CooPPS: A SYSTEM FOR THE COOPERATIVE PREDICTION OF PROTEIN STRUCTURES

2004 ◽  
Vol 02 (03) ◽  
pp. 471-495 ◽  
Author(s):  
LUIGI PALOPOLI ◽  
GIORGIO TERRACINA
Keyword(s):  
Structure Prediction ◽  
Protein Structures ◽  
Three Dimensional ◽  
Quality Parameters ◽  
Dimensional Structure ◽  
Prediction Problem ◽  
Common Reference ◽  
Prediction Tools ◽  
Definition Of

Predicting the three-dimensional structure of proteins is a difficult task. In the last few years several approaches have been proposed for performing this task taking into account different protein chemical and physical properties. As a result, a growing number of protein structure prediction tools is becoming available, some of them specialized to work on either some aspects of the predictions or on some categories of proteins; however, they are still not sufficiently accurate and reliable for predicting all kinds of proteins. In this context, it is useful to jointly apply different prediction tools and combine their results in order to improve the quality of the predictions. However, several problems have to be solved in order to make this a viable possibility. In this paper a framework and a tool is proposed which allows: (i) definition of a common reference applicative domain for different prediction tools; (ii) characterization of prediction tools through evaluating some quality parameters; (iii) characterization of the performances of a team of predictors jointly applied over a prediction problem; (iv) the singling out of the best team for a prediction problem; and (v) the integration of predictor results in the team in order to obtain a unique prediction. A system implementing the various steps of the proposed framework (CooPPS) has been developed and several experiments for testing the effectiveness of the proposed approach have been carried out.

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 Protein Structure Prediction Based on Improved Genetic Algorithm

2020 ◽  
Vol 11 (9) ◽  
pp. 450-454
Author(s):  
Jiaxi Liu ◽  
Keyword(s):  
Genetic Algorithm ◽  
Protein Structure ◽  
Amino Acid ◽  
Protein Structure Prediction ◽  
Structure Prediction ◽  
Protein Structures ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Improved Genetic Algorithm ◽  
Research Areas

The prediction of protein three-dimensional structure from amino acid sequence has been a challenge problem in bioinformatics, owing to the many potential applications for robust protein structure prediction methods. Protein structure prediction is essential to bioscience, and its research results are important for other research areas. Methods for the prediction an才d design of protein structures have advanced dramatically. The prediction of protein structure based on average hydrophobic values is discussed and an improved genetic algorithm is proposed to solve the optimization problem of hydrophobic protein structure prediction. An adjustment operator is designed with the average hydrophobic value to prevent the overlapping of amino acid positions. Finally, some numerical experiments are conducted to verify the feasibility and effectiveness of the proposed algorithm by comparing with the traditional HNN algorithm.

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.

Characterization of Monoclonal Anti-human Factor VII Antibody (B101/B1) that Recognized Three-dimensional Structures near Arg at Position 79 in the First EGF-like Domain

1998 ◽  
Vol 79 (01) ◽  
pp. 104-109 ◽  
Author(s):  
Osamu Takamiya
Keyword(s):  
Monoclonal Antibodies ◽  
Tissue Factor ◽  
Human Factor ◽  
Solid Phase ◽  
Three Dimensional ◽  
Coagulation Factors ◽  
Factor Vii ◽  
Dimensional Structure ◽  
Epidermal Growth

SummaryMurine monoclonal antibodies (designated hVII-B101/B1, hVIIDC2/D4 and hVII-DC6/3D8) directed against human factor VII (FVII) were prepared and characterized, with more extensive characterization of hVII-B101/B1 that did not bind reduced FVIIa. The immunoglobulin of the three monoclonal antibodies consisted of IgG1. These antibodies did not inhibit procoagulant activities of other vitamin K-dependent coagulation factors except FVII and did not cross-react with proteins in the immunoblotting test. hVII-DC2/D4 recognized the light chain after reduction of FVIIa with 2-mercaptoethanol, and hVIIDC6/3D8 the heavy chain. hVII-B101/B1 bound FVII without Ca2+, and possessed stronger affinity for FVII in the presence of Ca2+. The Kd for hVII-B101/B1 to FVII was 1.75 x 10–10 M in the presence of 5 mM CaCl2. The antibody inhibited the binding of FVII to tissue factor in the presence of Ca2+. hVII-B101/B1 also inhibited the activation of FX by the complex of FVIIa and tissue factor in the presence of Ca2+. Furthermore, immunoblotting revealed that hVII-B101/B1 reacted with non-reduced γ-carboxyglutaminic acid (Gla)-domainless-FVII and/or FVIIa. hVII-B101/B1 showed a similar pattern to that of non-reduced proteolytic fragments of FVII by trypsin with hVII-DC2/D4 on immunoblotting test. hVII-B101/B1 reacted differently with the FVII from the dysfunctional FVII variant, FVII Shinjo, which has a substitution of Gln for Arg at residue 79 in the first epidermal growth factor (1st EGF)-like domain (Takamiya O, et al. Haemosta 25, 89-97,1995) compared with normal FVII, when used as a solid phase-antibody for ELISA by the sandwich method. hVII-B101/B1 did not react with a series of short peptide sequences near position 79 in the first EGF-like domain on the solid-phase support for epitope scanning. These results suggested that the specific epitope of the antibody, hVII-B101/B1, was located in the three-dimensional structure near position 79 in the first EGF-like domain of human FVII.

