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We consider a generalized hydrophobic-polar model for proteins on square lattices. Besides the attraction between nonbonded hydrophobic monomers, the present model also takes into account an interaction between hydrophobic and polar units. By using the prunedenriched Rosenbluth method PERM , we investigate a specific polymer sequence composed of 42 monomers that has been proposed to simulate the physical properties of the parallel helix of pectate lyase C. For each temperature, the total number of generated chains varies from to Physical observables such as specific heat, total energy, end-to-end distance, radius of gyration, and the average number of hydrophobic-hydrophobic and hydrophobic-polar contacts, are evaluated for different values of the ratio between the hydrophobic-hydrophobic and the hydrophobic-polar contact energies. Eventually, a pseudo-phase diagram in the space of temperature and the ratio of contact energy scales is constructed. Introduction Proteins are responsible for a wide range of biological functions, including transport and storage of molecules, coordinated movements, enzymatic catalysis, mechanical support, and others .
Since there exist 20 different amino acids in nature, a protein with N monomers could be found, in principle, in any one of th 20N possible sequences . The complexity of the system arises from this huge number of combinations. Due to the enormous number of tasks to be necessarily fulfilled to ensure the stability of a biological system, a large number of proteins exists , although it is vanishingly small compared to the number of possible sequences.
The biological function of a protein chain is closely related to its sequence, hence, to its native conformation . In this sense, it is very useful to identify the structure which a specific sequence will assume according its environmental conditions.
It is well known that, as the temperature increases, a heteropolymer chain undergoes changes in its shape, from the native fold to globules, and random coils .
In this work, we calculate quantities like the specific heat, mean energy, end-to-end distance, and radius of gyration. Different temperatures and solvent conditions are considered to determine the phase diagram of a specific sequence composed by 42 monomers [8, 9, 10]. Model and Method Despite the variety of monomer units, simplified models have been proposed in order to better understand the conformational transitions of a polymer chain. Hence the implementation of this action-research pilot-project, which aims to: 1 diagnose the alcohol use patterns among the target-populations; 2 promote the development of specific interventions and 3 develop HR guidelines focused on vulnerable alcohol users.
Deeply rooted in participation, community, empowerment and pragmatic humanism principles, GIRA aims to promote reflection at all its levels and stages and establish relations between several members of community to whom the alcohol use is a relevant theme.
Scientific Production Presented — J.
Vilares, L. Parodi, C. Lameira, C. This interest is associated with the recognition of the importance of sleep habits and routines concerning health and well-being, learning and the results of children development. The project resulted in two posters presented at scientific events one of them at an international event , as well as 11 individual reports and 11 informative posters with the results in the first phase of the project.
These results were publicly presented to the school community involved, health professionals and local policymakers. Porto, Catholic University of Portugal, may Presented — Pinho, C. Other Production: Eleven individual reports were built for each school in the Vila Nova de Gaia municipality involved in the project, as well as 11 informative posters with the results at the 1st cycle of Basic Education. Communitary Actions: A public presentation of the results of the first phase of the project was carried out, involving children from the 1st Cycle of Basic Education.
The event was reported at local press. The results of this analysis will lead to the design of healthcare intervention strategies that meet the needs of said target-population. This assessment process is carried out according to several parameters, namely by taking into account the medical assistance gaps within the families or neighbourhoods, at a more personal level, concerning the medical assistance at home and also regarding the healthcare promotion actions to be developed in the vicinities or among several families.
The project resulted in 4 publications in proceedings of international scientific meetings, 3 publications in international journals with peer review, 1 book, 2 book chapters, 1 internal evaluation report, 1 poster in national event and 4 communications in international scientific events.
The dissemination of the project has resulted in the recognition of its relevance, both in international context and Portugal, namely its contribution to the Regulation of Information and Communication Technologies for access to distance education in prisons.
Scientific Production: Published — Barros, R.
Published — Monteiro, A. Lifelong learning through e-learning in european prisons: Rethinking digital and social inclusion pp. DS04 Published — Barros, R. Santo Tirso: Whitebooks. Published — Moreira, J. Comunicar, Universidade do Minho, Braga, 8 maio Presented — Monteiro, A. Inclusive digital online environments as a device for pedagogic differentiation: A taxonomy proposal.
Monteiro, A. Aprender em ambientes virtuais: autoconceito de aprendizagem de mulheres em contexto prisional. ICT applications: e-learning.
Scientific Production: Presented — Lucas, S. Presented — Lucas, S. A dor como objeto de prazer. Published — Azeredo, Z. Journal of Ageing and Innovation, 5 1 4 Published — Lucas, S.
ISBN: Lisboa: Pactor. A comparison of the results with those reported by others involving the same data set also testies to a better prediction accuracy in our case. Proteins ; It is widely believed that the amino acid AA sequence of a protein contains sufcient information to determine its three-dimensional structure.
There is an enormous gap between the number of protein structures that have been resolved so far and the huge number of proteins that have been sequenced. An accurate prediction of the three-dimensional structures of proteins is currently possible for those that enjoy a signicant sequence similarity to proteins of known threedimensional structures.
