Abstract: The literature reports a large number of approaches for
measuring the similarity between protein sequences. Most of these
approaches estimate this similarity using alignment-based techniques
that do not necessarily yield biologically plausible results, for two
reasons.
First, for the case of non-alignable (i.e., not yet definitively aligned
and biologically approved) sequences such as multi-domain, circular
permutation and tandem repeat protein sequences, alignment-based
approaches do not succeed in producing biologically plausible results.
This is due to the nature of the alignment, which is based on the
matching of subsequences in equivalent positions, while non-alignable
proteins often have similar and conserved domains in non-equivalent
positions.
Second, the alignment-based approaches lead to similarity measures
that depend heavily on the parameters set by the user for the alignment
(e.g., gap penalties and substitution matrices). For easily alignable
protein sequences, it's possible to supply a suitable combination of
input parameters that allows such an approach to yield biologically
plausible results. However, for difficult-to-align protein sequences,
supplying different combinations of input parameters yields different
results. Such variable results create ambiguities and complicate the
similarity measurement task.
To overcome these drawbacks, this paper describes a novel and
effective approach for measuring the similarity between protein
sequences, called SAF for Substitution and Alignment Free. Without
resorting either to the alignment of protein sequences or to substitution
relations between amino acids, SAF is able to efficiently detect the
significant subsequences that best represent the intrinsic properties of
protein sequences, those underlying the chronological dependencies of
structural features and biochemical activities of protein sequences.
Moreover, by using a new efficient subsequence matching scheme,
SAF more efficiently handles protein sequences that contain similar
structural features with significant meaning in chronologically
non-equivalent positions. To show the effectiveness of SAF, extensive
experiments were performed on protein datasets from different
databases, and the results were compared with those obtained by
several mainstream algorithms.
Abstract: In this paper we introduce the notion of protein interaction network. This is a graph whose vertices are the protein-s amino acids and whose edges are the interactions between them. Using a graph theory approach, we observe that according to their structural roles, the nodes interact differently. By leading a community structure detection, we confirm this specific behavior and describe thecommunities composition to finally propose a new approach to fold a protein interaction network.
Abstract: Certain tRNA synthetases have developed highly accurate molecular machinery to discriminate their cognate amino acids. Those aaRSs achieve their goal via editing reaction in the Connective Polypeptide 1 (CP1). Recently mutagenesis studies have revealed the critical importance of residues in the CP1 domain for editing activity and X-ray structures have shown binding mode of noncognate amino acids in the editing domain. To pursue molecular mechanism for amino acid discrimination, molecular modeling studies were performed. Our results suggest that aaRS bind the noncognate amino acid more tightly than the cognate one. Finally, by comparing binding conformations of the amino acids in three systems, the amino acid binding mode was elucidated and a discrimination mechanism proposed. The results strongly reveal that the conserved threonines are responsible for amino acid discrimination. This is achieved through side chain interactions between T252 and T247/T248 as well as between those threonines and the incoming amino acids.
Abstract: The amount of the information being churned out by the field of biology has jumped manifold and now requires the extensive use of computer techniques for the management of this information. The predominance of biological information such as protein sequence similarity in the biological information sea is key information for detecting protein evolutionary relationship. Protein sequence similarity typically implies homology, which in turn may imply structural and functional similarities. In this work, we propose, a learning method for detecting remote protein homology. The proposed method uses a transformation that converts protein sequence into fixed-dimensional representative feature vectors. Each feature vector records the sensitivity of a protein sequence to a set of amino acids substrings generated from the protein sequences of interest. These features are then used in conjunction with support vector machines for the detection of the protein remote homology. The proposed method is tested and evaluated on two different benchmark protein datasets and it-s able to deliver improvements over most of the existing homology detection methods.
Abstract: This article introduces the actual problem that is а
study of proposed by the authors Hydrocele ointment in amino acids’
metabolism of cows’ blood in inflammation of traumatic origin.
Hydrocele ointment has shown a positive effect on inflammatory
process and amino acids’ metabolism of animals treated with the
drug. Amino acid levels reached physiological parameters on the 10th
day after treatment; in the control group this parameter was higher
than normal.
Abstract: Application of pesticides in the paddy fields has
deleterious effects on non-target organisms including cyanobacteria
which are photosynthesizing and nitrogen fixing micro-organisms
contributing significantly towards soil fertility and crop yield.
Pesticide contamination in the paddy fields has manifested into a
serious global environmental concern. To study the effect of one such
pesticide, three cyanobacterial strains; Anabaena fertilissima,
Aulosira fertilissima and Westiellopsis prolifica were selected for
their stress responses to an Organochlorine insecticide - 6, 7, 8, 9, 10,
10-hexachloro-1, 5, 5a, 6, 9, 9a-hexahydro-6, 9-methano-2, 4, 3-
benzodioxathiepine-3-oxide, with reference to their photosynthesic
pigments-chlorophyll-a and carotenoids as well as accessory
pigments-phycobiliproteins (phycocyanin, allophycocyanin and
phycoerythrin), stress induced biochemical metabolites like
carbohydrates, proteins, amino acids, phenols and enzymes-nitrate
reductase, glutamine synthetase and succinate dehydrogenase. All
the three cyanobacterial strains were adversely affected by the
insecticide doses and inhibition was dose dependent. Reduction in
photosynthetic and accessory pigments, metabolites, nitrogen fixing
and respiratory enzymes of the test organisms were accompanied
with an initial increase in their total protein at lower Organochlorine
doses. On the other hand, increased amount of phenols in all the
insecticide treated concentrations was indicative of stressed activities
of the organisms.