A new model of amino acids evolution, evolution index of amino acids and its application in graphical representation of protein sequences

2010 ◽  
Vol 497 (4-6) ◽  
pp. 223-228 ◽  
Author(s):  
Yi Zhang
Keyword(s):  
Amino Acids ◽  
Graphical Representation ◽  
Protein Sequences ◽  
New Model

3D Graphical Representation of Protein Sequences Based on Conformational Parameters of Amino Acids

2014 ◽  
Vol 989-994 ◽  
pp. 3599-3604
Author(s):  
Qian Jun Xiao ◽  
Zong Gang Deng
Keyword(s):  
Amino Acids ◽  
Protein Sequence ◽  
Graphical Representation ◽  
Protein Sequences ◽  
3D Graphical Representation ◽  
Protein Graphs

Based on the helix and-sheet and the-turn conformational parameters, and and , of the 20 amino acids, we propose a new 3D graphical representation of protein sequence without circuit or degeneracy, which may reflect the innate structure of the protein sequence. Then the numerical characterizations of protein graphs, the leading eigenvalues of the L/L matrices associated with the graphical curves for protein sequences, was utilized as descriptors to analyze the similarity/dissimilarity of the nine ND5 protein sequences.

scholarly journals Novel Numerical Characterization of Protein Sequences Based on Individual Amino Acid and Its Application

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Yan-ping Zhang ◽  
Ya-jun Sheng ◽  
Wei Zheng ◽  
Ping-an He ◽  
Ji-shuo Ruan
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Catalytic Mechanism ◽  
Graphical Representation ◽  
Sequence Similarity ◽  
Protein Sequences ◽  
Numerical Characteristic ◽  
Individual Amino Acid ◽  
Numerical Characterization

The hydrophobicity and hydrophilicity of amino acids play a very important role in protein folding and its interaction with the environment and other molecules, as well as its catalytic mechanism. Based on the two physicochemical indexes, a 2D graphical representation of protein sequences is introduced; meanwhile, a new numerical characteristic has been proposed to compute the distance of different sequences for analysis of sequence similarity/dissimilarity on the basis of this graphical representation. Furthermore, we apply the new distance in the similarities/dissimilarities of ND5 proteins of nine species and predict the four major classes based on the dataset containing 639 domains. The results show that the method is simple and effective.

A Generalized Iterative Map for Analysis of Protein Sequences

2020 ◽  
Vol 23 ◽  
Author(s):  
Jiahe Huang ◽  
Qi Dai ◽  
Yuhua Yao ◽  
Ping-An He
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Correlation Analysis ◽  
Physicochemical Properties ◽  
Graphical Representation ◽  
Protein Sequences ◽  
Biological Sequences ◽  
Alignment Method ◽  
Alignment Free ◽  
Comparison Results

Aim and Objective: The similarities comparison of biological sequences is the important task in bioinformatics. The methods of the similarities comparison for biological sequences are divided into two classes: sequence alignment method and alignment-free method. The graphical representation of biological sequences is a kind of alignment-free methods, which constitutes a tool for analyzing and visualizing the biological sequences. In this article, a generalized iterative map of protein sequences was suggested to analyze the similarities of biological sequences. Materials and Methods: Based on the normalized physicochemical indexes of 20 amino acids, each amino acid can be mapped into a point in 5D space. A generalized iterative function system was introduced to outline a generalized iterative map of protein sequences, which can not only reflect various physicochemical properties of amino acids but also incorporate with different compression ratios of component of generalized iterative map. Several properties were proved to illustrate the advantage of generalized iterative map. The mathematical description of generalized iterative map was suggested to compare the similarities and dissimilarities of protein sequences. Based on this method, similarities/dissimilarities were compared among ND5 proteins sequences, as well as ND6 protein sequences of ten different species. Results: By correlation analysis, the ClustalW results were compared with our similarity/dissimilarity results and other graphical representation results to show the utility of our approach. The comparison results show that our approach has better correlations with ClustalW for all species than other approaches and illustrate the effectiveness of our approach. Conclusion: Two examples show that our method not only has good performances and effects in the similarity/dissimilarity analysis of protein sequences but also does not require complex computation.

