

scholarly journals Three-dimensional visualization and analysis of flowing droplets in microchannels using real-time quantitative phase microscopy

Lab on a Chip ◽  
2021 ◽  
Vol 21 (1) ◽  
pp. 75-82
Author(s):  
Yingdong Luo ◽  
Jinwu Yang ◽  
Xinqi Zheng ◽  
Jianjun Wang ◽  
Xin Tu ◽  
...  
Keyword(s):  
Real Time ◽  
High Throughput ◽  
Three Dimensional ◽  
Phase Variation ◽  
Quantitative Phase ◽  
Phase Microscopy ◽  
Quantitative Phase Microscopy ◽  
On Chip

We present real-time quantitative phase microscopy (RT-QPM) that can be used for on-chip three-dimensional visualization of droplets and high-throughput quantitative molecular measurement via real-time extraction of sample-induced phase variation.

scholarly journals Protein Structure Determination in Living Cells

2019 ◽  
Vol 20 (10) ◽  
pp. 2442 ◽  
Author(s):  
Teppei Ikeya ◽  
Peter Güntert ◽  
Yutaka Ito
Keyword(s):  
Protein Structure ◽  
Structure Determination ◽  
Structure Prediction ◽  
Structural Information ◽  
Nuclear Overhauser Effect ◽  
Protein Structures ◽  
Three Dimensional ◽  
Structural Data ◽  
Sample Tube ◽  
In Cells

To date, in-cell NMR has elucidated various aspects of protein behaviour by associating structures in physiological conditions. Meanwhile, current studies of this method mostly have deduced protein states in cells exclusively based on ‘indirect’ structural information from peak patterns and chemical shift changes but not ‘direct’ data explicitly including interatomic distances and angles. To fully understand the functions and physical properties of proteins inside cells, it is indispensable to obtain explicit structural data or determine three-dimensional (3D) structures of proteins in cells. Whilst the short lifetime of cells in a sample tube, low sample concentrations, and massive background signals make it difficult to observe NMR signals from proteins inside cells, several methodological advances help to overcome the problems. Paramagnetic effects have an outstanding potential for in-cell structural analysis. The combination of a limited amount of experimental in-cell data with software for ab initio protein structure prediction opens an avenue to visualise 3D protein structures inside cells. Conventional nuclear Overhauser effect spectroscopy (NOESY)-based structure determination is advantageous to elucidate the conformations of side-chain atoms of proteins as well as global structures. In this article, we review current progress for the structure analysis of proteins in living systems and discuss the feasibility of its future works.

scholarly journals Bifrost: A Python/C++ Framework for High-Throughput Stream Processing in Astronomy

2017 ◽  
Vol 06 (04) ◽  
pp. 1750007 ◽  
Author(s):  
Miles D. Cranmer ◽  
Benjamin R. Barsdell ◽  
Danny C. Price ◽  
Jayce Dowell ◽  
Hugh Garsden ◽  
...  
Keyword(s):  
Real Time ◽  
High Throughput ◽  
Radio Astronomy ◽  
Scientific Productivity ◽  
Data Transport ◽  
Time Data ◽  
Process Data ◽  
Real Time Processing ◽  
Real Time Data Processing ◽  
High Level

Radio astronomy observatories with high throughput back end instruments require real-time data processing. While computing hardware continues to advance rapidly, development of real-time processing pipelines remains difficult and time-consuming, which can limit scientific productivity. Motivated by this, we have developed Bifrost: an open-source software framework for rapid pipeline development. (a) Bifrost combines a high-level Python interface with highly efficient reconfigurable data transport and a library of computing blocks for CPU and GPU processing. The framework is generalizable, but initially it emphasizes the needs of high-throughput radio astronomy pipelines, such as the ability to process data buffers as if they were continuous streams, the capacity to partition processing into distinct data sequences (e.g. separate observations), and the ability to extract specific intervals from buffered data. Computing blocks in the library are designed for applications such as interferometry, pulsar dedispersion and timing, and transient search pipelines. We describe the design and implementation of the Bifrost framework and demonstrate its use as the backbone in the correlation and beamforming back end of the Long Wavelength Array (LWA) station in the Sevilleta National Wildlife Refuge, NM.

Transient CFD Visualization of Fossil Fuel Combustion Simulations

2003 ◽  
Author(s):  
Brian Dotson ◽  
Kent Eshenberg ◽  
Chris Guenther ◽  
Thomas O’Brien
Keyword(s):  
Power Plants ◽  
High Efficiency ◽  
Cfd Simulation ◽  
Low Cost ◽  
Three Dimensional ◽  
Cfd Simulations ◽  
Projection System ◽  
Computational Fluid Dynamics Cfd ◽  
High Level ◽  
Wall System

The design of high-efficiency lower-emission coal-fed power plants is facilitated by the extensive use of computational fluid dynamics (CFD) simulations. This paper describes work conducted at the National Energy Technology Laboratory (NETL) and Pittsburgh Supercomputing Center (PSC) to provide an environment for the immersive three-dimensional visualization of CFD simulation results. A low-cost high-resolution projection system has been developed in the visualization lab at NETL. This multi-wall system consists of four projection screens, three of which are tiled into four quadrants. The graphics for the multi-wall system are rendered using a cluster of eight personal computers. A high-level visualization interface named Mavis has also been developed to combine the powerful 3D modules of OpenDX with methods developed at NETL for studying multiphase CFD data. With Python, a completely new OpenDX user interface was built that extends and simplifies the features of a basic graphics library.

scholarly journals Different Synergy in Amyloids and Biologically Active Forms of Proteins

2019 ◽  
Vol 20 (18) ◽  
pp. 4436 ◽  
Author(s):  
Piotr Fabian ◽  
Katarzyna Stapor ◽  
Mateusz Banach ◽  
Magdalena Ptak-Kaczor ◽  
Leszek Konieczny ◽  
...  
Keyword(s):  
Amino Acids ◽  
Comparative Analysis ◽  
Protein Structure ◽  
Tertiary Structure ◽  
Protein Structures ◽  
Water Environment ◽  
Biologically Active ◽  
Radius Of Curvature ◽  
Hydrophobic Core ◽  
Structural Form

Protein structure is the result of the high synergy of all amino acids present in the protein. This synergy is the result of an overall strategy for adapting a specific protein structure. It is a compromise between two trends: The optimization of non-binding interactions and the directing of the folding process by an external force field, whose source is the water environment. The geometric parameters of the structural form of the polypeptide chain in the form of a local radius of curvature that is dependent on the orientation of adjacent peptide bond planes (result of the respective Phi and Psi rotation) allow for a comparative analysis of protein structures. Certain levels of their geometry are the criteria for comparison. In particular, they can be used to assess the differences between the structural form of biologically active proteins and their amyloid forms. On the other hand, the application of the fuzzy oil drop model allows the assessment of the role of amino acids in the construction of tertiary structure through their participation in the construction of a hydrophobic core. The combination of these two models—the geometric structure of the backbone and the determining of the participation in the construction of the tertiary structure that is applied for the comparative analysis of biologically active and amyloid forms—is presented.

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