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Current
Protein & Peptide Science
ISSN: 1389-2042
Current Protein and Peptide
Science
Volume 10, Number 3, June 2009
Contents
The Classic Basic Protein of Myelin – Conserved Structural
Motifs and the Dynamic Molecular Barcode Involved in Membrane
Adhesion and Protein-Protein Interactions Pp.
196-215
G. Harauz and D.S. Libich
[Abstract]
Quality Assessment of Protein Structure
Models Pp. 216-228
D. Kihara, H. Chen and Y.D. Yang
[Abstract]
Methods for Calculating the Entropy and
Free Energy and their Application to Problems Involving Protein
Flexibility and Ligand Binding Pp. 229-243
H. Meirovitch, S. Cheluvaraja and
R.P. White
[Abstract]
The Importance of Being Flexible: The
Case of Basic Region Leucine Zipper Transcriptional Regulators
Pp. 244-269
M. Miller
[Abstract]
A Guide to Template Based Structure Prediction
Pp. 270-285
X. Qu, R. Swanson, R. Day and J.
Tsai
[Abstract]
Predicting Affinity and Specificity of
Antigenic Peptide Binding to Major Histocompatibility Class
I Molecules Pp. 286-296
F. Sieker, A. May and M. Zacharias
[Abstract]
Abstracts
[Back to top]
The Classic Basic Protein of Myelin – Conserved
Structural Motifs and the Dynamic Molecular Barcode Involved
in Membrane Adhesion and Protein-Protein Interactions
G. Harauz and D.S. Libich
The myelin basic protein (MBP) family comprises a variety
of developmentally-regulated members arising from different
transcription start sites, differential splicing, and post-translational
modifications. The “classic” isoforms of MBP include
the 18.5 kDa form, which predominates in adult human myelin
and facilitates compaction of the mature myelin sheath in
the central nervous system, thereby maintaining its structural
integrity. In addition to membrane-association, the 18.5 kDa
and all other classic isoforms are able to interact with a
multitude of proteins, including Ca2+-calmodulin,
actin, tubulin, and SH3-domain containing proteins, and thus
may be signalling linkers during myelin development and remodelling.
All proteins in this family are intrinsically disordered,
creating a large effective surface to facilitate multiple
protein associations, and are post-translationally modified
to various degrees by methylation, phosphorylation, and deimination.
We have used spectroscopic (fluorescence, CD, EPR, and NMR)
approaches to study MBP’s conformational adaptability.
A highly-conserved central domain presents an amphipathic
α-helix
in association with a phospholipid membrane, and contains
a threonyl residue that is phosphorylated by MAP-kinases.
In multiple sclerosis, this segment represents a primary immunodominant
epitope. This helical structure is adjacent to a proline-rich
region that presents a classic SH3-ligand, comprises a second
MAP-kinase phosphorylation site, and forms a polyproline type
II helix. This domain of the protein is thus essential to
proper positioning of a protein-interaction motif, with the
local conformation and accessibility being modulated by MAP-kinases.
In addition, the C-terminus of 18.5 kDa MBP has been identified
by NMR spectroscopy as a Ca2+-calmodulin-binding
site, and is of note for having a high density of post-translational
modifications (protein kinase C phosphorylation, and deimination).
For the most part, any classic protein isoform functions as
an entropic spring that interacts in its entirety with membranes
and cytoskeletal proteins, but the central and C-terminal
motifs may represent molecular switches.
[Back to top]
Quality Assessment of Protein Structure Models
D. Kihara, H. Chen and Y.D. Yang
Computational protein tertiary structure prediction has
made significant progress over the last decade due to the
advancement of techniques and the growth of sequence and structure
databases. However, it is still not very easy to predict the
accuracy of a given predicted structure. Predicting the accuracy,
or quality assessment of a prediction model, is crucial for
a practical use of the model such as biochemical experimental
design and drug design. Recently several model quality assessment
programs (MQAPs) have been proposed for assessing global and
local accuracy of predicted structures. We will start with
reviewing the current status of protein structure prediction
methods with an emphasis on the source of errors. Then existing
MQAPs are classified into several categories and each is discussed.
The categories include methods which evaluate the quality
of template-target alignments, those which evaluate stereochemical
irregularities of prediction models, and methods which integrate
several features into a composite quality assessment score.
