scholarly journals FLU, an amino acid substitution model for influenza proteins

2010 ◽  
Vol 10 (1) ◽  
pp. 99 ◽  
Author(s):  
Cuong Dang ◽  
Quang Le ◽  
Olivier Gascuel ◽  
Vinh Le
2020 ◽  
Author(s):  
Huihui Chang ◽  
Yimeng Nie ◽  
Nan Zhang ◽  
Xue Zhang ◽  
Huimin Sun ◽  
...  

Abstract Background Amino acid substitution models play an important role in inferring phylogenies from mitochondrial proteins. Although different amino acid substitution models have been proposed, only a few were estimated from mitochondrial protein sequences for specific taxa such as the mtArt model for Arthropoda. The increasing of mitochondrial genome data from broad Orthoptera taxa provides an opportunity to estimate the Orthoptera-specific mitochondrial amino acid empirical model. Results We sequenced complete mitochondrial genomes of 54 Orthoptera species, and then estimated an amino acid substitution model (named mtOrt) by maximum likelihood method based on the 283 complete mitochondrial genomes available currently. The results indicated that there are obvious differences between mtOrt and the existing model, and the new model can better fit the Orthoptera mitochondrial protein datasets. Moreover, topologies of trees constructed using mtOrt and existing models are frequently different. MtOrt does indeed have an impact on likelihood improvement as well as tree topologies. The comparisons between the topologies of trees constructed using mtOrt and existing models show that the new model outperforms the existing models in inferring phylogenies from Orthoptera mitochondrial protein data. Conclusions The new mitochondrial amino acid substitution model of Orthoptera shows obvious differences from the existing models, and outperforms the existing models in inferring phylogenies from Orthoptera mitochondrial protein sequences.


2020 ◽  
Author(s):  
Huihui Chang ◽  
Yimeng Nie ◽  
Nan Zhang ◽  
Xue Zhang ◽  
Huimin Sun ◽  
...  

Abstract Background Amino acid substitution models play an important role in inferring phylogenies from mitochondrial proteins. Although different amino acid substitution models have been proposed, only a few were estimated from mitochondrial protein sequences for specific taxa such as the mtArt model for Arthropoda. The increasing of mitochondrial genome data from broad Orthoptera taxa provides an opportunity to estimate the Orthoptera-specific mitochondrial amino acid empirical model. Results We sequenced complete mitochondrial genomes of 54 Orthoptera species, and then estimated an amino acid substitution model (named mtOrt) by maximum likelihood method based on the 283 complete mitochondrial genomes available currently. The results indicated that there are obvious differences between mtOrt and the existing model, and the new model can better fit the Orthoptera mitochondrial protein datasets. Moreover, topologies of trees constructed using mtOrt and existing models are frequently different. MtOrt does indeed have an impact on likelihood improvement as well as tree topologies. The comparisons between the topologies of trees constructed using mtOrt and existing models show that the new model outperforms the existing models in inferring phylogenies from Orthoptera mitochondrial protein data. Conclusions The new mitochondrial amino acid substitution model of Orthoptera shows obvious differences from the existing models, and outperforms the existing models in inferring phylogenies from Orthoptera mitochondrial protein sequences.


2019 ◽  
Vol 467 ◽  
pp. 31-38 ◽  
Author(s):  
Gabriel S. Zamudio ◽  
Francisco Prosdocimi ◽  
Sávio Torres de Farias ◽  
Marco V. José

2018 ◽  
Author(s):  
Elias Primetis ◽  
Spyridon Chavlis ◽  
Pavlos Pavlidis

AbstractIntra-protein residual vicinities depend on the involved amino acids. Energetically favorable vicinities (or interactions) have been preserved during evolution, while unfavorable vicinities have been eliminated. We describe, statistically, the interactions between amino acids using resolved protein structures. Based on the frequency of amino acid interactions, we have devised an amino acid substitution model that implements the following idea: amino acids that have similar neighbors in the protein tertiary structure can replace each other, while substitution is more difficult between amino acids that prefer different spatial neighbors. Using known tertiary structures for α-helical membrane (HM) proteins, we build evolutionary substitution matrices. We constructed maximum likelihood phylogenies using our amino acid substitution matrices and compared them to widely-used methods. Our results suggest that amino acid substitutions are associated with the spatial neighborhoods of amino acid residuals, providing, therefore, insights into the amino acid substitution process.


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