A 2D Non-degeneracy Graphical Representation of Protein Sequence and Its Applications

2020 ◽  
Vol 15 (7) ◽  
pp. 758-766
Author(s):  
Xiaoli Xie ◽  
Yunxiu Zhao
Keyword(s):  
Amino Acids ◽  
Amino Acid ◽  
Protein Sequence ◽  
Graphical Representation ◽  
Protein Sequences ◽  
Important Research ◽  
Physiochemical Properties ◽  
New Methods ◽  
Alignment Free ◽  
Highly Correlated

Background: The comparison of the protein sequences is an important research filed in bioinformatics. Many alignment-free methods have been proposed. Objective: In order to mining the more information of the protein sequence, this study focus on a new alignment-free method based on physiochemical properties of amino acids. Methods: Average physiochemical value (Apv) has been defined. For a given protein sequence, a 2D curve was outlined based on Apv and position of the amino acid, and there is not loop and intersection on the curve. According to the curve, the similarity/dissimilarity of the protein sequences can be analyzed. Results and Conclusion: Two groups of protein sequences are taken as examples to illustrate the new methods, the protein sequences can be classified correctly, and the results are highly correlated with that of ClustalW. The new method is simple and effective.

scholarly journals DV-Curve Representation of Protein Sequences and Its Application

2014 ◽  
Vol 2014 ◽  
pp. 1-8 ◽  
Author(s):  
Wei Deng ◽  
Yihui Luan
Keyword(s):  
Amino Acids ◽  
Protein Sequence ◽  
Graphical Representation ◽  
Protein Sequences ◽  
Quantitative Comparison ◽  
The Other ◽  
Hp Model ◽  
Dual Vector ◽  
Numerical Characterization ◽  
Curve Representation

Based on the detailed hydrophobic-hydrophilic(HP) model of amino acids, we propose dual-vector curve (DV-curve) representation of protein sequences, which uses two vectors to represent one alphabet of protein sequences. This graphical representation not only avoids degeneracy, but also has good visualization no matter how long these sequences are, and can reflect the length of protein sequence. Then we transform the 2D-graphical representation into a numerical characterization that can facilitate quantitative comparison of protein sequences. The utility of this approach is illustrated by two examples: one is similarity/dissimilarity comparison among different ND6 protein sequences based on their DV-curve figures the other is the phylogenetic analysis among coronaviruses based on their spike proteins.

A Study on Host Tropism Determinants of Influenza Virus Using Machine Learning

2020 ◽  
Vol 15 (2) ◽  
pp. 121-134 ◽  
Author(s):  
Eunmi Kwon ◽  
Myeongji Cho ◽  
Hayeon Kim ◽  
Hyeon S. Son
Keyword(s):  
Machine Learning ◽  
Amino Acids ◽  
Influenza Virus ◽  
Random Forest ◽  
Physicochemical Properties ◽  
Protein Sequences ◽  
Influenza Viruses ◽  
Host Tropism ◽  
Post Hoc ◽  
Ha Protein

Background: The host tropism determinants of influenza virus, which cause changes in the host range and increase the likelihood of interaction with specific hosts, are critical for understanding the infection and propagation of the virus in diverse host species. Methods: Six types of protein sequences of influenza viral strains isolated from three classes of hosts (avian, human, and swine) were obtained. Random forest, naïve Bayes classification, and knearest neighbor algorithms were used for host classification. The Java language was used for sequence analysis programming and identifying host-specific position markers. Results: A machine learning technique was explored to derive the physicochemical properties of amino acids used in host classification and prediction. HA protein was found to play the most important role in determining host tropism of the influenza virus, and the random forest method yielded the highest accuracy in host prediction. Conserved amino acids that exhibited host-specific differences were also selected and verified, and they were found to be useful position markers for host classification. Finally, ANOVA analysis and post-hoc testing revealed that the physicochemical properties of amino acids, comprising protein sequences combined with position markers, differed significantly among hosts. Conclusion: The host tropism determinants and position markers described in this study can be used in related research to classify, identify, and predict the hosts of influenza viruses that are currently susceptible or likely to be infected in the future.