[Back to top]
Methods for Calculating the Entropy and Free Energy
and their Application to Problems Involving Protein Flexibility
and Ligand Binding
H. Meirovitch, S. Cheluvaraja and
R.P. White
The Helmholtz free energy, F and the entropy,
S are related thermodynamic quantities with a special
importance in structural biology. We describe the difficulties
in calculating these quantities and review recent methodological
developments. Because protein flexibility is essential for
function and ligand binding, we discuss the related problems
involved in the definition, simulation, and free energy calculation
of microstates (such as the α-helical
region of a peptide). While the review is broad, a special
emphasize is given to methods for calculating the absolute
F (S), where our HSMC(D) method is described
in some detail.
[Back to top]
The Importance of Being Flexible: The Case of Basic
Region Leucine Zipper Transcriptional Regulators
M. Miller
Large volumes of protein sequence and structure data
acquired by proteomic studies led to the development of computational
bioinformatic techniques that made possible the functional
annotation and structural characterization of proteins based
on their primary structure. It has become evident from genome-wide
analyses that many proteins in eukaryotic cells are either
completely disordered or contain long unstructured regions
that are crucial for their biological functions. The content
of disorder increases with evolution indicating a possibly
important role of disorder in the regulation of cellular systems.
Transcription factors are no exception and several proteins
of this class have recently been characterized as premolten/molten
globules. Yet, mammalian cells rely on these proteins to control
expression of their 30,000 or so genes. Basic region:leucine
zipper (bZIP) DNA-binding proteins constitute a major class
of eukaryotic transcriptional regulators. This review discusses
how conformational flexibility “built” into the
amino acid sequence allows bZIP proteins to interact with
a large number of diverse molecular partners and to accomplish
their manifold cellular tasks in a strictly regulated and
coordinated manner.
[Back to top]
A Guide to Template Based Structure Prediction
X. Qu, R. Swanson, R. Day and J.
Tsai
Template based protein structure prediction (commonly
referred to as homology or comparative modeling) uses knowledge
of solved structures to model a protein sequence’s native
or true fold. First, a parent structure is found and then
a template structure is built by mapping the target sequence
onto the parent structure. This putative structure is refined
using a combination of backbone moves, side-chain packing,
and loop modeling. Template based protein structure prediction
has always held great promise to produce atomically accurate
models close to the native conformation based on two major
assumptions. First, similar sequences exhibit similar protein
folds. Second, soluble proteins populate a discrete fold space
with many representatives already solved in our Protein Data
Bank (PDB). Ironically, beginning so close to the native structure
is also the primary source of problems confronting this method
and is the reason for the lack of progress in this category
of structure prediction. In this review, the general concepts
and procedures for template based structure prediction are
outlined based on the following topics: sequence alignment,
parent structure selection, template structure building, refinement,
evaluation, and final structure selection. Then, a description
of established software and algorithms is provided where the
advantages and limitations of the different methods will be
pointed out. This is followed by a discussion of the developments
in template based structure prediction up to the 7th
Critical Assessment of Structure Prediction meeting. Lastly,
we will address the increased difficulty in improving templates
that start so close to the native structure, and discuss the
improvements needed in this field.
[Back to top]
Predicting Affinity and Specificity of Antigenic Peptide
Binding to Major Histocompatibility Class I Molecules
F. Sieker, A. May and M. Zacharias
Major Histo-Compatibility (MHC) class I molecules are
major agents of the mammalian adaptive immune system. Class
I molecules bind short antigenic peptides with a length of
8-10 residues in the Endoplasmatic Reticulum (ER) and after
transport to the cell surface the peptides are presented to
T-lymphocytes. The binding site of class I molecules is formed
by a deep cleft between two α-helices
at top of an extended β-sheet.
Only tightly bound high-affinity peptides have a chance to
reach the cell surface and trigger an immune response. It
is therefore of great interest to identify possible high-affinity
antigenic peptides that could be used as vaccines to help
the immune system to detect viral infections or kill malignant
cells. A large number of crystal structures of antigenic peptides
in complex with class I alleles have been determined that
allow to understand the structural details important for peptide
binding. Biophysical and biochemical analysis of peptide-class
I complexes has resulted in a number of rules concerning the
selection of high-affinity peptides. However, an accurate
prediction of allele specific peptide-binding is still not
possible. This issue is currently addressed by various computational
tools developed by the bioinformatics community. The computational
efforts range from statistical analysis of peptide motifs
stored in databases to application of neural network methods
and support vector machine approaches. In addition, structure
based approaches to predict class I binding specificity including
molecular modeling and molecular dynamics (MD) simulations
will also be presented.
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