scholarly journals RNA-Puzzles: A CASP-like evaluation of RNA three-dimensional structure prediction

RNA ◽  
2012 ◽  
Vol 18 (4) ◽  
pp. 610-625 ◽  
Author(s):  
J. A. Cruz ◽  
M.-F. Blanchet ◽  
M. Boniecki ◽  
J. M. Bujnicki ◽  
S.-J. Chen ◽  
...  
Keyword(s):  
Structure Prediction ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Three Dimensional Structure

Ribosomal protein S17: Characterization of the three-dimensional structure by proton and nitrogen-15 NMR

Biochemistry ◽  
1993 ◽  
Vol 32 (47) ◽  
pp. 12812-12820 ◽  
Author(s):  
Barbara L. Golden ◽  
David W. Hoffman ◽  
V. Ramakrishnan ◽  
Stephen W. White
Keyword(s):  
Ribosomal Protein ◽  
Three Dimensional ◽  
Dimensional Structure ◽  
Three Dimensional Structure

scholarly journals Analysis of structural similarities between brain Thy-1 antigen and immunoglobulin domains. Evidence for an evolutionary relationship and a hypothesis for its functional significance

1981 ◽  
Vol 195 (1) ◽  
pp. 31-40 ◽  
Author(s):  
F E Cohen ◽  
J Novotný ◽  
M J E Sternberg ◽  
D G Campbell ◽  
A F Williams
Keyword(s):  
Functional Significance ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
Three Dimensional ◽  
Evolutionary Relationship ◽  
Dimensional Structure ◽  
Sequence Homologies ◽  
Beta Structure ◽  
Beta 2 Microglobulin

The Thy-1 membrane glycoprotein from rat brain is shown to have structural and sequence homologies with immunoglobulin (Ig) domains on the basis of the following evidence. 1. The two disulphide bonds of Thy-1 are both consistent with the Ig-fold. 2. The molecule contains extensive beta-structure as shown by the c.d. spectrum. 3. Secondary structure prediction locates beta-strands along the sequence in a manner consistent with the Ig-fold. 4. On the basis of rules derived from known beta-sheet structures, a three-dimensional structure with the Ig-fold is predicted as favourable for Thy-1. 5. Sequences in the proposed beta-strands of Thy-1 and known beta-strands of Ig domains show significant sequence homology. This homology is statistically more significant than for the comparison of proposed beta-strand sequences of beta 2-microglobulin with Ig domains. An hypothesis is presented for the possible functional significance of an evolutionary relationship between Thy-1 and Ig. It is suggested that both Thy-1 and Ig evolved from primitive molecules, with an Ig fold, which mediated cell--cell interactions. The present-day role of Thy-1 may be similar to that of the primitive domain.

scholarly journals Structural characterization of quaternary selenites of tungsten(VI), A 2W3SeO12 (A = NH4, Cs, Rb, K or Tl)

2021 ◽  
Vol 77 (4) ◽  
pp. 406-411
Author(s):  
Vineela Balisetty ◽  
Kanamaluru Vidyasagar
Keyword(s):  
Three Dimensional ◽  
Spectroscopic Studies ◽  
Solid State Reactions ◽  
Dimensional Structure ◽  
X Ray Diffraction ◽  
Compound K ◽  
Three Dimensional Structure ◽  
Thermal And Spectroscopic Studies ◽  
Anionic Framework

The quaternary A 2W3SeO12 (A = NH4, Cs, Rb, K or Tl) selenites have been prepared in the form of single crystals by hydrothermal and novel solid-state reactions. They were characterized by X-ray diffraction, thermal and spectroscopic studies. All of them have a hexagonal tungsten oxide (HTO) related [W3SeO12]2− anionic framework with pyramidally coordinated Se4+ ions. The known A 2W3SeO12 (A = NH4, Cs or Rb) compounds are isostructural with the Cs2W3TeO12 compound and have a non-centrosymmetric layered structure containing intra-layer Se—O bonds. The new compound K2W3SeO12(α) is isostructural with the K2W3TeO12 compound and has a centrosymmetric three-dimensional structure containing interlayer Se—O bonds. It is inferred that the new Tl2W3SeO12 compound has the same three-dimensional structure as K2W3SeO12(α).

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