scholarly journals Determinants of adenine-mutagenesis in diversity-generating retroelements

2020 ◽  
Author(s):  
Sumit Handa ◽  
Andres Reyna ◽  
Timothy Wiryaman ◽  
Partho Ghosh
Keyword(s):  
Amino Acids ◽  
Dark Matter ◽  
Reverse Transcription ◽  
Genetic Information ◽  
Human Microbiome ◽  
Protein Sequences ◽  
Catalytic Efficiency ◽  
Natural World ◽  
In Vitro System

Abstract Diversity-generating retroelements (DGRs) vary protein sequences to the greatest extent known in the natural world. These elements are encoded by constituents of the human microbiome and the microbial ‘dark matter’. Variation occurs through adenine-mutagenesis, in which genetic information in RNA is reverse transcribed faithfully to cDNA for all template bases but adenine. We investigated the determinants of adenine-mutagenesis in the prototypical Bordetella bacteriophage DGR through an in vitro system composed of the reverse transcriptase bRT, Avd protein, and a specific RNA. We found that the catalytic efficiency for correct incorporation during reverse transcription by the bRT-Avd complex was strikingly low for all template bases, with the lowest occurring for adenine. Misincorporation across a template adenine was only somewhat lower in efficiency than correct incorporation. We found that the C6, but not the N1 or C2, purine substituent was a key determinant of adenine-mutagenesis. bRT-Avd was insensitive to the C6 amine of adenine but recognized the C6 carbonyl of guanine. We also identified two bRT amino acids predicted to nonspecifically contact incoming dNTPs, R74 and I181, as promoters of adenine-mutagenesis. Our results suggest that the overall low catalytic efficiency of bRT-Avd is intimately tied to its ability to carry out adenine-mutagenesis.

scholarly journals Folding Rate Optimization Promotes Frustrated Interactions in Entangled Protein Structures

2019 ◽  
Vol 21 (1) ◽  
pp. 213
Author(s):  
Federico Norbiato ◽  
Flavio Seno ◽  
Antonio Trovato ◽  
Marco Baiesi
Keyword(s):  
Amino Acids ◽  
Structural Biology ◽  
Weak Interactions ◽  
Protein Structures ◽  
Protein Sequences ◽  
Control Case ◽  
Folding Rate ◽  
Empirical Observation ◽  
Rate Optimization ◽  
Kinetic Traps

Many native structures of proteins accomodate complex topological motifs such as knots, lassos, and other geometrical entanglements. How proteins can fold quickly even in the presence of such topological obstacles is a debated question in structural biology. Recently, the hypothesis that energetic frustration might be a mechanism to avoid topological frustration has been put forward based on the empirical observation that loops involved in entanglements are stabilized by weak interactions between amino-acids at their extrema. To verify this idea, we use a toy lattice model for the folding of proteins into two almost identical structures, one entangled and one not. As expected, the folding time is longer when random sequences folds into the entangled structure. This holds also under an evolutionary pressure simulated by optimizing the folding time. It turns out that optmized protein sequences in the entangled structure are in fact characterized by frustrated interactions at the closures of entangled loops. This phenomenon is much less enhanced in the control case where the entanglement is not present. Our findings, which are in agreement with experimental observations, corroborate the idea that an evolutionary pressure shapes the folding funnel to avoid topological and kinetic traps.

Sign in / Sign up

Export Citation Format

Share Document