An extreme form in this case is the prediction of the protein structure in one dimension, such as a characterization of AA residues to adopt one of the secondary structure conformations. Additionally, the prediction of residue accessibility can aid in elucidating the relationship between AA sequence and structure.
The prediction of solvent accessibility has been performed in a variety of ways, such as sequence alignment, neural network, and statistical analysis of AA composition.
Single and pair-information values for each possible pair from 8 to 8 positions were taken from the database. The relative solvent accessibilities in the various states were predicted with the different thresholds for each state, and the performance accuracy was compared to the previously reported results for the same data set. Similar predictions were made for three or more accessibility states, and a new hydropathy scale based on the characteristic of residues in the two-state model was developed.
E-mail: naderman modares. This enabled us to determine the propensity of single-residue and pairwiseresidue interactions to adopt a conformational state.
Naturally, it is necessary to consider the information contained by the neighboring residues on the conformation of a given residue. The denition of the information that y carries on the occurrence of event x is as follows: IS x:x log pS xR pS x log 1 pS xR 1 pS x 1 therefore, necessary to consider the information carried by the neighboring residues on the conformation of a given residue.
In a sequence environment of eight residues on either side of a central residue, the preference informational content I of a residue with sequence number j and AA type Rj for an accessibility state, for example, type S buried, intermediate, exposed in a three-state model, is approximated as ISj x:x ; Rj m,. The complementary event of S X. In a protein structure, the conformation of AA residues may depend on the whole sequence or at least the local sequence. It is, That is called pair-information, the information carried by the residue at j m on the accessibility state of the residue at j on the basis of the type of residue at j and j m.
If there are enough observations, the frequency ratio is a good approximation for the probability required. For a few observations, an estimation based on Bayesian reasoning of the information parameters was used. For the three-state prediction, x B,I,E , where B represents the buried residues, I represents the intermediate residues, and E represents the exposed residues. The rst term of Equation 2 requires a contingency table with 3 20 60 entries, and for pair-information it needs 20 20 3 1, entries.
The data set used contains about H. Dependence of the two-state prediction accuracy and the correlation coefcient on the solvent-accessibility threshold. The results were obtained with information theory over the protein data set. The solid line represents the correct prediction percentage, and the dashed represents the correlation coefcient.
With different thresholds of accessibility. AA rankings are different in different accessibility cutoffs. The relative solvent accessibility of each residue in the folded protein was calculated by the surface accessibility being divided by the maximum accessibility of that residue.
Here, the relative accessibility was divided over two to nine states with various thresholds. In this method, each protein in the data set was selected as a test protein and was removed from the data set. Informational parameters used in predicting solvent-accessibility states were calculated for the remaining proteins in the data set. This procedure was repeated until all the proteins were tested exactly once.
For comparison with the results of other methods, the data set of protein selected by Rost and Sander44 was used, and the aforementioned procedure was applied.
Other scales are derived via statistical analysis of the observed distribution of the residues between the solvent-accessible surface and the buried interior in proteins of known structures.
These scales in general are qualitative descriptions of the hydropathic behaviors of AAs, and in statistical scales, qualitative disagreements arise because of criterion differences for the determination of residue buriedness. The prediction quality was evaluated by the percentage of correctly predicted residues divided by the total number of residues in the data set.
The correlation coefcient between the observed x and predicted y solvent-accessibility states for a data set of N residues was calculated form Correlation coefcient x 2 x 2 y 2 y 2 xy x y Relative Solvent Accessibility of a Residue Accessible surface areas for individual atoms of the proteins were calculated from atomic coordinates deposited in the protein data bank with the program devised by our group.
For each atom, a sufciently large number of approximately evenly distributed points were placed on the solvation sphere of radius Ra Rw centered at the atomic position, where Ra and Rw are the Van der Waals radii of atom A and the solvent probe, respectively.
Self-information values were calculated with Equation 1 and are listed in Table III for the two-state accessibility models with different thresholds of accessibility for buried and exposed states.
Information values show different tendencies for different residues in the core or surface of globular proteins. The order of residues from the most hydrophobic positive values to the most hydrophilic negative values residues does not agree in all respects and varies with the determination of the accessibility state threshold for the classication of residues in the buried or exposed states.
Prediction of the Data Set A jackknife test was applied for the prediction. After the test protein was removed, the parameters were recalculated for the remaining data set. This procedure was repeated until the entire data set had been predicted. A problematic factor in this regard is the choice of solvent-accessibility cutoffs. The obtained results would change with changes in the cutoff levels.
Figure 1 shows the effects of the solvent-accessibility threshold on the prediction accuracy and the correlation coefcient for a two-state prediction. As shown, the prediction accuracy and correlation coefcient are threshold-dependent. Therefore, the thresholds for various accessibility state models were selected on the basis of these factors and the distribution of different residues into states. Use of Pair-Information The extensive data set chosen allowed us to use the pair-information parameters Equation 2 if the number of observations was sufcient to give a good estimation of the information values.