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  • 20D space  (2)
  • Chemistry  (2)
  • structural classes  (2)
  • 1
    Electronic Resource
    Electronic Resource
    Springer
    The protein journal 14 (1995), S. 309-326 
    ISSN: 1573-4943
    Keywords: Amino acid composition ; 20D space ; covariance matrix ; Mahalanobis distance
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology
    Notes: Abstract The accuracy of predicting protein folding types can be significantly enhanced by a recently developed algorithm in which the coupling effect among different amino acid components is taken into account [Chou and Zhang (1994)J. Biol. Chem. 269, 22014-22020]. However, in practical calculations using this powerful algorithm, one may sometimes face illconditioned matrices. To overcome such a difficulty, an effective eigenvalue-eigenvector approach is proposed. Furthermore, the new approach has been used to predict a recently constructed set of 76 proteins not included in the training set, and the accuracy of prediction is also much higher than those of other methods.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    The protein journal 12 (1993), S. 169-178 
    ISSN: 1573-4943
    Keywords: Alla ; all β ; a+β ; a/β ; Amino acid composition ; 20D space ; correlation angle
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology
    Notes: Abstract A new method is proposed for predicting the folding type of a protein according to its amino acid composition based on the following physical picture: (1) a protein is characterized as a vector of 20-dimensional space, in which its 20 components are defined by the compositions of its 20 amino acids; and (2) the similarity of two proteins is proportional to the mutual projection of their characterized vectors, and hence inversely proportional to the size of their correlation angle. Thus, the prediction is performed by calculating the correlation angles of the vector for the predicted protein with a set of standard vectors representing the norms of four protein folding types (i.e., alla, all β,a+β, anda/β). In comparison with the existing methods, the new method has the merits of yielding a higher rate of correct prediction, displaying a more intuitive physical picture, and being convenient in application. For instance, in predicting the 64 proteins in the development set based on which the standard vectors are derived, the average accuracy rate is 83.6%, which is higher than that obtained for the same set of proteins by any of the existing methods. The average accuracy predicted for an independent set of 35 proteins of known X-ray structure is 91.4%, which is significantly higher than any of the reported accuracies so far, implying that the new method is of great value in practical application. All of these have demonstrated that the new method as proposed in this paper is characterized by an improved feature in both self-consistency and extrapolating-effectiveness.
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  • 3
    Electronic Resource
    Electronic Resource
    Springer
    The protein journal 17 (1998), S. 261-272 
    ISSN: 1573-4943
    Keywords: Protein structure prediction ; α-helix content ; β-strand content ; structural classes ; resubstitution analysis ; jackknife analysis
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology
    Notes: Abstract The prediction of the secondary structural contents (those of α-helix and β-strand) of a globular protein is of great use in the prediction of protein structure. In this paper, a new prediction algorithm has been proposed based on Chou's database [Chou (1995), Proteins 21, 319–344]. The new algorithm is an improved multiple linear regression method, taking into account the nonlinear and coupling terms of the frequencies of different amino acids and the length of the protein. The prediction is also based on the structural classes of proteins, but instead of four classes, only three classes are considered, the α class, β class, and the mixed α+β and α/β class or simply the αβ class. Thus the ambiguity that usually occurs between α+β proteins and α/β proteins is eliminated. A resubstitution examination for the algorithm shows that the average absolute errors are 0.040 and 0.035 for the prediction of α-helix content and β-strand content, respectively. An examination of cross-validation, the jackknife analysis, shows that the average absolute errors are 0.051 and 0.045 for the prediction of α-helix content and β-strand content, respectively. Both examinations indicate the self-consistency and the extrapolating effectiveness of the new algorithm. Compared with other methods, ours has the merits of simplicity and convenience for use, as well as high prediction accuracy. By incorporating the prediction of the structural classes, the only input of our method is the amino acid composition and the length of the protein to be predicted.
