How does comparison of amino acid differences

Click through the PLOS taxonomy to find articles in your field. Abstract In this paper, we have proposed a novel alignment-free method for comparing the similarity of protein sequences. Introduction With the recent development of next-generation sequencing technologies, there has been an explosion in the numbers of available DNA and protein sequences.

Method Amino acid composition and distribution are two most fundamental information about a protein sequence.

By definition, we have 2 3 From eqs 1 and 2 we have and thus P i , j can be considered as a transition probability from amino acid A i to A j in the protein sequence. Construction of the 20 dimensional amino acid content ratio vector Given that the protein sequence is composed of only 20 amino acids, it is clear that.

Quantifying the distances among protein sequences based on their feature vectors Let S and T be two proteins and V S and V T be their D feature vectors. Results and Discussions To evaluate the performance of our method, we applied it into two datasets: 1 the ND5 dataset [ 22 ] and 2 the F10 and G11 dataset [ 23 ]. Datasets The ND5 dataset consists of the ND5 protein sequences of 9 species including human, gorilla, pigmy chimpanzee, common chimpanzee, fin whale, blue whale, rat, mouse, and opossum Table 1.

Download: PPT. Application to the ND5 dataset We first encoded the nine protein sequences into D feature vectors. Fig 1. The content ratios of twenty amino acids in the ND5 dataset.

Fig 2. The position ratios of twenty amino acids in the ND5 dataset. Fig 3. A heat map showing the similarity of nine species in the ND5 dataset. Fig 4. A heat map showing the similarity of nine species in the ND5 dataset based on the D amino acid position ratio vector.

Fig 5. A heat map showing the similarity of nine species in the ND5 dataset based on the D amino acid content ratio vector. Fig 6. A heat map showing the similarity of nine species in the ND5 dataset based on the D amino acid position ratio and content ratio vector. Table 3. The distance matrix of nine species calculated by ClustalW i. Application to the F10 and G11 dataset We also tested our method on the F10 and G11 datasets and plotted the heat map based on the pair-wise Euclidean distances in Fig 7.

Fig 7. A heat map showing the similarity of 20 xylanases in the F10 and G11 datasets. Conclusion In this paper, we have proposed a novel alignment-free method to compare protein sequences.

Supporting Information. S1 Fig. A heat map showing the similarity of nine species in the ND5 dataset based on the Hamming distance. S2 Fig. A heat map showing the similarity of 20 xylanases in the F10 and G11 datasets based on the Hamming distance. S1 Table. The nine ND5 protein sequences. S2 Table. The 10 sequences in the F10 xylanase family. S3 Table. The 10 sequences in the G11 xylanase family. Author Contributions Conceptualization: YL. References 1.

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PloS one. You may need to remind your students about the nature of DNA, genes, proteins, and amino acids and how they differ from one another. DNA is a molecule made up of four types of units called bases.

The sequence of bases in a gene determines the order of amino acids in a protein, and the order of amino acids acts as the blueprint for protein assembly.

Because the DNA sequence determines a protein's amino acid sequence, a gene shared by two closely related organisms should have similar, or even identical, amino acid sequences. That's because closely related species most likely diverged from one another fairly recently in the evolutionary span. Thus, they haven't had as much time to accumulate random mutations in their genetic codes.

For years, scientists have used DNA and amino acid sequences to decipher relationships between closely related species, such as different types of reptiles, birds, and even bacteria. The approach, called "molecular phylogeny," compares sequence data and ranks organisms' degree of relatedness based on the differences in their DNA.

As researchers sequence the genomes of an increasing number of organisms every year, they uncover more data to use in evolutionary studies. In the emerging field of phylogenomics , researchers simultaneously compare numerous genes—and will one day compare complete genomes—to build new evolutionary trees. In this activity, your students will analyze a suite of amino acid sequences from a gene that makes the protein Cytochrome C.

All eukaryotic organisms share this protein, which plays a central role in the energy-producing process of cellular respiration. Cytochrome C is an iron-containing molecule that carries electrons during the electron transport chain in cellular respiration. The protein is found in many lineages, including those of animals, plants, and numerous unicellular species. Its ubiquity makes it a convenient tool for studying evolution.

By counting the number of amino acid differences between humans and six other species, your students will be able to make predictions about how closely related humans are to each species. Divide the class into four teams. Assign each team one of the following genes: FOXP2, hemoglobin alpha, eyeless, and sonic hedgehog. Have students visit the Kyoto Encyclopedia of Genes and Genomes and look up their gene's amino acid sequence in humans.

We suggest some reasons for the different effectivenesses of the four approaches in the two different sequence settings, and offer some rules of thumb for assessing the significance of sequence relationships.

Abstract We examined two extensive families of protein sequences using four different alignment schemes that employ various degrees of "weighting" in order to determine which approach is most sensitive in establishing relationships. Gov't, P.