Library

X
feed icon rss

Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Electronic Resource
    Electronic Resource
    PROTEIN-DNA RECOGNITION PATTERNS AND PREDICTIONS (2005)
    Palo Alto, Calif. : Annual Reviews
    Annual Review of Biophysics and Biomolecular Structure 34 (2005), S. 379-398 
    Details
    ISSN: 1056-8700
    Source: Annual Reviews Electronic Back Volume Collection 1932-2001ff
    Topics: Biology , Physics
    Notes: Structural data on protein-DNA complexes provide clues for understanding the mechanism of protein-DNA recognition. Although the structures of a large number of protein-DNA complexes are known, the mechanisms underlying their specific binding are still only poorly understood. Analysis of these structures has shown that there is no simple one-to-one correspondence between bases and amino acids within protein-DNA complexes; nevertheless, the observed patterns of interaction carry important information on the mechanisms of protein-DNA recognition. In this review, we show how the patterns of interaction, either observed in known structures or derived from computer simulations, confer recognition specificity, and how they can be used to examine the relationship between structure and specificity and to predict target DNA sequences used by regulatory proteins.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1146/annurev.biophys.34.040204.144537
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
  • 2
    Electronic Resource
    Electronic Resource
    Relationship Between Amino Acid Properties and Protein Stability: Buried Mutations (1999)
    Springer
    The protein journal 18 (1999), S. 565-578 
    Details
    ISSN: 1573-4943
    Keywords: Amino acid properties ; unfolding free energy change ; protein stability ; protein mutants ; multiple regression technique ; secondary and tertiary structures
    Source: Springer Online Journal Archives 1860-2000
    Topics: Chemistry and Pharmacology
    Notes: Abstract In order to understand the mechanism of protein stability and to develop a simple method for predicting mutation-induced stability changes, we analyzed the relationship between stability changes caused by buried mutations and changes in 48 amino acid properties. As expected from the importance of hydrophobicity, properties reflecting hydrophobicity are strongly correlated with the stability of proteins. We found that subgroup classification based on secondary structure increased correlations significantly, and mutations within β-strand segments correlated better than did those in α-helical segments, which may result from stronger hydrophobicity of the β-strands. Multiple regression analyses incorporating combinations of three properties from among all possible combinations of the 48 properties increased the correlation coefficient to 0.88 and by an average of 13% for all data sets. Analyzing the stability of tryptophan synthase mutants with Glu49 replaced by all other residues except Arg revealed that combining buriedness, solvent-accessible surface area for denatured protein, and unfolding Gibbs free energy change increased the correlation to 0.95. Consideration of sequence and structural information (neighboring residues in sequence and in space) did not significantly strengthen the correlations in buried mutations, suggesting that nonspecific interactions dominate in the interior of proteins.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1023/A:1020603401001
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
  • 3
    Electronic Resource
    Electronic Resource
    Energy minimization method using automata network for sequence and side-chain conformation prediction from given backbone geometry (1994)
    New York, NY : Wiley-Blackwell
    Proteins: Structure, Function, and Genetics 19 (1994), S. 244-255 
    Details
    ISSN: 0887-3585
    Keywords: energy minimization ; rotamers ; automaton ; de novo design ; sequence prediction ; side-chain conformation prediction ; Chemistry ; Biochemistry and Biotechnology
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Medicine
    Notes: Globular proteins have high packing densities as a result of residue side chains in the core achieving a tight, complementary packing. The internal packing is considered the main determinant of native protein structure. From that point of view, we present here a method of energy minimization using an automata network to predict a set of amino acid sequences and their side-chain conformations from a desired backbone geometry for de novo design of proteins. Using discrete side-chain conformations, that is, rotamers, the sequence generation problem from a given backbone geometry becomes one of combinatorial problems. We focused on the residues composing the interior core region and predicted a set of amino acid Sequences and their side-chain conformations only from a given backbone geometry. The kinds of residues were restricted to six hydrophobic amino acids (Ala, Ile, Met, Leu, Phe, and Val) because the core regions are almost always composed of hydrophobic residues. The obtained sequences were well packed as was the native sequence. The method can be used for automated sequence generation in the de novo design of proteins. © 1994 Wiley-Liss, Inc.
    Additional Material: 6 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/prot.340190308
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
  • 4
    Electronic Resource
    Electronic Resource
    A new method for side-chain conformation prediction using a Hopfield network and reproduced rotamers (1996)
    New York, NY [u.a.] : Wiley-Blackwell
    Journal of Computational Chemistry 17 (1996), S. 1667-1683 
    Details
    ISSN: 0192-8651
    Keywords: Chemistry ; Theoretical, Physical and Computational Chemistry
    Source: Wiley InterScience Backfile Collection 1832-2000
    Topics: Chemistry and Pharmacology , Computer Science
    Notes: We present a new side-chain prediction method based on energy minimization using a Hopfield network, focusing on the buried residues of proteins. In this method, the network is composed of automata assigned to each rotamer to restrict side-chain conformational space. We reproduced a rotamer library that enabled us to more widely cover the space for side-chain conformations than those previously produced. The accuracy of the side-chain modeling was estimated by three standards: root mean square deviations (rmsds) between the modeled and the crystal structures, the percentages of correctly predicted side-chain torsion angles, and the percentages of correctly predicted hydrogen bonds. The average rmsd for buried side chains of 21 proteins was 1.10 Å. The value was almost always improved relative to the previous works. The percentage of side-chain X1 angles for buried residues was 87.3%. By considering the hydrogen bond energy, the average percentage of correctly predicted hydrogen bonds rose from 33% without hydrogen bond energy to 52% with the bond energy. We applied this method to homology modeling, where the protein backbone used to predict side-chain conformations deviates from the correct conformation, and could predict side-chain conformations as correctly as those using the correct backbones. © 1996 by John Wiley & Sons, Inc.
    Additional Material: 6 Ill.
    Type of Medium: Electronic Resource
    URL: http://dx.doi.org/10.1002/jcc.8
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Paper (German National Licenses)
    Fulltext
Close ⊗
This website uses cookies and the analysis tool Matomo. More information can be found here...