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  • 4
    Electronic Resource
    Electronic Resource
    Springer
    The protein journal 15 (1996), S. 775-786 
    ISSN: 1573-4943
    Keywords: Prediction ; protein ; α-helix content ; Β-strand content ; structural classes ; resubstitution ; jackknife
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology
    Notes: Abstract The prediction of the secondary structure content (α-helix andΒ-strand content) of a globular protein may play an important complementary role in the prediction of the protein's structure. We propose a new prediction algorithm based on Chou's database [Chou (1995),Proteins Struct. Fund Genet. 21, 319]. The new algorithm is an improved multiple linear regression method, taking the nonlinear and coupling terms of the frequencies of different amino acids into account. The prediction is also based on the structural classes of proteins. A resubstitution examination for the algorithm shows that the average errors are 0.040 and 0.033 for the prediction ofα-helix content andΒ-strand content, respectively. The examination of cross-validation, the jackknife analysis, shows that the average errors are 0.051 and 0.044 for the prediction ofα-helix content andΒ-strand content, respectively. Both examinations indicate the self-consistency and the extrapolative effectiveness of the new algorithm. Compared with the other methods available currently, our method has the merits of simplicity and convenience for use, as well as a high prediction accuracy. By incorporating the prediction of the structural classes, the only input of our method is the amino acid composition of the protein to be predicted.
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  • 5
    Electronic Resource
    Electronic Resource
    New York : Wiley-Blackwell
    Biopolymers 41 (1997), S. 673-702 
    ISSN: 0006-3525
    Keywords: protein folding ; coupling effect ; Chemistry ; Polymer and Materials Science
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: A 1-4 and 2-3 residue-correlation model is proposed to predict the β-turns in proteins. The average rate of correct prediction for the 455 β-turn tetrapeptides and 4018 non-β-turn tetrapeptides in the training data base is 80.1%, and that for the 223 β-turn tetrapeptides and 12562 non-β-turn tetrapeptides in the testing data base is 80.9%. Compared with the rates of correct prediction based on the residue-independent model reported previously, the quality of prediction is significantly improved by the new model, implying that the correlation effect between the 1st and the 4th residues and that between the 2nd and 3rd residues along a tetrapeptide are important for forming a β-turn in a protein during the process of its folding. © 1997 John Wiley & Sons, Inc. Biopoly 41: 673-702, 1997
    Additional Material: 4 Tab.
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  • 6
    Electronic Resource
    Electronic Resource
    New York : Wiley-Blackwell
    Biopolymers 34 (1994), S. 143-153 
    ISSN: 0006-3525
    Keywords: Chemistry ; Polymer and Materials Science
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology
    Notes: Microtubules, which play many diverse and important roles in biological systems, are usually made up of 13 nearly axial protofilaments formed from individual tubulin molecules. In this paper, a nonlinear dynamic model has been developed to elucidate the mechanism of the internal motion occurring during the assembly of microtubules. The results derived from the model indicate that such internal motion is associated with a solitary wave, or kink, excited by the energy released from the hydrolysis of GTP ⇒ GDP in microtubular solutions. As the kink moves forward, the individual tubulin molecules involved in the kink undergo motions that can be likened to the dislocation of atoms within the crystal lattice. Thus, the dynamic instability of microtubules may be characterized by a series of dislocation motions of the tubulin molecules. An energy estimate shows that a kink in the system possesses about 0.36-0.44 eV, which is quite close to but smaller than the 0.49 eV of energy released from the hydrolysis of GTP. Therefore, the relevant energy derived from our model is fully consistent with experimental observations; this finding also suggests that the hydrolysis energy may be responsible for exciting the solitary wave, or kink, leading to tubulin dislocation in microtubules.Our model, and its intrinsic properties, i.e., dynamic nonlinearity, thermodynamic irreversibility, as well as an energy input from a sustained source, implies that the growth of microtubules is a typical dissipative process and that their structure in vivo is typical of dissipative structures. © 1994 John Wiley & Sons, Inc.
    Additional Material: 5 Ill.
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