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BITS2007 Meeting
BITS2007 Meeting



26-28 April 2007 Napoli, Italy

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Globularity criteria to evaluate the structural quality of modeled proteins
 
Motivation
The basic problem of any computational approach to structure prediction is to
evaluate the quality of models. CASP results evidenced that most of the submitted
models are far from the real protein structure. Our work has been aimed to analyze
structural properties that characterize protein globularity, to suggest an operative
procedure for the analysis of globular quality of theoretical protein models obtained
by computational approaches in the absence of experimental target structures, and,
finally, to prevent the diffusion of theoretical models not suitable with the real
features of the protein globularity.


Methods
The analyses of experimental structures were performed using the PDBselect set of
experimentally determined, non-redundant protein structures with mutual sequence
similarity <25%. The secondary structure defined by the DSSP algorithm was used to
assign each protein to the right structural class, according to the four main SCOP
classes ("all-alpha", "all-beta", "alpha/beta", and "alpha+beta"). Some features
related to the globularity of proteins have been evaluated for each structure. Four
properties, i.e. the total accessible surface area (ASA), the number of MM-type
H-bonds, voids and water molecules in a layer of 5 Angstroms, correlated better then
others with the molecular weight. All four properties versus the molecular weights of
selected proteins in each structural class fit with linear regressions, and the linear
function was defined to estimate the expected value for each feature. Therefore, a
globularity score value was calculated for each protein by summing the ratios of the
differences between the calculated and predicted values for each of the four
properties versus the related errors (i.e. Root Mean Squared Error). On the basis of
the most frequent score values, calculated for the proteins belonging to the same
class, it was possible to identify a threshold score value specific for each of the
four structural classes. These threshold score values were then used as cut-off to
evaluate the structural properties of models predicted for the CASP6 protein
structure prediction experiment in the New Fold (NF) and difficult Fold Recognition
Analogous (FR/A) categories, and used as "testing dataset".


Results
We analyzed different structural properties of globular proteins for experimentally
solved proteins belonging to the four different structural classes. The properties
were found to be linearly correlated to protein molecular weight, but with some
differences among the four classes. These results were applied to develop an
evaluation test of theoretical models based on the expected globular properties of
proteins. In fact, a score value (i.e. globularity score) for all proteins was
calculated by using the parameters having the highest correlation coefficients with
the protein molecular weights (i.e. MM-type H-bonds, void number, total accessible
surface area and water molecules). 
To verify the success of our test, we applied our globularity score to several
protein models submitted to the sixth edition of CASP. Our results surprisingly show
that many of the models submitted (54.6%) should be discarded a priori because they
do not have the structural properties expected in globular proteins. 
Therefore, our study supports the need for careful checks to avoid the diffusion of
incorrect structural models and allows the evaluation of models in the absence of
experimental reference structures, thus preventing the diffusion of incorrect
structural models and the formulation of incorrect functional hypotheses. It can be
used to check the globularity of predicted models, and to supplement other methods
already used to evaluate their quality.
 
Id: 104
Place: Napoli, Italy
Centro Congressi "Federico II"
Via Partenope 36
Napoli
Starting date:
28-Apr-2007   12:30
Duration: 20'
Contribution type: Oral
Primary Authors: COSTANTINI, Susan (Centro di Ricerca Interdipartimentale di Scienze Computazionali e Biotecnologiche, Seconda Universita` di Napoli, Italy; Laboratorio di Bioinformatica e Biologia Computazionale, Istituto di Scienze dell'Alimentazione, CNR, Avellino, Italy)
Co-Authors: FACCHIANO, Angelo M (Centro di Ricerca Interdipartimentale di Scienze Computazionali e Biotecnologiche, Seconda Universita` di Napoli, Italy; Laboratorio di Bioinformatica e Biologia Computazionale, Istituto di Scienze dell'Alimentazione, CNR, Avellino, Italy)
COLONNA, Giovanni (Centro di Ricerca Interdipartimentale di Scienze Computazionali e Biotecnologiche, Seconda Universita` di Napoli, Italy)
Presenters: COSTANTINI, Susan
Material: slide Slides
 
Included in session: Session 7: Structural biology and drug design
Included in track: Structural biology and drug design
 




bits2007_support@ceinge.unina.it | Last modified 08 July 2009 10:35 |




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